Measuring Country Performance and State Behavior: a Survey of Composite Indices”

Composite Indicators and Rankings: Inventory 2011

Romina Bandura1

Working Paper2

1 Contact: [email protected] 2 Abbreviated version

List of Indices By Field

Economy ...... 13 1. Alternative Country Risk Rating (IRPA) ...... 13 2. APESMA Big Mac Index ...... 14 3. BAK Economic Attractiveness Index ...... 15 4. Bertelsmann Transformation Index ...... 16 5. Best Performing Cities ...... 17 6. Big Mac Index ...... 18 7. BradyNet Ratings Ladder ...... 19 8. Capital Access Index (CAI) ...... 20 9. Composite Indicators of Flexicurity ...... 21 10. Composite Score of Risk (BRS) ...... 23 11. Consumer Confidence Index (CCI) ...... 24 12. Cost of Doing Business ...... 25 13. Cost of Living Survey ...... 26 14. Country @ratings ...... 27 15. Country Risk Evaluation and Assessment Model (CREAM) ...... 28 16. Country Risk Monitoring Service ...... 29 17. CSGR Globalisation Index ...... 30 18. DHS Wealth Index ...... 31 19. Ducroire/Delcredere Country Risks ...... 32 20. Ease of Doing Business Index ...... 33 21. ECA Cost of Living Survey ...... 34 22. Economic Freedom of the World (EFW) Index ...... 35 23. Economic Vulnerability Index ...... 36 24. EIU Business Environment Rankings ...... 37 25. EIU Country Risk Service (CRS) ...... 38 26. EIU Worldwide Cost of Living Index (WCOL) ...... 39 27. Emerging Market Bond Indices (EMBI) ...... 40 28. Euro Monitor Ranking ...... 41 29. Eurochambres Economic Survey (EES) Indicators ...... 42 30. European Cities Monitor ...... 43 31. European Competitiveness Index (ECI) ...... 44 32. European E-Business Readiness Index ...... 45

Composite Indicators and Rankings: Inventory 2011 1 33. European Economic Sustainability Index (EESI) ...... 46 34. European Smart Cities ...... 47 35. Forbes Capital Hospitality Index (FCHI) ...... 48 36. Foreign Direct Investment Confidence Index ...... 49 37. FORELAND - Lender's risk rating ...... 50 38. G-Index - Globalization index ...... 51 39. Global Competitiveness Index ...... 52 40. Global Enabling Trade Index (ETI) ...... 53 41. Global Entrepreneurship Monitor (GEM) ...... 54 42. Global Financial Centres Index (GFCI) ...... 55 43. Global Investment Prospects Assessment (GIPA) ...... 57 44. Global Production Scoreboard ...... 58 45. Global Retail Development Index (GRDI)...... 59 46. Global Risk Service ...... 60 47. Global Venture Capital and Private Equity Country Attractiveness Index ...... 61 48. Growth and Development Bridge (GDB) Index ...... 62 49. Index measuring the strictness of employment legislation (EPL) ...... 63 50. Index of Economic Freedom ...... 64 51. Index of Globalization ...... 65 52. Institutional Investor Country Credit Ratings ...... 66 53. Internal Market Scoreboard and Internal Market Index ...... 67 54. International Country Risk Guide (ICRG) Ratings - Composite Risk Rating ...... 68 55. Inward FDI Performance Index ...... 69 56. Inward FDI Potential Index ...... 70 57. KPMG Global Corporate and Indirect Tax Survey ...... 71 58. Lisbon Index ...... 72 59. Lisbon Review Index ...... 73 60. Lisbon Scorecard and League Table ...... 74 61. Logistics Performance Index (LPI) ...... 75 62. Long Island Index ...... 77 63. Luxembourg Competitiveness Index (Tableau de bord "Compétitivité") ...... 78 64. Market Potential Index (MPI) ...... 79 65. McKinsey Global Confidence Index ...... 80 66. Microscope Index ...... 81 67. Networked Readiness Index (NRI) ...... 82 68. Offshore Location Attractiveness Index ...... 83 69. Outward FDI Performance Index ...... 84

Composite Indicators and Rankings: Inventory 2011 2 70. Qualitative Risk Measure in Foreign Lending (QLM-FE) ...... 85 71. Quality of Workforce Index (QWI) ...... 86 72. Regional Competitiveness Atlas ...... 87 73. Regional Competitiveness Index (RCI) ...... 88 74. Responsible Competitiveness Index ...... 89 75. Small Business Act for Europe (SBA) Factsheets...... 90 76. Sovereign Credit Rating (by Capital Intelligence) ...... 92 77. Sovereign Credit Rating (by FitchIBCA Duff&Phelps) ...... 93 78. Sovereign Credit Rating (by Moody's) ...... 95 79. Sovereign Credit Rating (by Standard and Poor's) ...... 96 80. Tax Misery and Reform Index ...... 97 81. Tourism Competitiveness Monitor ...... 98 82. Trade and Development Index (TDI) ...... 99 83. Transnationality Index of Host Economies ...... 100 84. UK Competitiveness Index ...... 101 85. World Competitiveness Scoreboard ...... 102 86. ZEW Indicator of Economic Sentiment ...... 103

Education ...... 104 87. Academic Ranking of World Universities (ARWU) ...... 104 88. Composite Learning Index (CLI) ...... 105 89. Education for All Development Index (EDI) and Gender related EFA Index (GEI) ...... 107 90. E-Readiness Index ...... 108 91. European Human Capital Index ...... 109 92. European Innovation Scoreboard (EIS) and Summary Innovation Index (SII) ...... 110 93. European Lifelong Learning Index (ELLI) ...... 112 94. Global Innovation Index (GII) ...... 113 95. ICT Opportunity Index ...... 114 96. Index of Knowledge Societies ...... 115 97. Innovation and Competitiveness Benchmark ...... 116 98. Innovation Capacity Index (ICI) ...... 117 99. Innovation Index ...... 118 100. Innovation Union Scoreboard (IUS) ...... 119 101. International Civic and Citizenship Education Study (ICCS) ...... 121 102. International Computer and Information Literacy Study (ICILS) ...... 122 103. Investment and Performance in the Knowledge Based Economy ...... 123 104. ITU Digital Access Index (DAI) ...... 124

Composite Indicators and Rankings: Inventory 2011 3 105. Knowledge Economy Index (KEI) ...... 125 106. Knowledge Index (KI) ...... 125 107. Knowledge-based Economy Index ...... 127 108. Programme for International Student Assessment (PISA) ...... 128 109. Progress in International Reading Literacy Study (PIRLS) ...... 129 110. QS World University Rankings ...... 130 111. Ranking Web of World Universities ...... 132 112. State Technology and Science Index...... 134 113. Technological Achievement Index (TAI) ...... 135 114. Technological Standing (TS) ...... 136 115. The Times Higher Education World Reputation Rankings ...... 138 116. Times Higher Education World University Rankings ...... 139 117. Trends in International Mathematics and Science Study (TIMSS) ...... 140 118. World Knowledge Competitiveness Index (WKCI) ...... 141

Environment ...... 143 119. Air Quality Index (AQI) ...... 143 120. Canadian Biodiversity Index (CBI) ...... 144 121. Climate Action Tracker ...... 145 122. Climate Analysis Indicators Tool (CAIT) ...... 147 123. Climate Change Performance Index (CCPI) ...... 148 124. Climate Change Vulnerability Index (CCVI) and Climate Change Risk Atlas ...... 149 125. Climate Competitiveness Index (CCI) ...... 150 126. Dashboard of Sustainability ...... 151 127. Ecological Footprint ...... 152 128. Environmental Degradation Index (EDI) ...... 153 129. Environmental Performance Index (EPI) ...... 154 130. Environmental Sustainability Index (ESI)...... 156 131. Environmental Vulnerability Index (EVI)...... 158 132. European Green City Index ...... 160 133. FEEM Sustainability Index (FEEM SI) ...... 161 134. Global Adaptation Atlas ...... 163 135. Global Climate Change Policy Tracker ...... 164 136. Global Climate Risk Index (CRI) ...... 165 137. Happy Planet Index ...... 166 138. Human Sustainable Development Index (HSDI) ...... 167 139. Index of Social Vulnerability to Climate Change (Africa) ...... 168

Composite Indicators and Rankings: Inventory 2011 4 140. Living Planet Index ...... 169 141. Low Carbon Competitiveness Index ...... 170 142. Social Vulnerability Index (SOVI)...... 172 143. National Biodiversity Index (NBI) ...... 173 144. Sustainability Rating ...... 174 145. Sustainable Society Index (SSI) ...... 175 146. Water Poverty Index (WPI) ...... 176

Governance ...... 177 147. Active Citizenship Composite Indicator (ACCI) ...... 177 148. African Governance Indicators ...... 179 149. Bribe Payers Index (BPI) ...... 181 150. CIFP Governance Index ...... 182 151. Cingranelli-Richards Human Rights Dataset ...... 183 152. Corruption Perception Index (CPI) ...... 184 153. Countries at the Crossroads ...... 185 154. Country Performance Assessments (CPA) ...... 187 155. Country Policy and Institutional Assessment (CPIA) and Country Performance Rating (CPR) ..188 156. Democracy Score (Nations in Transit Ratings) ...... 189 157. E-Government Development Index...... 190 158. E-Government Index ...... 191 159. EIU Political Instability Index ...... 192 160. Failed States Index ...... 193 161. Freedom of the Net Index...... 194 162. Freedom of the Press Index ...... 195 163. Global Corruption Barometer ...... 196 164. Global Integrity Index ...... 197 165. Global Peace Index (GPI) ...... 199 166. Global Political Risk Index (GPRI) ...... 200 167. Governance Indicators ...... 201 168. Human Rights Commitment Index...... 202 169. Human Rights Risk Atlas ...... 203 170. Ibrahim Index of African Governance ...... 204 171. Index of Democracy ...... 205 172. Index of State Weakness in the Developing World ...... 206 173. International Property Rights Index (IPRI) ...... 207 174. Latin American Index of Budget Transparency ...... 208

Composite Indicators and Rankings: Inventory 2011 5 175. Media Sustainability Index...... 209 176. Millennium Challenge Corporation Country Scorecards ...... 210 177. Opacity Index (O-Factor) ...... 211 178. Open Budget Index (OBI) ...... 212 179. Peace and Conflict Instability Ledger ...... 213 180. Political and Economic Risk Map ...... 214 181. Political Rights and Civil Liberties Ratings ...... 215 182. Political Risk Atlas ...... 216 183. Political Terror Scale ...... 217 184. Polity Country Scores ...... 218 185. Press Freedom Index ...... 219 186. Rule of Law Index ...... 220 187. The Observer Human Rights Index ...... 221 188. World Governance Assessment (WGA) ...... 222

Health ...... 223 189. Ageing Vulnerability Index ...... 223 190. AIDS Program Effort Index (API) ...... 224 191. Alcohol Policy Index ...... 225 192. Australian Federal Police Drug Harm Index ...... 227 193. Early Motherhood Risk Ranking ...... 228 194. EIU Quality of Death Index ...... 229 195. Global Burden of Disease (GBD) ...... 230 196. Health Utilities Index (HUI) ...... 231 197. Index of Social Health ...... 232 198. Mother's Index ...... 233 199. New Zealand Illegal Drugs Harm Index (NZ-DHI) ...... 234 200. Overall Health System Achievement Index ...... 235 201. Overall Health System Performance Index ...... 236 202. Reproductive Risk Index ...... 237

Wellbeing ...... 238 203. African Gender and Development Index (AGDI) ...... 238 204. American Human Development Index ...... 239 205. Assessing the Achievement of the Millennium Development Goals (MDGs) ...... 240 206. Basic Capabilities Index (BCI) ...... 241 207. Canadian Index of Wellbeing (CIW) ...... 242 208. Child and Youth Wellbeing Index (CWI) ...... 243

Composite Indicators and Rankings: Inventory 2011 6 209. Child Development Index ...... 244 210. Child Well Being Index ...... 245 211. Cochise County Quality of Life Index ...... 246 212. Crime Index ...... 247 213. Development Web Model ...... 248 214. EU Regional Human Development Index ...... 249 215. EU Regional Poverty Index ...... 250 216. Famine Early Warning System (FEWSNet)...... 251 217. Food Insecurity...... 253 218. Food Security Risk Index ...... 254 219. Gallup-Healthways Well-Being Index ...... 255 220. Gender Empowerment Measure (GEM) ...... 221. Gender Equity Index (GEI) ...... 222. Gender Inequality Index (GII) ...... 223. Girls Discovered...... 224. Global Gender Gap Index ...... 225. Global Hunger Index ...... 226. Global Quality of Living ...... 227. Happiness Indices...... 228. Human Development Index (HDI) ...... 229. Human Poverty Index (HPI) ...... 230. Illicit Drug Index (IDI) ...... 231. Index of Human Insecurity ...... 232. Index of Human Progress ...... 233. Inequality-adjusted Human Development Index (IHDI) ...... 234. International Index of Social Progress (ISP) ...... 235. Legatum Prosperity Index ...... 236. Most Livable Cities ...... 237. Multidimensional Poverty Assessment Tool (MPAT) ...... 238. Multidimensional Poverty Index (MPI) ...... 239. Netherlands Living Conditions Index (LCI) ...... 240. Personal Security Index (PSI) ...... 241. Physical Quality of Life Index (PQLI) ...... 242. Poverty and Hunger Index (PHI) ...... 243. Poverty Maps ...... 244. Pro-Poor Policy (PPP) Index ...... 245. Quality of Life Index ......

Composite Indicators and Rankings: Inventory 2011 7 246. Quality of Life Index ...... 247. Regional Index of Sustainable Economic Well-being (R-ISEW) ...... 248. Retirement Index ...... 249. Social Institutions and Gender Index (SIGI) ...... 250. Total Wealth and Genuine Savings ...... 251. UK Drug Harm Index ...... 252. UK Well-being Index (in development) ...... 253. Welfare Index ...... 254. Wellbeing Indices: Human Wellbeing Index (HWI), Ecosystem Wellbeing Index (EWI), Wellbeing Index (WI) and Wellbeing Stress Index (WSI) ...... 255. Women's Economic Opportunity Index ...... 256. World's Best Countries ......

Other ...... 257. Australian SAM Sustainability Index (AuSSI) ...... 258. BIC3D Index ...... 259. CIFP Fragility Index ...... 260. Civil Society Index ...... 261. Commitment to Development Index (CDI) ...... 262. Composite Index of National Capability (CINC) ...... 263. Cultural/Ethnic Homogeneity Preference Index ...... 264. Disaster Deficit Index (DDI) ...... 265. Disaster Risk Index (DRI) ...... 266. Dow Jones Sustainability Indexes ...... 267. Eco Index ...... 268. Environmental, Social and Governance Risks (ESG rating) ...... 269. E-Participation Index ...... 270. Ethibel Sustainability Index ...... 271. Ethics Index ...... 272. Ethno-linguistic and religious fractionalization Index and Political Instability Index ...... 273. Global Civil Society Index (GCSI) ...... 274. Global Firepower ...... 275. Global Go-To Think Tank Index ...... 276. Global Natural Disasters Risks Hotspots ...... 277. Humanitarian Response Index (HRI) ...... 278. Least Secure Countries ...... 279. Local Disaster Index (LDI) ...... 280. Major Military Spenders ......

Composite Indicators and Rankings: Inventory 2011 8 281. Mineral Extraction Risk Assessment (MERA) ...... 282. MSCI ESG Indices ...... 283. Official Development Assistance (ODA) Rankings ...... 284. Oxfam Survey of Donors' Practice ...... 285. Prevalent Vulnerability Index (PVI) ...... 286. Quality of ODA (QuODA) ...... 287. Risk Management Index (RMI) ...... 288. Terrorism Index ...... 289. Terrorism Risk Index (TRI) ...... 290. World City Network - Global network connectivity rankings ......

Composite Indicators and Rankings: Inventory 2011 9 Overview

The following document presents an update of the February 2008 survey of country indices that rank or assess countries according to some economic, political, social or environmental measure.3 The present update includes new indices launched between end- February 2008 and end-February 2011 and adds indices omitted in the previous surveys.

Definitions

The aim of the survey is to identify indices that rank or assess one country, regions, a group of countries, and institutions in a diverse set of fields grouped by 1) Economy 2) Education 3) Environment 4) Governance 5) Health 6) Wellbeing and 7) Other.

Organizations and academics elaborate composite indices, based on several indicators or sub-indices. These indicators and sub-indices are aggregated following some methodology to give an overall score for the unit of analysis. The scores are used to either create a ranking to show progress (or setbacks) or to simply present the data— without necessarily ranking the units.4

Rankings and assessments are also elaborated using a single indicator. In general rankings are elaborated under these methods:

. An elaborate index is prepared, composed of sub-indices which are weighted to give an overall score; . A simple index is constructed based on a subset of indicators; . A single indicator is used to rank the country.

Frequently, the way to present the rankings is through a “League Table” showing the index scores in descending order. An alternative form of presentation is categorical classifications based on a range of the numerical value of these indices (for example, Freedom House classifies the countries into “Free”, “Partially free” and “Not free”). Yet another form is to show—through colored bars or arrows—the progress or setbacks in a specific policy area (for example, the MDG’s assessments).

Methodology

The inventory presented in this document is not exhaustive.5 The research leading to the inventory was based on reports, websites, books, and academic papers. The inventory presents indices in alphabetical order, providing for each entry the author or organization

3 The original survey is Bandura, Romina. 2005. “Measuring Country Performance and State Behavior: A Survey of Composite Indices”. UNDP/ODS Background Paper, Office of Development Studies, New York. [www.thenewpublicfinance.org/background/measuring.pdf]. This is a third update to the original paper. 4 The literature on composite indices (and their methodologies) is vast. For references, see Bandura 2005. 5 It would be greatly appreciated, if readers, who are aware of indices not presented in this survey, would send their suggestions by email to [email protected]

Composite Indicators and Rankings: Inventory 2011 10 responsible for it, a description of the index and its methodology together with the year of creation, frequency of issuance and the relevant sources, including websites. This information corresponds to indices found in publications or websites, which are either updated frequently or are “one-time events”. Private firms offer online paid subscription services (for example, credit rating agencies or private consultancy firms) and often times do not disclose their methodologies to the public, thus only the limited information available in their websites is included in the inventory.

The description and methodology of these indices is taken directly from the author or organization, that is, they are excerpts from websites and publications. The sources from which these excerpts were taken are clearly listed in each index entry.

Composite Indicators and Rankings: Inventory 2011 11 Inventory of Indices (By field and in alphabetical order)

Important Note: Unless otherwise indicated, the methodology of indices that has been elaborated by private companies offering paid subscription services is the one disclosed solely by the company’s website.

Each entry contains the following information:

. Name of Index: how the index is identified in the websites or publications. . Developer (s): refers to the person and/or organization responsible for elaborating the index. . Year Launched / Latest Edition: refers to the year in which the index was elaborated and the last year in was updated. . Number of Dimensions / Description of Main Dimensions (weights): refers to the structure of the index and the weights (if disclosed). . Number of indicators: refers to the quantity of indicators used, either from objective or subjective data. . Units ranked: refers to the quantity of countries or institutions analyzed. . Link to Publication: URL of the report that contains the index or assessment. . Link to data: URL of the actual data / ranking. . Description and Methodology: refers to what the index intends to measure and how it is constructed

If in any entry the sign “−” or “N/A” appears, it means that no information is available.

The length of the methodology varies from index to index. Some developers disclose very detailed methodologies, others don’t.

Fields used:

. Economy (including country risk, competitiveness, globalization) . Education (including cultures, innovational, knowledge, learning, technology) . Environment . Governance (including human rights) . Health . Well-being (including poverty, gender, quality of life, development) . Other

Composite Indicators and Rankings: Inventory 2011 12 Economy

1. Alternative Country Risk Rating (IRPA)

Developer 1 CLAES Developer 2 D3E Year launched 2004 Latest Edition 2009 Field Economy Number of Main Dimensions 5 Description of Main Dimensions 1. Economic 2. Social 3. Environment 4. Institutions 5. Technology. 12 (Weights in Parenthesis) indicators chosen: 1. Primary exports as a % of total goods exports 2. Debt service as a % of total exports of goods and services 3. Protected areas as a % of total country surface 4. Carbon dioxide emissions in metric tons per capita 5. Social expenditure as a % of GDP 6. Literacy rate 7. Household income distribution 8. Gross enrollment rate 9. Internet users 10. Political and civil liberties 11. Support for Democracy 12. % of undernourished (Equal weights) Number of Underlying 12 Indicators Number of units ranked 18 Type of units ranked LAC countries Link to report http://www.economiasur.com/publicaciones/OdeDBuonomoGudynasR PaisActualizado09.pdf Link to data Annex to: http://www.economiasur.com/publicaciones/OdeDBuonomoGudynasR PaisActualizado09.pdf

The IRPA Index was constructed as an alternative to sovereign credit ratings and it expresses Latin American countries’ vulnerabilities in the social, political, economic and environmental spheres. The index is based on 11 indictors: 1. Primary exports as a % of total goods exports 2. Debt service as a % of total exports of goods and services 3. Protected areas as a % of total country surface 4. Carbon dioxide emissions in metric tons per capita 5. Social expenditure as a % of GDP 6. Literacy rate 7. Household income distribution 8. Gross enrollment rate 9. Internet users 10. Political and civil liberties 11. Support for Democracy. 12. . % of undernourished (Added in 2009)

For each of these 12 indicators a value of “acceptable risk” is calculated and a new variable is formed (for each indictor) based on this formula: (Value of the indicator for the country – Value of acceptable risk) / Value of acceptable risk. For each country, the values of these new 12 variables are added and then countries are ranked form highest value (meaning higher risk) to lower value (i.e. lower risk). Values of IRPA that fall between 1.0-5.0 are considered tolerable levels of risk; 5.01-10 indicates a threatening situation; 10.01-20 a critical situation and more than 20 is considered a situation of default.

Composite Indicators and Rankings: Inventory 2011 13 2. APESMA Big Mac Index

Developer 1 APESMA - Association of Professional Engineers Scientists and Managers, Australia Developer 2 Year launched N/A Latest Edition 2005 Field Economy Number of Main Dimensions 1 Description of Main Dimensions Purchasing power (Weights in Parenthesis) Number of Underlying Indicators 2 Number of units ranked 12 Type of units ranked Countries Link to report http://www.apesma.asn.au/students/careers/big_mac_index.asp Link to data N/A

An international comparison (but not ranking) of graduate engineer salaries. The index shows the number of minutes that a graduate engineer needs to work in selected countries to purchase a Big Mac. The comparison assumes a 40-hour week.

Composite Indicators and Rankings: Inventory 2011 14 3. BAK Economic Attractiveness Index

Developer 1 BAK Basel Economics Developer 2 Year launched 2008 Latest Edition 2008 Field Economy Number of Main Dimensions 4 Description of Main Dimensions 1. Taxation (personal and business rates) 30%, 2. Accessibility (Weights in Parenthesis) (global and continental) 20%, 3. Regulation (labor market, product market) 20% and 4. capacity for innovation (patents, publications and Shanghai Index) 30% Number of Underlying Indicators 9 Number of units ranked 192 Type of units ranked Regions of Europe Link to report http://www.bakbasel.ch/wDeutsch/services/news_media/media/medi enmitteilungen/2008/098_attractiveness_performance_indexW3Dna vanchorW261010022.shtml Link to data http://www.bakbasel.ch/downloads/services/news_media/media/med ienmitteilungen/2008/20080904_mm_attractiveness_performance_in dex_en.pdf

BAK Basel Economics looked into the following question: what makes an economic region attractive to whom and why? The analyses show that attractiveness is the key to economic regions achieving better economic performance.

The BAK Economic Attractiveness Index comprises the following indicators: taxation (personal and business rates), accessibility (global and continental), regulation (labor market, product market) and capacity for innovation (patents, publications and Shanghai Index). Among these indicators, taxation and capacity for innovation are regarded as slightly more important and, at 30% each, are weighted somewhat higher than accessibility and regulation, which are weighted at 20% each. The BAK Performance Index is calculated as follows: per capita GDP (50% weighting), GDP growth and employment growth (25% each). The indexes encompass 192 regions of Western Europe, defined according to the official NUTS2 classification.

Composite Indicators and Rankings: Inventory 2011 15

4. Bertelsmann Transformation Index

Developer 1 Bertelsmann Foundation Developer 2 Year launched 2001 Latest Edition 2010 Field Economy Number of Main Dimensions 2 Description of Main Dimensions 2 indices: 1. Status Index (democracy and market economy) 2. (Weights in Parenthesis) Management Index Number of Underlying Indicators 17 criteria subdivided in 52 questions Number of units ranked 128 Type of units ranked Countries Link to report http://www.bertelsmann-transformation- index.de/11.0.html?&L=1 Link to data http://www.bertelsmann-transformation-index.de/en/bti/ranking/

The BTI provides the international public and political actors with a comprehensive view of the status of democracy and a market economy as well as the quality of political management in each of these countries. It consists of the Status Index, the Management Index, and a Trend Indicator. The scores given in the Status Index are comprised of two indices that measure the status of transition to democracy and a market economy. The Management Index establishes the quality of political management and the Trend Indicator informs about the direction of development with respect to constitutional democracy and a socially responsible market economy during the period of analysis 2007-09. The three indices are comprised of a number of specific scores. Using detailed indicators, experts on the 128 countries measured the extent to which twenty-three criteria were fulfilled.

The Status Index shows the development achieved by 128 states on their way toward democracy and a market economy. States with functioning democratic and market-based structures receive the highest scores. Evaluations are based on a set of eighteen political and fourteen economic indicators, encompassing the following 12 criteria. Criteria for democracy status: stateness, political participation, rule of law, institutional stability and political and social integration. Criteria for market economy status: level of socioeconomic development, market structures and competition, currency and price stability, private property, welfare regime, strength of the economy and sustainability.

The Management Index reveals the extent to which governments and political actors have been consistent and determined in their pursuit of a market-based democracy. Those states showing progress in the last five years and in which transformation has resulted from astute management receive the highest scores. The assessments are based on a set of twenty indicators used in measuring the five following criteria: reliable pursuit of goals, effective use of resources, governance capability, consensus building and international cooperation.

The trend indicator refers to the development of political as well as economic transformation. If the difference in score between the BTI 2008 and BTI 2010 is at least 0.5, an improvement or deterioration is indicated. If the difference is 1.0 or greater, this is noted as major change.

Status Index: The Status Index's overall result represents the mean value of the scores for the dimensions "Political Transformation" and "Economic Transformation". The mean value was calculated using the exact, unrounded values for both these dimensions, which, in turn, were derived from the ratings for the five political criteria (based on 18 indicators) and the seven economic criteria (based on 14 indicators).

Composite Indicators and Rankings: Inventory 2011 16 5. Best Performing Cities

Developer 1 Milken Institute Developer 2 Year launched 1999 Latest Edition 2010 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Job growth 2. Wage and salary growth, and 3. technology (Weights in Parenthesis) growth. Job growth (I=2004) 0.143, Job growth (I=2008) 0.143, Wage and salary growth (I=2003) 0.143, Wage and salary growth (I=2007) 0.143, Short-term job growth (Apr09-Apr10) 0.143, Relative high-tech GDP growth (I=2004) 0.071, Relative high-tech GDP growth (I=2008) 0.071, High-tech GDP location quotient 0.071, Number of high-tech industries with GDP LQ>1 0.071 Number of Underlying Indicators 9 Number of units ranked 200 Type of units ranked US Metro areas Link to report http://www.milkeninstitute.org/publications/publications.taf?cat=R

esRep&function=detail&ID=38801250 Link to data http://www.milkeninstitute.org/publications/publications.taf?cat=R

esRep&function=detail&ID=38801250

The Best-Performing Cities index was designed to measure objectively which U.S. metropolitan areas are most successful in terms of job creation and retention, the quality of jobs being produced, and overall economic performance. Specifically, it pinpoints where jobs are being created and maintained, where wages and salaries are increasing, and where economies and businesses are growing and thriving. The index allows businesses, industry associations, economic development agencies, investors, academics, government officials, and public policy groups to assess, monitor, and gain insight into each metro’s relative performance. It also provides benchmarking data that can be used in developing strategies to improve and maintain a metro’s economic performance. Moreover, it is a tool for understanding consumer markets and business expansion opportunities.

The components shown below are used to calculate our index rankings. The index measures growth in jobs, wages and salaries, and technology output over a five-year span (2004– 2009 for jobs and technology output and 2003-2008 for wages and salaries) to adjust for extreme variations in business cycles. It also incorporates the latest year’s performance in these areas (2008– 2009 for jobs and technology output and 2007–2008 for wages and salaries). Lastly, it includes 12-month job growth performance (April 2009 to April 2010) to capture relative recent momentum among metropolitan economies.

Component Weights: Job growth (I=2004) 0.143, Job growth (I=2008) 0.143, Wage and salary growth (I=2003) 0.143, Wage and salary growth (I=2007) 0.143, Short-term job growth (Apr09-Apr10) 0.143, Relative high-tech GDP growth (I=2004) 0.071, Relative high-tech GDP growth (I=2008) 0.071, High-tech GDP location quotient 0.071, Number of high-tech industries with GDP LQ>1 0.071 Note: I refers to the beginning year of index.

The Best-Performing Cities index is solely an outcomes-based measure. It does not incorporate explicit input measures (business costs; cost-of-living components, such as housing; and other quality-of-life measures, such as commute times or crime rates). Static input measures, although important, are subject to large variations and can be highly subjective, making them less meaningful than more objective indicators of outcome.

Composite Indicators and Rankings: Inventory 2011 17

6. Big Mac Index

Developer 1 The Economist Developer 2 Year launched 1986 Latest Edition 2010 Field Economy Number of Main Dimensions 1 Description of Main Dimensions (Weights in Parenthesis) Purchasing power Number of Underlying Indicators 2 Number of units ranked 120 Type of units ranked Countries Link to report http://www.economist.com/markets/bigmac/about.cfm Link to data http://www.economist.com/markets/bigmac/about.cfm

This index is based on the Purchasing Power Parity theory and aims to determine if the currency of a country is at the right level, using as a basket the Big Mac hamburger sold by McDonald’s. The methodology consists of a Big Mac PPP - the exchange rate that would leave a burger in that country costing the same as in the US (the Big Mac PPP is the local price of a Big Mac divided by the American dollar price). This Big Mac PPP is then compared to the actual exchange rate of the country. If the actual exchange rate is higher than the Big Mac PPP, the currency is undervalued.

Composite Indicators and Rankings: Inventory 2011 18

7. BradyNet Ratings Ladder

Developer 1 BradyNet Inc Developer 2 Year launched 2000 Latest Edition 2003 Field Economy Number of Main Dimensions N/A Description of Main Dimensions (Weights in Parenthesis) N/A Number of Underlying Indicators N/A Number of units ranked N/A Type of units ranked Countries Link to report http://www.bradynet.com/e907.html Link to data http://www.bradynet.com/e907.html

The ratings ladder is the calculated average rating of the four agencies participating on BradyNet: Moody's, S&P, FitchIBCA Duff & Phelps, and Thomson Financial Bankwatch. Specific points are assigned to each possible rating level. Starting with 100 points assigned to a perfect AAA (or Aaa) rating, points are then subtracted for every ratings level below AAA for each country. In case of a positive or negative outlook, 1 point is added or subtracted, respectively. The average is calculated from these assigned points.

Composite Indicators and Rankings: Inventory 2011 19

8. Capital Access Index (CAI)

Developer 1 Milken Institute Developer 2 Year launched 1998 Latest Edition 2009 Field Economy Number of Main Dimensions 7 Description of Main Dimensions 1. Macroeconomic environment (ME 25%) 2. Institutional (Weights in Parenthesis) environment (IE 25%) 3. financial and banking institutions (FI 10%) 4/ equity market development (EM 10%) 5. bond market development (BM 10%) 6. alternative sources of capital (AC 10%) 7. international funding (IF 10%). Number of Underlying Indicators 56 Number of units ranked 122 Type of units ranked Countries Link to report http://www.milkeninstitute.org/publications/publications.taf?cat= ResRep&function=detail&ID=38801238 Link to data Tables and annexes of http://www.milkeninstitute.org/publications/publications.taf?cat= ResRep&function=detail&ID=38801238

The Capital Access Index is Capital Access Index, an annual ranking of entrepreneurial access to capital around the world. The index helps businesses and entrepreneurs discern which countries’ capital markets have the most breadth, depth and vitality. It is based on the evaluation of seven components comprised of 56 variables: macroeconomic environment (ME), institutional environment (IE), financial and banking institutions (FI), equity market development (EM), bond market development (BM), alternative sources of capital (AC), and international funding (IF).

To calculate component scores, first the non-surveyed or missing variables in the FI, EM, BM, AC, and IF components are assigned a score of zero. This step reflects the fact that the variable in question is so small that its effect on capital access is immaterial. For some countries, non-surveyed variables are missing due to slow data reporting but exist for prior years. In these cases, the prior year’s values are used for the current year rather than assigning a score of zero. Second, the variables are ranked by decile according to the directional relationship to capital access. The resulting scores of one to 10 are then assigned for countries ranking lowest to highest in terms of capital access. The score for each subcategory is calculated by a simple average of the variables, but only if the data in the category are greater than or equal to 50 percent of the total variables in that category. Third, the Capital Access Index is calculated using the weighted average of the seven components. The first two components, ME and IE, are weighted 25 percent each. The other five components, FI, EM, BM, AC, and IF, are each weighted as 10 percent of the final CAI score.

Theoretically, the scores can range from zero to 10. However, because every country has some kind of macroeconomic and institutional structure, the minimum for each of these two categories is one; therefore the lowest possible score is 0.5.

Composite Indicators and Rankings: Inventory 2011 20

9. Composite Indicators of Flexicurity

Developer 1 European Commission Joint Research Centre (EC -JRC) Developer 2 Year launched 2010 Latest Edition 2010 Field Economy Number of Main Dimensions 4 Description of Main Dimensions 1. Lifelong Learning (LLL) 2. Active Labor Market Policies (Weights in Parenthesis) (ALMP) 3. Modern Social Security Systems (MSS) and 4. Flexible and Reliable Contractual Arrangements (FCA) Number of Underlying Indicators 64 Number of units ranked 23 Type of units ranked EU Link to report http://publications.jrc.ec.europa.eu/repository/handle/111111111/135 18 Link to data http://ec.europa.eu/social/main.jsp?langId=en&catId=89&newsId=9

08&furtherNews=yes

The European Commission’s Lisbon Agenda aims to enhance both flexibility and security in the labour markets in order to reconcile competitiveness and sustainable economic growth with more and better jobs and greater social cohesion (COM(2007)359). The pursuit of a balance between flexibility and security addresses simultaneously -the flexibility of labour markets, work organization and labour relations, and - security, including employment and social security for weaker groups in and out of the labour market. The project aimed to develop statistical tools to measure flexicurity achievements of EU Member States through a set of four composite indicators corresponding to the four dimensions of flexicurity identified by the Commission (COM(2007)359): 1. Lifelong Learning (LLL) 2. Active Labour Market Policies (ALMP) 3. Modern Social Security Systems (MSS) and 4. Flexible and Reliable Contractual Arrangements (FCA).

Life Long Learning Composite Indicator: A set of 9 indicators has been selected for the construction of the Life Long Learning Composite Indicator. The weighting scheme adopted for the construction of the Life Long Learning Composite Indicator strictly follows the suggestion addressed in the LIME project. All indicators were assigned the same weight (100). Indicators referred to gender (Male and Female) were given the weight of 50. All the weights have been then rescaled to sum 1. The structure of the composite indicator is very simple. It was decided not to include different levels of aggregation of the indicators. The composite indicator is computed putting all input indicators at the same level.

The Active labour market policies (ALMP) Composite Indicator: A set of 16 indicators were selected, all of them drawn from a unique data source: the Eurostat’s Labour Market Policies database. This source covers all labour market policies or interventions undertaken by Member States, which are divided in three main categories:

1. Services: This category refers to labour market interventions where the main activity of participants is job search-related and where participation usually does not result in a change of labour market status. 2. Regular Activation Measures: This category refers to labour market interventions where the main activity of participants is other than job-search related and where participation usually results in a change in labour market status. 3. Support: This category refers to interventions that provide financial assistance, directly or indirectly, to individuals for labour market reasons or which compensate individuals for disadvantages caused by labour market circumstances.

The LMP database is based on the collection of information from administrative sources, relating to public expenditure on and participants to the different types of labour market programs. As the construction of the

Composite Indicators and Rankings: Inventory 2011 21 ALMP index is exclusively focused on active policies, only indicators referring to the first two categories (i.e. services and activation measures) were retained. In fact, support measures essentially concern monetary transfers, i.e. measures of a more passive nature; hence they will be the focus of the Composite indicator on the social security component of flexicurity.

The weighting scheme adopted for the construction of the Composite Indicator consists of attributing equal weights to all indicators within the same dimension. This strategy avoids rewarding those dimensions which include more indicators (e.g. Expenditure as percentage of GDP) relative to those with fewer ones (e.g. Spending/participants per person wanting to work). As a result, although variables are not given the same weight overall, all dimensions included in the indicator are equally important. The composite indicator for ALMPs has a relatively simple structure although, unlike the indicator for LLL, it includes different levels of aggregation of input indicators. It consists of three different pillars or dimensions, corresponding to those highlighted in section 2 and in table 1 above: 1. Overall expenditure on ALMPs (i.e. spending as a share of GDP); including 7 indicators corresponding to the different types of policies. 2. ALMPs spending per participant; including 6 indicators (as there is no participants' number for labour market services). 3. Intensity of ALMPs per person wanting to work; including 3 indicators.

The Modern Social Security Systems (MSS) Composite Indicator: The social security systems are considered in a narrow sense, as the focus lies mainly on transfers to the unemployed, thereby disregarding other categories of welfare spending such as health care, pensions etc. 20 indicators have been selected from different sources. Therefore, the Modern Social Security (MSS) index covers five dimensions, each including a number of indicators varying from 3 to 7: 1. Overall spending and coverage of unemployment benefits.. 2. Financial incentive to take up work for people out of employment. 3. Amount and duration of individual unemployment benefits.. 4. Childcare services.

The weighting scheme adopted for the construction of the MSS index consists of attributing equal weights to all indicators within the same dimension. This strategy avoids rewarding those dimensions which include more indicators (e.g. financial incentives) relative to those with fewer ones (e.g. overall spending and coverage of unemployment benefits). The only exceptions concern the dimension of childcare services, where a double weight was attributed to indicators of care availability for 30 hours or more, relative to those for less than 30 hours. As a result, all dimensions included in the index are equally important, although individual variables do not necessarily have the same weight across different dimensions. The three composite indicators for Modern Social Security Systems share a simple structure. It consists of four different dimensions:

1 Overall expenditure and coverage of unemployment benefits, including three indicators. 2 Financial Incentives to take up a job, including 5 indicators. 3 Amount and duration of individual unemployment benefits; including 6 indicators, as the strictness of rules for unemployment benefits' recipients is excluded. 4 Childcare services, including 6 indicators.

The Flexible and reliable Contractual Arrangement (FCA) Composite Indicator: The flexible and reliable contractual arrangements (FCA) dimension of flexicurity is computed by using 19 indicators. The Flexible and reliable Contractual Arrangement (FCA) index covers three dimensions, each of them including a number of indicators (which varies across dimensions). Dimensions and indicators: 1) Regulations on dismissals and use of flexible contractual forms – external flexibility. 2) Flexibility of working time - internal flexibility. 3) Flexibility of work organisation to help combine work and family responsibilities

The weighting scheme adopted for the construction of the FCA index consists of attributing equal weights to all indicators within the same dimension. This strategy avoids rewarding those dimensions which include more indicators (e.g. internal flexibility) relative to those with fewer ones (e.g. flexibility of work organization to help combine work and family responsibilities). There is only exception to this rule which concerns atypical work, where all five variables have been weighted as one single variable. As a result, all dimensions included in the index are equally important, although individual variables do not necessarily have the same weight across different dimensions.

Composite Indicators and Rankings: Inventory 2011 22 10. Composite Score of Risk (BRS)

Developer 1 BERI Developer 2 Year launched 1967 Latest Edition 2010 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Operations Risk Index (ORI), 2. Political Risk Index (PRI), 3. (Weights in Parenthesis) Remittance and Repatriation Factor (R-Factor). Number of Underlying Indicators N/A Number of units ranked 50 Type of units ranked Countries Methodology N/A Link to report http://www.beri.com/brs.asp Link to data http://www.beri.com/brs.asp

Composite Indicators and Rankings: Inventory 2011 23 11. Consumer Confidence Index (CCI)

Developer 1 The Conference Board Developer 2 Year launched 1967 Latest Edition 2011 Field Economy Number of Main Dimensions 5 Description of Main Dimensions 1. Current business conditions. 2. Current employment conditions. (Weights in Parenthesis) 3. Business conditions six months hence. 4. Employment conditions six months hence. 5. Total family income six months hence. Number of Underlying Indicators 5 Number of units ranked 1 Type of units ranked US Methodology On a Separate Word Doc Link to report http://www.conference-board.org/data/consumerdata.cfm Link to data http://www.conference-board.org/data/consumerconfidence.cfm

The Consumer Confidence Index (CCI) is a barometer of the health of the U.S. economy from the perspective of the consumer. The index is based on consumers’ perceptions of current business and employment conditions, as well as their expectations for six months hence regarding business conditions, employment, and income. The Consumer Confidence Index and its related series are among the earliest sets of economic indicators available each month and are closely watched as leading indicators for the U.S. economy. The CCS concepts and questions used to compute the Consumer Confidence Index, Present Situation Index, and Expectations Index are still the same. The indexes are based on responses to five questions in the survey:

Present Situation Index 1. Respondents’ appraisal of current business conditions. 2. Respondents’ appraisal of current employment conditions.

Expectations Index 3. Respondents’ expectations regarding business conditions six months hence. 4. Respondents’ expectations regarding employment conditions six months hence. 5. Respondents’ expectations regarding their total family income six months hence

Each of the five CCS survey questions has three response options: positive, negative, or neutral. The response proportions to each question are seasonally adjusted. For each question, the positive figure is divided by the sum of the positive and negative to yield a proportion, which we call the "relative" value. For each question, the average relative value for the calendar year 1985 is then used as a benchmark to yield the index value for that question. The indexes are then averaged together as follows:

. Consumer Confidence Index: Average of all five indexes . Present Situation Index: Average of indexes for questions 1 and 2 . Expectations Index: Average of indexes for questions 3, 4, and 5

Data as of January 2011 (final) use the Census X-12 seasonal adjustment software for the publication series where needed. Seasonal adjustment helps remove periodic seasonal fluctuations in the series due to events such as weather, holidays, and the beginning and end of the school year. While the CCS series are typically not highly seasonal, the X-12 software helps reduce any residual seasonality in the various data series.

Composite Indicators and Rankings: Inventory 2011 24 12. Cost of Doing Business

Developer 1 Milken Institute Developer 2 Year launched 2005 Latest Edition 2007 Field Economy Number of Main Dimensions 5 Description of Main Dimensions 1. Wage 2. Office rent 3. Industrial rent 4. Tax cost 5. Electricity (Weights in Parenthesis) cost Number of Underlying Indicators N/A Number of units ranked 50 Type of units ranked US states Methodology N/A Link to report http://www.milkeninstitute.org/publications/publications.taf?cat =indexes&function=detail&ID=29&type=CDB Link to data http://www.milkeninstitute.org/publications/publications.taf?cat =indexes&function=detail&ID=29&type=CDB

The Cost-of-Doing-Business Index indicates each state’s comparative advantages or disadvantages in attracting and retaining businesses. Each state is measured on the five individual categories, and those weighted scores are compiled to make the overall index. An index score of 100 means that the state is equal to the U.S. average in that particular category.

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13. Cost of Living Survey

Developer 1 Mercer Developer 2 Year launched N/A Latest Edition 2010 Field Economy Number of Main Dimensions 6 Description of Main Dimensions 1. Housing 2. Transport 3. Food 4. Clothing 5. Household goods (Weights in Parenthesis) and 6. Entertainment Number of Underlying Indicators 200 Number of units ranked 214 Type of units ranked Cities Link to report http://www.mercer.com/costofliving Link to data http://www.mercer.com/costoflivingpr#City_rankings

The Mercer survey covers 214 cities across five continents and measures the comparative cost of over 200 items in each location, including housing, transport, food, clothing, household goods and entertainment. It is the world’s most comprehensive cost of living survey and is used to help multinational companies and governments determine compensation allowance for their expatriate employees. New York is used as the base city for the index and all cities are compared against New York. Currency movements are measured against the US dollar. The cost of housing – often the biggest expense for expats - plays an important part in determining where cities are ranked.

Composite Indicators and Rankings: Inventory 2011 26 14. Country @ratings

Developer 1 COFACE Developer 2 Year launched 2005 Latest Edition 2010 Field Economy Number of Main Dimensions 7 Description of Main Dimensions 1) Growth vulnerability 2) Foreign currency liquidity crisis 3) (Weights in Parenthesis) External over indebtedness 4) Sovereign financial vulnerability 5) Banking sector's fragilities 6) Fragility of governance and geopolitical environment 7) Companies' payment behaviour. Number of Underlying Indicators N/A Number of units ranked 165 Type of units ranked Countries Link to report http://www.coface.com/CofacePortal/COM_en_EN/pages/home/ri sks_home/country_risks Link to data N/A

The Country @rating reflects the average level of short-term non-payment risk associated with companies in a particular country. It reflects the extent to which a country's economic, financial, and political outlook influences financial commitments of local companies. However, international trade actors know that sound companies can operate in risky countries and unsound companies in less-risky countries and that overall risk will depend not only on a company's qualities but also on those of the country in which it operates. Ratings are based on twofold expertise: macroeconomic expertise in assessing country risk based on a battery of macroeconomic financial and political indicators and microeconomic expertise that draws on Coface databases covering 50 million companies worldwide and 50 years experience with payment in trade flows it guarantees.

Country @ratings is calculated via a battery of indicators, grouped in seven families and rates each one individually. The seven risk families are: 1) Growth vulnerability 2) Foreign currency liquidity crisis 3) External over indebtedness 4) Sovereign financial vulnerability 5) Banking sector's fragilities 6) Fragility of governance and geopolitical environment 7) Companies' payment behaviour. Coface determines an overall rating for each of the 150 countries monitored. Like rating agencies, Coface ranks country ratings on seven risk levels.

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15. Country Risk Evaluation and Assessment Model (CREAM)

Developer 1 Exclusive Analysis Developer 2 Year launched 2004 Latest Edition 2010 Field Economy Number of Main Dimensions 4 Description of Main Dimensions (Weights in Parenthesis) 1. War 2. Terrorism 3. Civil Unrest and 4. Political Risk Number of Underlying Indicators N/A Number of units ranked 108 Type of units ranked Countries Link to report http://www.exclusive-analysis.com/services/cream.html Link to data http://www.exclusive-analysis.com/services/cream.html

It forecasts violent and political risks, including war, terrorism, civil unrest and business risks. The numbers on CREAM range from 0 to 10, and are designed to represent assessment of risks to assets and people. They are an aggregation of the incidents which are forecast to occur under each risk category in the various countries (combining the frequency and the scale of damage caused). There are four main categories of risk: 1. War 2. Terrorism 3. Civil Unrest and 4. Political Risk For each country, these four categories are given numerical ratings on thirty day, one year and three year horizons. They are therefore predictive, and represent the average level of risk to assets and people over the time periods in question. The ratings are as follows:

3.2 and above Severe risk 2.4 to 3.1 High risk 1.6 to 2.3 Elevated risk 0.8 to 1.5 Caution 0 to 0.7 Low risk

Composite Indicators and Rankings: Inventory 2011 28

16. Country Risk Monitoring Service

Developer 1 Political and Economic Risk Consultancy, Ltd. (PERC) Developer 2 Year launched 1976 Latest Edition 2010 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 9 Type of units ranked Asian Countries Link to report http://asiarisk.com/ Link to data N/A

It provides reports on the individual countries covered by their network that demonstrate how and why risk are changing in the country concerned and what companies should be watching for in the near and medium- term that could affect the business environment.

Composite Indicators and Rankings: Inventory 2011 29

17. CSGR Globalisation Index

Developer 1 Warwick University (CSGR -Lockwood and Redoano) Developer 2 Year launched 2005 Latest Edition 2010 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Economic 2. Social 3. Political (Weights in Parenthesis) Number of Underlying Indicators 16 Number of units ranked 200 Type of units ranked Countries Link to report http://www2.warwick.ac.uk/fac/soc/csgr/index/ Link to data http://www2.warwick.ac.uk/fac/soc/csgr/index/download

The index measures the economic, social and political dimensions of globalisation for countries on an annual basis and combines these into an overall globalisation index, or score. First, they construct three separate sub-indices of globalisation (economic, social, and political). Then they calculate the simple unweighted average of these three sub-indices to give an overall globalisation index. The method used is panel normalisation. To illustrate, suppose the variable is trade. First, the minimum and maximum values of this variable over the years 1970-2001, and over all countries, are found. In the case of the trade variable, it turns out that the maximum is 1448 %, for Netherlands Antilles in 1980, and the minimum is 6%, for Sudan in 1987. Then, if the trade variable for some country (say the UK) in some year is x%, then the panel normalised value of x is

y = (x – 6)/(1448-6)

Note that with this normalisation, all values of y lie between zero and one. Note also that, with this method, the means and the variances of different variables can still be different to each other, although they will be much closer to each other than before panel normalisation.

Once the different variables in the index have been normalised, they have to be ‘added together’ to generate the index. The index is constructed by taking a weighted average of the variables, where the weights are positive and add up to one. The weights have been chosen to maximise the informativeness of the index: statistically optimal weights. Briefly, statistically optimal weighting (or principal component weighting, as it is more properly known) works as follows. Take for example, the four variables that make up the economic globalisation index. In 2000, these were available for 119 countries. Thus, in 2000, they are using 119x4 pieces of information. When they aggregate these four variables to make the index, they end up with only one piece of information about each country: thus they are ‘throwing away’ 119x3 pieces of information. Statistically optimal weighting ensures that when they do this, they retain as much as possible of the original information about the countries.

Composite Indicators and Rankings: Inventory 2011 30

18. DHS Wealth Index

Developer 1 ICF Macro Developer 2 Year launched 2004 Latest Edition 2004 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 1 Type of units ranked US Link to report http://www.measuredhs.com/topics/wealth/methodology.cfm Link to data http://www.measuredhs.com/topics/wealth/methodology.cfm

The Wealth Index is a composite measure of the cumulative living standard of a household. The wealth index is calculated using easy-to-collect data on a household’s ownership of selected assets, such as televisions and bicycles, materials used for housing construction, and types of water access and sanitation facilities. Generated with a statistical procedure known as principal components analysis, the Wealth Index places individual households on a continuous scale of relative wealth.

Information on the wealth index is based on data collected in the Household Questionnaire. This questionnaire includes questions concerning the household’s ownership of a number of consumer items such as a television and car; dwelling characteristics such as flooring material; type of drinking water source; toilet facilities; and other characteristics that are related to wealth status. Each household asset for which information is collected is assigned a weight or factor score generated through principal components analysis. The resulting asset scores are standardized in relation to a standard normal distribution with a mean of zero and a standard deviation of one. These standardized scores are then used to create the break points that define wealth quintiles as: Lowest, Second, Middle, Fourth, and Highest.

Each household is assigned a standardized score for each asset, where the score differs depending on whether or not the household owned that asset (or, in the case of sleeping arrangements, the number of people per room). These scores are summed by household, and individuals are ranked according to the total score of the household in which they reside. The sample is then divided into population quintiles -- five groups with the same number of individuals in each. A single asset index is developed on the basis of data from the entire country sample and used in all the tabulations presented. Separate asset indices are not prepared for rural and urban population groups on the basis of rural or urban data, respectively.

Wealth quintiles are expressed in terms of quintiles of individuals in the population, rather than quintiles of individuals at risk for any one health or population indicator. All health, nutrition and population indicators are calculated after applying the sampling weights so that the resulting numbers are generalizable to the total population. For each indicator in these tables, the total or population average presented is the weighted sum of the quintile values for that indicator, where the weight assigned to each quintile value is the proportion of the total number of individuals at risk in that quintile. The total value for indicators produced by this weighting scheme are representative of the total population, as they take into account the fact that the numbers of individuals at risk may vary across wealth quintiles. Similarly, each quintile value itself can be reproduced as a weighted average of urban/rural rates (weighted by proportions urban/rural) or the male/female rates (weighted by the proportion male/female). As a result of this weighting scheme, the population average for a given indicator presented in the tables will usually differ from a simple mean of the population subgroups.

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19. Ducroire/Delcredere Country Risks

Developer 1 Ducroire/Delcredere Developer 2 Year launched 1990 Latest Edition 2010 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 245 Type of units ranked Countries Link to report http://www.ducroiredelcredere.be/WebDucDel/Website.nsf /weben/Country+risks?OpenDocument Link to data http://www.ducroiredelcredere.be/WebDucDel/Website.nsf /weben/Country+risks?OpenDocument

Ducroire | Delcredere makes quantitative and qualitative assessment of risks. The result of this analysis is, for each country and the various types of insured transactions, the setting of premium categories, country insurance ceilings and, if necessary, some particular terms of cover.

1. Premium categories for the insurance of export transactions 1.a. Political risk assessment 1.b. Commercial risk assessment 2. Cover capacity by country 3. Particular terms of cover 4. Market size indicators on www.ondd.be

Composite Indicators and Rankings: Inventory 2011 32 20. Ease of Doing Business Index

Developer 1 World Bank Developer 2 IFC Year launched 2004 Latest Edition 2011 Field Economy Number of Main Dimensions 9 Description of Main Dimensions 1. Starting a business 2. dealing with construction permits 3. (Weights in Parenthesis) registering property 4. getting credit 5. protecting investors 6. paying taxes 7. trading across borders 8. enforcing contracts and 9. closing a business Number of Underlying Indicators N/A Number of units ranked 183 Type of units ranked Countries Link to report http://doingbusiness.org/reports/doing-business/doing-business-

2011 Link to data http://doingbusiness.org/reports/doing-business/doing-business-

2011

The indicators presented and analyzed in Doing Business measure business regulation and the protection of property rights—and their effect on businesses, especially small and medium-size domestic firms. First, the indicators document the degree of regulation, such as the number of procedures to start a business or to register and transfer commercial property. Second, they gauge regulatory outcomes, such as the time and cost to enforce a contract, go through bankruptcy or trade across borders. Third, they measure the extent of legal protections of property, for example, the protections of investors against looting by company directors or the range of assets that can be used as collateral according to secured transactions laws. Fourth, a set of indicators documents the tax burden on businesses. Finally, a set of indicators measures different aspects of employment regulation.

The Doing Business data are collected in a standardized way. The Doing Business team, with academic advisers, designs a survey. The survey uses a simple business case to ensure comparability across economies and over time—with assumptions about the legal form of the business, its size, its location and the nature of its operations. Surveys are administered through more than 8,200 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials and other professionals routinely administering or advising on legal and regulatory requirements. The data from surveys are subjected to numerous tests for robustness. The ease of doing business index ranks economies from 1 to 183. For each economy the index is calculated as the ranking on the simple average of its percentile rankings on each of the 9 topics included in the index: starting a business, dealing with construction permits, registering property, getting credit, protecting investors, paying taxes, trading across borders, enforcing contracts and closing a business. The ranking on each topic is the simple average of the percentile rankings on its component indicators. If an economy has no laws or regulations covering a specific area—for example, bankruptcy—it receives a “no practice” mark. Similarly, an economy receives a “no practice” or “not possible” mark if regulation exists but is never used in practice or if a competing regulation prohibits such practice. Either way, a “no practice” mark puts the economy at the bottom of the ranking on the relevant indicator. Higher rankings indicate simpler regulation and stronger protection of property rights. More complex aggregation methods— such as principal components and unobserved components—yield a nearly identical ranking. The choice of aggregation method has little influence on the rankings because the 9 sets of indicators provide sufficiently broad coverage across topics. Doing Business also uses a simple method to calculate which economies improve the most on the ease of doing business. First, it selects the economies that reformed in 3 or more of the 9 topics included in this year’s ease of doing business ranking. Second, Doing Business ranks these economies on the increase in their ranking on the ease of doing business from the previous year using comparable rankings.

Composite Indicators and Rankings: Inventory 2011 33 21. ECA Cost of Living Survey

Developer 1 ECA International Developer 2 Year launched N/A Latest Edition 2010 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Food 2. Basic 3. General (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 100 Type of units ranked Cities Link to report http://www.eca- international.com/news/press_releases/7276/Hong_Kong___co st_of_living_continues_to_rise_ Link to data http://www.eca- international.com/news/press_releases/7276/Hong_Kong___co st_of_living_continues_to_rise_

ECA International’s cost of living indices are calculated based upon surveys carried out annually in March and September using a basket of day-to-day goods and services. The data used above refers to year on year movements between ECA’s September 2010 and 2009 surveys. The data is used by ECA clients to calculate cost of living allowances for assignees.

The survey covers: Food: Groceries; dairy produce; meat and fish; fresh fruit and vegetables Basic: Drink and tobacco; miscellaneous goods; services General: Clothing; electrical goods; motoring; meals out

Certain living costs such as accommodation, utilities (electricity, gas, water costs), car purchase and school fees are not included in the survey. Such items can make a significant difference to expenses but are usually compensated for separately in expatriate packages.

Composite Indicators and Rankings: Inventory 2011 34 22. Economic Freedom of the World (EFW) Index

Developer 1 Fraser Institute Developer 2 Year launched 1996 Latest Edition 2010 Field Economy Number of Main Dimensions 5 Description of Main Dimensions 1. Size of Government: Expenditures, Taxes, and Enterprises 2. Legal (Weights in Parenthesis) Structure and Security of Property Rights 3. Access to Sound Money 4. Freedom to Trade Internationally 5. Regulation of Credit, Labor, and Business Number of Underlying Indicators 42 Number of units ranked 141 Type of units ranked Countries Link to report http://www.freetheworld.com/release.html Link to data http://www.freetheworld.com/datasets_efw.html

The EFW index measures the degree to which the policies and institutions of countries are supportive of economic freedom. The cornerstones of economic freedom are personal choice, voluntary exchange, freedom to compete, and security of privately owned property. Thirty-eight components and subcomponents are used to construct a summary index and to measure the degree of economic freedom in five areas: 1. size of government; 2. legal structure and protection of property rights; 3. access to sound money; 4. international exchange; and 5. regulation. Each component and sub-component is placed on a scale from 0 to 10 that reflects the distribution of the underlying data. The component ratings within each area are averaged to derive ratings for each of the five areas. In turn, the summary rating is the average of the five area ratings. Countries are ranked from highest to lowest score of economic freedom.

Composite Indicators and Rankings: Inventory 2011 35

23. Economic Vulnerability Index

Developer 1 Lino Briguglio on behalf of the Islands and Small States Institute, Malta Developer 2 Year launched 1992 Latest Edition 2003 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 117 Type of units ranked Countries Link to report http://www.unep.org/OurPlanet/imgversn/103/17_mea.htm Link to data http://www.unep.org/OurPlanet/imgversn/103/17_mea.htm

The index attempts to measure the extent to which a country's economy is exposed to economic forces outside its control. One effect of this exposure is susceptibility to downside shocks. The latest version of the index (2003) consists of four components, namely trade openness (exports plus imports over GDP), export concentration (the three major categories of exports of merchandise or services as a percentage of total exports), dependence on strategic imports (imports of food and fuel over total imports of merchandise) and peripherality (transport and freight costs as a percentage of imports of merchandise). All economic vulnerability indices produced by the Islands and Small States Institute indicate that small island developing states tend to be more economically vulnerable than other groups of countries.

Composite Indicators and Rankings: Inventory 2011 36 24. EIU Business Environment Rankings

Developer 1 Economist Intelligence Unit (EIU) Developer 2 Year launched 1997 Latest Edition 2008 Field Economy Number of Main Dimensions 10 Description of Main Dimensions 1. Political environment, 2. Macroeconomic environment, 3. (Weights in Parenthesis) Market opportunities, 4. Policy towards free enterprise and competition, 5. Policy towards foreign investment, 6. Foreign trade and exchange controls, 7. Taxes, 8. Financing, 9. Labour market and 10. Infrastructure (equal weights) Number of Underlying Indicators 91 Number of units ranked 82 Type of units ranked Countries Link to report http://graphics.eiu.com/specialReport/globalisation_stalled.pdf Link to data http://viewswire.eiu.com/site_info.asp?info_name=BER_graph&p age=noads

The business rankings model measures the quality or attractiveness of the business environment in the 82 countries covered by Country Forecasts using a standard analytical framework. It is designed to reflect the main criteria used by companies to formulate their global business strategies, and is based not only on historical conditions but also on expectations about conditions prevailing over the next five years. The business rankings model examines ten separate criteria or categories, covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. Each category contains a number of indicators that are assessed by the Economist Intelligence Unit for the last five years and the next five years. The number of indicators in each category varies from five (foreign trade and exchange regimes) to 16 (infrastructure), and there are 91 indicators in total. Almost half of the indicators are based on quantitative data and the other indicators are qualitative in nature and are drawn from a range of data sources and business surveys.

The rankings are calculated in several stages. First, each of the 91 indicators is scored on a scale from 1 (very bad for business) to 5 (very good for business). The aggregate category scores are derived on the basis of simple or weighted averages of the indicator scores within a given category. These are then adjusted, on the basis of a linear transformation, to produce index values on a 1-10 scale. An arithmetic average of the ten category index values is then calculated to yield the aggregate business environment score for each country, again on a 1-10 scale. The use of equal weights for the categories to derive the overall score reflects in part the theoretical uncertainty about the relative importance of the primary determinants of investment. Surveys of foreign direct investors' intentions yield widely differing results on the relative importance of different factors. Weighted scores for individual categories based on correlation coefficients of recent foreign direct investment inflows do not in any case produce overall results that are significantly different to those derived from a system based on equal weights. For most quantitative indicators the data are arrayed in ascending or descending order and split into five bands (quintiles). The countries falling in the first quintile are assigned scores of 5, those falling in the second quintile score 4 and so on. The cut-off points between bands are based on the average of the raw indicator values for the top and bottom countries in adjacent quintiles. The 2004-08 ranges are then used to derive 2009-13 scores. This allows for intertemporal as well as cross-country comparisons of the indicator and category scores.

In the forecast we assign an average grade to elements of the business environment over 2009-13, not to the likely situation in 2013 only. The scores based on quantitative data are usually calculated on the basis of the numeric average for an indicator over the period.

Composite Indicators and Rankings: Inventory 2011 37

25. EIU Country Risk Service (CRS)

Developer 1 Economist Intelligence Unit (EIU) Developer 2 Year launched 1997 Latest Edition 2010 Field Economy Number of Main Dimensions 2 Description of Main Dimensions (Weights in Parenthesis) 1. Broad categories of risk 2. Specific Investment risk Number of Underlying Indicators N/A Number of units ranked 120 Type of units ranked Countries Link to report http://store.eiu.com/product/730000273.html Link to data http://www.eiu.com/site_info.asp?info_name=sovereign_ratings&rf=0

The purpose of the Country Risk Model (CRM) is to provide complete internationally comparable and regularly updated country risk scores for developing and highly indebted countries, and to generate credit ratings of the relative risks from a macroeconomic and financial standpoint. The risk ratings methodology examines risk from two distinct perspectives: 1) broad categories of risk grouped in analytical categories of political, economic policy, economic structure and liquidity factors; and 2) risk exposure associated with investing in particular types of financial instruments, namely specific investment risk. This includes risk associated with taking on foreign-exchange exposure against the US dollar, foreign-currency loans to sovereigns and foreign-currency loans to banks.

The CRM operates by asking the EIU's country expert to answer a series of quantitative and qualitative questions on recent and expected political and economic trends in the relevant country. Letter scores range from "A" (the lowest risk) to "E" (the highest risk). Overall scores are awarded in one-point increments, and can range from 0 ("A" category) to a maximum of 100 points ("E" category) for the highest-risk countries. These four types of general political and macroeconomic risk (political risk, economic policy risk, economic structure risk and liquidity risk) are assessed independently of their association with a particular investment vehicle. They are each given a letter grade. These factors are then used to compile an overall score and rating for the country. In terms of specific investment riskthese break down as follows: Currency risk, Sovereign debt risk, Banking sector risk.

Ratings bands: The ratings bands of "A" to "E" as they pertain to political risk, economic policy risk, economic structure risk and liquidity risk are a convenient summary for translating the score obtained in the model into a letter category. For example, an "A" rating signifies the country is very strong in a particular category, and conversely an "E" underscores a severe weakness.

Composite Indicators and Rankings: Inventory 2011 38 26. EIU Worldwide Cost of Living Index (WCOL)

Developer 1 Economist Intelligence Unit (EIU) Developer 2 Year launched 1980 Latest Edition 2010 Field Economy Number of Main Dimensions 10 Description of Main Dimensions 1. Shopping basket (25%) 2. Alcoholic beverages (3.5%) 3. Household (Weights in Parenthesis) supplies (4.5%) 4. Personal care (4.0%) 5. Tobacco (2.5%) 6. Utilities (6.5%) 7. Clothing (13%) 8. Domestic help (3.5%) 9. Recreation & entertainment (18%) 10. Transportation (19.5%). Number of Underlying Indicators 167 Number of units ranked 130 Type of units ranked Cities Link to report N/A Link to data http://eiu.enumerate.com/asp/wcol_HelpWhatIsWCOL.asp

The Worldwide Cost of Living survey enables human resources line managers and expatriate executives to compare the cost of living in over 130 cities in nearly 90 countries and calculate fair compensation policies for relocating employees. The survey gathers detailed information on the cost of more than 160 items-- from food, toiletries and clothing to domestic help, transport and utility bills--in every city. More than 50,000 individual prices are collected in each survey round and surveys are updated each June and December. A cost-of-living index is calculated from the price data to express the difference in the cost of living between any two cities.

Each city report lists local prices for 167 products and services. These are divided into 13 sub-categories, the first 10 of which are included in the weighted index calculation: Shopping basket 2. Alcoholic beverages 3. Household supplies 4. Personal care 5. Tobacco 6. Utilities 7. Clothing 8. Domestic help 9. Recreation & entertainment 10. Transportation. The final three subcategories are included in the price survey but not included in the index calculation: Housing rents, International schools, health & sports and Business trip costs. The cost-of-living index, or general index, shows the difference in living costs between cities. The cost of living in the base city is always expressed as 100. The cost of living in the destination is then indexed against this number. So to take a simple example, if London is the base (100) and New York is the destination, and the New York index is 120, then New York is 20% more expensive than London.

Such a calculation would be made according to a well-established statistical formula that takes prices in both cities, makes an average of them, and uses this average as the basis for the index comparison. This formula is adopted by the Economist Intelligence Unit for its indices. With the EIU formula, for example, the paradoxical situation of the two cities being more expensive than each other cannot arise: if city A = 100 and city B = 110, then this relationship is maintained, even if city B is used as a base (when B = 100 then A = 91). In other words, the EIU indices are reversible. This property ensures that the cost of living allowances established with the aid of the indices are consistent in that executives transferred from city A to B can be dealt with on the same footing as those transferred from city B to A. In addition, the indices are nearly circular. This means that the relationship between any three cities is maintained regardless of which of the cities is used as a base with which to compare the other two. This logical inter-relationship is important in assuring equitable cost of living compensation as executives are transferred from location to location.

The index is based on the arithmetic mean of price levels in the two selected cities. In order to calculate the index for the two hypothetical cities examined on the previous page, we must first calculate the average price of each item. Every EIU Cost of Living index applies an identical set of weights for each product in the survey.

Composite Indicators and Rankings: Inventory 2011 39 27. Emerging Market Bond Indices (EMBI)

Developer 1 JP Morgan Developer 2 Year launched 1995 Latest Edition 2011 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked N/A Type of units ranked Countries Link to report N/A Link to data http://www.jpmorgan.com/pages/jpmorgan/investbk/solutions /research/EMBI

The JP Morgan bond indices (EMBI, EMBI+, EMBI Global and EMBI Global Constrained) track total returns for traded external debt instruments in the emerging markets. Included in the EMBI Global, for example, are US dollar denominated Brady bonds, Eurobonds, traded loans and local market debt instrument issued by sovereigns classified as low or middle income by the World Bank and those countries that have restructured debt over the past 10 years. Moreover, instruments have to have face values of over U$500 million with at least 2.5 years to maturity. Country sub-indices are used to evaluate country risk through their yield spreads (difference between country EMBI and US treasury yield).

Composite Indicators and Rankings: Inventory 2011 40 28. Euro Monitor Ranking

Developer 1 Lisbon Council Developer 2 Allianz SE Year launched 2010 Latest Edition 2010 Field Economy Number of Main Dimensions 4 Description of Main Dimensions 1. Fiscal sustainability 2. Competitiveness and domestic demand 3. (Weights in Parenthesis) Jobs, productivity and resource efficiency and 4. Private and foreign debt (equal weights amongst indicators) Number of Underlying Indicators 15 Number of units ranked 16 Type of units ranked Eurozone countries Link to report http://www.lisboncouncil.net/publication/publication/62-the-2010- euro-monitor.html Link to data http://www.lisboncouncil.net/publication/publication/62-the-2010- euro-monitor.html

The Euro Monitor is intended to be an annual macroeconomic scorecard that will evaluate EMU countries on their ability to achieve balanced macroeconomic growth, which, in turn, will allow the countries in question to deliver prosperity to their people and contribute to the strength and stability of the entire euro area. 15 quantitative indicators, which are themselves divided into four categories, compose the index: 1. Fiscal sustainability 2. Competitiveness and domestic demand 3. Jobs, productivity and resource efficiency and 4. Private and foreign debt.

A country’s performance in these four areas is of critical importance in determining the trust that country will enjoy on financial markets and thus for the level of the risk premiums it will be demanded to pay by those markets. Financial markets are very precise in the way they make distinctions. Dodgy state finances are certainly more likely to be tolerated in the case of a country which enjoys high productivity and employment growth than in a country with a stalling economy.

All 15 individual indicators are quantitative indicators. Countries are given a rating score ranging from 1 to 10 in each of the 15 indicators. Since the individual indicators are assigned an equal weighting in the overall Euro Monitor rating score, the overall score for each country corresponds to the average rating of all 15 indicators, meaning that it is also expressed as a value from 1 to 10. The country rating in each category is calculated as the average of the indicator ratings in that category. Throughout, we have used annual values for all years until 2009 and estimates for 2010. We have defined three rating classes: values 1-4 (coded in the charts in red) signal poor performance, 5-7 (coded in dark blue) indicate middling performance and 8-10 (coded in light blue) good performance. Just as an alert threshold, values 1-4 can be seen as indicative values which guide the assessment but are to be complemented by economic judgment and country-specific expertise.

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29. Eurochambres Economic Survey (EES) Indicators

Developer 1 Eurochambres Developer 2 Year launched 1993 Latest Edition 2011 Field Economy Number of Main Dimensions 4 Description of Main Dimensions 1. Total turnover, domestic sales and export sales 2. Employment 3. (Weights in Parenthesis) Investment and 4. Business confidence - No single index Number of Underlying Indicators 4 Number of units ranked 119 Type of units ranked EU regions Link to report http://www.eurochambres.eu/Content/Default.asp?PageID=1&DocI

D=2919 Link to data http://www.eurochambres.eu/Content/Default.asp?PageID=1&DocI

D=2919

The Economic Survey is an annual, qualitative regional survey of business expectations in Europe. It is based on a harmonised questionnaire sent to entrepreneurs from 23 EU Member States as well as Bulgaria, Croatia, Romania and Turkey during the autumn 2004. Over 76,000 companies responded. Data have been aggregated at regional level, with 119 European regions included. A set of 12 questions were posed to companies on their past, current and short term business expectations (4 indicators: 1. total turnover, domestic sales and export sales 2. employment 3. investment and 4. business confidence). Entrepreneurs were asked to give a qualitative response, i.e. "better than the previous year", "the same as the previous year" or "worse than the previous year". Responses from entrepreneurs were collected and aggregated using random and representative sampling techniques thereby guaranteeing representativity by size, sector and region. In most countries all regions participated in the survey. In some, often smaller states, the country as a whole was regarded as “a region”. The regional results have then been centralised in each country, a national weighted aggregate was calculated and extensive comments on the results have also been prepared. Subsequently EUROCHAMBRES brought the national reports and regional data together, and prepared a European report on the main trends resulting from the survey. National and European results presented in the European Analysis were weighted according to national GDPs. Also when calculating averages or other aggregates (Euro Zone countries, survey average etc.), GDP was used for weighting.

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30. European Cities Monitor

Developer 1 CUSHMAN & WAKEFIELD Developer 2 Year launched 1990 Latest Edition 2010 Field Economy Number of Main Dimensions 12 Description of Main Dimensions 1. Easy access to markets, customers or clients 2. Availability of (Weights in Parenthesis) quality staff 3. Quality of telecommunications 4. Transport links with other cities and internationally. 5. Ease of travelling within the city, 6. Languages spoken. 7. Cost of staff, 8. Value for money 9. Climate created by government, 10. Quality of life and 11. Availability of office 12. Freedom from pollution. Number of Underlying Indicators 12 Number of units ranked 36 Type of units ranked European cities Link to report http://www.europeancitiesmonitor.eu/ Link to data http://www.europeancitiesmonitor.eu/wp- content/uploads/2010/10/ECM-2010-Full-Version.pdf

The survey provides an overview of the perceptions that corporate occupiers have about cities across Europe and their relative attractiveness. The underlying data is researched independently for C&W by TNS BMRB and 500 senior executives from leading European companies give their views on Europe's leading business cities. In total, 500 companies were surveyed from nine European countries. The sample was systematically selected from “Europe’s largest companies”. A representative sample of industrial, consumer, retail & distribution companies and professional services companies were included. The sample changes typically by around half of the companies each year. The interviewees were Board Directors or Senior Managers, with responsibility for location. All interviews were conducted by telephone in May/June 2010 by mother tongue interviewers. Interviews took an average of 20 minutes to complete.

The scores shown for each city throughout the report are based on the responses and weighted by TNS BMRB according to nominations for the best, second best and third best. Each score provides a comparison with other cities’ scores and over time for the same city.

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31. European Competitiveness Index (ECI)

Developer 1 Centre for International Competitiveness Developer 2 Robert Huggins Associates Year launched 2004 Latest Edition 2007 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Creativity 2. Economic Performance and 3. Infrastructure (Weights in Parenthesis) and accessibility Number of Underlying Indicators 37 Number of units ranked 25 Type of units ranked EU Link to report http://www.cforic.org/downloads.php Link to data http://www.cforic.org/downloads.php

The ECI measures, compares and examines the competitiveness of Europe’s regions and nations. We define such competitiveness as the capability of an economy to maintain increasing standards of living for those who participate in it, by attracting and maintaining firms with stable or rising market shares in an activity. As such, the competitiveness of a region will depend on its ability to anticipate and successfully adapt to internal and external economic and social challenges, by providing new economic opportunities, including higher quality jobs.

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32. European E-Business Readiness Index

Developer 1 European Commission Developer 2 Year launched 2004 Latest Edition 2007 Field Economy Number of Main Dimensions 2 Description of Main Dimensions 1. Adoption of ICT by business 2. Use of ICT by business (Weights in Parenthesis) Number of Underlying Indicators 12 Number of units ranked 27 Type of units ranked EU Countries Link to report http://ec.europa.eu/enterprise/sectors/ict/competitiveness/ebi/index_ en.htm Link to data http://ec.europa.eu/enterprise/sectors/ict/files/ebizreadinessindex_2 007_en.pdf

The e-business readiness index monitors progress in the implementation of the eEurope 2005 Action Plan. This annual survey aims to produce harmonised and comparable statistics on the European enterprises access to and use of ICT systems. The survey measures the level and the type of the ICT used by European business. For this reason the indicators of the index are grouped into two categories measuring the various components of a country’s technological development: 6 basic indicators for the group ‘Adoption of ICT by business’ and 6 basic indicators for the group ‘Use of ICT by business’. The raw data for the basic indicators are expressed as percentages: 11 indicators are percentages of enterprises and one indicator (a4) is percentage of employees. In the present case, the components indicators are aggregated using a participatory weighing scheme involving a panel of national representatives. Weights were assigned to the indicators according to a “budget allocation scheme”, which consists in asking each expert in the panel to distribute 100 “points” proportionally to the relevance of the indicators for measuring e-Readiness. The set of weights given below represents the average of weights provided by twelve national representatives of the e-BSN6. a1 a2 a3 a4 a5 a6 0.18 0.16 0.10 0.16 0.21 0.20 b1 b2 b3 b4 b5 b6 0.17 0.17 0.21 0.21 0.12 0.13

Using the nc basic indicators (denoted Ik,k=1,…,nc) and the corresponding weights (noted denoted wk,k=1,…,nc) for the aggregation, the value of the composite indicator CI (adoption or use) is given by:

The validity, interpretability and explanatory power of the e-business readiness index depends on the quality and completeness of the data. The basic indicators are being updated in view of the i2010 initiative and the dynamic nature of e-business will obviously cause adjustment needs in 2007-2010.

The e-business index is presented as a weighted average of the component indicators by considering the budget allocation weights. One should observe the fact that this report is about the ICT Adoption and Use of enterprises.

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33. European Economic Sustainability Index (EESI)

Developer 1 European Policy Centre Developer 2 Year launched 2010 Latest Edition 2010 Field Economy Number of Main Dimensions 6 Description of Main Dimensions 1. Deficits, national debt, growth, competitiveness, governance/ (Weights in Parenthesis) corruption and cost of ageing (equal weights) Number of Underlying Indicators 6 Number of units ranked 26 Type of units ranked EU Link to report http://www.epc.eu/pub_details.php?cat_id=2&pub_id=1127 Link to data http://www.epc.eu/documents/uploads/pub_1127_eesi.pdf

The EESI enables a comparison of the long term economic sustainability of EU Member States. Each EU country is simultaneously assessed according to six criteria (deficits, national debt, growth, competitiveness, governance/ corruption and cost of ageing) and then ranked against the other 26.

A country’s relative position to all other EU countries is constructed by summing a relative (unweighted) score across all six domains. A relative score can only meaningfully measure distance from each other. This means that there is no possibility of comparing these scores to non-EU countries which have not been included in the index in the first place. The index also does not provide an absolute assessment of the economic sustainability of Europe – rather it assesses where EU countries stand in relation to each other. This provides a score which allows all EU countries to be ranked according to their long-term economic sustainability, and provides a benchmark to understand the underlying position of each country within the context of a fast-changing economic environment and significant policy changes.

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34. European Smart Cities

Developer 1 Centre of Regional Science at the Vienna University of Technology Developer 2 Delft University of Technology, Department of Geography at University of Ljubljana Year launched 2007 Latest Edition 2007 Field Economy Number of Main Dimensions 6 Description of Main Dimensions 1. Economy 2. People 3. Governance 4. Mobility 5. Environment (Weights in Parenthesis) 6. Smart Living (equal weights) Number of Underlying Indicators 74 Number of units ranked 70 Type of units ranked European cities Link to report http://www.smart-cities.eu/ Link to data http://www.smart- cities.eu/download/smart_cities_final_report.pdf

It assesses medium-sized cities and their perspectives for development. For the ranking two criteria were selected: Cities should be of medium size and they should be covered by accessible and relevant databases. The most comprehensive list of cities in Europe provides the Espon 1.1.1 project. It covers almost cities 1,600 cities in the Espon space (EU27+NO+CH) with data on population and some functional data.

Three criteria were elaborated on the basis of these 1,600 cities: . Urban population between 100,000 and 500,000 (to obtain medium-sized cities) . At least 1 University (to exclude cities with weak knowledge basis) . Catchment area less than 1.500,000 inhabitants (to exclude cities which are dominated by a bigger city)

The smart city model: A Smart City is a city well performing in 6 characteristics, built on the ‘smart’ combination of endowments and activities of self-decisive, independent and aware citizens.

Standardization and aggregation: To compare the different indicators it is necessary to standardize the values. One method to standardize is by z-transformation. This method transforms all indicator values into standardized values with an average 0 and a standard deviation 1. This method has the advantages to consider the heterogeneity within groups and maintain its metric information. Furthermore a high sensitivity towards changes is achieved.

z-transformation:

To receive results on the level of factors, characteristics and the final result for each city it is necessary to aggregate the values on the indicator level. For the aggregation of indicators of factors we consider also the coverage rate of each indicator. A certain result from an indicator of an indicator covering all 70 cities weights therefore a little more than from an indicator covering only 60 cities. Besides this small correction the results were aggregated on all levels without any weighting. The aggregation was done additive but divided through the number of values added. That allows us to include also cities which do not cover all indicators. Their results are calculated with the values available. Still, it is necessary to provide a good coverage over all cities to receive reasonable results. For the 70 cities by 74 indicators we achieve a coverage rate of 87 %.

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35. Forbes Capital Hospitality Index (FCHI)

Developer 1 Forbes Developer 2 Year launched 2006 Latest Edition 2006 Field Economy Number of Main Dimensions 5 Description of Main Dimensions 1. GDP growth 2. GDP per capita 3.Trade balance 4. population (Weights in Parenthesis) 5. Unemployment Number of Underlying Indicators 5 Number of units ranked 135 Type of units ranked Countries Link to report http://www.forbes.com/2006/01/24/capital-hospitality- index_06caphosp_land.html Link to data http://www.forbes.com/2006/01/24/capital-hospitality-

index_06caphosp_land.html

The FCHI assesses the degree to which nations are qualified for or receptive to foreign investment. Forbes began with a list of principles employed by the U.S. Chamber of Commerce when considering international investments. Seeking out several of the world's top institutions of sociological and economic theory, they gathered the results of surveys, statistical studies and socio-economic data on each of the 135 countries in the index, assigning relative percent-rankings for each of the chamber's largely qualitative principles. Then they aggregated scores across ten separate categories to develop the first Forbes Capital Hospitality Index. The FCHI measures macroeconomic indicators like GDP growth and international trade, along with societal factors affecting investment, including poverty, bureaucracy, technological advancement and corruption. Scores represent a 'percent rank' whereby a score of 80 is better than 80% of countries in each of ten categories for which data is available. Total score takes an average across those categories (no less than 7 out of 10) for each country.

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36. Foreign Direct Investment Confidence Index

Developer 1 AT Kearney Developer 2 Year launched 1998 Latest Edition 2010 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 44 Type of units ranked Countries Link to report http://www.atkearney.com/images/global/pdf/Investing_in_a_R

ebound-FDICI_2010.pdf Link to data http://www.atkearney.com/images/global/pdf/Investing_in_a_R

ebound-FDICI_2010.pdf

The index serves to gauge the likelihood of investment in specific markets in order to gain insight into likely trends in future global FDI flows. It relies on a survey to executives of 42 different countries that express their views of other 64 countries, receiving 90% of FDI flows. The index is computed as a weighted average of a number of high, medium, low and “no interest” responses to a question about the likelihood of direct investment in a market over the next one to three year period. Index values are based on non-source country responses about various markets. For example, the index ranking the US reflects all non- US company responses about the US market. All index values have been calculated on a scale of 0 to 3, with 3 representing “highly attractive” and 0 “non-attractive”.

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37. FORELAND - Lender's risk rating

Developer 1 BERI Developer 2 Year launched 1978 Latest Edition 2010 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 50 Type of units ranked Countries Link to report http://www.beri.com/forelend.asp Link to data http://www.beri.com/forelend.asp

FORELAND provides executives in banks and corporations with perspective on the capacity and willingness of 50 countries to meet obligations in convertible currency during a five-year period. The lender’s risk rating is a weighted score comprised of a computerized quantitative rating (ability of a country to raise the needed foreign exchange to meet debt obligations), a qualitative rating (competence, corruption, loan profile, etc.), and a political/economic rating (stability of the nation's power structure and direction of the economy).

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38. G-Index - Globalization index

Developer 1 AT Kearney Developer 2 Foreign Policy Year launched 2001 Latest Edition 2007 Field Economy Number of Main Dimensions 4 Description of Main Dimensions 1. Economic Integration 2. Personal contact 3. Technological (Weights in Parenthesis) connectivity 4. Political engagement Number of Underlying Indicators 14 Number of units ranked 72 Type of units ranked Countries Link to report http://www.atkearney.com/index.php/Publications/globalization-

index.html Link to data http://www.atkearney.com/index.php/Publications/globalization-

index.html

The Globalization Index tracks and assesses changes in four key components of global integration, incorporating measures such as trade and investment flows, movement of people across borders, volume of international telephone calls, Internet usage, and participation in international organizations. Economic integration combines data on trade and foreign direct investment (FDI) inflows and outflows. Personal contact tracks international travel and tourism, international telephone calls, and cross-border remittances and personal transfers (including worker remittances, compensation to employees, and other person-to- person and nongovernmental transfers). Technological connectivity counts the number of Internet users, Internet hosts, and secure servers through which encrypted transactions are carried out. Finally, political engagement includes each country’s memberships in a variety of representative international organizations, personnel and financial contributions to U.N. peacekeeping missions, ratification of selected multilateral treaties, and amounts of governmental transfer payments and receipts.

For most variables, each year’s inward and outward flows are added, and the sum is divided by the country’s nominal economic output (GDP) or, where appropriate, its population. Two of the political engagement indicators remain as absolute numbers: memberships in international organizations and number of treaties ratified. A country’s contributions to U.N. peacekeeping missions are measured as a weighted average of financial contribution divided by the country’s GDP, and the country’s personnel contribution divided by the country’s population. Hence, the indicator counts a country’s contributions relative to its capacity to contribute, rather than the absolute size of contribution. This overall process produces data for each year that enable comparisons between countries of all sizes.

The resulting data for each given variable are then "normalized" through a process that assigns values to data points for each year relative to the highest data point that year. The highest data point is valued at 1, and all other data points are valued as fractions of 1. The range of normalized scores for each variable each year is then multiplied by a "scale factor." For simplicity's sake, the base year (1998 in this case) is assigned a value of 100. The given variable's scale factor for each subsequent year is the percentage growth or decline in the GDP- or population-weighted score of the highest data point, relative to 100. With the scale factor, comparisons between countries in the same year are preserved, and comparisons between changes in individual variables over time are possible. Country variable scores are then summed, with triple weighting on FDI and double weighting on trade due to those factors’ particular importance in the ebb and flow of globalization. Technological variables and political variables are each collapsed into single indicators, with equal weightings for the component variables. Globalization Index scores for every country and year are derived by summing all the indicator scores.

Composite Indicators and Rankings: Inventory 2011 51 39. Global Competitiveness Index

Developer 1 World Economic Forum (WEF) Developer 2 Year launched 2004 Latest Edition 2010 Field Economy Number of Main Dimensions 3 Description of Main Dimensions a) Basic requirements: 1. Institutions (25%) 2. Infrastructure (25%) 3. (Weights in Parenthesis) Macroeconomic Stability (25%) 4.Health and primary education (25%) b) Efficiency enhancers: 5. Higher education and training (17%) 6. Goods Market Efficiency (17%) 7. Labor Market Efficiency (17%) 8. Financial Markets Development (17%) 9. Technological Readiness (17%) 10. Market size (17%) c) Innovation: 11. Business Sophistication (50%) 12. Innovation (50%). Weights of 3 dimension depends on country's development stage Number of Underlying Indicators 100 Number of units ranked 139 Type of units ranked Countries Link to report http://www3.weforum.org/docs/WEF_GlobalCompetitivenessReport_2010-

11.pdf Link to data http://gcr.weforum.org/gcr2010/

The Global Competitiveness Index is a unified approach, capturing both the macroeconomic and microeconomic foundations of competitiveness as well as the static and dynamic consequences. The Global Competitiveness Index is a weighted average of three sub-indices: basic requirements, efficiency enhancers and innovation factors which comprise 12 pillars of competitiveness. Countries are ranked in decreasing order of competitiveness.

The computation of the GCI is based on successive aggregations of scores from the indicator level (i.e., the most aggregated level) all the way up to the overall GCI score. We use an arithmetic mean to aggregate individual variables within a category. For the higher aggregation levels, the percentages used are shown below. This percentage represents the category’s weight within its immediate parent category. Reported percentages are rounded to the nearest integer, but exact figures are used in the calculation of the GCI. For example, the score a country achieves in the 9th pillar accounts for 17 percent of this country’s score in the efficiency enhancers subindex, irrespective of the country’s stage of development. Similarly, the score achieved on the subpillar transport infrastructure accounts for 50 percent of the score of the infrastructure pillar. Unlike the case for the lower levels of aggregation, the weight put on each of the three subindexes (basic requirements, efficiency enhancers, and innovation and sophistication factors) is not fixed. Instead, it depends on each country’s stage of development.

To make the aggregation possible, these variables are transformed onto a 1-to-7 scale in order to align them with the Survey results. We apply a min-max transformation, which preserves the order of, and the relative distance between, country scores. Variables that are followed by the designation “1/2” enter the GCI in two different pillars. In order to avoid double counting, we assign a half-weight to each instance.

Composite Indicators and Rankings: Inventory 2011 52

40. Global Enabling Trade Index (ETI)

Developer 1 World Economic Forum (WEF) Developer 2 Year launched 2008 Latest Edition 2010 Field Economy Number of Main Dimensions 4 Description of Main Dimensions 1. Market access 2. Border administration 3. Transport and (Weights in Parenthesis) communications infrastructure and 4. business environment (equal weights) Number of Underlying Indicators 56 Number of units ranked 125 Type of units ranked Countries Link to report http://schwabfound.weforum.org/en/initiatives/gcp/GlobalEnablin

gTradeReport/index.htm Link to data https://members.weforum.org/pdf/GETR10/Global-Enabling-

Trade-Report-2010.pdf

The ETI measures the extent to which individual economies have developed institutions, policies, and services facilitating the free flow of goods over borders and to destination. The structure of the Index reflects the main enablers of trade, breaking them into four overall issue areas, captured in the subindexes: 1. The market access subindex measures the extent to which the policy framework of the country welcomes foreign goods into the economy and enables access to foreign markets for its exporters. 2. The border administration subindex assesses the extent to which the administration at the border facilitates the entry and exit of goods. 3. The transport and communications infrastructure subindex takes into account whether the country has in place the transport and communications infrastructure necessary to facilitate the movement of goods within the economy and across the border. 4. The business environment subindex looks at the quality of governance as well as at the overarching regulatory and security environment impacting the business of importers and exporters active in the country.

Each of these four subindexes is composed in turn of a number of pillars of enabling trade, of which there are nine in all. These are: 1. Domestic and foreign market access 2. Efficiency of customs administration 3. Efficiency of import-export procedures 4. Transparency of border administration 5. Availability and quality of transport infrastructure 6. Availability and quality of transport services 7. Availability and use of ICTs 8. Regulatory environment and 9. Physical security.

These pillars are calculated on the basis of both hard data and survey data. The survey data are mainly derived from the responses to the World Economic Forum’s Executive Opinion Survey and range from 1 to 7. In addition, survey data from the World Bank’s Logistics Performance Index (LPI) have also been included. The hard data were collected from various recognized sources. The hard data indicators used in the ETI, as well as the results from the LPI survey, are normalized to a 1-to-7 scale in order to align them with the Executive Opinion Survey results. Each of the pillars has been calculated as an unweighted average of the individual component variables. The subindexes are then compounded as unweighted averages of the included pillars. In the case of the domestic and foreign market access pillar, which is itself composed of two subpillars (domestic market access and foreign market access), the overall pillar is the unweighted average of the two subpillars. Likewise, in the case of the availability and quality of transport infrastructure pillar, which is itself composed of two subpillars (availability of transport infrastructure and quality of transport infrastructure), the overall pillar is the unweighted average of the two subpillars. The overall ETI is then calculated as the unweighted average of the four subindexes.

Composite Indicators and Rankings: Inventory 2011 53 41. Global Entrepreneurship Monitor (GEM)

Developer 1 Babson College Developer 2 London Business School Year launched 1999 Latest Edition 2010 Field Economy Number of Main Dimensions 3 Description of Main Dimensions Survey on entrepreneurial attitudes, activity and aspirations (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 59 Type of units ranked Countries Link to report http://www.gemconsortium.org/download/1295835839766/GEM%20 GLOBAL%20REPORT%202010rev.pdf Link to data http://www.gemconsortium.org/download/1295835839766/GEM%20 GLOBAL%20REPORT%202010rev.pdf

GEM is an annual assessment of the national level of entrepreneurial activity. This report reveals results of the measures of entrepreneurial attitudes, activity and aspirations from the GEM 2010 Adult Population Survey (APS). These results include comparisons of economies in the three development phases, and also comparisons of different geographic regions within each development phase. We highlight particular economies in some cases to illustrate unique findings.

We first examine entrepreneurial attitudes, activities and aspirations in the 59 participating economies. Entrepreneurial attitudes encompass several dimensions: views about the presence of good entrepreneurial opportunities in one’s area, beliefs about one’s capabilities for starting a business, fear of failure, perceptions about the status of entrepreneurs and their media image, the attractiveness of entrepreneurship as a career choice and finally, intent to start a business. With regard to entrepreneurship activity, we analyze Total Early-Stage Entrepreneurship Activity (TEA), which combines nascent and new business measures. TEA is then discussed in terms of its relationship to development level, expressed as GDP per capita, adjusted for purchasing power parity (PPP). We then describe the necessity and opportunity-driven components of TEA. Additional characteristics include the proportion of entrepreneurs operating in various business sectors, as well as age and gender factors. The discussion then turns to established business and business discontinuance. Finally, we describe the aspirations of entrepreneurs: growth projections for their businesses, the level of innovativeness from a product, market, and competitive standpoint and the extent their customers come from outside their economy. The final sections include an overview of results from the National Expert Survey (NES) and an analysis of entrepreneurship and the global economy in 2010.

Composite Indicators and Rankings: Inventory 2011 54 42. Global Financial Centres Index (GFCI)

Developer 1 Z/Yen Group Developer 2 City of London Corporation Year launched 2006 Latest Edition 2009 Field Economy Number of Main Dimensions 14 Description of Main Dimensions 1. The availability of skilled personnel 2. The regulatory (Weights in Parenthesis) environment 3. Access to international financial markets 4. The availability of business infrastructure 5. Access to customers 6. A fair and just business environment 7. Government responsiveness 8. The corporate tax regime 9. Operational costs 10. Access to suppliers of professional services 11. Quality of life 12. Culture & language 13. Quality / availability of commercial property and 14. The personal tax regime. Number of Underlying Indicators 62 Number of units ranked N/A Type of units ranked Financial centers Link to report http://www.zyen.com/Activities/On-line_surveys/GFCI.htm Link to data http://www.zyen.com/Activities/On-line_surveys/GFCI.htm

The GFCI is an index of indices, based on a number of existing rankings, in combination with a regular survey of senior industry figures. The GFCI provides ratings for financial centres calculated by a factor assessment model built using two distinct sets of input:

1. Instrumental factors - drawn from external sources. The infrastructure competitiveness for a financial centre, for example, is indicated by instrumental factors including a cost of property survey and an occupancy costs index; a fair and just business environment is indicated by ratings such as a corruption perception index and an opacity index. 2. Comparative sources - 62 instrumental factors were used to construct the GFCI 3 ratings. Not all centres have data for all instrumental factors and the statistical model takes account of these gaps; financial centre assessments to construct the GFCI 3 ratings 18,878 financial centre assessments drawn from 1,236 respondents to an online questionnaire. Respondents assessed the competitiveness of financial centres which they knew.

The 62 instrumental factors were selected to reflect the 14 competitiveness factors.

Competitiveness Factors and their relative importance Competitiveness Factors Rank Average Score The availability of skilled personnel 1 5.37 The regulatory environment 2 5.16 Access to international financial markets 3 5.08 The availability of business infrastructure 4 5.01 Access to customers 5 4.90 A fair and just business environment 6 4.67 Government responsiveness 7 4.61 The corporate tax regime 8 4.47 Operational costs 9 4.38 Access to suppliers of professional services 10 4.33 Quality of life 11 4.30

Composite Indicators and Rankings: Inventory 2011 55 Culture & language 12 4.28 Quality / availability of commercial property 13 4.04 The personal tax regime 14 3.89

At the outset of the GFCI, a number of guidelines were set out. These guidelines are to ensure that centre assessments and instrumental factors were selected and used in a way that will generate a credible, dynamic rating of centre competitiveness for financial services institutions.

Creating the GFCI does not involve totaling or averaging instrumental factors.

The guidelines for financial centre assessments by respondents are:  responses are collected via an online questionnaire which runs continuously. A link to this questionnaire is emailed to the target list of respondents at regular intervals;  financial centre assessments will be included in the GFCI model for 36 months after they have been received. Financial centre assessments from the month when the GFCI is created are given full weighting and earlier responses are given a reduced weighting on a log scale. This scale has been revised between GFCI 1 and GFCI 2 to enhance its effectiveness, and used again for GFCI 3

The financial centre assessments and instrumental factors are used to build a predictive model of centre competitiveness using a support vector machine (SVM). SVMs are based upon statistical techniques that classify and model complex historic data in order to make predictions on new data. SVMs work well on discrete, categorical data but also handle continuous numerical or time series data. The SVM used for the GFCI provides information about the confidence with which each specific classification is made and the likelihood of other possible classifications.

A factor assessment model is built using the centre assessments from responses to the online questionnaire. Assessments from respondents home centres are excluded from the factor assessment model to remove home bias. Financial centre predictions from the SVM are re-combined with actual financial centre assessments to produce the GFCI a set of financial centre ratings. The GFCI is dynamically updated by either an updated instrumental factor or new financial centre assessments. These updates permit, for instance, a recently changed index of rental costs to dynamically adjust the competitiveness rating of the centres.

Part of the process of building the GFCI was extensive sensitivity testing to changes in instrumental factors and financial centre assessments. The accuracy of predictions given by the SVM were tested against actual assessments. Over 80% of the predictions made were accurate to within 5%.

Composite Indicators and Rankings: Inventory 2011 56 43. Global Investment Prospects Assessment (GIPA)

Developer 1 UNCTAD Developer 2 Year launched 2004 Latest Edition 2008 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 154 Type of units ranked Countries Link to report http://www.unctad.org/en/docs/iteiit20057_en.pdf Link to data http://www.unctad.org/en/docs/iteiit20057_en.pdf

The Global Investment Prospects Assessment (GIPA) is designed to assess short- and medium-term prospects for FDI. It analyses predicted future patterns of FDI flows at the global, regional, national, and industry levels from the perspectives of global investors, host countries and international FDI experts. It is made up of three surveys: 1) a worldwide survey of the largest TNCs with headquarters in developed and developing countries and in Central and Eastern Europe 2) A worldwide survey of international FDI experts who typically assist TNCs in their overseas location decisions. 3) A worldwide survey of national investment promotion agencies (IPAs) regarding their perception of TNCs’ investment strategies and of FDI prospects for their respective countries and regions. Countries are ranked by their attractiveness as FDI destinations.

Composite Indicators and Rankings: Inventory 2011 57 44. Global Production Scoreboard

Developer 1 Global-Production.com Developer 2 Year launched 2003 Latest Edition 2010 Field Economy Number of Main Dimensions 2 Description of Main Dimensions 1. Potential 2.Performance (no weights provided) (Weights in Parenthesis) Number of Underlying Indicators 13 Number of units ranked 25 Type of units ranked Emerging countries Link to report N/A Link to data http://www.global-production.com/scoreboard/index.htm

The Global Production Scoreboard benchmarks emerging economies as locations for global production activities. The Scoreboard uses a set of indicators, measuring potential and performance-related dimensions of individual countries. The indicators included in the Scoreboard have been selected to permit intercountry comparisons, regarding not only the potential, but also the performance of emerging economies as locations for global production activities.

Composite Indicators and Rankings: Inventory 2011 58 45. Global Retail Development Index (GRDI)

Developer 1 AT Kearney Developer 2 Year launched 2002 Latest Edition 2010 Field Economy Number of Main Dimensions 4 Description of Main Dimensions 1. Country and business risk (25%) 2. Market attractiveness (25%) 3. (Weights in Parenthesis) Market saturation (25%) 4. Time pressure (25%) Number of Underlying Indicators 25 Number of units ranked 30 Type of units ranked Emerging countries Link to report http://www.atkearney.com/images/global/pdf/2010_Global_Retail_ Development_Index.pdf Link to data http://www.atkearney.com/index.php/Publications/global-retail- development-index.html

The GRDI helps retailers prioritize their global development strategies by ranking the retail expansion attractiveness of emerging countries based on a set of 25 variables including economic and political risk, retail market attractiveness, retail saturation levels, and modern retailing sales area and sales growth. The GRDI focuses on opportunities for mass merchant and food retailers, which are typically the bellwether for modern retailing concepts in a country

Composite Indicators and Rankings: Inventory 2011 59 46. Global Risk Service

Developer 1 Global Insight Developer 2 Year launched N/A Latest Edition 2010 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators 54 Number of units ranked 140 Type of units ranked Countries Link to report http://www.ihsglobalinsight.com/ProductsServices/Produc tDetail874.htm Link to data http://www.ihsglobalinsight.com/ProductsServices/Produc tDetail874.htm

Composite Indicators and Rankings: Inventory 2011 60 47. Global Venture Capital and Private Equity Country Attractiveness Index

Developer 1 IESE Business School - University of Navarra Developer 2 Ernst & Young Year launched 2010 Latest Edition 2010 Field Economy Number of Main Dimensions 6 Description of Main Dimensions 1. Economic Activity 2. Depth of a Capital Market 3. Taxation 4. (Weights in Parenthesis) Investor Protection and Corporate Governance 5. Human and Social Environment 6. Entrepreneurial Culture and Opportunities. (equal weights) Number of Underlying Indicators 70 Number of units ranked 66 Type of units ranked Countries Link to report http://vcpeindex.iese.us/ Link to data http://vcpeindex.iese.us/

The purpose of this index is to benchmark countries with respect to their attractiveness for institutional investors who decide upon international allocations in VC and PE limited partnerships. It contributes to solving the investor’s problem: where to allocate the capital. The basic and important principle of our index is to make use of “latent drivers”: criteria that are not directly observable, but driven by others which can be measured. We assume that the better these criteria are developed, the more deal supporting institutions will likewise exist to facilitate VC and PE activity. An unobservable criterion is assessed with several proxy parameters. In principle, we measure the attractiveness of a country by six main criteria. The “six key drivers” are: 1. Economic Activity 2. Depth of a Capital Market 3. Taxation 4. Investor Protection and Corporate Governance 5. Human and Social Environment 6. Entrepreneurial Culture and Opportunities.

We disaggregate the six key drivers in sub-categories. These categories are either actual data series or further sub-constructs, and we call them “level 2 constructs”. This approach has two major advantages: first, individual data series do not gain too much weight when they are grouped; second, the overall results can be traced to more granulated levels and hence, facilitate interpretations.

The weighting scheme: We apply equal weights for all data series, when we aggregate them to the level 2 constructs. Then again, we use equal weights for the level 2 constructs to aggregate the six key drivers. Finally, the weight of the key drivers depends on the number of level 2 constructs included. For example, “1 Economic Activity” consists of three level 2 constructs, while “3 Taxation” consists of only two. Overall, we use 22 level 2 constructs for our index, and hence, “1 Economic Activity” receives a weight of 3/22, which is 0.136, while the weight of “3 Taxation” is 2/22 - 0.091. The advantage of this weighting scheme is that the key drivers that consist of more level 2 constructs gain more weight. That way, we also smooth outliers in individual data series.

Separate VC and PE indices: To account for differences with respect to the two market segments, VC vs. PE, we propose three alternative indices. The first combines both segments. The second focuses on early stage VC and the third on later stage PE only. For the VC and PE indices we simply discard data series that are less important for either market segment: for the VC index, we regard the level 2 construct “2.4 Debt and Credit Market” as relatively unimportant, and hence discard it. When calculating the PE index, we discard “3.1.2 Entrepreneurship Incentive”, “3.1.3 Labor and Tax Contributions”, and “3.2 Administrative Tax Burdens”, and further, “5.1 Education and Human Capital”, “6.1 Innovation and R&D”, “6.2 Ease of Starting and Running a Business” and “6.4 ICT Infrastructure” from the criteria. The weights for the individual index items in the separate VC and PE indices are calculated analogue to the above explained procedure.

Composite Indicators and Rankings: Inventory 2011 61 48. Growth and Development Bridge (GDB) Index

Developer 1 Anh-Nga Tran-Nguyen, Marwan Elkhoury and Philippe Brusick

Developer 2 Year launched 2010 Latest Edition 2010 Field Economy Number of Main Dimensions 4 Description of Main Dimensions 1) Capacity and resources; 2) infrastructure and institutional (Weights in Parenthesis) framework; 3) macroeconomic framework; 4) structural and global integration factors Number of Underlying Indicators 38 Number of units ranked 45 Type of units ranked Countries Link to report http://www.gdbridge.org/gdb_index Link to data http://www.gdbridge.org/gdb_index

GDB Index benchmarking is a tool to be used by policy makers for measuring performance and identifying potential for improvement, and by investors for making informed decisions on investment allocations and risk mitigation. The GDB Index can be used to benchmark and rate countries according to their economic fundamentals, to assess their strengths, weaknesses, opportunities and threats (SWOT), and to analyse their economic prospects. The GDB Index is derived from a solid model built on the findings of the vast literature on economic growth and development. The model has 38 measurable variables included in four categories of economic fundamentals (or economic pillars): 1) capacity and resources; 2) infrastructure and institutional framework; 3) macroeconomic framework; 4) structural and global integration factors. The GDB divides the world into five groups, based on their per capita GDP and GDP growth rates.

Composite Indicators and Rankings: Inventory 2011 62 49. Index measuring the strictness of employment legislation (EPL)

Developer 1 OECD Developer 2 Year launched 1999 Latest Edition 2008 Field Economy Number of Main Dimensions 3 Description of Main Dimensions (i) protection of regular workers against individual dismissal; (ii) (Weights in Parenthesis) regulation of temporary forms of employment; and (iii) specific requirements for collective dismissals. Different weight versions Number of Underlying Indicators 21 Number of units ranked 30 OECD countries and 10 emerging economies Type of units ranked Countries Link to report http://www.oecd.org/dataoecd/36/9/43116624.pdf Link to data www.oecd.org/employment/protection

The OECD employment protection indicators are compiled from 21 items covering three different aspects of employment protection: • Individual dismissal of workers with regular contracts: incorporates three aspects of dismissal protection: (i) procedural inconveniences that employers face when starting the dismissal process, such as notification and consultation requirements; (ii) notice periods and severance pay, which typically vary by tenure of the employee; and (iii) difficulty of dismissal, as determined by the circumstances in which it is possible to dismiss workers, as well as the repercussions for the employer if a dismissal is found to be unfair (such as compensation and reinstatement). • Additional costs for collective dismissals: most countries impose additional delays, costs or notification procedures when an employer dismisses a large number of workers at one time. This measure includes only additional costs which go beyond those applicable for individual dismissal. It does not reflect the overall strictness of regulation of collective dismissals, which is the sum of costs for individual dismissals and any additional cost of collective dismissals. • Regulation of temporary contracts: quantifies regulation of fixed-term and temporary work agency contracts with respect to the types of work for which these contracts are allowed and their duration. This measure also includes regulation governing the establishment and operation of temporary work agencies and requirements for agency workers to receive the same pay and/or conditions as equivalent workers in the user firm, which can increase the cost of using temporary agency workers relative to hiring workers on permanent contracts.

The index is constructed in several steps. These 21 items are scored in comparable units and are normalized to range from 0 to 6, with higher scores representing stricter regulation. After converting each item to a cardinal scale, the indicators are calculated using weights. Three versions of the overall summary indicator are available, reflecting changes over time in the breadth of information incorporated into the indicator: a) Version 1 is an unweighted average of the sub-indicators for regular and temporary contracts. The indicator for regular contracts does not include item 9 (maximum to make a claim of unfair dismissal) and the indicator for temporary contracts does not include items 16 (authorisation and reporting requirements for TWAs) and 17 (equal treatment for TWA workers). b) Version 2 is the weighted sum of the sub-indicators for regular and temporary contracts and collective dismissals. The indicators for regular and temporary contracts are the same as for version 1. c) Version 3 of the overall summary indicator incorporates three new data items collected for the first time in 2008 (items 9, 16 and 17).

Composite Indicators and Rankings: Inventory 2011 63 50. Index of Economic Freedom

Developer 1 Heritage Foundation Developer 2 Wall Street Journal Year launched 1995 Latest Edition 2011 Field Economy Number of Main Dimensions 10 Description of Main Dimensions 1. Business Freedom 2. Trade Freedom 3. Fiscal Freedom 4. (Weights in Parenthesis) Government Spending 5. Monetary Freedom 6. Investment Freedom 7. Financial Freedom 8. Property rights 9. Freedom from Corruption 10. Labor Freedom (EQUAL weights) Number of Underlying Indicators 52 Number of units ranked 183 Type of units ranked Countries Link to report http://www.heritage.org/index/ Link to data http://www.heritage.org/index/explore

Economic freedom is defined as the absence of government coercion or constraint on the production, distribution, or consumption of goods and services beyond the extent necessary for citizens to protect and maintain liberty itself. To measure economic freedom and rate each country, the authors of the Index study 50 independent economic variables falling into 10 broad categories, or factors, of economic freedom: 1. Trade policy 2. Fiscal burden of government 3. Government intervention in the economy 4. Monetary policy 5. Capital flows and foreign investment 6. Banking and finance 7. Wages and prices 8. Property rights 9. Regulation 10. Informal market activity. All 10 factors are equally important to the level of economic freedom in any country − the factors are weighted equally. We measure ten components of economic freedom, assigning a grade in each using a scale from 0 to 100, where 100 represents the maximum freedom. The ten component scores are then averaged to give an overall economic freedom score for each country.

Composite Indicators and Rankings: Inventory 2011 64 51. Index of Globalization

Developer 1 KOF-Swiss Federal Institute of Technology Zurich Developer 2 Year launched 2002 Latest Edition 2010 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Economic Globalization (37%) 2. Social Globalization (Weights in Parenthesis) (39%) and 3. Political Globalization (25%) Number of Underlying Indicators 24 Number of units ranked 156 Type of units ranked Countries Link to report http://globalization.kof.ethz.ch/ Link to data http://globalization.kof.ethz.ch/static/pdf/rankings_2010.pdf

The index measures the three main dimensions of globalization: economic, social, and political. In addition to three indices measuring these dimensions, an overall index of globalization and sub-indices referring to actual economic flows, economic restrictions, data on personal contact, data on information flows, and data on cultural proximity are calculated. In constructing the indices of globalization, each original variable has been transformed to an index on a zero to ten scale, where ten is the maximum value for a specific variable over the period 1970-2003, and zero is the minimum value.1 Higher values denote more globalization. When higher values of the original variable indicate higher globalization, the formula ((Vi-Vmin)/(Vmax- Vmin)*10) has been used for transformation. Conversely, when higher values indicate less globalization, the formula is ((Vmax-Vi)/(Vmax-Vmin)*10). The weights for calculating the sub-indices are determined using principal components analysis. The analysis partitions the variance of the variables used in each sub- group. The weights are then determined in a way that maximizes the variation of the resulting principal component, so that the indices capture the variation as fully as possible. The same procedure is applied to the sub-indices in order to derive the overall index of globalization.

Composite Indicators and Rankings: Inventory 2011 65 52. Institutional Investor Country Credit Ratings

Developer 1 Institutional Investor Magazine Developer 2 Year launched 1979 Latest Edition 2007 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 173 Type of units ranked Countries Link to report http://www.iimagazinerankings.com/CountryCredit/index.asp Link to data http://www.iimagazinerankings.com/CountryCredit/GlobalRanking.asp

Credit ratings are based on information provided by senior economists and analysts in leading global banks and money management and securities firms. Respondents have graded each country on a scale from 1 to 100, 100 being the least chance of default. Participants also ranked ten political, economic and financial indicators in order of their importance for each region and for selected countries. Participants’ responses were weighted according to their institutions’ assets.

Composite Indicators and Rankings: Inventory 2011 66 53. Internal Market Scoreboard and Internal Market Index

Developer 1 European Commission Developer 2 Year launched 1997 Latest Edition 2010 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators 12 Number of units ranked 27 Type of units ranked EU Countries Link to report http://ec.europa.eu/internal_market/score/index_en.htm#score Link to data http://ec.europa.eu/internal_market/score/docs/score21_en.pdf

The Internal Market Scoreboard examines the records of member-states in ensuring that the internal Market works in practice. It does so by first examining how quickly and how well each of the Member States transposes Internal Market directives into national law. The Scoreboard also highlights the number of infringement proceedings taken against each Member State. Given the vital role European standards play in reducing the cost and administrative burdens in doing business in the European Union, it is important that they are transposed by national standards organisations. The Scoreboard reports on the transposition records of the national standards organisations. Lastly, the Scoreboard also focuses on how well the Internal Market is functioning in practice in two ways. Firstly, the Internal Market Index aims to track progress in the Internal Market towards becoming a fully functioning single market. Secondly, the Commission has carried out a study on price convergence which is another indicator of how well the Internal Market is functioning.

The Internal Market Index tracks over time the effects of Internal Market policy. Internal Market policy aims to achieve the free circulation of goods, services, capital and workers within the European Union. The Index is computed as a weighted sum of 12 base indicators: 1. Sectoral and ad hoc state aid 2. Values of pension fund 3. Telecommunication costs 4. Electricity prices 5. Gas prices 6. Relative price level 7. Retail lending interest rate over savings rate 8. Intra-EU Foreign Direct Investment 9. Intra EU trade 10. Workers from other Members States 11. Value of published public procurement and 12. Postal tariffs. The weights have been provided though the budget allocation method* by involving a panel of national experts on the internal market (the Internal Market Advisory Committee). The Index is calculated by aggregating the data from each of the Member States. Although all the data is not available for all Member States, it is possible to measure the extent to which the index has increased in each Member State. This does not allow ranking Member States’ relative Internal Market performance. A rapid increase in the index may simply indicate that a Member State started from a low level and a slow increase could be a sign that a Member State started from a level where there was little room for further improvement. But it is possible to see how much the index has increased in each Member State since 1994 – and to identify the variables within the index responsible for the change. The weights have been provided though the budget allocation method (Jesinghaus 1997) by involving a panel of national experts on the internal market (the Internal Market Advisory Committee).

Composite Indicators and Rankings: Inventory 2011 67 54. International Country Risk Guide (ICRG) Ratings - Composite Risk Rating

Developer 1 PRS Group Developer 2 Year launched 1980 Latest Edition 2010 Field Economy Number of Main Dimensions 3 Description of Main Dimensions Political Risk index (100 points), Financial Risk (50 points) and (Weights in Parenthesis) Economic Risk (50 points) Number of Underlying Indicators 22 Number of units ranked 150 Type of units ranked Countries

Link to report https://www.prsgroup.com/ICRG.aspx

Link to data https://www.prsgroup.com/CountryData.aspx

The International Country Risk Guide (ICRG) rating comprises 22 variables in three subcategories of risk: political, financial, and economic. A separate index is created for each of the subcategories. The Political Risk index is based on 100 points, Financial Risk on 50 points, and Economic Risk on 50 points. The total points from the three indices are divided by two to produce the weights for inclusion in the composite country risk score. The composite scores, ranging from zero to 100, are then broken into categories from Very Low Risk (80 to 100 points) to Very High Risk (zero to 49.9 points).

Composite Indicators and Rankings: Inventory 2011 68 55. Inward FDI Performance Index

Developer 1 UNCTAD Developer 2 Year launched 1988 Latest Edition 2007 Field Economy Number of Main Dimensions 2 Description of Main Dimensions Global FDI flows, Global GDP (Weights in Parenthesis) Number of Underlying Indicators 2 Number of units ranked 141 Type of units ranked Countries Link to report http://www.unctad.org/templates/webflyer.asp?intitemid=2471&lang=1 Link to data http://www.unctad.org/templates/webflyer.asp?intitemid=2471&lang=1

The Inward FDI Performance Index ranks countries by the FDI they receive relative to their economic size. It is the ratio of a country’s share in global FDI inflows to its share in global GDP. A value greater than one indicates that the country receives more FDI than its relative economic size, a value below one that it receives less (a negative value means that foreign investors disinvest in that period). The index thus captures the influence on FDI of factors other than market size, assuming that, other things being equal, size is the "base line" for attracting investment. These other factors can be diverse, ranging from the business climate, economic and political stability, the presence of natural resources, infrastructure, skills and technologies, to opportunities for participating in privatization or the effectiveness of FDI promotion.

Composite Indicators and Rankings: Inventory 2011 69 56. Inward FDI Potential Index

Developer 1 UNCTAD Developer 2 Year launched 1988 Latest Edition 2006 Field Economy Number of Main Dimensions 12 Description of Main Dimensions 1. GDP per capita, 2. The rate of GDP growth over the previous 10 (Weights in Parenthesis) years 3. The share of exports in GDP 4, the average number of telephone lines per 1,000 inhabitants and mobile telephones per 1,000 inhabitants 5. Commercial energy use per capita to measure the availability of traditional infrastructure 6. The share of R&D spending in GDP 7. The share of tertiary students in the population 8. Country risk. 9. The world market share in exports of natural resources, 10. The world market share of imports of parts and components for automobiles and electronic products 11. The world market share of exports of services, 12. The share of world FDI inward stock Number of Underlying Indicators 12 Number of units ranked 141 Type of units ranked Countries Link to report http://www.unctad.org/templates/webflyer.asp?intitemid=2472&lang=1 Link to data http://www.unctad.org/templates/webflyer.asp?intitemid=2472&lang=1

The Inward FDI Potential Index captures several factors (apart from market size) expected to affect an economy’s attractiveness to foreign investors. It is an average of the values (normalized to yield a score between zero, for the lowest scoring country, to one, for the highest) of 12 variables (no weights are attached): 1. GDP per capita, an indicator of the sophistication and breadth of local demand (and of several other factors), with the expectation that higher income economies attract relatively more FDI geared to innovative and differentiated products and services 2. The rate of GDP growth over the previous 10 years, a proxy for expected economic growth. 3. The share of exports in GDP, to capture openness and competitiveness 4. As an indicator of modern information and communication infrastructure, the average number of telephone lines per 1,000 inhabitants and mobile telephones per 1,000 inhabitants 5. Commercial energy use per capita to measure the availability of traditional infrastructure 6. The share of R&D spending in GDP captures local technological capabilities 7. The share of tertiary students in the population, indicating the availability of high-level skills 8. Country risk, a composite indicator capturing some macroeconomic and other factors that affect the risk perception of investors. The variable is measured in such a way that high values indicate less risk 9. The world market share in exports of natural resources, to proxy for the availability of resources for extractive FDI 10. The world market share of imports of parts and components for automobiles and electronic products, to capture participation in the leading TNC integrated production systems (WIR02) 11. The world market share of exports of services, to seize the importance of FDI in the services sector that accounts for some two thirds of world FDI 12. The share of world FDI inward stock, a broad indicator of the attractiveness and absorptive capacity for FDI, and the investment climate.

Composite Indicators and Rankings: Inventory 2011 70

57. KPMG Global Corporate and Indirect Tax Survey

Developer 1 KPMG Developer 2 Year launched 1993 Latest Edition 2010 Field Economy Number of Main Dimensions 2 Description of Main Dimensions 1. Corporate 2. Value added tax (Weights in Parenthesis) Number of Underlying Indicators 2 Number of units ranked 114 Type of units ranked Countries Link to report http://www.kpmg.com/LU/en/IssuesAndInsights/Articlespublicati ons/Pages/KPMG%27sCorporateandIndirectTaxRateSurvey2010. aspx Link to data http://www.kpmg.com/Global/en/IssuesAndInsights/ArticlesPubli cations/Documents/Corp-and-Indirect-Tax-Oct12-2010.pdf

KPMG International’s Corporate and Indirect Tax Survey has been run every year since 1993. It now covers 114 countries. This year’s survey compares corporate income tax rates as at 1 July, 2010 with their equivalent each year back to 2000. The survey also includes information on Value Added Taxes or Goods and Services Taxes in 114 countries, going back six years.

Composite Indicators and Rankings: Inventory 2011 71 58. Lisbon Index

Developer 1 European Commission Developer 2 Year launched 2000 Latest Edition 2010 Field Economy Number of Main Dimensions 8 Description of Main Dimensions Lisbon targets1. 85% for employment rate among men aged 15-54 2. (Weights in Parenthesis) 64% for employment rate among women aged 15-54 3. 50% employment rate for people aged 55-64 4. 10% of early school leavers aged 18-24 5. 85% of secondary education attainment for people aged 20-24 6. 12.5% of lifelong learning participation of people aged 25-64 7. 2% for business expenditure in R&D as % of GDP 8. 1% for government, higher education and non-pro.t expenditure in R&D as % of GDP Number of Underlying Indicators 8 Number of units ranked 27 Type of units ranked EU Link to report http://ec.europa.eu/regional_policy/sources/docgener/focus/2010_03_ lisbon_index.pdf Link to data http://ec.europa.eu/regional_policy/sources/docgener/focus/2010_03_ lisbon_index.pdf

The Lisbon Index measures how far regions are from eight Lisbon targets for 2010. A region scores 100 if it has reached all eight targets, while the region farthest away from all eight targets scores 0. The Lisbon Index shows how close an EU region is to eight derived Lisbon 2010 targets.

The methodology developed for this indicator had four goals: (1) To take into account the Lisbon targets in a manner that would be easy to understand; (2) To ensure that the same value receives the same score each year; (3) To avoid double or even triple counting; (4) To combine the individual indicators in such a way that the same change receives the same weight across related indicators.

The first goal was reached by using the distance from the Lisbon target for the eight indicators instead of the absolute values of the indicators (also known as a ratio transformation). These distances are then transformed into a score between 0 and 1. The region farthest removed from the target receives 0, and regions which have reached the target or exceeded it receive 1. All these scores are combined and transformed from an indicator between 0 and 100. The region farthest removed from the Lisbon targets receives 0 and any which have reached all targets receive 100. The second goal was reached by fixing the maximum distance from the target. This meant that, for example, an employment rate of 65% always receives the same score, be it in 2000 or in 2007. In addition, outliers were not taken into account, to avoid distorting the distribution of an indicator; this is also known as cutting 'noses and tails'. The third goal was reached by calculating Lisbon targets for mutually exclusive indicators based on the official targets. This had to be done for both the employment targets and the R&D targets. The fourth goal had consequences for the employment rates and the R&D targets. For the employment rates, the minimum values were adjusted in such a way that an increase of 1 percentage point always leads to the same increase in the Lisbon Index. For the R&D targets, the weightings used to combine the indicators were adjusted to ensure that an increase of 1 percentage point would lead to the same increase in the Lisbon Index.

Calculation of the Lisbon Index: Each of the eight indicators is transformed into a score that varies between 0 and 1. Score = 1- (Lisbon target - regional rate) / (Lisbon target – minimum regional rate)

Composite Indicators and Rankings: Inventory 2011 72 59. Lisbon Review Index

Developer 1 World Economic Forum (WEF) Developer 2 Year launched 2002 Latest Edition 2010 Field Economy Number of Main Dimensions 8 Description of Main Dimensions 1. Creating an Information Society for All 2. Developing a European (Weights in Parenthesis) Area for Innovation, Research and Development 3. Liberalization: Completing the Single Market/State Aid and Competition Policy 4. Building Network Industries: In Telecommunications, Utilities and Transportation 5. Creating Efficient and Integrated Financial Services 6. Improving the Enterprise Environment: Business Start-ups/ Regulatory Framework 7. Increasing Social Inclusion: Bringing People to the Workforce, Upgrading Skills and Modernizing Social Protection 8. Enhancing Sustainable Development (equal weights) Number of Underlying Indicators 67 Number of units ranked 33 Type of units ranked EU Link to report http://www3.weforum.org/docs/WEF_LisbonReview_Report_2010.pdf Link to data http://www3.weforum.org/docs/WEF_LisbonReview_Report_2010.pdf

The Lisbon Review Index compares the performance of individual EU members to provide a sense of which countries are making the most progress and which are lagging behind. It also takes stock of the change in relative performances of individual countries since the last Lisbon Review in 2008 to gauge the countries’ relative progress.

The present analysis is based on the same methodology used in the past four editions of this study, breaking the Lisbon Strategy into eight distinct dimensions that capture the areas highlighted by Europe’s leaders as critical for reaching the goal of becoming the world’s most competitive economy. The eight dimensions are: 1.Creating an Information Society for All 2. Developing a European Area for Innovation, Research and Development 3. Liberalization: Completing the Single Market/State Aid and Competition Policy 4. Building Network Industries: In Telecommunications, Utilities and Transportation 5. Creating Efficient and Integrated Financial Services 6. Improving the Enterprise Environment: Business Start-ups/ Regulatory Framework 7. Increasing Social Inclusion: Bringing People to the Workforce, Upgrading Skills and Modernizing Social Protection 8. Enhancing Sustainable Development

The assessment of Europe’s competitiveness is based on publicly available hard data from respected institutions (such as Internet penetration rates, unemployment rates, etc.) and data from the World Economic Forum’s Executive Opinion Survey (EOS).

The overall Lisbon scores for each country are calculated as an unweighted average of the individual scores in the eight dimensions.

Composite Indicators and Rankings: Inventory 2011 73 60. Lisbon Scorecard and League Table

Developer 1 Centre for European Reform Developer 2 Year launched 2000 Latest Edition 2010 Field Economy Number of Main Dimensions 5 Description of Main Dimensions 1. Innovation 2.liberalisation 3.enterprise 4.employment and social (Weights in Parenthesis) exclusion 5.sustainable development and the environment Number of Underlying Indicators 12 Number of units ranked 27 Type of units ranked EU Countries Link to report http://www.cer.org.uk/pdf/rp_967.pdf Link to data http://www.cer.org.uk/pdf/rp_967.pdf

It provides a comprehensive assessment of EU’s progress on the Lisbon Agenda. The Scorecard picks out countries doing big progress and those falling behind (“heroes” versus “villains”). The scorecard includes a ranking of all the EU members-states on their economic reform performance.

Composite Indicators and Rankings: Inventory 2011 74 61. Logistics Performance Index (LPI)

Developer 1 World Bank Developer 2 Year launched 2007 Latest Edition 2010 Field Economy Number of Main Dimensions 6 Description of Main Dimensions 1. Efficiency of the clearance process (i.e. speed, simplicity and (Weights in Parenthesis) predictability of formalities) by border control agencies, including Customs; 2. Quality of trade and transport related infrastructure (e.g. ports, railroads, roads, information technology); 3. Ease of arranging competitively priced shipments; 4. Competence and quality of logistics services (e.g., transport operators, customs brokers); 5. Ability to track and trace consignments; 6. Timeliness of shipments in reaching destination within the scheduled or expected delivery time. Number of Underlying Indicators N/A Number of units ranked 155 Type of units ranked Countries Link to report http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTTRAN SPORT/EXTTLF/0,,contentMDK:21514122~menuPK:3875957~page PK:210058~piPK:210062~theSitePK:515434,00.html Link to data http://siteresources.worldbank.org/INTTLF/Resources/LPI2010_for_w

eb.pdf

The Logistics Performance Index is based on a worldwide survey of operators on the ground (global freight forwarders and express carriers), providing feedback on the logistics “friendliness” of the countries in which they operate and those with which they trade. Feedback from operators is supplemented with quantitative data on the performance of key components of the logistics chain in the country of work. The LPI measures performance along the logistics supply chain within a country and offers two different perspectives: International and Domestic. International LPI provides qualitative evaluations of a country in six areas by its trading partners - logistics professionals working outside the country. Domestic LPI provides both qualitative and quantitative assessments of a country by logistics professionals working inside it. It includes detailed information on the logistics environment, core logistics processes, institutions, and performance time and cost data.

The Country Scorecard uses six key dimensions to benchmark countries performance and also displays the derived overall LPI index. The scorecard allows comparisons with the World (with the option to display World best performer) and with the Region or income group (with the option to display the Region’s or income group best performer). The Global LPI Ranking presents performance scores of all countries on the overall LPI index. World Map provides a color-coded map for the global view of the overall LPI index and the six key dimensions. The Cross-Country Comparison allows bar-chart comparison of up to 20 countries on their overall LPI index and six key dimensions. The LPI is the weighted average of the country scores on the six key dimensions: 1. Efficiency of the clearance process (i.e. speed, simplicity and predictability of formalities) by border control agencies, including Customs; 2. Quality of trade and transport related infrastructure (e.g. ports, railroads, roads, information technology); 3. Ease of arranging competitively priced shipments; 4. Competence and quality of logistics services (e.g., transport operators, customs brokers); 5. Ability to track and trace consignments; 6. Timeliness of shipments in reaching destination within the scheduled or expected delivery time.

The scorecards demonstrate comparative performance - the dimensions show on a scale from 1 to 5 relevant to the possible Comparison groups – all countries (World), region and income groups. The LPI is constructed from these six indicators using principal component analysis (PCA). In the LPI, the inputs for PCA are country scores on the six questions above, averaged across all respondents providing data on a

Composite Indicators and Rankings: Inventory 2011 75 given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation prior to conducting the PCA. The output from the analysis is a single indicator— the LPI—that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the original six indicators accounted for by the LPI.

To construct the international LPI, normalized scores for each of the six component indicators are multiplied by their component loadings in the table below and then summed. The component loadings represent the weight accorded to each of the component indicators in constructing the international LPI. Since the loadings are similar for all six indicators, the international LPI is relatively close to a simple average of the six component indicators.

Dimension Weight Customs 0.42 Infrastructure 0.42 International shipments 0.37 Logistics quality and competence 0.42 Tracking and tracing 0.41 Timeliness 0.40

Confidence intervals: A vital part of the LPI dataset is the estimated 80 percent confidence interval calculated for each country’s score. The confidence interval is used to construct upper and lower bounds for a country’s LPI score. These bounds are then used to calculate lower and upper bounds on country rankings. Together, these ranges are designed to take account of the fact that the LPI is based on a survey and is therefore subject to sampling error. Confidence intervals and low high ranges for scores and ranks are larger for small markets that have few respondents, which reflects the greater uncertainty to which these estimates are subject. To calculate the confidence interval, the standard error of LPI scores is estimated across all respondents for a particular country. The upper and lower bounds of the confidence interval are then

where LPI is a country’s LPI score, N is the number of survey respondents for that country, s is the estimated standard error of each country’s LPI score, and t is Student’s t-distribution. The high and low scores are also used to calculate upper and lower bounds on country rankings. The upper bound is the LPI rank a country would receive if its LPI score were at the upper bound of the confidence interval rather than the center. The lower bound is the LPI rank a country would receive if its LPI score were at the lower bound of the confidence interval rather than the center. In both cases, the scores of all other countries are kept constant. The average confidence interval on the 1–5 scale is 0.22, or about 7.5 percent of the average country’s LPI score. On average, this is equivalent to 10 places in the LPI ranking. It is therefore necessary to be cautious in interpreting small differences in LPI scores and rankings.

When comparing LPI results for 2010 and 2007, it is important to pay attention to the confidence intervals. The focus should be on statistically significant changes as indicated by nonoverlapping low-high ranges, rather than on simple comparisons of individual scores. Only when, for example, the lower bound of a country’s 2010 LPI score is higher than its 2007 upper bound can it be concluded that there has been a statistically significant improvement in performance. This approach takes account of the influence of sampling error in both surveys. Although representing the most comprehensive data source currently available on country logistics and trade facilitation environments, the LPI is also subject to important limitations. First, the experience of international freight forwarders may not represent the broader logistics environment in poor countries, where they tend to coexist with more traditional operators. The two groups’ interactions with government agencies, as well as service levels, might differ. Second, for landlocked or island countries, the LPI may capture access problems outside the country being assessed—for example, transit difficulties. The low rating of a landlocked country such as Rwanda might not give full justice to its trade facilitation efforts because they are dependent on complex international transit systems. And landlocked countries cannot address transit inefficiencies through domestic reforms.

Composite Indicators and Rankings: Inventory 2011 76 62. Long Island Index

Developer 1 Long Island Index Developer 2 Year launched 2004 Latest Edition 2010 Field Economy Number of Main Dimensions 5 Description of Main Dimensions 1. Economy 2. Housing 3. Environment 4. Taxes 5. Education (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 1 Type of units ranked Long Island Link to report http://www.longislandindex.org/ Link to data http://www.longislandindex.org/fileadmin/Reports_and_Maps/201 1_Index/Getting_it_Done_2011_LI_Index_Special_Analysis.pdf

The Long Island Index is a project that gathers and publishes data on the Long Island region. The Index does not advocate specific policies. Instead, our goal is to be a catalyst for action, by engaging the community in thinking about our region and its future. Specifically, the Index seeks to:

 Measure where we are and show trends over time  Encourage regional thinking  Compare our situation with other similar regions  Increase awareness of issues and an understanding of their interrelatedness  Inspire Long Islanders to work together in new ways to achieve shared goals

Composite Indicators and Rankings: Inventory 2011 77 63. Luxembourg Competitiveness Index (Tableau de bord "Compétitivité")

Developer 1 Observatoire de la Compétitivité, Luxembourg Developer 2 Year launched 2000 Latest Edition 2009 Field Economy Number of Main Dimensions 10 Description of Main Dimensions 1. Macro performance 2. Employment 3.Productivity and cost 4. (Weights in Parenthesis) Functioning of markets 5. Institutions and regulation 6. Entrepreneurship 7. Education 8. Knowledge economy 9. Social Cohesion 10. Environment (equal weights) Number of Underlying Indicators 78 Number of units ranked 1 Type of units ranked Luxembourg Link to report http://www.odc.public.lu/indicateurs/tableau_de_bord/index.html Link to data http://www.odc.public.lu/publications/perspectives/PPE_16.pdf

It measures progress in competitiveness in Luxemburg. Ten categories are grouped into 3 dimensions of competitiveness: economics, social and environmental. These indicators are used in three ways: first, indicators are analyzed in comparison to the European average, which serves as a benchmark. If the value of Luxemburg is 20 % better or equal to the mean of the EU, the indicator is classified as “green” (favorable position). If the value is 20 % less than the mean of the EU, the indicator sis classified as “red” (unfavorable position). In the case that the value of Luxemburg is between + 20 % and - 20 % of the EU average the indicator is classified as "orange" (neutral position). Secondly, the evolution of performance is analyzed across years, as a temporal dimension. Thirdly, the indicators are synthesized into a composite index -- l’Observatoire de la Compétitivité calculates a summary competitiveness index. The 78 indicators are standardized, classified into 10 categories and each category is aggregated using equal weights (10%) A second aggregation is done, in order to minimize the differences of level of indicators within categories with two methods of standardization used: 1) in order to deal with inconsistencies between nominal and effective weights, categories are rescaled using a minmax approach and then average them 2) alternatively, the Copeland method can be used. Scores for countries are presented with both methods, in decreasing order.

Composite Indicators and Rankings: Inventory 2011 78 64. Market Potential Index (MPI)

Developer 1 MSU-CIBER Developer 2 Year launched 1995 Latest Edition 2009 Field Economy Number of Main Dimensions 8 Description of Main Dimensions 1. Market Size (10/50) 2. Market Growth Rate (6/50) 3. Market (Weights in Parenthesis) Intensity (7/50) 4. Market Consumption Capacity (5/50) 5. Commercial Infrastructure (7/50) 6. Economic Freedom (5/50) 7. Market Receptivity (6/50) and 8. Country Risk (4/50). Number of Underlying Indicators 19 Number of units ranked 27 Type of units ranked Countries Link to report http://globaledge.msu.edu/resourcedesk/mpi/ Link to data http://globaledge.msu.edu/resourcedesk/mpi/

The index aims to assist companies in comparing the Emerging Markets in terms of market potential. The index is constructed based on 8 dimensions encompassing 19 variables. These eight dimensions form, in turn, 8 sub-indices: 1. Market Size (variables: urban population and electricity consumption) with a weight of 10/50 2. Market Growth Rate (variables: Average annual growth rate of commercial energy use between years 1996-2001 and Real GDP growth rate (%)) with a weight of 6/50 3. Market Intensity (variables include GNI per capita estimates using PPP (US Dollars) and Private consumption as a percentage of GDP (%)) with a weight of 7/50 4. Market Consumption Capacity (Percentage share of middle-class in consumption/income) with a weight of 5/50 5. Commercial Infrastructure (variables include Telephone mainlines (per 100 habitants), Cellular mobile subscribers (per 100 habitants), Number of PC's (per 100 habitants), Paved road density (km per million people), Internet hosts (per million people), Population per retail outlet, Television sets (per 1000 persons)) with weight of 7/50 6. Economic Freedom (variables include Economic Freedom Index by Heritage Foundation Political Freedom Index by Freedom House) with weight of 5/50 7. Market Receptivity (variables Per capita imports from US (US Dollars) and Trade as a percentage of GDP (%)) with weight of 6/20 and 8. Country Risk (Country risk rating by Euromoney) with weight of 4/50. The index is based on a scale of 0-100 and countries are ranked from highest market potential (the maximum being 100) to lowest (the minimum being 0).

Composite Indicators and Rankings: Inventory 2011 79 65. McKinsey Global Confidence Index

Developer 1 McKinsey Developer 2 Year launched 2004 Latest Edition 2007 Field Economy Number of Main Dimensions N/A Description of Main Dimensions Attitudes of business executives (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 200 Type of units ranked Countries Link to report http://mkqpreview1.qdweb.net/Organization/Talent/The_McKinsey _Global_Survey_of_Business_Executives__Confidence_Index_Jan uary_2007_1880 Link to data http://mkqpreview1.qdweb.net/Organization/Talent/The_McKinsey _Global_Survey_of_Business_Executives__Confidence_Index_Jan uary_2007_1880

The Confidence Index is a barometer of the attitudes of business executives about the economy's near-term prospects. It expresses, in a single figure, responses to a standard set of four questions about current economic conditions and expectations. An index above 50 means that positive responses outnumber negative ones. The surveys of global executives garnered responses from 5,500 chief executives and other senior corporate leaders around the world: 11 percent from the developed countries of the Asia-Pacific region, 31 percent from Europe, 41 percent from North America, and 18 percent from developing markets. The index scores are presented for regions as well as key countries.

Composite Indicators and Rankings: Inventory 2011 80 66. Microscope Index

Developer 1 IFC Developer 2 Year launched 2007 Latest Edition 2009 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Regulatory framework (40%), 2. investment climate (20%) and (Weights in Parenthesis) 3. institutional development (40%) Number of Underlying Indicators 13 Number of units ranked 55 Type of units ranked Countries Link to report http://www.ifc.org/ifcext/gfm.nsf/Content/A2F-EIUMicroscope Link to data Page 13 of http://www.ifc.org/ifcext/gfm.nsf/AttachmentsByTitle/A2F-EIU- Microscope2009- English/$FILE/Microfinance_ENG_WEB_Sept+25.pdf

This expanded global index evaluates microfinance as a commercially viable and sustainable activity using three distinct categories: 1) the institutional and regulatory framework for microfinance, including official legal recognition, interest rate restrictions, market distortions, capital requirements and regulatory capacity; 2) the general investment climate, especially accounting standards, governance tendencies and transparency requirements among microfinance providers; and 3) the level of institutional development, as measured by market concentration, the range of services provided beyond credit and the quality of borrower information. The study assigns countries a score of 0-4 for each of 13 indicators, where 4 equals the best conditions for microfinance and 0 the worst. The indicators are then normalised so that each country is scored on a scale of 0=100 for each. These 13 indicators are then grouped into three categories to produce the overall index score. For the purposes of this study, microfinance institutions (MFIs) are defined narrowly, as those that provide “microcredit”—that is, loans to non-salaried workers that are typically less than or equal to 250% of gross national income per capita (GNI per capita). Microcredit operations are carried out by a variety of institutions, some regulated by financial authorities and some not.

The 13 indicators for this index, and the categories into which they are subdivided, are as follows: Regulatory framework 1) Regulation of microcredit operations 2) Formation and operations of regulated/supervised specialised MFIs 3) Formation and operation of non-regulated MFIs 4) Regulatory and examination capacity Investment climate 1) Political stability 2) Capital market stability 3) Judicial system 4) Accounting standards 5) Governance standards 6) MFI transparency Institutional development 1) Range of MFI services 2) Credit bureaus 3) Level of competition

Scoring methodology: Each of the 13 scoring criteria are scored from 0 to 4, where 4= best and 0 = worst. These indicator scores are aggregated to produce an overall scoring range of 0 – 100, where 100= best.

Composite Indicators and Rankings: Inventory 2011 81 67. Networked Readiness Index (NRI)

Developer 1 World Economic Forum (WEF) Developer 2 Year launched 2001 Latest Edition 2010 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Environment 2. Readiness 3. Usage (no weights provided) (Weights in Parenthesis) Number of Underlying Indicators 68 Number of units ranked 133 Type of units ranked Countries Link to report http://networkedreadiness.com/gitr/ Link to data http://networkedreadiness.com/gitr/

The NRI measures the degree of preparation of a nation or community to participate in and benefit from ICT developments. The NRI is a composite of three other dimensions: 1) the environment for ICT offered by a given country 2) the readiness of the country’s key stakeholders (individuals, business and governments) to use ICT and 3) the usage of ICT amongst key stakeholders. In turn, these 3 dimensions are sub-indices themselves with equal weights in the overall NRI, formed by the following: 1) Environment component index: market environment, political and regulatory environment and infrastructure environment 2) Readiness Component Index: Individual readiness, business readiness and government readiness and 3) Usage Components Index: Individual usage, business usage and government usage. This represents 48 variables. Countries are ranked from highest to lowest readiness.

Composite Indicators and Rankings: Inventory 2011 82 68. Offshore Location Attractiveness Index

Developer 1 AT Kearney Developer 2 Year launched 2003 Latest Edition 2004 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Financial infrastructure (40%) 2. People skills and (Weights in Parenthesis) availability (30%) 3. Business environment (30%) Number of Underlying Indicators 39 Number of units ranked 25 Type of units ranked Countries http://www.atkearney.com/index.php/Publications/making- Link to report offshore-decisions.html?q=offshore http://www.atkearney.com/index.php/Publications/making- Link to data offshore-decisions.html?q=offshore

The index measures the viability of countries as offshore destinations based on three dimensions: their financial structure, people skills and availability and business environment. It aims to assist companies understand and compare the factors that make countries attractive as potential locations for offshore services. The index is based on data gathered from corporate surveys, IT and BPO activities, availability of skilled labor and national initiatives to promote offshoring. A total of 39 measurements were gathered with the following structure: 1) financial structure (40% weight in index) includes variables such as average wages, relative tax burden, cost of corruption and fluctuating exchange rates, telecommunication systems amongst others 2) people skills and availability (30% weight in the index) includes variables such as total workforce, university educated workforce, existing IT and business process outsourcing (BPO) market size, scores of standardized education and language tests amongst others 3) Business environment (weight of 30%) includes variables such as investor and analyst ratings of overall business and political environment, AT Kearney’s Foreign Direct Investment Confidence Index, extent of bureaucracy and software piracy rates amongst others. Thus, financial structure is rated on a scale from 1 to 4 while the other 2 components on a scale from 1 to 3 for an overall score. Countries are ranked from highest score (more attractive as offshore destination) to lowest (less attractive as offshore destination).

Composite Indicators and Rankings: Inventory 2011 83 69. Outward FDI Performance Index

Developer 1 UNCTAD Developer 2 Year launched 1988 Latest Edition 2010 Field Economy Number of Main Dimensions 2 Description of Main Dimensions Share of a country´s outward FDI in world FDI as a ratio of its share (Weights in Parenthesis) in world GDP. Number of Underlying Indicators 2 Number of units ranked 128 Type of units ranked Countries Link to report http://www.unctad.info/en/Surveys/World-Investment-Report-2010/ Link to data http://www.unctad.org/Templates/Page.asp?intItemID=1923&lang=1

The Outward FDI Performance Index is calculated as the share of a country’s outward FDI in world FDI as a ratio of its share in world GDP. The Index reflects two sets of factors that determine outward FDI by transnational corporations (TNCs) headquartered in a given country: 1. "Ownership advantages", or firm- specific competitive strengths of TNCs (such as innovation, brand names, managerial and organizational skills, access to information, financial or natural resources, and size and network advantages) that they are exploiting abroad or wish to augment through foreign expansion and 2. "Location factors", which reflect primarily economic factors conducive to the production of different goods and services in home and host economies, such as relative market size, production or transport costs, skills, supply chains, infrastructure and technology support. Driven by the competitive pressures of a globalizing world economy, both factors work together to lead firms to invest abroad by establishing foreign affiliates. These affiliates then become a source of the competitive strength of their respective corporate networks.

Composite Indicators and Rankings: Inventory 2011 84 70. Qualitative Risk Measure in Foreign Lending (QLM-FE)

Developer 1 BERI Developer 2 Year launched 1999 Latest Edition 2008 Field Economy Number of Main Dimensions 11 Description of Main Dimensions Level of resolve toward honoring international obligations 3.0, (Weights in Parenthesis) Foreign loan structure and terms: 3.0, Corruption in financial transactions: 3.5, Concessionary loans and grants: 3.0, Net technocratic competence: 4.0, Legal framework: 3.5 Number of Underlying Indicators N/A Number of units ranked 115 Type of units ranked Countries Link to report http://www.beri.com/qlm.asp Link to data http://www.beri.com/qlm.asp

It measures factors that have a direct influence on meeting international obligations but that cannot be assessed through regularly published statistics. The 11 criteria listed below have a weighted total of 20. Each criterion is rated from 5 (best case) to zero (worst case). Therefore, a perfect country would receive a score of 100 (20 x 5).

Weighting Level of resolve toward honoring international obligations 3.0 Foreign loan structure and terms: Range, concessionary to short term 2.0 Current market terms 1.0 Corruption in financial transactions: Direct fraud 2.0 Indirect diversion of funds 1.5 Concessionary loans and grants: Level of access 1.5 Influence of strategic importance 1.5 Net technocratic competence: Overall assessment 2.5 Political interference 1.5 Legal framework: Convertibility for principal, interest, fees 2.0 Taxation constraints 1.5

Composite Indicators and Rankings: Inventory 2011 85 71. Quality of Workforce Index (QWI)

Developer 1 BERI Developer 2 Year launched 1980 Latest Edition 2011 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Workforce Performance (40%), 2. Workforce Characteristics (Weights in Parenthesis) (35%) 3. Workforce Organization and Practices (25%). Number of Underlying Indicators 15 Number of units ranked 42 Type of units ranked Countries Link to report http://www.beri.com/qwi.asp Link to data http://www.beri.com/qwi.asp

QWI is a detailed assessment of labor conditions in 42 countries for 7 years of history, the present year, and forecast for next year. The objective of QWI is to measure the quality of the workforce and provide business with a means of (1) comparing countries and (2) making such decisions as the degree to which capital-intensive operations are feasible. The measure for both manufacturing and services is based on 15 criteria grouped under three sub-indices. The weights for the three sub-indices reflect their relative importance to the quality of a workforce. Workforce Performance receives a weighting of 40%. Workforce Characteristics receives a weight of 35% (this sub-index measures the attributes of the workforce that contribute to its ability to perform) Workforce Organization and Practices, with a weight of 25%, is about the environment within which personnel work; this sub-index measures the legal framework for labor and attitudes of workers and their unions affecting worker performance. The ratings given for each criterion are relative to all 42 countries. For example, if a country's management quality had improved in 2000 compared to 1990, its rating could decline if other countries improved even more during the same period.

Composite Indicators and Rankings: Inventory 2011 86 72. Regional Competitiveness Atlas

Developer 1 Eurochambres Developer 2 Year launched 2007 Latest Edition 2008 Field Economy Number of Main Dimensions 6 Description of Main Dimensions 1. Economic performance (economic background and GDP growth) 2. (Weights in Parenthesis) Employment 3. Training and lifelong learning 4. Research and Development / Innovation 5. Transport and Energy 6. Internationalisation Number of Underlying Indicators 16 Number of units ranked 268 Type of units ranked EU regions Link to report On a Separate Word Doc Link to data http://www.eurochambres.eu/Content/Default.asp?PageID=79

The atlas is a snapshot of the economic performance of European regions using key economic indicators. The objective of the document is to stimulate the debate on how regions can further enhance their economic development, involving all relevant stakeholders, and thus contribute to overall European growth. Six main indicators, all key to the competitiveness of enterprises, were chosen for analysis: 1. Economic performance (economic background and GDP growth) 2. Employment 3. Training and lifelong learning 4. Research and Development / Innovation 5. Transport and Energy 6. Internationalisation.

European regions were ranked according to these indicators, and for each Member State and indicator, the region showing the biggest progression in comparison to the previous year was singled out, resulting in a comparison of the best progressing regions of the 27 Member States.

The objective of this Atlas is to gather data from all regions of the European Member States and obtain an overview of the economic situation for all of them (268 in total) in relation to a selected list of competitiveness topics. Considering the large number of regions and with a view to the chosen topics, the following procedure was applied in order to offer the reader an easy overview on the situation for each topic, treating available data in a coherent manner:

• Definition of a reference indicator for each topic. • Extraction of the data for all European regions for the reference indicator. • Ranking of the regions starting with the best progressing ones – based on the progress they have achieved since the previous edition of the Atlas. • Selection of the best progressing region of each Member State for the given reference indicator, top-down ranking of those 27 regions (except when data were missing or too old). • Definition of additional indicators that complement the reference indicator. • Extradition of the data of the additional indicators only for the 27 pre-selected regions.

Composite Indicators and Rankings: Inventory 2011 87 73. Regional Competitiveness Index (RCI)

Developer 1 European Union (EU) Developer 2 Paola Annoni and Kornelia Kozovska Year launched 2010 Latest Edition 2010 Field Economy Number of Main Dimensions 11 Description of Main Dimensions 11 pillars into 3 major groups: 1. key basic drivers: (Weights in Parenthesis) Institutions, Macro-economic stability, Infrastructure, Health and Quality of Primary & Secondary Education. 2. Competitiveness: Higher Education/ Training and Lifelong Learning, Labor Market Efficiency and Market Size. 3. Technological Readiness, Business Sophistication and Innovation, included in the third group. (weighted on the level of development) Number of Underlying Indicators 69 Number of units ranked 271 Type of units ranked EU regions Link to report On a separate word doc Link to data http://easu.jrc.ec.europa.eu/eas/downloads/pdf/JRC58169.pdf

Eleven pillars are included in the RCI with the objective of describing different dimensions of the level of competitiveness. The pillars are designed to capture short- as well as long term capabilities of the region. They are classified into three major groups: the pillars Institutions, Macro-economic stability, Infrastructure, Health and Quality of Primary & Secondary Education are included in the first group and represent the key basic drivers of all types of economies. As the regional economy develops, other factors enter into play for its advancement in competitiveness and are grouped in the second group of pillars – Higher Education/ Training and Lifelong Learning, Labor Market Efficiency and Market Size. At the most advanced stage of development of a regional economy, key drivers for regional improvement are factors related to Technological Readiness, Business Sophistication and Innovation, included in the third group.

The set of 69 indicators is chosen according to the literature review, experts’ opinion and data availability. A detailed statistical analysis is carried out separately for each pillar with the aim of assessing the consistency of the proposed framework both at the level of indicators and of pillars. The analysis is twofold: a univariate analysis indicator by indicator and a multivariate analysis on each pillar as a whole. The former allows for detecting possible problems with: i) missing data; ii) distribution asymmetry and outliers and iii) different measurement scales. These problems are addressed by adopting: i) specific imputation methods; ii) power-type transformations to correct for skeweness; iii) standardization. The multivariate analysis is carried out at the pillar level on the set of indicators as a whole. The aim is to assess their contribution in describing the latent dimension behind each pillar. ‘Anomalous’ indicators are in some cases detected and excluded from further analysis. The statistical analysis showed as most consistent pillars Institutions, Quality of Primary and Secondary Education, Labor Market Efficiency, Market Size and Innovation. The set of weights adopted for aggregating the sub-indexes depend on the level of development of the regions, classified into medium, intermediate and high stage on the basis of their GDP value. Regions in the medium stage are assigned more weight to the basic and efficiency pillars in comparison to the innovation pillars. The level of competitiveness of more developed economies, on the other hand, takes into account to a larger extent their innovation capability as a key driver for their advancement. The weighting scheme of pillar groups has the effect of not penalizing regions on factors where they lay too far behind. The RCI message is then more constructive: the index provides a measure of competitiveness which allows for fair comparison of European regions and highlights realistic areas of improvement.

Composite Indicators and Rankings: Inventory 2011 88 74. Responsible Competitiveness Index

Developer 1 Accountability (MacGillivray, Sabapathy and Zadek) Developer 2 Copenhagen Centre Year launched 2003 Latest Edition 2007 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Policy drivers 2. Business action 3. Social enablers (Weights in Parenthesis) Number of Underlying Indicators 21 Number of units ranked 108 Type of units ranked Countries Link to report http://www.accountability21.net/responsibleCompetitiveness.as px?id=3488 Link to data http://www.accountability21.net/responsibleCompetitiveness.as px?id=2088

The Responsible Competitiveness Index helps responsible businesses to improve their performance and build economic competitiveness, social progress and sustainability. It illuminates which countries have social conditions and are advancing public policies that encourage responsible competitiveness. The product of a yearlong research project, which screened over 600 relevant indicators where 21 indicators met strict justification criteria. It is arranged into a simple model of three reinforcing subthemes: policy drivers, business action and social enablers.

The process involved: Identified the best available data; • Data were rescaled and standardised; • Scores converted into percentages with the maximum (minimum) score being awarded 100% (0%); • Sub-themes were calculated by taking the mean of scores across the 7 indicators .

3 classifications from the World Bank (Atlas method) were used: • low income, $875 or less GNI per capita, (23 economies) • medium income, $876-$10,725 GNI per capita, (56 economies); • high income, $10,726+ GNI per capita, (29 economies);

Sub-theme weighting varies with development.

• Uses a multiple regression:

Composite Indicators and Rankings: Inventory 2011 89 75. Small Business Act for Europe (SBA) Factsheets

Developer 1 European Commission Developer 2 Year launched 2008 Latest Edition 2010 Field Economy Number of Main Dimensions 10 Description of Main Dimensions I Create an environment in which entrepreneurs and family (Weights in Parenthesis) businesses can thrive and entrepreneurship is rewarded II Ensure that honest entrepreneurs who have faced bankruptcy quickly get a second chance III Design rules according to the "Think Small First" principle IV Make public administrations responsive to SMEs' needs V Adapt public policy tools to SME needs: facilitate SMEs' participation in public procurement and better use State Aid possibilities for SMEs VI Facilitate SMEs' access to finance and develop a legal and business environment supportive to timely payments in commercial transactions VII Help SMEs to benefit more from the opportunities offered by the Single Market VIII Promote the upgrading of skills in SMEs and all forms of innovation IX Enable SMEs to turn environmental challenges into opportunities X Encourage and support SMEs to benefit from the growth of markets Number of Underlying Indicators 88 Number of units ranked 27 Type of units ranked EU Link to report http://ec.europa.eu/enterprise/policies/sme/facts-figures- analysis/performance-review/index_en.htm#h2-2 Link to data http://ec.europa.eu/enterprise/policies/sme/facts-figures- analysis/performance- review/pdf/2009_en/spr2009_methodology.pdf

The Small Business Act (SBA) fact sheets are statistical information tools designed as an input for assessing the business and policy environment for SMEs in Member States (hereinafter MS) and Partner Countries. The purpose of the fact sheets is to provide a snapshot of how the SME environment looks like in a given country, as well as how this environment has been changing over the medium term, using the prism of statistical data. This is done by grouping together a total of 88 indicators measuring a wide variety of different SME policy aspects under the ten principles of the SBA. Additionally, basic figures on the size and structure of the SME sector are presented, as well as information on recent developments in the field of SME-policy. Recent information contained in the individual indicators is summed up and visualized in the SBA radar chart, comparing a country’s position against the EU27 average. These charts encapsulate the main results of this statistical exercise in a concise and user-friendly way.

The fact sheets and the SBA radar charts are constructed in several steps:  The policy areas relevant for this exercise have to be identified  Appropriate indicators have to be found  The indicators have to be grouped together under the existing SBA criteria  Sector averages have to be formed on the basis of the individual indicators in this section  Finally, to compare the results of the normalisation, benchmarks have to be defined against which individual countries’ performances can be assessed.

Identification of relevant policy areas: The policy areas are based on the principles cited in the SBA communication of 25 June 2008 by the Commission. The "Small Business Act" for Europe comprising:

Composite Indicators and Rankings: Inventory 2011 90

1. Create an environment in which entrepreneurs and family businesses can thrive and entrepreneurship is rewarded 2. Ensure that honest entrepreneurs who have faced bankruptcy quickly get a second chance 3. Design rules according to the “Think Small First” principle 4. Make public administrations responsive to SMEs’ needs 5. Adapt public policy tools to SME needs: facilitate SMEs’ participation in public procurement and better use State Aid possibilities for SMEs 6. Facilitate SMEs’ access to finance and develop a legal and business environment supportive to timely payments in commercial transactions 7. Help SMEs to benefit more from the opportunities offered by the Single Market 8. Promote the upgrading of skills in SMEs and all forms of innovation 9. Enable SMEs to turn environmental challenges into opportunities 10. Encourage and support SMEs to benefit from the growth of markets

Choice of indicators: The principles behind the selection of the indicators are the following: Indicators should have a direct relevance to the phenomenon they are supposed to describe. Preferably, indicators should be policy indicators, i.e. they should provide a proxy for the degree of policy activity developed in a country in that area. And the indicators should be reliable and adhere to specific quality standards. All indicators used for the fact sheets have been classified in one of the 10 SBA areas.

Normalization: First of all, for each variable the latest available observation was taken. For each area an average2 of all selected normalised indicators pertaining to that area is calculated. These sector averages were plotted on the SBA radar to represent the countries’ performance in this area against the EU average. Indicators have been selected on the following criteria:  data should be available for the six major EU economies (Germany, France, Italy, Poland, Spain and the United Kingdom), and  either data should be available for at least 18 of the EU countries (two thirds of these countries), or the EU countries for which data are available should cover at least 75% of the total number of the EU27 SMEs in the non-financial business economy.

The minimum number of indicators that would qualify for a sector average was set at four. Consequently for a number of areas where only three or less indicators could be identified, no sector average has been calculated. In order to arrive at an average for indicators that come with different units of measurement (Euros against absolute numbers, percentages, etc.) the individual indicators were normalised to ensure comparability. For each indicator the minimum and maximum values across all 37 countries (the lowest and the highest data points, i.e. the two countries for which the value of the indicator was the lowest and the highest) have been identified. Then the score for any particular country was adjusted so that the lowest data point was deducted from the specific data point for the country. The result was then scaled onto the 0 -1 range by the difference between the highest data point and the lowest data point of the series (i.e. the difference between the country with the highest value of all countries and the country with the lowest value of all countries for the given indicator). This approach amounts to benchmarking a specific country’s performance against that of the “best in class” country for that particular indicator. Next, scores per SBA- principle are calculated taking an unweighted average from the normalised individual variables provided at least 4 values are available at the EU27 level, and data for the country are available for the same variables.

It was decided to assess individual country indicators for given SBA-principles against the non-weighted averages for the EU27. In the accompanying text on the individual areas, individual countries’ performances have been typically classified as being “(significantly) higher than EU27”, “(significantly) less than EU27 average” or “on par with EU2 average”. Similarly, changes over time have been qualified as “constant”, “(significantly) increased”, or “(significantly) decreased”. The nature of the qualification depends on the number of standard deviations of the normalised from the benchmark, with 0.5 and 1.5 as switching points. For instance, if a country is less than 0.5 standard deviations (over all EU countries for which data are available) from the EU27 average, it will be classified as “on par with EU-27 average”; or if the change is more than 1,5 times the standard deviation (over all EU countries), it will be labelled “significantly improved”.

Composite Indicators and Rankings: Inventory 2011 91 76. Sovereign Credit Rating (by Capital Intelligence)

Developer 1 Capital Intelligence Developer 2 Year launched 1985 Latest Edition 2010 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 39 Type of units ranked Countries Link to report http://www.bankersalmanac.com/addcon/infobank/credit_rati ngs/capital-intelligence-ratings.aspx Link to data N/A

It is an assessment of a sovereign government's ability and willingness to fulfill its local and foreign currency obligations in a timely manner. Central to this assessment is an analysis of the main determinants of public debt dynamics (e.g. economic growth, fiscal stance), the country's capacity for generating foreign exchange from domestic factors of production, its ability to attract the means for debt servicing from external sources, and the soundness of fiscal, monetary and exchange rate management.

Composite Indicators and Rankings: Inventory 2011 92 77. Sovereign Credit Rating (by FitchIBCA Duff&Phelps)

Developer 1 FitchIBCA Duff&Phelps Developer 2 Year launched 1924 Latest Edition 2011 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 80 Type of units ranked Countries Link to report http://www.fitchratings.com/index_fitchratings.cfm Link to data N/A

(The methodology can be accessed in the US Department of State website or the Fitch website − login required): ratings are based on a series of analysis of data. Questionnaires are sent to relevant officials seeking information about indebtedness and debt servicing capacity. A series of interviews are conducted where policy is assessed together with the tradable sector, the country’s sensitivity to shocks and availability to absorb them, an assessment of political risk as well as a set of orthodox indicators (such as the ratio of debt to exports and the like). Subject areas covered are the following: i. Demographic, educational and structural factors ii Labor market analysis iii Structure of output and trade iv. Dynamism of the private sector v. Balance of supply and demand vi. Balance of payments vii. Analysis of medium-term growth constraints viii. Macroeconomic policy ix. Trade and foreign investment policy x. Banking and finance xi. External assets xii. External liabilities xiii. Politics and the state xiv. International position. Countries are assigned a short term and a medium/long term rating. One key factor in assigning the short term rating is the country’s official foreign reserve holding compared to imports. Other factors are taken into account as well, such as export earnings volatility or high level of overseas short term investments. The ratings assigned to countries are as follows:

Long-Term Credit Ratings Investment Grade AAA Highest credit quality. 'AAA' ratings denote the lowest expectation of credit risk. They are assigned only in case of exceptionally strong capacity for timely payment of financial commitments. This capacity is highly unlikely to be adversely affected by foreseeable events. AA Very high credit quality. 'AA' ratings denote a very low expectation of credit risk. They indicate very strong capacity for timely payment of financial commitments. This capacity is not significantly vulnerable to foreseeable events. A High credit quality. 'A' ratings denote a low expectation of credit risk. The capacity for timely payment of financial commitments is considered strong. This capacity may, nevertheless, be more vulnerable to changes in circumstances or in economic conditions than is the case for higher ratings. BBB Good credit quality. 'BBB' ratings indicate that there is currently a low expectation of credit risk. The capacity for timely payment of financial commitments is considered adequate, but adverse changes in circumstances and in economic conditions are more likely to impair this capacity. This is the lowest investment-grade category.

Speculative Grade BB Speculative. 'BB' ratings indicate that there is a possibility of credit risk developing, particularly as the result of adverse economic change over time; however, business or financial alternatives may be available to allow financial commitments to be met. Securities rated in this category are not investment grade.

Composite Indicators and Rankings: Inventory 2011 93 B Highly Speculative. 'B' ratings indicate that significant credit risk is present, but a limited margin of safety remains. Financial commitments are currently being met; however, capacity for continued payment is contingent upon a sustained, favorable business and economic environment. CCC, CC, C High default risk. Default is a real possibility. Capacity for meeting financial commitments is solely reliant upon sustained, favorable business or economic developments. A 'CC' rating indicates that default of some kind appears probable. 'C' ratings signal imminent default. DDD, DD, and D Default. The ratings of obligations in this category are based on their prospects for achieving partial or full recovery in a reorganization or liquidation of the obligor. While expected recovery values are highly speculative and cannot be estimated with any precisions, the following serve as general guidelines. 'DDD' obligations have the highest potential for recovery, around 90%-100% of outstanding amounts and accrued interest. 'DD' indicates potential recoveries in the range of 50%-90% and 'D' the lowest recovery potential, i.e. below 50%. Short-Term Credit Ratings Fl Highest credit quality. Indicates the strongest capacity for timely payment of financial commitments; may have an added "+" to denote any exceptionally strong credit feature. F2 Good credit quality. A satisfactory capacity for timely payment of financial commitments, but the margin of safety is not as great as in the case of the higher ratings. F3 Fair credit quality. The capacity for timely payment of financial commitments is adequate; however, near-term adverse changes could result in a reduction to non-investment grade. B Speculative. Minimal capacity for timely payment of financial commitments, plus vulnerability to near- term adverse changes in financial and economic conditions. C High default risk. Default is a real possibility. Capacity for meeting financial commitments is solely reliant upon a sustained, favorable business and economic environment. D Default. Denotes actual or imminent payment default.

Composite Indicators and Rankings: Inventory 2011 94 78. Sovereign Credit Rating (by Moody's)

Developer 1 Moody's Developer 2 Year launched 1914 Latest Edition 2011 Field Economy Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 100 Type of units ranked Countries Link to report http://www.moodys.com/ Link to data N/A

Composite Indicators and Rankings: Inventory 2011 95 79. Sovereign Credit Rating (by Standard and Poor's)

Developer 1 Standard and Poor's Developer 2 Year launched 1916 Latest Edition 2011 Field Economy Number of Main Dimensions 10 Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 100 Type of units ranked Countries Link to report http://www.standardandpoors.com/ratings/sovereigns/ratings- list/en/us/?sectorName=Governments&subSectorCode=39&sub SectorName=Sovereigns Link to data N/A

Sovereign credit ratings reflect S&P’s opinions on the ability and willingness of sovereign governments to service their commercial financial obligations in full and on time. A rating is a forward-looking estimate of default probability. Standard & Poor's appraisal is both quantitative and qualitative. Standard & Poor's divides the analytical framework for sovereigns into 10 categories and each sovereign is ranked on a scale of one (the best) to six for each of the 10 analytical categories. There is no exact formula for combining the scores to determine ratings. The analytical variables are interrelated and the weights are not fixed, either across sovereigns or over time. Most categories incorporate both economic and political risk, the key determinants of credit risk. Economic risk addresses the government's ability to repay its obligations on time and is a function of both quantitative and qualitative factors. Political risk addresses the sovereign's willingness to repay debt. The 100 sovereigns Standard & Poor's monitors carry ratings between 'AAA' and 'SD' (Selective Default).

Composite Indicators and Rankings: Inventory 2011 96 80. Tax Misery and Reform Index

Developer 1 Forbes Developer 2 Year launched 2000 Latest Edition 2009 Field Economy Number of Main Dimensions 6 Description of Main Dimensions 1. Corporate income 2. Personal Income 3. Wealth tax 4. (Weights in Parenthesis) Employer Social Security 5. employee social security 6. VAT/Sales (weights unavailable) Number of Underlying Indicators 6 Number of units ranked 65 Type of units ranked Countries and cities Link to report http://www.forbes.com/global/2009/0413/034-tax-misery- reform-index.html Link to data http://www.forbes.com/global/2009/0413/034-tax-misery- reform-index.html

Tax Misery & Reform Index offers a global view of the top marginal rates of taxation--the ones that typically most affect a successful entrepreneur. The Misery scores is a sum of six tax rates: Corporate income, personal income, wealth tax, employer social security, employee social security and VAT/sales.

Composite Indicators and Rankings: Inventory 2011 97 81. Tourism Competitiveness Monitor

Developer 1 World Travel and Tourism Council Developer 2 Year launched 2002 Latest Edition 2004 Field Economy Number of Main Dimensions 8 Description of Main Dimensions 1. Price Competitiveness 2. Human Tourism 3. Infrastructure 4. (Weights in Parenthesis) Environment 5. Technology 6. Human Resources 7. Openness and 8. Social Number of Underlying Indicators 8 Number of units ranked 200 Type of units ranked Countries Link to report http://www.wttc.org/eng/Tourism_News/Press_Releases/Press_R eleases_2004/New_Statistics_launched/ Link to data http://www.wttc.org/eng/Tourism_News/Press_Releases/Press_R eleases_2004/New_Statistics_launched/

The Competitiveness monitor tracks a wide range of information which indicates to what extent a country offers a competitive environment for travel and tourism development. The Competitiveness Monitor is based on a set of social and economic data that are available and comparable across all countries. The data is compiled using a series of indicators, which form eight indices, which are recalibrated to allow across the board comparisons. These are: 1. Price Competitiveness 2. Human Tourism 3. Infrastructure 4. Environment 5. Technology 6. Human Resources 7. Openness and 8. Social. The Monitor uses a 'traffic light' system to indicate the relative positions, rather than the absolute performance of different countries. Green, amber and red lights indicate respectively, above average, average and below average performance.

Composite Indicators and Rankings: Inventory 2011 98 82. Trade and Development Index (TDI)

Developer 1 UNCTAD Developer 2 Year launched 2005 Latest Edition 2007 Field Economy Number of Main Dimensions 11 Description of Main Dimensions A) Input Measure Index and B) Output Measure Index based on 3 (Weights in Parenthesis) dimensions: 1. Structural and institutional (SI): human capital, physical infrastructure, financial environment, institutional quality, economic structure and environmental sustainability; 2. trade policies and processes (TP): Openness to trade, effective access to foreign markets; and 3. level of development (LD): economic, gender and social Number of Underlying Indicators 29 Number of units ranked 110 Type of units ranked Countries Link to report http://www.unctad.org/Templates/webflyer.asp?docid=9201&intIt

emID=3830&lang=1 Link to data Appendix of: http://www.unctad.org/en/docs/ditctab20072part1_en.pdf

The Trade and Development index (TDI) uses indicators to assess the level of trade and development in countries, looking at the interactions among different factors that determine trade and human development outcomes. The constituent elements of TDI are grouped under three broad sets of determinants which will be referred to as dimensions: structural and institutional (SI); trade policies and processes (TP); and level of development (LD). The three broad dimensions of the TDI comprise 11 components, which in turn are composed of 29 indicators. In constructing the TDI, the indicators are aggregated to form the respective components. The weighted sum of the components is the TDI. The TDI is conceptualized as having a positive relationship with trade and development performance. A higher value of the TDI reflects a higher trade and development performance, and vice versa. A companion of TDI value is TDI ranking, which gives an assessment of any country performance relative to the whole country sample. TDI values should then serve as a tool to track the progress of countries in respect of trade and development performance across countries and over time. The TDI is the sum of two indices, which are in turn weighted sums of components, whose respective weights are estimated by the multivariate statistical technique of principal components analysis (PCA).

The TDI is based on two broad sets of measures: InputMI and OutputMI. Two broad sets of determinants are included in InputMI: they are referred to as dimensions and include structural and institutional context, and trade policies and processes. Under the trade and development performance dimension, OutputMI groups a set of performance-related indicators. The relationships among these dimensions, which themselves are composed of a number of components, are complex, mutually interacting and multi- directional, so that each of the components is both a cause of change in others and an outcome of their influences. Each of these components is in turn composed of a set of indicators. The three basic dimensions of the TDI are composed of 13 components, which in turn are composed of 34 indicators. In constructing the TDI, the indicators are aggregated to form the respective components. The methodology used to compute a composite index based on principal component analysis. By using this methodology, the structural and institutional context and trade policies and processes are aggregated by taking the weighted sum of 11 components to form the InputMI that reflects both dimensions. Similarly, the OutputMI is computed by taking the weighted sum of two components under trade and development performance dimension. A composite index based on principal component analysis was elaborated.

Composite Indicators and Rankings: Inventory 2011 99 83. Transnationality Index of Host Economies

Developer 1 UNCTAD Developer 2 Year launched 2003 Latest Edition 2010 Field Economy Number of Main Dimensions 3 Description of Main Dimensions 1. Foreign assets to total assets, 2. Foreign sales to total sales and 3. (Weights in Parenthesis) Foreign employment to total employment. Equal weights Number of Underlying Indicators 3 Number of units ranked 110 Type of units ranked Countries Link to report http://www.unctad.org/en/docs/wir2010_en.pdf Link to data http://www.unctad.org/en/docs/wir2010_en.pdf

The index is calculated for each country as the average of the following four shares: 1. FDI inflows as a share of gross fixed capital formation 2. FDI inward stock as a percentage of GDP 3. Value added of foreign affiliates as a percentage of total national value added and 4. Employment of foreign affiliates as a percentage of total employment. The index is calculated only for those countries which have the available data for each of these 4 components. Countries are ranked from higher transnationality to lower by groups: developed countries, developing countries and CEE.

Composite Indicators and Rankings: Inventory 2011 100 84. UK Competitiveness Index

Developer 1 Centre for International Competitiveness Developer 2 Year launched 2000 Latest Edition 2010 Field Economy Number of Main Dimensions 3 Description of Main Dimensions Measure 1: Inputs; Measure 2: Output; and Measure 3: (Weights in Parenthesis) Outcomes - are given an equal weighting Number of Underlying Indicators 15 Number of units ranked 1 Type of units ranked UK Link to report http://www.cforic.org/pages/ukci2010.php Link to data http://www.cforic.org/downloads.php

The aim of the UK Competitiveness Index is to assess the relative economic competitiveness of regions and localities in the UK by constructing a single index that reflects, as fully as possible, the measurable criteria constituting place competitiveness. Given the methodological parameters, a number of different modes of creating the index, and the variables to be included, have been considered. After testing, the 3-Factor model for measuring competitiveness is adopted. The 3-Factor model consists of a linear framework for analysing competitiveness based on: (1) input; (2) output; and (3) outcome factors. In order to achieve a valid balance between each of the indicators, in terms of their overall significance to the composite index, each of the three measures - Measure 1: Inputs; Measure 2: Output; and Measure 3: Outcomes - are given an equal weighting, since it is hypothesised that each will be interrelated and economically bound by the other. For each measure an index was calculated with a UK average base of 100, and the distribution range for each measure calculated (in the case of unemployment rates these values are inverted). As expected, it is found that some of the ranges have both a skewed and a long distribution range, the result being that these variables have an overly strong influence on the composite index. Therefore, each datum is transformed into its logarithmic form to produce distributions that are closer to the ‘normal’ curve, and that dampen out extreme values so that no single variable distorts the final composite score.

Composite Indicators and Rankings: Inventory 2011 101 85. World Competitiveness Scoreboard

Developer 1 IMD Developer 2 Year launched 1989 Latest Edition 2010 Field Economy Number of Main Dimensions 4 Description of Main Dimensions 1. Economic performance (Domestic economy, international trade, (Weights in Parenthesis) international investment, employment and prices) 2. Government efficiency (public finance, fiscal policy, institutional framework, business legislation and societal framework) 3. Business Efficiency (productivity, labor market, finance, management practices and attitudes and values) 4. Infrastructure (Basic infrastructure, Technological infrastructure, scientific infrastructure, health and environment and education). 2/3 hard statistics, 1/3 opinion polls Number of Underlying Indicators 241 Number of units ranked 58 Type of units ranked Countries Link to report http://www.imd.org/research/publications/wcy/World- Competitiveness-Yearbook-Results/#/ Link to data http://www.imd.org/research/publications/wcy/upload/scoreboard.pdf

The scoreboard assesse the competitiveness of nations, ranking and analyzing how a nation’s environment creates and sustains the competitiveness of enterprises The index is based on 4 main competitiveness factors with 5 sub-factors each: 1) Economic performance (Domestic economy, international trade, international investment, employment and prices) 2) Government efficiency (public finance, fiscal policy, institutional framework, business legislation and societal framework) 3) Business Efficiency (productivity, labor market, finance, management practices and attitudes and values) 4) Infrastructure (Basic infrastructure, Technological infrastructure, scientific infrastructure, health and environment and education). Each of the 5 sub factors are weighted equally at 5%. A set of 323 indicators are gathered: hard data (statistics) represents 2/3 of the total weight and the IMD Executive Opinion Survey represent 1/3 of the total weight in the index. Of the 323 indicators only 241 are used in the overall index – the remaining 82 are used as background information. A standardized value is computed for each of the 241 criteria/indicators, and then a ranking of each of the criteria/indicators is done individually for the 60 countries (from best to worst). Since the indicators are standardized, different indices can be constructed and these are given scores. With these scores, rankings are made for the Overall Scoreboard, the Competitiveness Factors Ranking and the Sub-factors ranking. The Overall Scoreboard aggregates the standardized values for 241 ranked indicators. Countries are ranked from best to worst in terms of competitiveness.

Composite Indicators and Rankings: Inventory 2011 102 86. ZEW Indicator of Economic Sentiment

Developer 1 ZEW Developer 2 Year launched 1999 Latest Edition 2011 Field Economy Number of Main Dimensions 1 Description of Main Dimensions difference between the percentage share of analysts that are (Weights in Parenthesis) optimistic and the share of analysts that are pessimistic for the German economy in six months Number of Underlying Indicators 1 Number of units ranked 1 Type of units ranked Germany Link to report http://www.zew.de/en/publikationen/Konjunkturerwartungen/Konj unkturerwartungen.php3 Link to data http://www.zew.de/en/publikationen/Konjunkturerwartungen/Konj unkturerwartungen.php3

The ZEW Indicator of Economic Sentiment is reflects the difference between the share of analysts that are optimistic and the share of analysts that are pessimistic for the expected economic development in Germany in six months. The survey also asks for the expectations for the Euro-zone, Japan, Great Britain and the U.S.A. The ZEW Indicator of Economic Sentiment is calculated from the results of the ZEW Financial Market Survey. It is constructed as the difference between the percentage share of analysts that are optimistic and the share of analysts that are pessimistic for the German economy in six months. Example: If 30 per cent of participants expect the German economic situation to improve within the next six months, 30 per cent expect no change and 40 per cent expect the economic situation to deteriorate, the ZEW Indicator of Economic Sentiment would take a value of -10. Thus, a positive number means that the share of optimists outweighs the share of pessimists and vice versa.

Composite Indicators and Rankings: Inventory 2011 103 Education

87. Academic Ranking of World Universities (ARWU)

Developer 1 Center of World Class Universities Developer 2 Institute of Higher Education of Shanghai Jiao Tong University, China Year launched 2003 Latest Edition 2010 Field Education Number of Main Dimensions 6 Description of Main Dimensions 1. Quality of Education Alumni of an institution winning Nobel (Weights in Parenthesis) Prizes and Fields Medals Alumni (10%) 2. Quality of Faculty Staff of an institution winning Nobel Prizes and Fields Medals Award (20%) 3. Highly cited researchers in 21 broad subject categories (20%) 4. Research Output Papers published in Nature and Science N&S (20%) 5. Papers indexed in Science Citation Index-expanded and Social Science Citation Index PUB (20%) 6. Per Capita Performance Per capita academic performance of an institution PCP (10%) Number of Underlying Indicators 6 Number of units ranked 1,000 Type of units ranked Institutions: Universities Link to report http://www.arwu.org/ Link to data http://www.arwu.org/ARWU2010.jsp

The Academic Ranking of World Universities (ARWU) uses six objective indicators to rank world universities, including the number of alumni and staff winning Nobel Prizes and Fields Medals, number of highly cited researchers selected by Thomson Scientific, number of articles published in journals of Nature and Science, number of articles indexed in Science Citation Index - Expanded and Social Sciences Citation Index, and per capita performance with respect to the size of an institution. More than 1000 universities are actually ranked by ARWU every year and the best 500 are published on the web. ARWU considers every university that has any Nobel Laureates, Fields Medalists, Highly Cited Researchers, or papers published in Nature or Science. In addition, universities with significant amount of papers indexed by Science Citation Index-Expanded (SCIE) and Social Science Citation Index (SSCI) are also included. In total, more than 1000 universities are actually ranked and the best 500 are published on the web. Universities are ranked by several indicators of academic or research performance, including alumni and staff winning Nobel Prizes and Fields Medals, highly cited researchers, papers published in Nature and Science, papers indexed in major citation indices, and the per capita academic performance of an institution. For each indicator, the highest scoring institution is assigned a score of 100, and other institutions are calculated as a percentage of the top score. The distribution of data for each indicator is examined for any significant distorting effect; standard statistical techniques are used to adjust the indicator if necessary.

Scores for each indicator are weighted to arrive at a final overall score for an institution. The highest scoring institution is assigned a score of 100, and other institutions are calculated as a percentage of the top score. An institution's rank reflects the number of institutions that sit above it. Indicators and Weights for ARWU: 1.Quality of Education Alumni of an institution winning Nobel Prizes and Fields Medals Alumni (10%) 2. Quality of Faculty Staff of an institution winning Nobel Prizes and Fields Medals Award (20%) 3. Highly cited researchers in 21 broad subject categories HiCi (20%) 4. Research Output Papers published in Nature and Science N&S (20%) 5. Papers indexed in Science Citation Index-expanded and Social Science Citation Index PUB (20%) 6. Per Capita Performance Per capita academic performance of an institution PCP (10%)

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88. Composite Learning Index (CLI)

Developer 1 Canadian Council on Learning Developer 2 Year launched 2006 Latest Edition 2010 Field Education Number of Main Dimensions 4 Description of Main Dimensions 1. Learning to Know 2. Learning to Do 3. Learning to Live (Weights in Parenthesis) together 4. Learning to be. Number of Underlying Indicators 17 Number of units ranked 1 Type of units ranked Canada Methodology On a Separate Word Doc Link to report http://www.cli-ica.ca/en.aspx http://publications.jrc.ec.europa.eu/repository/handle/11111111 Link to data 1/13518

The Composite Learning Index (CLI) is Canada’s annual measure of progress in lifelong learning. It is based on a combination of statistical indicators that reflect the many ways Canadians learn, whether in school, in the home, at work or within the community. It is a measurement tool that expresses how learning in all aspects of life is critical to the success of individuals, communities and the country as a whole. On an individual level, Canadians stand to benefit from lifelong learning through higher wages, better job prospects, improved health and more fulfilling lives. The CLI uses a wide range of learning indicators to generate numeric scores for more than 4,500 communities across Canada. A high CLI score means that a particular city, town or rural community possesses the kinds of learning conditions that foster social and economic well-being. A low CLI score means that a community is under- performing in certain aspects that are key to lifelong learning. The CLI is based on four pillars of learning that recognize the broad scope of lifelong learning—at home, in the classroom, at work and in the community. The structural model of the CLI is depicted in Figure 1. The measures on the left- hand side represent the indicators of a particular pillar of learning. Together, the measures are combined to calculate an overall index for each of the four pillars of learning, as well as an overall composite, or CLI, score. The outcomes are combined to produce an overall social and economic index.

Learning outcomes used in the 2010 CLI: Economic outcomes: Income, Unemployment rate. Social outcomes: Adult literacy, Early childhood development, Population health, Environmental responsibility Voter participation.

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The relative importance of each measure of the CLI is determined based on this connection between learning and the social and economic benefits of learning. Using a statistical approach to determine the strength of this correlation for each measure ensures that the CLI has the highest association with the social and economic outcomes it is trying to maximize. This is why a high score on the CLI not only represents the state of learning in that community, but it also means that a particular community has the learning conditions needed to succeed economically and socially.

Data imputation: One of the biggest challenges in producing a composite index that describes conditions for communities is finding data that provide reliable and accurate estimates at the community level. For measures that do not include data at this level, the approach used by CCL is to impute data based on the best estimate possible. Surveys reported by Statistics Canada often reflect the best available sources of data, but often only provide estimates for larger geographic regions, such as metropolitan areas, economic regions and provinces. In order to impute data at the community level for measures, such as the participation in job-related training, data at the lowest level of available of geography (in this case regional data) are used to produce the CLI score. It is likely that the regional results will reflect similar trends for its underlying communities, providing a credible inference for each community.

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89. Education for All Development Index (EDI) and Gender related EFA Index (GEI)

Developer 1 UNESCO Developer 2 Year launched 2002 Latest Edition 2010 Field Education Number of Main Dimensions 4 Description of Main Dimensions 1. Universal primary education (25%) 2. Adult literacy (25%) 3. (Weights in Parenthesis) Quality of Education (25%) and 4. Gender (25%) Number of Underlying Indicators 4 Number of units ranked 128 Type of units ranked Countries http://www.unesco.org/new/en/education/themes/leading-the- Link to report international-agenda/efareport/reports/2010-marginalization/ Link to data

The EDI is a measure of overall progress towards the goal of Education for All (EFA). EFA constitute 6 main education goals (called the “Dakar goals”- adopted in 2000 in The World Education Forum to be achieved by 2015. Two of these six goals also became Millennium Development Goals later in 2000). The EDI captures four goals of the six: 1. Universal primary education 2. Adult literacy 3. Quality of Education and 4. Gender. Progress towards these four goals subcategories is measured using key indicators. In the case of universal primary education the indicator chosen is the Net Enrollment Ratio (NER). In the case of achieving a 50% improvement in adult literacy by 2015 (goal 4) the adult literacy rate is used. For quality of education several indicators are used such as the repletion rate, pupil/teacher ratio, % of trained teachers amongst others.

The gender aspects of education are presented as a separate index – called the Gender-related EFA Index (GEI). The GEI aims to capture the country’s relative achievement in gender parity in participation in primary and secondary education and gender parity in adult literacy. It is calculated as a simple average value of the Gender Parity Index (GPI) in primary education, secondary education and adult literacy. The EDI is a simple average of the values of these four subcomponents. As each of its subcomponents is a percentage, the EDI value can vary from 0 to 100% (or 0 to 1 in ratio form). The closer a country’s EDI value is to the maximum, the nearer the country is to the goal and the greater the extent of its EFA achievement. Countries are ranked in terms of level of EDI from highest to lowest and in turn into 4 categories: “Achieved goals” (EDI value of 0.95-1.00), “Close to the goal” (EDI value of 0.95-0.97), “Intermediate position” (EDI of 0.80-0.84) and “Far from the goal” (EDI less than 0.80).

Composite Indicators and Rankings: Inventory 2011 107 90. E-Readiness Index

Developer 1 Economist Intelligence Unit (EIU) Developer 2 Pyramid Research Year launched 2000 Latest Edition 2009 Field Education Number of Main Dimensions 6 Description of Main Dimensions 1. Connectivity and technology infrastructure 20% ,2. (Weights in Parenthesis) Business environment 15% 3. Social and cultural environment 15%, 4. Legal environment 10%, 5. Government policy and vision 15%, 6. Consumer and business adoption 25% Number of Underlying Indicators 81 Number of units ranked 70 Type of units ranked Countries Link to report http://graphics.eiu.com/pdf/E-readiness%20rankings.pdf Link to data http://graphics.eiu.com/pdf/E-readiness%20rankings.pdf

E-readiness measures the extent to which a country’s business environment is conducive to Internet-based commercial opportunities. It is based on collection of factors that indicate how amenable a market is to Internet-based opportunities. The index uses nearly 100 quantitative and qualitative criteria (data based on EIU and Pyramid Research), grouped into 6 categories: Connectivity and technology infrastructure 20% , Business environment 15% , Social and cultural environment 15%, Legal environment 10%, Government policy and vision 15%, Consumer and business adoption 25%

Changes to our methodology in 2009:

 Three new “usage” indicators have been added to the “consumer and business adoption” category: use of Internet by consumers, use of online public services by citizens and use of online public services by businesses (see box on page 20). Two previously existing indicators assessing the availability of online public services for citizens and businesses have been moved to the “government policy and vision” category.  An “e-participation” indicator has been added to the government policy and vision category, which compares countries on the extent to which citizens are engaged in the political process through digital channels. This is based on the UN e-participation index.  An indicator of international Internet bandwidth per head has been added to the “connectivity and technology infrastructure” category. Elsewhere in this category, erstwhile measures have been eliminated—personal computers, due to doubts about this indicator’s relevance to e-readiness, and WiFi hotspots, due to concerns with data comparability.  The “educational level” indicator in the “social and cultural environment” category has been broadened to incorporate data on gross enrolment in education, in addition to the existing measure of school life expectancy.  The “electronic ID” indicator, previously housed in “connectivity and technology infrastructure”, has been moved to the “legal environment” category. Also in this category, the indicator “laws covering the Internet” has been recalibrated to focus exclusively on cybercrime, data privacy and anti-spam legislation.

To ensure that the new indicators are in proper balance with the others, we have reviewed and in some cases adjusted indicator weights in a few categories. Lastly, we have moved from a 1-5 to a 1- 10 scoring scale for all indicators, in order to allow for a greater level of scoring granularity.

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91. European Human Capital Index

Developer 1 Lisbon Council Developer 2 Year launched 2006 Latest Edition 2010 Field Education Number of Main Dimensions 4 Description of Main Dimensions 1. Human capital stock, 2. Human capital utilization, 3. (Weights in Parenthesis) Human capital productivity and 4. Demographic outlook Number of Underlying Indicators N/A Number of units ranked 12 Type of units ranked EU Link to report http://www.ibm.com/ibm/governmentalprograms/lisbon_cou ncil_european_human_capital_index_cee.pdf Link to data http://www.ibm.com/ibm/governmentalprograms/lisbon_cou ncil_european_human_capital_index_cee.pdf

In 2006, the Lisbon Council set out to define and measure human capital, seeking to quantify numerically the way human capital is developed over the course of a person’s lifetime in different countries. In the end, the European Human Capital Index assigned countries a specific score based on their ability to develop and sustain their human capital, then ranked those countries according to their performance. Specifically, it looked at countries’ ability to develop and nurture their human capital in four separate categories – human capital stock, human capital utilisation, human capital productivity and demographic outlook, assigning a score to each country in each category. Then, it brought those scores together to form a composite ranking, allowing us to compare and contrast human capital development strategies across countries and regions.

We chose these four components for the European Human Capital Index because they each represent one aspect of how human capital contributes to the generation of economic activity. In subsequent pages, each component will be analysed in detail. To compile the ranking, we first scored 10 of the 12 new EU member states plus Croatia and Turkey in each of these four areas. Then, we compiled the four scores into a single composite index giving each country a relative core for its current ability and future outlook in developing and deploying human capital. The result gives a figure which is indicative of these countries long-term economic potential relative to one another.

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92. European Innovation Scoreboard (EIS) and Summary Innovation Index (SII)

Developer 1 European Commission Developer 2 Year launched 2000 Latest Edition 2009 Field Education Number of Main Dimensions 7 1. Human resources, 2. Finance and support, 3. Firm investments, Description of Main Dimensions 4. Linkages and entrepreneurship, 5. Throughputs, 6. Innovators, (Weights in Parenthesis) 7. Economic effects. Number of Underlying Indicators 29 Number of units ranked 27 Type of units ranked EU Countries Link to report http://www.eis.eu/ Link to data http://www.eis.eu/

The European Innovation Scoreboard (EIS) tracks and benchmarks the relative innovation performance of EU27 Member States. The number of dimensions increased to 7 and grouped into 3 main blocks covering enablers, firm activities and outputs. For each of the 7 innovation dimensions average performance will be summarized by calculating a composite innovation index. For each of the 3 blocks of dimensions average performance will be summarized by calculating a weighted composite index using the composite innovation indexes for those dimensions belonging to a specific block. Overall innovation performance will be summarized in the Summary Innovation Index.

Step 1: Transforming data: Most of the EIS indicators are fractional indicators with values between 0% and 100%. Some EIS indicators are unbound indicators, where values are not limited to an upper threshold. These indicators can be highly volatile and have skewed data distributions (where most countries show low performance levels and a few countries show exceptionally high performance levels). For these indicators – Public-private co-publications, EPO patents, Community trademarks and Community designs, all measured per million population – data will be transformed using a square root transformation.

Step 2: Identifying outliers: Positive outliers are identified as those relative scores which are higher than the EU27 mean plus 3 times the standard deviation. Negative outliers are identified as those relative scores which are smaller than the EU27 mean minus 3 times the standard deviation. These outliers are not included in determining the Maximum and Minimum scores in the normalisation process.

Step 3: Setting reference years: For each indicator a reference year is identified based on data availability for all core EIS countries, i.e. those countries for which data availability is at least 75%.

Step 4: Sorting data over time: Reference year data are then used for “2008”, etc. If data for a year-in- between is not available we substitute with the value for the previous year (except for indicators using CIS data where we use the average of 2004 and 2006 to impute for 2005). If data are not available at the beginning of the time series, we replace missing values with the latest available year. If real data become available for the EIS 2009 or EIS 2010 for any of these ‘missing’ data, then the ‘imputed’ values will be replaced by the real data. This might cause some marginal deviations between the composite index scores between the EIS 2008, 2009 and 2010 reports.

Step 5: Extrapolating data; For all indicators and countries we extrapolate data for 2009 and 2010 by assuming the same percentage increase between “2008” and “2007”, where for all fractional indicators extrapolated data can never be above 100. The rationale for this extrapolation is to take account of further increases in indicator values beyond the maximum or below the minimum values found within the observed

Composite Indicators and Rankings: Inventory 2011 110 5 year time period. This way we can fix the Maximum and Minimum scores (cf. Step 6) for the EIS 2009 and EIS 2010 to ensure full comparability of SII scores between the EIS 2008 report and future EIS reports.

Step 6: Determining Maximum and Minimum scores: The Maximum score is the highest relative score found for the whole time period (including the two extrapolated years) within the group of core EIS countries (i.e. those countries for which data availability is at least 75%) excluding positive outliers and ‘small’ countries with populations of 1 million or less (i.e. Cyprus, Iceland, Luxembourg and Malta) as these small countries are 1) responsible for some of the observed outliers (cf. Step 2) and 2) due to their small size cannot be taken as representative for most of the other (larger) countries. Similarly, the Minimum score is the lowest relative score found for the whole time period within the group of core EIS countries excluding negative outliers and ‘small’ countries.

Step 7: Calculating re-scaled scores: Re-scaled scores of the relative scores for all years are calculated by first subtracting the Minimum score and then dividing by the difference between the Maximum and Minimum score. The maximum re-scaled score is thus equal to 1 and the minimum re-scaled score is equal to 0. For positive and negative outliers and small countries where the value of the relative score is above the Maximum score or below the Minimum score, the re-scaled score is thus set equal to 1 respectively 0.

Step 8: Calculating composite innovation indexes: For each year and for each innovation dimension (Human resources, Finance and support, Firm investments, Linkages & entrepreneurship, Throughputs, Innovators, Economic effects) a dimension composite innovation index (DCII) is calculated as the unweighted average of the re-scaled scores for all indicators within the respective dimension.

For each year and for each block of dimensions (Enablers, Firm activities, Outputs) a block composite innovation index (BCII) is calculated as the unweighted average of the re-scaled scores for all indicators within the respective block.

For each year the Summary Innovation Index (SII) is calculated as the unweighted average of the re-scaled scores for all indicators. The SII will only be calculated if data are available for at least 70% of the indicators.

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93. European Lifelong Learning Index (ELLI)

Developer 1 Bertelsmann Foundation Developer 2 Year launched 2010 Latest Edition 2010 Field Education Number of Main Dimensions 4 Description of Main Dimensions 1. Learning to Know 2. Learning to Do 3. Learning to Live (Weights in Parenthesis) together 4. Learning to be Number of Underlying Indicators 36 Number of units ranked 27 Type of units ranked EU

Link to report http://www.elli.org/en/home.html http://www.elli.org/fileadmin/user_upload/About_ELLI/Docu

Link to data ments/ELLI_EU_eng_final.pdf

The European Lifelong Learning Index (ELLI) is an annual measure of Europe’s “state of play” of learning throughout the different stages of life from “cradle to grave” and across the different learning environments of school, community, work and home life. The ELLI Index measures learning in four different domains taken from the UNESCO framework completed by Jaques Delors that include learning to know, learning to do, learning to live together and learning to be. ELLI combines 36 indicators to compile an overall index as well as four subindices. Indicators, taken from various data sources, reflect a wide range of learning activities, such as participation rates in formal education and training, literacy skills, employees participating in vocational training, internet access and usage, civic engagement and cultural activities. The ELLI Index follows the methodological approach and the statistical model of the Composite Learning Index (CLI), developed by the Canadian Council of Learning. The conceptual framework is based on the four UNESCO pillars of learning.

The score for each learning dimension is produced from a twostage process. First, a factor analysis is used to convert the set of measures included in the dimension to a set of factor scores that represent the original variables. The factor scores are mathematically more convenient for the second stage, which uses the scores to predict the outcome factor using multiple linear regression. The weights that are produced as a result of this two-stage procedure are used to combine the measures into the learning dimension. There are several benefits to this technique. First, the composite produced has the strongest relationship to the human capital outcome of all possible linear combinations. Second, the composite has an intuitive interpretation, in that each of the measures can be seen to have a positive contribution to social and economic well-being. A third benefit is that each model also produces a summary of how well the outcome factor is explained by the set of predictors, referred to as the coefficient of determination. Once all the dimension scores have been produced, the final composite ELLI score is computed by combining the four dimension scores. The contribution of the separate scores is determined by how well each model was able to predict the outcome. The purpose of this weighting is to ensure that, just as with the independent dimension scores, the overall ELLI index has the best ability to predict the human contribution to social and economic well-being. Another advantage of this method is the transparency of computing both the separate dimension scores and the overall composite; the relative contribution of a single measure is consistent between the dimension score and the ELLI index score.

Composite Indicators and Rankings: Inventory 2011 112 94. Global Innovation Index (GII)

Developer 1 INSEAD Developer 2 India's Confederation Industry (CII) Year launched 2007 Latest Edition 2010 Field Education Number of Main Dimensions 2 Description of Main Dimensions 1. Innovation input index 2, Innovation Output Index - equal (Weights in Parenthesis) weight (7 pillars: 1. Institutions 2. Human Capacity 3. ICT and Uptake of infrastructure 4. Market Sophistication 5. Business Sophistication 6. Scientific Outputs 7. Creative Outputs and Wellbeing) Number of Underlying Indicators 60 Number of units ranked 132 Type of units ranked Countries Link to report http://www.globalinnovationindex.org/gii/main/home.cfm Link to data http://www.globalinnovationindex.org/gii/main/home.cfm

The Global Innovation Index and Report is an assessment of innovation-this time covering 132 nations. The Global Innovation Index (GII) was conceived at INSEAD as a formal model to capture the response readiness of nations and regions to the challenge and potential of innovation. This is directly linked to a country’s ability to benefit from a variety of macro parameters like sophisticated technologies, enhanced human capacities, organisational and operational developments, and improved policy environment.

The GII model rests relies on seven pillars, which underpin the factors that enhance innovative capacity and demonstrate results from successful innovation. A key objective of the GII is that by looking at the overall index of a country, one can get an idea of how a country compares relative to other countries; specifically, countries facing similar global and innovation challenges. Calculating the GII included selecting qualitatively relevant variables, estimating missing data, and finally, calculating the index by averaging the normalised data. The model uses a combination of objective data drawn from a variety of public and private sources and subjective data drawn from the World Economic Forum’s annual Executive Opinion Survey. The latter helps to capture concepts for which objective (or hard) data are typically unavailable. 60 variables were chosen in the end, based on their qualitative relevance to the GII Framework. These were then divided into seven pillars and under each pillar were sub-divided under the various sub-pillar heads. Data of those countries which had less than 60 per cent of the variables were dropped. In some of the cases we filled in missing data by plugging in values for the previously latest available year. Variable data was normalised in such a way that the range was from 1-7. A variable was either positively normalised or negatively normalised. A variable for which a higher absolute value indicates a good outcome was positively normalized (example: GDP per capita) whereas a variable for which a higher absolute value indicate a worse outcome (Gini coefficient) was negatively normalised. Thus the process of normalisation gave a score of 7 for the best performing country and a score of 1 is for the worst performing country for a particular variable. The formula used for normalization was:

Positive normalization: 6 x (country score – sample minimum)/ (sample maximum – sample minimum) + 1 Negative normalization: – 6 x (country score – sample minimum)/ (sample maximum – sample minimum) + 7

The variables under a sub-pillar were averaged to come to the sub-pillar score. Then all the sub-pillar scores under a certain pillar were averaged to come to the pillar score. Next, the pillar scores for the five enablers were averaged to come to the Innovation Input Index score. Likewise the two performance pillar scores were also averaged to come to the Innovation Output Index score. In the last step the Innovation Input and Innovation Output scores were averaged to come to the GII index score.

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95. ICT Opportunity Index

Developer 1 International Telecommunications Union (ITU) Developer 2 Year launched 2007 Latest Edition 2007 Field Education Number of Main Dimensions 4 Description of Main Dimensions 1- Network index 2. Skills index 3. Uptake index 4. (Weights in Parenthesis) Intensity index Number of Underlying Indicators 10 Number of units ranked 183 Type of units ranked Countries Link to report http://www.itu.int/ITU-D/ict/publications/ict-

oi/2007/index.html Link to data

The ICT Opportunity Index is a tool to track the digital divide by measuring the relative difference in ICT Opportunity levels among economies and over time. It is the result of the merger of the ITU’s Digital Access Index (DAI) and Orbicom’s Monitoring the Digital Divide/Infostate conceptual framework. The index is composed of 4 sub-indices and ten indicators that help measure ICT networks, education and skills, uptake and intensity of the use of ICT. The four sub-indices are composed of the following indicators: 1- Network index: fixed telephone lines per 100 inhabitants, mobile cellular subscribers per 100 inhabitants, and international internet bandwidth (kbps per inhabitant). 2- Skills index: adult literacy rate, and gross school enrolment rates. 3- Uptake index: computers per 100 inhabitants, Internet users per 100 inhabitants and proportion of households with a TV. 4- Intensity index: total broadband internet subscribers per 100 inhabitants, international outgoing telephone traffic (minutes) per capita. For analytical purposes, economies are grouped into four categories, ranging from high to low ICT Opportunities divided into 4 categories: high, upper, medium and low ICT-OI values.

Composite Indicators and Rankings: Inventory 2011 114 96. Index of Knowledge Societies

Developer 1 United Nations (UN) Developer 2 Year launched 2005 Latest Edition 2005 Field Education Number of Main Dimensions 3 Description of Main Dimensions 1. Assets 2. Advancement and 3. Foresightedness (EQUAL weights) (Weights in Parenthesis) Number of Underlying Indicators 14 Number of units ranked 45 Type of units ranked Countries Link to report http://unpan1.un.org/intradoc/groups/public/documents/UN/UNPAN 020643.pdf Link to data http://unpan1.un.org/intradoc/groups/public/documents/UN/UNPAN 020643.pdf

The IKS is a synthetic measure that aims at capturing a Member State’s achievement as far as the conditions fundamental for the development of a Knowledge Society are concerned. Such conditions are grouped into three main dimensions: Assets, Advancement and Foresightedness, each of which is measured by a number of underlying indicators. “Assets” are represented by: a large pool of young and educated people and the development of the means through which information can flow. “Advancement” is the degree to which a Member State nurtures and advances its human and informational resources. “Foresightedness” is the degree to which a Member State grows and develops along its path to a Knowledge Society, while minimizing the impact of negative externalities on people and the natural environment. The underlying indicators are expressed in different units and may have different interpretations (positive/negative impact on a Knowledge Society). Therefore the first step for the calculation of IKS has been to express each underlying indicator in a homogeneous and comparable way. Performance in each indicator is expressed as a value between 0 and 1 by applying the following general formula:

According to this formula, the country with the lower performance will get an Index value of zero; the country with the best performance will be assigned a value of one; while all other countries will have values reflecting their relative distance from the best and worst performer. Some indicators have different interpretations with respect to the IKS. In some cases a high value represents a positive outcome, as for example, expected years of schooling, or research and development expenses, while in other cases a high value is, according to the logic of IKS, detrimental, as emissions of CO2 or military expenditure. In these latter cases we have reversed the Index value to make the interpretation of the value the same as that of all other indicators. The formula used to express these indicators as a value between 0 and 1 is, therefore, the following:

With this approach all indicators bear the same meaning: the higher the value, the better; and the same interpretation is given to IKS: the higher the value achieved by a country the better its performance as a Knowledge Society. Once the single indicators have been standardized according to the formulas described above, we have calculated an Index corresponding to each dimension (Assets Index, Advancement Index and Foresightedness Index) by averaging the values of the underlying indicators. IKS is calculated by averaging the values of all the three dimensions’ indices.

Composite Indicators and Rankings: Inventory 2011 115 97. Innovation and Competitiveness Benchmark

Developer 1 The Information Technology and Innovation Foundation (ITIF) Developer 2 Year launched 2009 Latest Edition 2009 Field Education Number of Main Dimensions 6 Description of Main Dimensions 1. Human capital (10) 2. Innovation capacity (20) 3. (Weights in Parenthesis) Entrepreneurship (12) 4. IT infrastructure (20) 5. Economic policy (13); and 6. Economic performance (25) Number of Underlying Indicators 16 Number of units ranked 40 Type of units ranked Countries Link to report http://archive.itif.org/index.php?id=226 Link to data http://www.itif.org/files/2009-atlantic-century.pdf

The Innovation and Competitiveness Benchmark creates a holistic understanding of how a country is performing in terms of global innovation and competitiveness and whether or not that performance is expected to continue, decline, or increase in the future. The 16 indicators used in this study to assess global competitiveness fall into six broad categories: (1) human capital; (2) innovation capacity; (3) entrepreneurship; (4) IT infrastructure; (5) economic policy; and (6) economic performance. ITIF used the following 16 indicators to evaluate the global competitiveness of the United States and other countries:

1. Human capital: higher education attainment in the population ages 25–34; and the number of science and technology researchers per 1,000 employed. 2. Innovation capacity: corporate investment in research and development (R&D); government investment in R&D; and share of the world’s scientific and technical publications. 3. Entrepreneurship: venture capital investment; and new firms. 4. Information technology (IT) infrastructure: e-government; broadband telecommunications; and corporate investment in IT. 5. Economic policy: effective marginal corporate tax rates; and the ease of doing business. 6. Economic performance: trade balance; foreign direct investment inflows; real GDP per working-age adult; and productivity.

In order to calculate an overall score for each country the report calculated scores for each indicator and each nation on the basis of their standard deviation from the mean for each variable. Each indicator was weighted by importance. Collectively the weights equaled 100. The standard deviation was multiplied by the weight and the adjusted standard deviations were added together for the overall indicator. Each country’s total score was then divided by the best score possible. Thus, each country’s final score is a percentage of the total score a nation would have achieved if it had finished first in every category. To rank change between the base year (the base year is generally 1999 or 2000) and current year (the latest year for which data are available), ITIF calculated both absolute and percentage change for each indicator, added each for all indicators and calculated the mean score of the two numbers and found the corresponding standard deviation.

Composite Indicators and Rankings: Inventory 2011 116 98. Innovation Capacity Index (ICI)

Developer 1 World Economic Forum (WEF) Developer 2 Augusto Lopez Claros and Yasmina Mata - EDF Global Consulting Year launched 2001 Latest Edition 2011 Field Education Number of Main Dimensions 5 Description of Main Dimensions 1. Institutional environment 2. Human capital, training and social (Weights in Parenthesis) inclusion 3. Regulatory and legal framework 4. Research and development 5. Adoption and use of information and communication technologies - different weighting Number of Underlying Indicators 60 Number of units ranked 131 Type of units ranked Countries Link to report http://www.innovationfordevelopmentreport.org/ici.html Link to data http://www.innovationfordevelopmentreport.org/papers/ICIranki ngs2010_11.pdf

Innovation Capacity Index (ICI), a tool for assessing the extent to which nations have succeeded in developing a climate that will nourish the potential for innovation. The Index allows policymakers and entrepreneurs around the world to examine the broad range of country-specific factors which underlie innovation capacity, creating a quantified framework for formulating and implementing better policies for the creation of an environment supportive of innovation. The ICI identifies over 60 factors that are seen to have a bearing on a country’s ability to create an environment that encourages innovation, such as a nation’s institutional environment, human capital endowment, the presence of social inclusion, the regulatory and legal framework, the infrastructure for research and development, and the adoption and use of information and communication technologies, among others. Fully 90 percent of the variables used in the construction of the Index are “hard” and, therefore, not dependent on a survey instrument.

The index is based on five pillars: 1. Institutional environment 2. Human capital, training and social inclusion 3. Regulatory and legal framework 4. Research and development 5. Adoption and use of information and communication technologies. For synthetic purposes only, the variables are grouped into conceptual subsections, which may be thought of as subindexes. The ICI ranks countries according to their overall performance and also provides scores by pillars and subindexes which give a general idea of performance in those areas.

Weights: This was achieved in two stages: first, we obtained a set of raw pillar and index scores without imposing any prior organizational principle on the data with respect to a country’s level of income, its political regime, or its geographical location; second, we used statistical techniques developed by Pavlidis and Noble (2001) to create a template for a correlation analysis with respect to numerical values assigned to each category; that is, income levels were given a number from 1 to 4, from lowest to highest income, and political regimes from 1 to 4, from least democratic to most democratic, and so on, thus generating three category data sets. In this way the raw index and pillar scores were used as templates and compared with the category data, in order to find if there was a correlation between the different categories and scores. Only those correlations with p-values equal to or lower than 0.05 were deemed significant According to these tests, the two main categories with the greatest influence on the index and pillar scores were income levels followed by political regime. In the age of globalization, geographic location appears to play a role of declining importance. This created 16 possible country clusters based on four income categories and four different types of political regime.

Composite Indicators and Rankings: Inventory 2011 117 99. Innovation Index

Developer 1 US Commerce Department - Economic Development Administration Developer 2 Year launched 2009 Latest Edition 2009 Field Education Number of Main Dimensions 4 Description of Main Dimensions 1. Human Capital 2. Economic Dynamics 3. Productivity (Weights in Parenthesis) and employment 4. Economic Wellbeing Number of Underlying Indicators N/A Number of units ranked 1 Type of units ranked US Link to report http://www.statsamerica.org/innovation/ Link to data http://www.statsamerica.org/innovation/

The Innovation Index compares a region or county of your choice to the U.S. for assessing innovation capacity. As a result, this tool allows the exploration of the different dimensions of innovation. In a sense, the index opens the “black box” of innovation so users can look inside.

First, the innovation index comprises two broad categories: inputs to innovation, which measure innovation capacity, and outputs of innovation, which measure the results. Within each large class, the index provides additional detail and individual measures that collectively compose the broad categories. So, for example, economic dynamics play an important “input” role in innovation. The term “economic dynamics” captures a variety of indicators: venture capital, broadband penetration, investments in R&D, and business formation. The index enables one to explore each of these variables in depth and download detailed data by simply clicking the drill-down feature. Human capital is also a vital input to innovation. Therefore, the index provides different perspectives to evaluate a region’s human capital.

In addition, this tool includes state-level indicators—total R&D spending and science and technology graduates—that can help evaluate the strength of a state’s investments to support innovation. Innovation is not only about inputs, however. A region’s economy must translate these inputs into productive outcomes: employment in high-technology firms, greater output per worker, the creation of patents, to name a few. By examining the output indicators, one can explore how well your economy converts innovation inputs into performance.

Because the index is not dealing with simple linear relationships, there is no direct cause-and-effect connection between inputs and outputs. The innovation index is designed to show the innovation process more clearly. The tool, in general, lets the practitioner explore innovation within your region by guiding questions and conversations about the region’s performance. Generally, the tool provides information on how users can improve their region’s innovation capacity by aligning, linking, and focusing relevant energy and investments.

Composite Indicators and Rankings: Inventory 2011 118 100. Innovation Union Scoreboard (IUS)

Developer 1 European Commission Developer 2 Year launched 2006 Latest Edition 2010 Field Education Number of Main Dimensions 3 Description of Main Dimensions 1. Enablers 2. Firm activities and 3. Outputs (equal weights) (Weights in Parenthesis) Number of Underlying Indicators 25 Number of units ranked 33 Type of units ranked EU Link to report http://ec.europa.eu/enterprise/policies/innovation/facts-figures- analysis/innovation-scoreboard/index_en.htm Link to data http://ec.europa.eu/enterprise/policies/innovation/facts-figures- analysis/innovation-scoreboard/index_en.htm

The Scoreboard draws on 25 research and innovation-related indicators grouped into three main categories:  "Enablers", i.e. the basic building blocks which allow innovation to take place (human resources, finance and support, open, excellent and attractive research systems)  "Firm activities" which show how innovative Europe's firms are (firm investments, linkages & entrepreneurship, intellectual assets); and  "Outputs" which show how this translates into benefits for the economy as a whole (innovators, economic effects).

The Enablers capture the main drivers of innovation performance external to the firm and it differentiates between 3 innovation dimensions. The Human resources dimension includes measures the availability of a high-skilled and educated workforce. The new Open, excellent and attractive research systems dimension includes measures the international competitiveness of the science base. The Finance and support dimension and measures the availability of finance for innovation projects and the support of governments for research and innovation activities. Firm activities capture the innovation efforts at the level of the firm and it differentiates between 3 innovation dimensions. The Firm investments dimension R&D and non- R&D investments that firms make in order to generate innovations. The Linkages & entrepreneurship dimension measures entrepreneurial efforts and collaboration efforts among innovating firms and also with the public sector. The Intellectual assets dimension captures different forms of Intellectual Property Rights (IPR) generated as a throughput in the innovation process. Outputs capture the effects of firms’ innovation activities and it differentiates between 2 innovation dimensions. The Innovators dimension measures the number of firms that have introduced innovations onto the 2 market or within their organisations, covering both technological and nontechnological innovations and the presence of high-growth firms. The indicator on innovative high-growth firms corresponds to the new EU2020 headline indicator, which will be completed within the next two years. The Economic effects dimension captures the economic success of innovation in employment, exports and sales due to innovation activities. The overall innovation performance of each country has been summarized in a composite indicator: the Summary Innovation Index (SII).

Step 1: Data availability: The Innovation Union Scoreboard uses the most recent statistics from Eurostat and other internationally recognised sources as available at the time of analysis.

Step 2: Identifying extreme values: Positive outliers are identified as those scores which are higher than the mean plus 2 times the standard deviation. Negative outliers are identified as those scores which are smaller than the mean minus 2 times the standard deviation.

Composite Indicators and Rankings: Inventory 2011 119 Step 3: Transforming data that have highly skewed distributions across Countries: Most of the indicators are fractional indicators with values between 0% and 100%. Some indicators are unbound indicators, where values are not limited to an upper threshold. These indicators may have skewed (non-symmetric) distributions where most countries show low performance levels and a few countries show exceptionally high performance levels (skewness above zero). Values of skewness above 1 were found for 8 indicators out of 24 due to few countries performing extremely well in those indicators. These indicators could be transformed, at all time points, using a Box-Cox transformation with 0.6.

Step 4: Imputation of missing values: If data for the latest year are missing, they are imputed with the data of the latest available year. If data for a year-in-between are missing, they are imputed with the value of the previous year. If data are not available at the beginning of the time series, they are imputed with the oldest available year. In case the data for an indicator are not available for a given country at any time point, the composite score is evaluated without that indicator by re-calculating the weights for the other indicators such that their sum is one. This is equivalent to replacing the missing indicator with the weighted average calculated across all the others.

Step 5: Determining Maximum and Minimum scores: The Maximum score is the highest score for each indicator found for the whole time period within all countries. Similarly, the Minimum score is the lowest score for each indicator found for the whole time period within all countries.

Step 6: Normalising scores: After determining minimum and maximum scores across countries for each indicator, the normalized scores for all years are calculated by using the min-max normalization approach. The minimum score is subtracted from each indicator, and the result is divided by the difference between the Maximum and Minimum score. The maximum normalised score is thus equal to 1 and the minimum normalised score is equal to 0.

Step 7: Calculating composite scores at pillar level: The indicators within each pillar are aggregated linearly with equal weights.

Step 8: Calculating composite innovation scores: For each year a composite innovation score is calculated following two alternative and equally plausible strategies: - Strategy 1: the SII is calculated as linear aggregation with equal weights of the scores for the three pillars. The European Countries fall into four performance groups: Innovation leaders (with score at least 20% above that of EU27), Innovation followers (with score between 90% and 120% of that of EU27), Moderate innovators (with score between 50% and 90% of that of EU27) and Modest innovators (with score below 50% of that of EU27). - Strategy 2: as a geometric aggregation across the pillars (enablers, firm activities and outputs). This methodology combines a full compensability within each dimension with partial compensability across the three dimensions. Indeed the geometric aggregation penalises a country with a low performance in at least one dimension. This type of aggregation is adopted as every dimension is crucial for innovation, i.e. the three different dimensions of innovation are equally legitimate.

Step 9: Robustness analysis of composite innovation scores: Besides the two scenarios analyzed above, composite scores have also been evaluated considering weights varying over a predefined range. The three pillars are further combined using geometric aggregation and weights varying in the range (0.25 – 0.40), to simulate the presence of uncertainty in their set up. Instead of one single set of weights of value 1/3 each, weights are randomly sampled from the range above and used in the evaluation of the composite scores. This exercise has the objective to examine the extent to which country rankings depend on alternative choices for the weights of the pillars.

The Scoreboard places Member States into the following four country groups:  Innovation leaders- performance well above that of the EU27 average.  Innovation followers - performance close to that of the EU27 average.  Moderate innovators - performance below that of the EU27 average.  Modest innovators - performance well below that of the EU27 average.

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101. International Civic and Citizenship Education Study (ICCS)

Developer 1 International Association for the Evaluation of Educational Achievement (IEA) Developer 2 Year launched 1999 Latest Edition 2009 Field Education Number of Main Dimensions N/A Description of Main Dimensions Civic and citizenship education (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 39 Type of units ranked Countries Link to report http://www.iea.nl/icces.html Link to data http://iccs.acer.edu.au/uploads/File/Reports/ICCS_10_Initial _Findings.pdf

The purpose of the International Civic and Citizenship Education Study (ICCS) is to investigate the ways in which young people are prepared to undertake their roles as citizens in a range of countries. The study builds on the previous IEA study of civic education (CIVED) undertaken in 1999. It will report on student achievement on a test of conceptual understandings and competencies in civic and citizenship education. It will also collect and analyze data about student dispositions and attitudes relating to civic and citizenship education

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102. International Computer and Information Literacy Study (ICILS)

Developer 1 International Association for the Evaluation of Educational Achievement (IEA) Developer 2 Year launched 2013 Latest Edition 2013 Field Education Number of Main Dimensions N/A Description of Main Dimensions Computer literacy (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 19 Type of units ranked Countries Link to report http://www.iea.nl/icils.html Link to data Not released yet

ICILS will examine the outcomes of student computer and information literacy (CIL) education across countries. Computer and information literacy refers to an individual’s ability to use computers to investigate, create, and communicate in order to participate effectively at home, at school, in the workplace, and in the community.

Composite Indicators and Rankings: Inventory 2011 122 103. Investment and Performance in the Knowledge Based Economy

Developer 1 European Commission Developer 2 Year launched 2002 Latest Edition 2007 Field Education Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked EU-27 + US and Japan Type of units ranked Countries Link to report http://ec.europa.eu/invest-in- research/monitoring/statistical02_en.htm Link to data ftp://ftp.cordis.europa.eu/pub/era/docs/keyfigures_2007.pdf

The two composite indicators refer to the overall investment and performance in the transition to the knowledge-based economy. They focus on the ‘knowledge dimension’ of that transition and, therefore, do not take into account the other dimensions (e.g. employment, sustainable development, etc.) of the Lisbon Agenda.

The composite indicator of investment in the knowledge-based economy addresses the two crucial dimensions of investment: creation and dissemination of new knowledge. It includes key indicators relating to R&D effort, investment in highly-skilled human capital (researchers and PhDs), the capacity and quality of education systems (education spending and life-long learning), purchase of new capital equipment that may contain new technology, and the modernisation of public services (e-government). The second composite indicator regroups the four most important elements of the performance in the transition to the knowledge-based economy: productivity, scientific and technological performance, usage of the information infrastructure and effectiveness of the education system. The aggregation method is the weighted average of sub-indicators, based on a conceptual grouping of the indicators. These conceptual groups may contain one indicator or several. The different conceptual groups are given equal weightings, while within each group the components indicators are also accorded an equal weight.

Composite Indicators and Rankings: Inventory 2011 123 104. ITU Digital Access Index (DAI)

Developer 1 International Telecommunications Union (ITU) Developer 2 Year launched 2003 Latest Edition 2003 Field Education Number of Main Dimensions 5 Description of Main Dimensions 1. Infrastructure 2. Affordability 3. Knowledge 4. Quality 5. (Weights in Parenthesis) Usage - Equal weights Number of Underlying Indicators 8 Number of units ranked 181 Type of units ranked Countries Link to report http://www.itu.int/ITU- D/ict/publications/wtdr_03/material/DAI.pdf Link to data http://www.itu.int/ITU-D/ict/dai/

Digital Access Index (DAI), measures the overall ability of individuals in a country to access and use new ICTs. The DAI is built around four fundamental vectors that impact a country's ability to access ICTs: infrastructure, affordability, knowledge and quality and actual usage of ICTs. The DAI has been calculated for 181 economies where European countries were among the highest ranked. The DAI allows countries to see how they compare to peers and their relative strengths and weaknesses. The DAI also provides a transparent and globally measurable way of tracking progress towards improving access to ICTs.

Eight indicators are used to represent the five factors. Each indicator is divided by a “goalpost” the maximum value established for that indicator. Each indicator is then summed to obtain an overall index score. The DAI has been calculated for 181 economies and are classified according to high, upper, medium and low ICT access. The DAI allows countries to see how they compare to peers and their relative strengths and weaknesses. It also provides a transparent and globally measurable way of tracking progress towards improving access to ICTs.

Composite Indicators and Rankings: Inventory 2011 124 105. Knowledge Economy Index (KEI)

Developer 1 World Bank Developer 2 Year launched 2008 Latest Edition 2009 Field Education Number of Main Dimensions 4 Description of Main Dimensions 1. Economic incentive and institutional regime, 2. (Weights in Parenthesis) Education and human resources, 3. Innovation system and 4. ICT (equal weights) Number of Underlying Indicators 12 Number of units ranked 145 Type of units ranked Countries Link to report http://siteresources.worldbank.org/INTUNIKAM/Resources /KAMbooklet.pdf Link to data http://info.worldbank.org/etools/kam2/KAM_page5.asp

106. Knowledge Index (KI)

Developer 1 World Bank Developer 2 Year launched 2008 Latest Edition 2009 Field Education Number of Main Dimensions 3 Description of Main Dimensions (Weights 1. education and human resources, 2. the innovation system in Parenthesis) and 3. ICT (equal weights) Number of Underlying Indicators 9 Number of units ranked 145 Type of units ranked Countries Link to report http://siteresources.worldbank.org/INTUNIKAM/Resources /KAMbooklet.pdf Link to data http://info.worldbank.org/etools/kam2/KAM_page5.asp

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The KAM Knowledge Index (KI) measures a country's ability to generate, adopt and diffuse knowledge. This is an indication of overall potential of knowledge development in a given country. Methodologically, the KI is the simple average of the normalized performance scores of a country or region on the key variables in three Knowledge Economy pillars – education and human resources, the innovation system and information and communication technology (ICT).

The Knowledge Economy Index (KEI) takes into account whether the environment is conducive for knowledge to be used effectively for economic development. It is an aggregate index that represents the overall level of development of a country or region towards the Knowledge Economy. The KEI is calculated based on the average of the normalized performance scores of a country or region on all 4 pillars related to the knowledge economy - economic incentive and institutional regime, education and human resources, the innovation system and ICT.

For the purposes of calculating KI and KEI, each pillar is represented by three key variables:

The Economic Incentive and Institutional Regime: Tariff & Nontariff Barriers / Regulatory Quality / Rule of Law Education and Human Resources: Adult Literacy Rate / Secondary Enrollment / Tertiary Enrollment The Innovation System: Royalty and License Fees Payments and Receipts / Patent Applications Granted by the US Patent and Trademark Office / Scientific and Technical Journal Articles

These three variables are available in 2 forms: scaled by population and in absolute values. Thus, both KE and KIE are also available in "weighted" and "unweighted” forms. In innovation, absolute size of resources matters, as there are strong economies of scale in the production of knowledge and because knowledge is not consumed in its use.

Information and Communication Technology (ICT): Telephones per 1,000 people / Computers per 1,000 people Internet Users per 10,000 people

The most commonly cited of the KAM’s several indexes is the Knowledge Economy Index (KEI)—a broad measure of the overall level of preparedness of a country or region for the knowledge economy. The KEI summarizes each country’s performance on 12 variables corresponding to the four knowledge economy pillars. The KEI is constructed as the simple average of the normalized values of those indicators, from 0 to 10. A KEI score that is close to 10 implies relatively good development of the four knowledge economy pillars as compared to other countries, while a score close to 0 indicates relatively poor development.

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107. Knowledge-based Economy Index

Developer 1 Milken Institute Developer 2 Year launched 2000 Latest Edition 2001 Field Education Number of Main Dimensions 12 Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators 12 Number of units ranked 50 Type of units ranked US states Link to report http://www.milkeninstitute.org/publications/publications.taf?fun ction=indexes Link to data

The Knowledge-based Economy Index (formerly New Economy Index) measures which states are in the best position to take advantage of the opportunities for growth in the information age. The Index measures 12 criteria considered crucial to successful economies, from research and development dollars to venture capital investment and measures of globalization. The data is then merged to determine each state’s place on the Index.

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108. Programme for International Student Assessment (PISA)

Developer 1 OECD Developer 2 Year launched 2000 Latest Edition 2009 Field Education Number of Main Dimensions 4 Description of Main Dimensions 1. Science 2. Math 3. Reading 4. Problem solving (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 75 Type of units ranked Countries Link to report www.oecd.org/edu/pisa/2009 Link to data www.oecd.org/edu/pisa/2009

PISA is an internationally standardized assessment that was jointly developed by participating countries and administered to 15-year-olds in schools. Tests are typically administered to between 4,500 and 10,000 students in each country. PISA assesses how far students near the end of compulsory education have acquired some of the knowledge and skills that are essential for full participation in society. In all cycles, the domains of reading, mathematical and scientific literacy are covered not merely in terms of mastery of the school curriculum, but in terms of important knowledge and skills needed in adult life. In the PISA 2003 cycle, an additional domain of problem solving was introduced to continue the examination of cross- curriculum competencies. Countries are ranked in terms of scores in Mathematical Literacy, Problem Solving, Reading Literacy and Scientific Literacy.

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109. Progress in International Reading Literacy Study (PIRLS)

Developer 1 International Association for the Evaluation of Educational Achievement (IEA) Developer 2 Year launched 2001 Latest Edition 2011 Field Education Number of Main Dimensions 1 Description of Main Dimensions 4th graders reading achievement (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 53 Type of units ranked Countries Link to report http://www.iea.nl/pirls2011.html Link to data http://www.iea.nl/pirls2011.html

An assessment that measures trends in children’s reading literacy achievement and policy and practices related to literacy. PIRLS measure trends in fourth-graders’ reading achievement every four years. PIRLS assessed a range of reading comprehension strategies for two major reading purposes – literary and informational. More than half of the questions were in the constructed-response format, requiring students to generate and write their answer.

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110. QS World University Rankings

Developer 1 QS Developer 2 Year launched 2004 Latest Edition 2010 Field Education Number of Main Dimensions 5 Description of Main Dimensions Academic Peer Review 40%, Employer/Recruiter Review 10%, (Weights in Parenthesis) Student Faculty Ratio 20%, Citations per Faculty 20% and International Factors (faculty and students) 5% each. Number of Underlying Indicators N/A Number of units ranked 2500 Type of units ranked Institutions: Universities Link to report http://www.topuniversities.com/university-rankings/world- university-rankings Link to data http://www.topuniversities.com/university-rankings/world- university-rankings

QS rankings provide information on the top universities in the world, the best universities by subject rank and the universities voted by employers. Beginning with the world's top 500 universities based on citations per paper, the list has evolved since 2004. In 2010, the surveys featured over 2,500 institutions, with 660 being evaluated at either an indicator or overall level. There are certain kinds of institution that may appear in other evaluations but are included either entirely or partly from our study. These are: RESEARCH INSTITUTES, SINGLE FACULTY INSTITUTIONS, SINGLE LEVEL INSTITUTIONS.

International Faculty (Index): International reputation is an undeniable component of today's world class universities. Representing 5% each in this evaluation, the international students score and international faculty score are calculated based on those proportions. In the first year of the QS World University Rankings, an independent study was done of the results, which concluded that the "International Students" indicator was the only one negatively correlated with the overall performance of an institution and recommended its withdrawal. It, and the "International Faculty" indicator are included largely because this is a WORLD university ranking and set forth to track performance of institutions worldwide against indicators that are, like it or not, prerequisite to being heralded as a world class university. There is no longer a negative correlation between either of these indicators and the overall performance. The international migration of students and faculty is a major trend in higher education and is inevitably driven both by the march of globalisation and the pursuit of alternative higher education revenue streams by universities and governments. It cannot be ignored or denied.

Academic Reputation Index: The Academic Reputation Index is the centrepiece of the QS World University Rankings carrying a weighting of 40%. It is an approach to international university evaluation that QS pioneered in 2004 and is the component that attracts the greatest interest and scrutiny. In concert with the Employer Reputation index it is the aspect which sets this ranking most clearly apart from any other.

Employer Reputation Index: The majority of undergraduate students leave university in search of employment after their first degree, making the reputation of their university amongst employers a crucial consideration. A common approach to the evaluation of employability in domestic rankings is graduate employment rate, there are two reasons why this indicator does not work at an international level - the first is that this evaluation looks at the top universities in the world - all of whom have very high employment rates - so it doesn't provide very much discernment. The second is that, since we are looking at different countries, the results would react to local economic conditions and not necessarily just the quality of the institution. So, instead, we survey employers to ask their opinion on the quality of graduates.

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Standardization, Weightings and Aggregation:

The current weightings - assigned by indicator - have been derived on the basis of on-going dialogue with some of our trusted advisors: Academic Peer Review 40%, Employer/Recruiter Review 10%, Student Faculty Ratio 20%, Citations per Faculty 20% and International Factors 5% each. The appropriate allocation of weightings has to take into account a little more than simply the importance of the criterion being measured, it also has to consider the appropriateness of the indicators to evaluate that criterion. Once the data is collected and the weightings are decided upon, the next thing to do is to calculate standard scores for each column of data so that they are compatible with each other and allow us to combine the data reliably and apply the weightings fairly in the calculation of the overall score. From 2007, a more complicated, but widely used standardization or normalization method has been adopted involving z-scores. In order to calculate z-scores the mean and the standard deviation of the sample are required. These are as follows:

Standard Deviations and Means for Individual Indicators in 2010 Indicator Mean Standard Deviation Academic Peer Review 74.72 61.25 Employer Review 5.90 8.79 Student Faculty 0.09 0.05 Citations per Faculty 30.39 32.40 International Faculty 0.14 0.14 International Students 0.11 0.10

Once the scores are calculated, their position on the normal curve is plotted resulting in their score for each indicator. The resulting scores are finally scaled between 1 and 100 for each indicator to result in a set of results compatible with those for the other indicators

COMPILING THE FINAL SCORE: We simply multiply each indicator score by its weighting factor, sum the size resulting figures together, round to one decimal place and then scale to the top performing institution, resulting in a final score out of 100.

Based very loosely on the Carnegie Classification of Institutions of Higher Education in the US, but operated on a much simpler basis, these classifications take into account three key aspects of each university to assign their label.  Size – based on the (full time equivalent) size of the degree-seeking student body. Where an FTE number is not provided or available, one will be estimated based on common characteristics of other institutions in the country or region in question  Subject Range – four categories based on the institution’s provision of programs in the five broad faculty areas used in the university rankings. Due to radically different publication habits and patterns in medicine, an additional category is added based on whether the subject institution has a medical school  Research Intensity – four levels of research activity evaluated based on the number of documents retrievable from Scopus in the five year period preceding the application of the classification. The thresholds required to reach the different levels are different dependent on the institutions pre- classification on aspects 1 and 2.

Composite Indicators and Rankings: Inventory 2011 131 111. Ranking Web of World Universities

Developer 1 Cybermetrics Lab Developer 2 Consejo Superior de Investigaciones Científicas (CSIC) - Spain Year launched 2004 Latest Edition 2011 Field Education Number of Main Dimensions 4 Description of Main Dimensions 1. Visibility (50%) 2. Size (20%) 3. Rich files (15%) and (Weights in Parenthesis) Scholar (15%) Number of Underlying Indicators 4 Number of units ranked 12,000 Type of units ranked Institutions: Universities Link to report http://www.webometrics.info/ Link to data http://www.webometrics.info/top12000.asp

The Ranking Web covers more than 20,000 Higher Education Institutions worldwide. We intend to motivate both institutions and scholars to have a web presence that reflect accurately their activities. If the web performance of an institution is below the expected position according to their academic excellence, university authorities should reconsider their web policy, promoting substantial increases of the volume and quality of their electronic publications. The Webometrics ranking has a larger coverage than other similar rankings. The ranking is not only focused on research results but also in other indicators which may reflect better the global quality of the scholar and research institutions worldwide.

The unit for analysis is the institutional domain, so only universities and research centres with an independent web domain are considered. If an institution has more than one main domain, two or more entries are used with the different addresses. The first Web indicator, Web Impact Factor (WIF), was based on link analysis that combines the number of external inlinks and the number of pages of the website, a ratio of 1:1 between visibility and size. This ratio is used for the ranking, adding two new indicators to the size component: Number of documents, measured from the number of rich files in a web domain, and number of publications being collected by Google Scholar database.

Four indicators were obtained from the quantitative results provided by the main search engines as follows:

 Size (S). Number of pages recovered from four engines: Google, Yahoo, Live Search and Exalead.  Visibility (V). The total number of unique external links received (inlinks) by a site can be only confidently obtained from Yahoo Search.  Rich Files (R). After evaluation of their relevance to academic and publication activities and considering the volume of the different file formats, the following were selected: Adobe Acrobat (.pdf), Adobe PostScript (.ps), Microsoft Word (.doc) and Microsoft Powerpoint (.ppt). These data were extracted using Google, Yahoo Search, Live Search and Exalead.  Scholar (Sc). Google Scholar provides the number of papers and citations for each academic domain. These results from the Scholar database represent papers, reports and other academic items.

The four ranks were combined according to a formula where each one has a different weight but maintaining the ratio 1:1

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The inclusion of the total number of pages is based on the recognition of a new global market for academic information, so the web is the adequate platform for the internationalization of the institutions. A strong and detailed web presence providing exact descriptions of the structure and activities of the university can attract new students and scholars worldwide.

The number of external inlinks received by a domain is a measure that represents visibility and impact of the published material, and although there is a great diversity of motivations for linking, a significant fraction works in a similar way as bibliographic citation.

The success of self-archiving and other repositories related initiatives can be roughly represented from rich file and Scholar data. The huge numbers involved with the pdf and doc formats means that not only administrative reports and bureaucratic forms are involved. PostScript and Powerpoint files are clearly related to academic activities.

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112. State Technology and Science Index

Developer 1 Milken Institute Developer 2 Year launched 2002 Latest Edition 2008 Field Education Number of Main Dimensions 5 Description of Main Dimensions 1. Research and development inputs 2. Risk capital and (Weights in Parenthesis) entrepreneurial infrastructure 3. Human capital investment 4. Technology and science workforce 5. Technology concentration and dynamism Number of Underlying Indicators 77 Number of units ranked 50 Type of units ranked US states Link to report http://www.milkeninstitute.org/publications/publications.taf?functi on=indexes Link to data http://www.milkeninstitute.org/publications/publications.taf?functi on=indexes

The State Technology and Science Index looks at the ecosystem of economic development and sustainability, such as a State’s research and development capabilities, entrepreneurial capacity and risk capital infrastructure, human capital, and the intensity of its technology and science workforce, and gauges the technology and science assets that can be leveraged to promote economic development. The five pillars are: 1. Research and development inputs 2. Risk capital and entrepreneurial infrastructure 3. Human capital investment 4. Technology and science workforce 5. Technology concentration and dynamism.

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113. Technological Achievement Index (TAI)

Developer 1 UNDP Developer 2 Year launched 2001 Latest Edition 2001 Field Education Number of Main Dimensions 4 Description of Main Dimensions 1. Creation of technology 2. Diffusion of recent innovations 3. (Weights in Parenthesis) Diffusion of old innovations and 4. Human skills (Equal weights) Number of Underlying Indicators 8 Number of units ranked 72 Type of units ranked Countries Link to report http://hdr.undp.org/en/media/completenew1.pdf Link to data Annex 2.1 of http://hdr.undp.org/en/media/completenew1.pdf

The TAI was introduced in the 2001 Human Development Report and aims to capture how well a country is in creating and diffusing technology and building a human skill base—reflecting capacity to participate in the technological innovations of the network age. The TAI focuses on 4 dimensions of technology that are equally weighted in the index: 1) Creation of technology (Patents granted per capita and Receipts of royalty and license fees from abroad per capita) 2) Diffusion of recent innovations (Internet hosts per capita and High- and medium-technology exports as a share of all exports) 3) Diffusion of old innovations (Logarithm of telephones per capita - mainline and cellular combined - and Logarithm of electricity consumption per capita) and 4) Human skills (Mean years of schooling and Gross enrolment ratio at tertiary level in science, mathematics and engineering). The information used to construct the index was based on international data series and rankings were made for 72 countries − for which data was available. In turn, these countries are classified into Leaders (TAI > than 0.50), Potential Leaders (TAI 0.35-0.49); Dynamic Adopters (TAI 0.20-0.34) and marginalized (TAI < 0.20).

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114. Technological Standing (TS)

Developer 1 Technology Policy and Assessment Center - Georgia Institute of Technology Developer 2 Year launched 1987 Latest Edition 2007 Field Education Number of Main Dimensions 3 Description of Main Dimensions 1. High tech exports (1/3) 2. Survey question on (Weights in Parenthesis) technological standing (1/3) 3. electronic exports (1/3) Number of Underlying Indicators N/A Number of units ranked 33 Type of units ranked Countries Link to report http://www.au.af.mil/au/awc/awcgate/nsf/nsf_hi_tech_indicat ors_33_nations.pdf Link to data http://www.au.af.mil/au/awc/awcgate/nsf/nsf_hi_tech_indicat ors_33_nations.pdf

High Tech Indicators compares the technological competitiveness of 33 nations, including a large number of industrializing economies. Each indicator is comprised of both statistical data (‘S”) and data from a survey of experts (“E”).

Raw data are transformed to “S-scores.” Each indicator component is scaled from 0 to 100 and then averaged to generate comparable indicators with a 0 to 100 range. For survey items, 100 represents the highest response category for a question; for statistical data, 100 typically represents the value attained by the country with the largest value among the 33-country set. “0” reflects the lowest possible value – the minimum value for survey items. In the event a country has a negative statistical value (e.g., Foreign Direct Investment), values are adjusted upward to have the lowest negative value set as an S-score of 0. Thus, this is a relative scaling so that a country’s apparent "decline" over time or low score is only relative to the other countries in the set of 33. [In 2007, we have also provided data to the NSF that are rescaled to locate the USA at 100.] Questions used and statistical data sources, and variable definitions are detailed in the HTI Appendix: Indicator Formulations and Data Sources (included herein). The questions are also available, as posed, in the HTI 2007 Survey at //tpac.gatech.edu.1

One Output indicator – Technological Standing – and four Input indicators – National Orientation, Socioeconomic Infrastructure, Technological Infrastructure, and Productive Capacity are presented.

Technological Standing (TS): An indicator of a country's recent overall success in exporting high technology products. S: value of high tech exports; value of electronics exports E: question addressing current high technology production capability.

The emphasis on electronics reflects our assumption that this has been a vital contributor to much high technology development in recent years.

Traditional Indicator formulation: TS = (X)/3 + (A2)/3 + (Q14a)/3

National Orientation (NO): Evidence that a nation is undertaking directed action to achieve technological competitiveness. Such action can be manifested at the business, government, or cultural levels, or any combination of the three. S: investment risk index (constructed from the Political Risk Services data series)

Composite Indicators and Rankings: Inventory 2011 136 E: questions addressing national strategy, implementation, entrepreneurship, and attitudes toward technology. Traditional Indicator formulation: NO = Q1 + (Q2 + Q3)/2 + Q4 + F1V/4.

Socioeconomic Infrastructure (SE): The social and economic institutions that support and maintain the physical, human, organizational, and economic resources essential to the functioning of a modern, technology-based industrial nation. S: Harbison-Myers Human Skills Index (from UNESCO data on % in higher education and % in secondary school) E: questions addressing national policies toward multinational investment, mobility of capital. Traditional Indicator formulation: SE = (Q5 + Q10 + HMHS)/3.

Technological Infrastructure (TI). Institutions and resources that contribute directly to a nation's capacity to develop, produce, and market new technology. Central to the concept are the ideas of economic investment and social support for technology absorption and utilization. These could take the forms of monetary payments, laws and regulations, and social institutions. Also included is the physical and human capital in place to develop, produce, and market new technology. S: number of scientists in R&D; electronic data processing purchases E: questions addressing technical training and education, contributions to knowledge, R&D with industrial relevance, technological mastery.

Traditional Indicator formulation: TI = [(Q7 + Q8)/2 + Q9 + Q11 + EDP + S&E]/5.

Productive Capacity (PC): The physical and human resources devoted to manufacturing products, and the efficiency with which those resources are used. S: electronics production E: questions addressing supply of skilled labor, indigenous component supply, indigenous management capability.

Traditional Indicator formulation: PC = [((Q6+Q12+Q13)/3)+A26/2]/1.5

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115. The Times Higher Education World Reputation Rankings

Developer 1 Times Higher Education Developer 2 Year launched 2011 Latest Edition 2011 Field Education Number of Main Dimensions 2 Description of Main Dimensions 1. Teaching (1/3) 2. Research (2/3) (Weights in Parenthesis) Number of Underlying Indicators 2 Number of units ranked 100 Type of units ranked Institutions: Universities Link to report http://www.timeshighereducation.co.uk/world-university- rankings/ Link to data http://www.timeshighereducation.co.uk/world-university- rankings/2010-2011/reputation-rankings.html

The world's top universities ranked exclusively on their reputation for teaching and research. The World Reputation Rankings, a subsidiary of the overall World University Rankings, are based on the largest global survey of academic opinion ever undertaken: more than 13,000 experienced academics from 131 countries give their expert insight. They are a measure of a university's reputation for excellence, in both teaching and research, among experienced university academics around the world. The reputation rankings are drawn from an Academic Reputation Survey carried out by polling company Ipsos for our rankings data provider, Thomson Reuters, as part of the Thomson Reuters Global Institutional Profiles Project. The same survey results formed two of the 13 performance indicators used to create the Times Higher Education World University Rankings 2010-11, published on 16 September 2010. The reputation data are revealed here in isolation for the first time.

Respondents could highlight what they believed to be the strongest universities, regionally and globally, in their specific fields, selecting from hundreds of disciplines and from more than 6,000 academic institutions. "Action-based" questions - such as "where would you recommend a top undergraduate should study for the best postgraduate supervision?" - were used to encourage more thoughtful responses and more meaningful results.

Our table ranks institutions according to an overall measure of their esteem that combines data on their reputations for research and teaching. The two scores are combined at a ratio of 2:1, giving more weight to research, because feedback from the global higher education community suggests that academics have a greater confidence in their ability to make accurate judgements on research quality. The reputation scores are based on the number of times an institution was cited by survey respondents as being "the best" in their narrow fields of expertise. Each respondent was able to nominate a maximum of 10 institutions. The number one ranked institution, Harvard University, was selected most often. The scores of all the other institutions in the table are expressed as a percentage of Harvard's score, set at 100. For example, the Massachusetts Institute of Technology received 88.4 per cent of the number of nominations for research that Harvard received, giving it a score of 88.4 compared with Harvard's 100. This scoring system is different from the one used in the World University Rankings, and is intended to provide a clearer and more meaningful perspective of the reputation data.

Composite Indicators and Rankings: Inventory 2011 138 116. Times Higher Education World University Rankings

Developer 1 Times Higher Education Developer 2 Year launched 2004 Latest Edition 2011 Field Education Number of Main Dimensions 5 Description of Main Dimensions 1. Teaching — the learning environment (worth 30 per cent of (Weights in Parenthesis) the final ranking score) 2. Research — volume, income and reputation (worth 30 per cent) 3. Citations — research influence (worth 32.5 per cent) 4. Industry income — innovation (worth just 2.5 per cent) 5. International mix — staff and students (worth 5 per cent) Number of Underlying Indicators 13 Number of units ranked 200 Type of units ranked Institutions: Universities Link to report http://www.timeshighereducation.co.uk/world-university- rankings/ Link to data http://www.timeshighereducation.co.uk/world-university- rankings/2010-2011/top-200.html

These global university league tables are a source of broad comparative performance information on universities. The tables represent the most comprehensive and sophisticated exercise ever undertaken to provide transparent, rigorous and genuinely meaningful global-performance comparisons for use by university faculty, strategic leaders, policymakers and prospective students.

The tables use 13 separate indicators (up from just six under our old system) designed to capture a broad range of activities, from teaching and research to knowledge transfer.

These elements are brought together into five categories: 1. Teaching — the learning environment (worth 30 per cent of the final ranking score) 2. Research — volume, income and reputation (worth 30 per cent) 3. Citations — research influence (worth 32.5 per cent) 4. Industry income — innovation (worth just 2.5 per cent) 5. International mix — staff and students (worth 5 per cent)

The weightings for the five categories, and the 13 indicators within them, vary considerably. High weightings are given where consultation has shown unmistakable enthusiasm for the indicator as a valuable proxy and clear confidence in the data we have. Lower weightings are employed where confidence in the data or the usefulness of the indicator is less pronounced.

To calculate the overall ranking score, "Z-scores" were created for all datasets. This standardises the different data types on a common scale and allows fair comparisons between the different types of data — which is essential when combining diverse information into a single ranking. Each data point is given a score based on its distance from the average (mean) of the entire dataset, where the scale is the standard deviation of the dataset. The Z-score is then turned into a "cumulative probability score" to give the final totals.

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117. Trends in International Mathematics and Science Study (TIMSS)

Developer 1 International Association for the Evaluation of Educational Achievement (IEA) Developer 2 Year launched 1995 Latest Edition 2011 Field Education Number of Main Dimensions 2 Description of Main Dimensions mathematics and science, 4th and 8th grade (Weights in Parenthesis) Number of Underlying Indicators Number of units ranked 60 Type of units ranked Countries Link to report http://www.iea.nl/timss2011.html Link to data http://timss.bc.edu/timss2011/index.html

The Trends in International Mathematics and Science Study is designed to help countries all over the world improve student learning in mathematics and science. It collects educational achievement data at the fourth and eighth grades to provide information about trends in performance over time together with extensive background information to address concerns about the quantity, quality, and content of instruction.

Composite Indicators and Rankings: Inventory 2011 140 118. World Knowledge Competitiveness Index (WKCI)

Developer 1 Centre for International Competitiveness Developer 2 Year launched 2002 Latest Edition 2008 Field Education Number of Main Dimensions 5 Description of Main Dimensions 1. Human capital, 2. financial capital,3. knowledge capital, 4. (Weights in Parenthesis) regional economy outputs and 5. knowledge sustainability. Number of Underlying Indicators 19 Number of units ranked 145 Type of units ranked Regions Link to report http://www.cforic.org/pages/wkci.php Link to data http://www.cforic.org/pages/wkci.php

The WKCI is an integrated and overall benchmark of the knowledge capacity, capability and sustainability of each region, and the extent to which this knowledge is translated into economic value, and transferred into the wealth of the citizens of each region. As such, the competitiveness of a region will depend on its ability to anticipate and successfully adapt to internal and external economic and social challenges, by providing new economic opportunities, including higher quality jobs. The WKCI compares 145 regions across 19 knowledge economy benchmarks. The selected variables analysed can be usefully divided into five components: human capital, financial capital, knowledge capital, regional economy outputs and knowledge sustainability.

In order to create the composite World Knowledge Competitiveness Index all data are first converted so that the mean and variance of each variable is set at zero and one respectively. After the standardisation, a multivariate data reduction technique called factor analysis is applied to the data set. Factor analysis is used to simplify complex and diverse relationships that exist among a set of observed variables by uncovering common dimensions or factors that link together the seemingly unrelated variables, and consequently provide insights into the underlying structure of the data. In general, these dimensions are uncorrelated with one another. To extract the common part of variations among the original variables (i.e. commonalities), an extraction method called image factoring is employed. The dimensions obtained are then rotated. A rotation method called varimax is used with Kaiser normalisation. While identifying common dimensions of the underlying structure, factor analysis also shows the location of each case (i.e. region in this study) within the underlying structure, by providing the case’s scores for the dimensions identified. We use these scores for the dimensions as sub-composite indices. Subsequently, we aggregate these sub-composite indices with a view to obtaining a single composite. A quantitative analytical technique called Data Envelopment Analysis (DEA) is used to obtain a single composite index from the above sub-composite indices. DEA is a linear programming technique originally developed for the estimation of the relative efficiency of a set of units (called decision making units, DMUs) producing a set of outputs from common inputs. It neither assigns weights to variables with any dependent variable chosen a priori, nor assigns weights set a priori. Instead, it seeks a set of weights for each unit that maximises a weighted sum of variables, with the constraint that no units have a weighted sum larger than one. As a result, each unit receives a score between 0 and 1. This process is repeated for all units in the data set, giving each unit a score unique to each iteration. Finally a geometric mean of all the scores is taken for each unit, providing a DEA score.

The DEA model can be stated as follows. Let xij (i = 1, ..., m) be the scores of m sub-composite indices for region j ( j = 1, ..., n). A composite score of region j, denoted here as C, is then maximised as:

Max Cj = ( V1 x1 + .... + Vm xmj) subject to:

Composite Indicators and Rankings: Inventory 2011 141 (V1 x1 + .... + Vm xmj) ≤ 1 j = 1, ...., n.

Vi > 0 for all i.

Let us denote the maximised composite score for region j as Cj (max j). While Cj (max j) is obtained for region j, other regions also gain composite scores under the weights V1, …,Vm that are set to maximise the region j’s score. They can be denoted as C1 (max j), C2 (max j), Cn…, (max j).

This maximisation process is undertaken for all regions in the data set. As a result, each region receives n composite scores, one of which is obtained from maximisation of its own composite score. Finally a geometric mean of Cj (max 1), Cj (max 2), …, Cj (max j) …, Cj (max n) is taken for region j, providing a DEA score of region j (j = 1, ..., n).

DEA scores range from zero to one. To facilitate a more intuitive understanding, we convert DEA scores to ones whose average is 100 with a variance similar to variances of the original variables. For this, we first convert original variables so that their averages become 100 (i.e. divide the scores of regions for each variable by its average and then multiply them by 100). We then take a geometric mean of the variances of the converted variables, which we denote by (variance) original. Finally, we standardize DEA scores for regions 1 to n, multiply them by (variance) original, and add 100. The obtained scores, whose average equals 100, still maintain relative distance between regions but have a variance similar to the original variables.

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119. Air Quality Index (AQI)

Developer 1 US EPA Developer 2 Year launched N/A Latest Edition 2009 Field Environment Number of Main Dimensions 5 Description of Main Dimensions 1. Ground-level ozone, 2. Particle pollution 3. Carbon (Weights in Parenthesis) monoxide 4. Sulfur dioxide, and 5. nitrogen dioxide Number of Underlying Indicators 5 Number of units ranked 1 Type of units ranked US Link to report http://www.airnow.gov/index.cfm?action=aqibasics.aqi Link to data http://www.airnow.gov/index.cfm?action=aqibasics.aqi

The AQI is an index for reporting daily air quality. It tells you how clean or polluted your air is, and what associated health effects might be a concern for you. The AQI focuses on health effects that you may experience within a few hours or days after breathing polluted air. EPA calculates the AQI for five major air pollutants regulated by the Clean Air Act: ground-level ozone, particle pollution (also known as particulate matter), carbon monoxide, sulfur dioxide, and nitrogen dioxide. For each of these pollutants, EPA has established national air quality standards to protect public health .Ground-level ozone and airborne particles are the two pollutants that pose the greatest threat to human health in this country

Think of the AQI as a yardstick that runs from 0 to 500. The higher the AQI value, the greater the level of air pollution and the greater the health concern. Each category corresponds to a different level of health concern. The six levels of health concern and what they mean are:

. "Good" AQI is 0 - 50. Air quality is considered satisfactory, and air pollution poses little or no risk. . "Moderate" AQI is 51 - 100. Air quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people. For example, people who are unusually sensitive to ozone may experience respiratory symptoms. . "Unhealthy for Sensitive Groups" AQI is 101 - 150. Although general public is not likely to be affected at this AQI range, people with lung disease, older adults and children are at a greater risk from exposure to ozone, whereas persons with heart and lung disease, older adults and children are at greater risk from the presence of particles in the air. . "Unhealthy" AQI is 151 - 200. Everyone may begin to experience some adverse health effects, and members of the sensitive groups may experience more serious effects. . . "Very Unhealthy" AQI is 201 - 300. This would trigger a health alert signifying that everyone may experience more serious health effects. . "Hazardous" AQI greater than 300. This would trigger a health warnings of emergency conditions. The entire population is more likely to be affected.

Composite Indicators and Rankings: Inventory 2011 143 120. Canadian Biodiversity Index (CBI)

Developer 1 International Institute for Sustainable Development (IISD) Developer 2 Year launched 2006 Latest Edition 2006 Field Environment Number of Main Dimensions 4 Description of Main Dimensions 1. Species & Genes 2. Animal Habitats & Plant Communities 3. (Weights in Parenthesis) Landscape & Global Influences 4. Human Influences Number of Underlying Indicators 24 Number of units ranked 1 Type of units ranked Canada Link to report http://www.iisd.org/pdf/2006/measure_cbi.pdf Link to data http://www.iisd.org/pdf/2006/measure_cbi.pdf

The Canadian Biodiversity Index (CBI) assesses and conveys biodiversity issues and management across Canada. Based on consultation with external organizations, two ecounits were identified within the context of which the CBI was tested. Ecounits were large enough to be able to measure indicators and identify a desired future state for each indicator within each theme measured. The two selected ecounits were ultimately determined based on whether they had enough relevant data available. Indicators were selected, where possible, that currently exist in monitoring programs within the ecounits. Others were adapted from biodiversity indicator lists such as those provided with the Testing Manual and CBI Framework. The first step in indicator selection was identifying key biodiversity issues within the four CBI themes: 1. Species & Genes 2. Animal Habitats & Plant Communities 3. Landscape & Global Influences 4. Human Influences.

Once ecounits were identified and indicators for each theme selected, datasets or links to datasets available on the internet via reports or tables were obtained from organizations who hold the data. Desired future state values, or DFS, were selected in relation to assigning the CBI score scales. DFS values can either represent values at the top of the scale where more is better, at the bottom of the scale where less is better, or in many cases the middle of the scale where too much becomes a nuisance and too little is a concern. We attempted to define DFS values for each individual indicator for each ecounit based on some existing desired goal or level. In most cases DFS values were not readily available (i.e. already articulated). In all cases, the source of the DFS value (and how it was obtained by the testing team) was carefully referenced.

All indicators were “normalized” to a common scale from 0-100, based on attainment of their DFS. This allowed indicators measuring different things and expressed in different units of measure to be compared. The scale was set for each indicator in each ecounit, and the scale divided into 5 subcategories that were used to distinguish and compare performance among the indicators. Current data were plotted on these normalized graphs.

Current data were plotted on the normalized graphs and repeated for each data point from previous years for the given indicator to reveal historical trends where possible. An aggregate CBI score was calculated for each theme, and an overall aggregate score calculated for the entire ecounit, following the guidance provided in the Testing Manual. Additionally, for the purposes of testing an alternate scoring method, theme scores and final ecounit scores were also calculated and presented in this report following an alternative methodology as revealed from testing. This is further detailed in following sections and outlined in the final recommendations.

Composite Indicators and Rankings: Inventory 2011 144 121. Climate Action Tracker

Developer 1 ECOfys Developer 2 Climate Analytics Year launched 2010 Latest Edition 2010 Field Environment Number of Main Dimensions N/A Description of Main Dimensions (Weights in Parenthesis) N/A Number of Underlying Indicators N/A Number of units ranked 56 Type of units ranked Countries Link to report http://www.climateactiontracker.org/ Link to data http://www.climateactiontracker.org/

This "Climate Action Tracker" is an independent science-based assessment, which tracks the emission commitments and actions of countries. The Climate Action Tracker assesses the aggregated reductions that are achieved by developed countries by their proposed targets. It does not only look at the proposed reduction but also quantifies potential credits or debits from accounting for land use, land-use change and forestry (LULUCF). The aim of this project is to provide interested readers with an up-to-date assessment of the individual national pledges, with an overview of their aggregate effects. The intention is to make these pledges transparent and to encourage those countries that have not yet done so to make (or increase) their pledge. To assess the pledges made by the G20 countries, we evaluated the details in their proposals and projected actions. We assessed historical emissions, future baseline emissions and the target paths proposed by the developed countries or the emission levels (assuming implementation of the climate plan) for the developing countries. Where the pledge was unclear, we made assumptions, which are made explicit the relevant page. We also collected details of what other studies consider adequate pledges for these countries. We placed all of the countries in one of the following four categories:

1. Role model: These countries pledge reductions that are more stringent than any value for them in the studies analysed. They are leading the way by showing that it is possible to pledge very ambitious reductions. 2. Sufficient: These countries’ pledges are in the more stringent two thirds of the range given by the studies. They propose stringent reductions in line with most of the studies’ results. They also provide sufficient information to assess their pledge. 3. Medium: countries’ pledges are in the least stringent third of the range given by the studies. These countries' pledges might be considered Sufficient if other countries were to pledge more ambitious reductions. But, if all countries would be in this category, overall reductions would clearly not be sufficient. 4. Inadequate: These countries’ proposed emission targets are above the range given in the studies (and, in some cases, even above their reference scenario).

If a country is at the border between two categories, several elements are important in the rating:  Unconditional / conditional: Some countries have made a pledge that is conditional to an international agreement on climate change or to the provision of international financing. Other countries have made pledges that are unconditional and some are unclear on this issue. We have always used the unconditional pledge as default, which is rated. We also show the conditional pledge in the figures. If a country provided only a pledge conditional to financing, it is rated one category lower than an unconditional pledge of the same stringency would be. If a country provided only a pledge conditional to an international agreement and if a country is at the border of two categories, it is rated in the lower category. In such cases more information and clarity on the conditionality of the pledge or an additional unconditional pledge could improve the rating.

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 Details of the pledge: Some countries’ pledges are based only on an announcement by e.g. the president of the country, while some other pledges are accompanied with detailed reports. If a country is at the border of two categories and if the details of the pledge were not available or if the assessment required us to make many additional assumptions, we rated the country in the lower category. In such cases more information could improve the rating.

 Debits and credits from LULUCF accounting. Developed countries can receive credits and debits from accounting for land use, land-use change and forestry (LULUCF). If a country is at the border of two categories and if the credits/debits from LULUCF are not specified in detail by the country but are significant according to our assessment, we rated the country in the lower category. In such cases more information and clarity on the LULUCF accounting could improve the rating.

For each country we prepared a graph. The graph shows whether or not a given country’s pledge is sufficient to meet the required emission reductions by the year 2020. The pledge is categorised using the colour of the bar in the year 2020, according to the methodology specified above.

Developed countries aggregate The pledges of the G20 countries were assessed to see whether these are compatible with the proposed range for this group of developed countries of -25% to -40% below 1990 levels by 2020. The graph compares the aggregated reductions resulting from the pledges, with the required range.

Global Pathway for Climate Action Tracker To assess the impact of the targets put forward by countries, we construct a global emissions pathway to 2100 and using MAGICC v6.0, calculate a distribution of possible outcomes in global temperature, CO2 concentration, and total greenhouse gas concentration. The total global pathway is then run through MAGICC multiple times in order to obtain a probability distribution of outcomes, using a large set of model parameters that were constrained using various datasets of historical climate observations.

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122. Climate Analysis Indicators Tool (CAIT)

Developer 1 World Resources Institute Developer 2 Year launched 2004 Latest Edition 2007 Field Environment Number of Main Dimensions 3 Description of Main Dimensions GHG emissions, Socio-Economic factors, (Weights in Parenthesis) Natural factors Number of Underlying Indicators N/A Number of units ranked 200 Type of units ranked Countries Link to report http://cait.wri.org/ Link to data http://cait.wri.org/

The CAIT provides a comprehensive and comparable database of greenhouse gas emissions data (including all major sources and sinks) and other climate-relevant indicators. CAIT can be used for analyzing a wide variety of data-related climate change issues and to help support future policy decisions made under the Climate Convention and in other fora. It ranks countries in different areas: 1) GHG emissions: yearly GHG emissions, Cumulative Emissions from 1950 to 2000 (MtC and Tons C per person), Carbon Intensity of Energy Use 2) Socio-economic Factors: Health, Education, Size of government, Energy Use and Governance and 3) Natural Factors: Heating and Cooling needs, Fossil Fuel Reserves, Energy Use Mix , Land area and Population.

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123. Climate Change Performance Index (CCPI)

Developer 1 Germanwatch Developer 2 Europe Climate Action Year launched 2006 Latest Edition 2011 Field Environment Number of Main Dimensions 3 Description of Main Dimensions 1. Emissions trend (50%) 2. emissions level (30%) (Weights in Parenthesis) 3. climate policy (20%) Number of Underlying Indicators 12 Number of units ranked 57 Type of units ranked Countries Link to report http://www.germanwatch.org/klima/ccpi11.pdf Link to data http://www.germanwatch.org/klima/ccpi11tm.pdf

The index compares the 57 states that together are responsible for more than 90 percent of annual worldwide carbon dioxide emissions. Their climate change performance is evaluated according to uniform criteria and the results are ranked. With the help of the Index, the climate change policy, emissions level and emissions trend of a country can swiftly be accessed and judged. The climate change performance is measured via twelve different indicators. They can be classified in the categories emissions trend, emissions level and climate policy. With a weight of 70%, climate policy and emissions trend together count for more than the overall value of the emissions level. This allows achievements in reducing emissions to be adequately reflected. On the other hand, the category "emissions level" with a weight of 30%, ensures that countries which are making their emissions reductions from a very high level are not being rewarded too generously. The methodology that is used for the CCPI’s ranking follows the OECD guideline for creating performance indicators. The choice of standardisation method sets the frame according to which the results of countries are evaluated in separate areas. A single value therefore only has a meaning in its relation to others. The CCPI thus only compares climate change protection efforts, it does not assign absolute values. The CCPI‘s final ranking is calculated from the weighted average of the achieved scores of the evaluated countries in the CCPI‘s separate indicators. An absolute evaluation is not made. The CCPI only evaluates countries in comparison with one another. The following formula is used to calculate the index:

The current evaluation method sets zero as the bottom cut off, 100 points are the maximum that can be achieved. A country that was best in one indicator receives full point (in that indicator). The best possible overall score is therefore 100 points. Important for interpretation is the following: 100 points are possible in principle, but for each partial indicator, and for the overall score, still only means the best relative performance, which is not necessarily the optimal climate change protection effort

As their weighted averages are what count to the overall score, the rankings within the separate indicators have a less important function. The differences between countries’ efforts to protect the climate is only to be seen clearly in the achieved points, not in the ranking itself.

Composite Indicators and Rankings: Inventory 2011 148 124. Climate Change Vulnerability Index (CCVI) and Climate Change Risk Atlas

Developer 1 Maplecroft Developer 2 Year launched 2010 Latest Edition 2010 Field Environment Number of Main Dimensions 3 Description of Main Dimensions 1. Exposure to climate related disasters 2. human sensitivity 3. (Weights in Parenthesis) Future Vulnerability Number of Underlying Indicators 42 Number of units ranked 170 Type of units ranked Countries Link to report http://www.maplecroft.com/about/news/climate_change_risk_li st_highlights_vulnerable_nations_and_safe_havens_05.html Link to data N/A

The Climate Change Vulnerability Index (CCVI) enables organizations to identify areas of risk within their operations, supply chains and investments. It evaluates 42 social, economic and environmental factors to assess national vulnerabilities across three core areas. These include: exposure to climate-related natural disasters and sea-level rise; human sensitivity, in terms of population patterns, development, natural resources, agricultural dependency and conflicts; thirdly, the index assesses future vulnerability by considering the adaptive capacity of a country’s government and infrastructure to combat climate change.

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125. Climate Competitiveness Index (CCI)

Developer 1 UNEP Developer 2 Accountability Year launched 2010 Latest Edition 2010 Field Environment Number of Main Dimensions 2 Description of Main Dimensions 1. Climate Accountability Index 2. Climate Performance (Weights in Parenthesis) Index (equally weighted) Number of Underlying Indicators 26 Number of units ranked 95 Type of units ranked Countries http://www.climatecompetitiveness.org/images/CCI_Downl Link to report oad_Main_Report_PDF/cci-exec-summary.pdf Link to data http://www.climatecompetitiveness.org/

The Climate Competitiveness Index is a new analysis of how countries create enduring economic value through low carbon technology, products and services. The 2010 Climate Competitiveness Index assesses climate accountability and performance to identify how 95 countries are progressing towards the low carbon economy. CCI is the largest data-set and largest country-sample index to have been developed in the climate competitiveness space. It is a dynamic index with two components:

1. The Climate Accountability Index includes 13 variables examining the degree to which a country has the leadership, institutions, systems and practices in place to deliver climate competitiveness. So in addition to government actors, it considers the role of business associations, investment promotion agencies and consumer groups. The Climate Accountability Index is drawn from national disclosures, gathered by a multilingual team of trained analysts using a checklist of over 150 parameters. 2. The Climate Performance Index pulls together a broad range of national-level climate indicators, containing 13 hard and soft climate-related datasets from IEA, WEF, Gallup, Swiss RE and AccountAbility. Performance covers price signals, energy networks, carbon management by businesses and the decarbonisation track record to date. Countries that combine high performance on both dimensions are considered best placed to thrive in the low carbon economy.

The Climate Performance Index combines equally weighted sub-themes to analyse incentives and price signals, awareness and risk management, access to clean electricity and intensity emissions trends. The results show a mild positive correlation between accountability and performance in 95 countries. The mean of the two sub-indexes can be taken as the Climate Competitiveness Index.

Composite Indicators and Rankings: Inventory 2011 150

126. Dashboard of Sustainability

Developer 1 Consultative Group on Sustainable Development Indicators / IISD Developer 2 Year launched 1999 Latest Edition 2010 Field Environment Number of Main Dimensions 3 Description of Main Dimensions 1. Economic 2. Environment 3. Social Care (Weights in Parenthesis) Number of Underlying Indicators 60 Number of units ranked 200 Type of units ranked Countries Link to report http://www.iisd.org/cgsdi/dashboard.asp Link to data http://esl.jrc.it/envind/dashbrds.htm

The Dashboard is a free software package that illustrates the complex relationships among economic, social, instructional and environmental issues. The Dashboard focuses on the Millennium Development Goals indicator set, but features also a number of other indices, e.g. the UN CSD set, the Ecological Footprint, the ESI, CDI and various governance indices. The tool allows interactive weighting and recomposition of indicator sets, linkage analysis, interactive colour-coded maps and other specific functions aimed at visualising and handling complex indicator sets. A simple interface to Excel allows indicator developers to create their own dashboards.

The colour for the level 2 circle segments (in the picture above the three segments for Economy, Social Care and Environment, as well as the PPI) is being calculated by multiplying performance points with weighting coefficients. The Policy Performance Index (PPI) is calculated on the basis of the overall points achieved, and the PPI colour results from the position of the country (city) in the database (which is not necessarily the same as the sum of the colours of the sub-indices). All indicators within one Dashboard circle are given the same weight, i.e. they are equally weighted. The three circles (in the case of the CGSDI dashboard) are given equal weight, too, for the aggregation to the overall "Policy Performance Index" (PPI).

Performance valuation: Policy performance is displayed through a seven-colour code ranging from dark red ("critical") over yellow ("average") to dark green ("best"). The valuation is relative to the 100 countries (CGSDI) resp. 103 cities (Ecosistema Urbano) included in the database. The software tool uses a point system, ranging from 0 (worst case, dark red) to 1000 points (best country or city, dark green). All other values are calculated by linear interpolation between these extremes. In rare cases, such as the CGSDI indicators "inflation rate" and "sub-soil assets", we use an outlier correction scheme that ensures a sufficient number of countries in each colour category. The present CGSDI dashboard uses inter-country comparisons, and thus provides only a judgement for one year (the data are mostly about 2-3 years old). For the main function of the dashboard, i.e. the identification of the weak and strong points in comparison to others, this geographical valuation is sufficient (we are aware of the sometimes bad geographical comparability of the underlying data – but all global databases have to cope with this problem). Why not valuation by sustainability targets? Although it is principally possible to substitute the current "MinMax valuation" with a point system based on sustainability targets, we do not envisage such a system for the CGSDI unless it can be proven that such targets are based on a societal consensus. Such skepticism is based on the observation that there are many more targets than political issues around; best example is the huge difference between the CO2 reduction targets of the IPCC (the Inter-Governmental Panel on Climate Change asks for a 75% reduction, some European governments have fought for, and obtained, a substantial increase in the Kyoto protocol).

Composite Indicators and Rankings: Inventory 2011 151 127. Ecological Footprint

Developer 1 WWF Developer 2 Year launched 2000 Latest Edition 2010 Field Environment Number of Main Dimensions 6 Description of Main Dimensions 1. Carbon 2. Grazing 3. Forest 4. Fishing 5. Copland 6. Built- (Weights in Parenthesis) up land Number of Underlying Indicators 6 Number of units ranked 148 Type of units ranked Countries http://wwf.panda.org/about_our_earth/all_publications/living_ Link to report planet_report/ http://wwf.panda.org/about_our_earth/all_publications/living_ Link to data planet_report/demands_on_our_planet/

Every human activity uses biologically productive land and/or fishing grounds. The Ecological Footprint is the sum of this area, regardless of where it is located on the planet. It has 6 components:

Both the Ecological Footprint (which represents demand for resources) and biocapacity (which represents the availability of resources) are expressed in units called global hectares (gha), with 1gha representing the productive capacity of 1ha of land at world average productivity.

Composite Indicators and Rankings: Inventory 2011 152 128. Environmental Degradation Index (EDI)

Developer 1 Raghbendra Jha and KV Bhanu Murthy Developer 2 Australian National University and U of Delhi Year launched 2003 Latest Edition 2003 Field Environment Number of Main Dimensions 4 Description of Main Dimensions 1 PCFWW – Annual per capita fresh water withdrawals. 2. (Weights in Parenthesis) PAPCPM - Printing and writing paper consumed per capita. 3. PCCO2 - Per capita CO2 emission. 4. CO2SH - Share of world total CO2. Equal weights Number of Underlying Indicators 4 Number of units ranked 174 Type of units ranked Countries Link to report N/A Link to data http://rspas.anu.edu.au/economics/publish/papers/wp2004/wp- econ-2004-03.pdf

The authors use the method of Principal Components Analysis (PCA) to construct an Environmental Degradation Index (EDI) for each country and global environmental degradation (GED) as the sum of the EDI’s. They rank the countries according to the EDI. They use the EDI to relate consumption to environmental degradation. They identify outliers and influential observations among both the environmental and consumption related variables. Canonical Discriminant analysis is then used to classify development classes along environmental lines. Then they estimate a simultaneous equation model to analyze the pattern of causation between per capita income, consumption and environmental degradation. They estimate a Global Environmental Kuznets curve (GEKC) as a relation between EDI ranks and ranks of the consumption-based EDI. Six variables from the Human Development report are chosen for the EDI and then2 of these are dropped: 1 PCFWW – Annual per capita fresh water withdrawals. 2. CENTFWW - Annual fresh water withdrawals as a percentage of water resources. 3. PAPCPM - Printing and writing paper consumed per capita. 4. PCCO2 - Per capita CO2 emission. 5. CO2SH - Share of world total CO2. 6. DEFOR – Rate of deforestation. Two variables were discarded, viz., the second (CENTFWW) and the sixth (DEFOR) and define the EDI for the ith country as:

And the Global Environmental Degradation (GED) is given by:

Composite Indicators and Rankings: Inventory 2011 153 129. Environmental Performance Index (EPI)

Developer 1 Yale University Developer 2 Columbia University Year launched 2002 Latest Edition 2010 Field Environment Number of Main Dimensions 2 Description of Main Dimensions 1. ENVIRONMENTAL HEALTH: Environmental Burden of (Weights in Parenthesis) Disease (25%), Water (effects on humans) (12.5%), Air Pollution (effects on humans) (12.5%) 2. ECOSYSTEM VITALITY: Air Pollution (effects on ecosystems) (4.167%) Water (4.167%), Biodiversity and Habitat (4.167%), Forestry (4.167%), Fisheries (4.167%), Agriculture (4.167%), Climate Change (25%) Number of Underlying Indicators 25 Number of units ranked 163 Type of units ranked Countries Link to report http://epi.yale.edu/file_columns/0000/0157/epi2010_report.pdf Link to data http://epi.yale.edu/

The 2010 EPI measures the effectiveness of national environmental protection efforts in 163 countries. Reflecting our belief that on-the-ground results are the best way to track policy effectiveness, EPI indicators focus on measurable outcomes such as emissions or deforestation rates rather than policy inputs, such as program budget expenditures. Each indicator can be linked to well-established policy targets.

The EPI measures two core objectives of environmental policy:

1. Environmental Health, which measures environmental stresses to human health; and 2. Ecosystem Vitality, which measures ecosystem health and natural resource management.

The 2010 EPI relies on 25 indicators that capture the best worldwide environmental data available on a country scale. We chose the indicators through a careful analytical process that included a broad review of the environmental science literature, in-depth consultation with scientific experts in each policy category, evaluation of candidate data sets, identification of proxy variables where necessary, and expert judgment. The EPI also incorporates criteria from other policy assessments, including the Millennium Ecosystem Assessment, the Intergovernmental Panel on Climate Change, the Biodiversity Indicator Partnership, and the Global Environmental Outlook-4. Although several significant gaps in issue area coverage remain (see Box 2.1), the 2010 EPI offers a comprehensive look across the pollution control and natural resource management challenges every country faces.

The 25 indicators reflect state-of-the-art data and the best current thinking in environmental health and ecological science. Some represent direct measures of issue areas; others are proxy measures that offer a rougher gauge of policy progress by tracking a correlated variable. Each indicator corresponds to a long- term public health or ecosystem sustainability target. For each country and each indicator, a proximity-to- target value is calculated based on the gap between a country’s current results and the policy target. These targets are drawn from four sources: (1) treaties or other internationally agreed upon goals; (2) standards set by international organizations; (3) leading national regulatory requirements; or (4) expert judgment based on prevailing scientific consensus.

The data matrix covers all of the countries for which an EPI can be calculated. In a few cases – such as for the access to water and sanitation, water quality index, emissions from land use change and carbon-dioxide emissions per electricity generation metric – imputation methods were used to fill gaps. Where country

Composite Indicators and Rankings: Inventory 2011 154 values are imputed they are clearly denoted in the separately downloadable spreadsheet. Further information on the imputation methods are available in the indicator metadata.

Using the 25 indicators, scores are calculated at three levels of aggregation, allowing analysts to drill down to better understand the underlying causes of high or low performance. Compared to the 2006 and 2008 EPIs, the structure of the EPI has changed in 2010 as a result of methodological refinements, so a comparison of EPI rankings across years is of indicative value only.

The aggregation process proceeds in the following steps:

1. Scores are calculated for each of the ten core policy categories based on one to four underlying indicators. Each underlying indicator represents a discrete data set. The ten policy categories are as follows: (1) Environmental Burden of Disease; (2) Water Resources for Human Health; (3) Air Quality for Human Health; (4) Air Quality for Ecosystems; (5) Water Resources for Ecosystems; (6) Biodiversity and Habitat; (7) Forestry; (8) Fisheries; (9) Agriculture; and (10) Climate Change.

Each indicator’s is weighted. Scores are next calculated for the objectives of Environmental Health and Ecosystem Vitality with weights allocated as shown below. The overall Environmental Performance Index is then calculated, based on the mean of the two broad objective scores. The rankings are based on the Index scores.

Composite Indicators and Rankings: Inventory 2011 155 130. Environmental Sustainability Index (ESI)

Developer 1 Yale University Developer 2 Columbia University Year launched 2000 Latest Edition 2005 Field Environment Number of Main Dimensions 5 Description of Main Dimensions 1. Environmental Systems 2. Reducing Stresses 3. Reducing (Weights in Parenthesis) Human Vulnerability 4. Social and Institutional Capacity and 5. Global Stewardship. Number of Underlying Indicators 21 Number of units ranked 146 Type of units ranked Countries Link to report N/A Link to data http://sedac.ciesin.columbia.edu/es/esi/

The ESI benchmarks the ability of nations to protect the environment over the next several decades. A total of 146 countries met our inclusion criteria for the 2005 ESI. The decision to include a country in the index is based on country size, variable coverage, and indicator coverage as follows:

1. Country Size: Small countries are excluded. Countries with a total 2003 population under 100,000 or with land area under 5,000 square kilometers are excluded from the ESI because the nature of the interactions between elements of environmental sustainability are fundamentally different compared to larger countries. In particular, very small countries with large enough economies to be included in international data compilations resemble cities more than countries. They lack any sizable hinterland and have evolved to rely almost entirely on outsiders for provision of critical natural resources. Such profound differences make it difficult to justify including them in the same framework as other countries.

2. Variable coverage: While we seek to include as many countries as possible, the large number of missing observations makes it difficult to accurately and appropriately rank a country. We exclude countries that have observations for fewer than 45 of the 76 requisite data points for the ESI.

3. Indicator coverage: Some countries that survive the first two screens do not have even coverage across all 21 ESI indicators. We require that all countries in the ESI have observed variables for each of the ESI indicators, with two exceptions. Air Quality and Water Quality have relatively low country coverage across their constituent variables, but these indicators are judged too important to be eliminated. Because they are such vital issues, we want to retain the information we can for countries that report air and water quality, and we choose not to exclude the many countries that fail to report such data. If a country was missing all variables in any one of the remaining 19 indicators, it was removed.

Variable Standardization for Cross-Country Comparisons: To calculate the ESI scores for each country and to facilitate the aggregation of variables into indicators, the raw data need to be transformed to comparable scales. Some of the ESI variables already are denominated to make such cross-country comparison possible. Where this is not the case, we identify an appropriate denominator such as GDP, agricultural GDP, the total value of imports of goods and services, total population, the world average price of gasoline, city population, population aged 0-14 years, total land area, populated land area, as well as known amphibian, breeding bird, and mammal species.

Variable transformation: After making the variables fit for cross-country comparisons, the next step is to prepare them for the imputation and aggregation processes. The procedure spelled out below explains the data transformations undertaken prior to and after the imputations, as well as the impacts they may have on the Environmental Sustainability Index scores. First, we test all variables for normality of distribution. In

Composite Indicators and Rankings: Inventory 2011 156 many cases, the observations exhibit substantial skewness (see formula below). Most variables also exhibit patterns of heteroskedasticity, which means that the variance of the observations increases with the magnitude of the data. Both interfere with the imputation model’s assumption of multivariate normality.

A perfectly normally distributed variable is symmetric around its mean and hence has a skewness of zero. Skewed and/or heteroskedastic variables can be transformed to improve these properties but this may also change their distributions in ways that may affect the interpretation of the ESI scores. The logarithmic function, for example, is commonly used to reduce the influence of a few very large values by moving them closer to the mean. Similarly, it shifts very small values closer to the center of the distribution. Although the transformation may help approximating the normal distribution more closely, it will cause countries with exceptional values on a particular issue to no longer be such distinct outliers.

In addition to improving the imputation model, we also argue in favor of transformations as a means of reducing the impact of outliers on the ESI. In our experience, extremely small or large values have a relatively high probability of being measurement errors. A more normal, symmetric distribution implies that the majority of observations fall within two standard deviations of the mean (for a normal distribution, two standard deviations include 95% of the data) and extreme values occur with small probability.

However, in order to strike a balance between improving the distributional characteristics of the data and minimizing the impacts of the transformations on the ESI scores and ranks, we apply a 2-step procedure that recognizes the importance of normality for the imputations but its less significant value for the aggregation:

1. Prior to the generation of multiple imputations we transform all variables that have a skewness value larger than two using the base-10 logarithm or power transformations. In most cases the distributional effects of the transformations are beneficial. 2. After the imputations, we transform the variables back to their original scale with the exception of those variables with extreme skewness values of at least four. In doing so, we ensure that only variables with extreme values outside four standard deviations are corrected for symmetry.

Composite Indicators and Rankings: Inventory 2011 157 131. Environmental Vulnerability Index (EVI)

Developer 1 SOPAC Developer 2 Year launched 2004 Latest Edition 2005 Field Environment Number of Main Dimensions 7 Description of Main Dimensions 1.Climate Change = CC 2. Biodiversity = CBD 3. Water = W 4. (Weights in Parenthesis) Agriculture and fisheries = AF 5. Human health aspects = HH 6.Desertification = CCD 7. Exposure to Natural disasters = D Number of Underlying Indicators 50 Number of units ranked 235 Type of units ranked Countries Link to report http://vulnerabilityindex.net/Files/EVI%20Final%20Report%202 005.pdf Link to data http://vulnerabilityindex.net/EVI_Results.htm

The EVI is based on 50 indicators for estimating the vulnerability of the environment of a country to future shocks. These indicators are combined by simple averaging and reported simultaneously as a single index, a range of policy-relevant thematic sub-indices and as a profile showing the results for each indicator. Simple averages across indicators were used because they can be easily understood and more complex models do not appear to offer any advantages to the expression or utility of the index.

There are three distinct aspects of vulnerability recognisable for environmental, economic and social aspects of countries, all of which need to be evaluated to provide an overall sense of the issues at play. These are the risks associated with hazards, resistance and acquired vulnerability (damage). The first aspect relates to the likelihood of hazards coming into play, while the latter two aspects are related to the ability of the environment to withstand the effects of hazards. In the EVI, indicators were specifically selected to ensure that information on these three aspects is incorporated in the overall vulnerability of countries. There are 32 indicators of hazards, 8 of resistance and 10 that measure damage. The hazard indicators relate to the frequency and intensity of hazardous events. The resistance indicators refer to the inherent characteristics of a country that would tend to make it more or less able to cope with natural and anthropogenic hazards. Damage indicators relate to the vulnerability that has been acquired through loss of ecological integrity or increasing levels of degradation of ecosystems. For most indicators, signals are based on average levels observed over the past 5 years, but may include data for much longer periods for geological events. All of the EVI’s indicators are transformed to a common scale so that they can be combined by averaging, and to facilitate the setting of thresholds of vulnerability. This new scale has been designed to reflect the environmental vulnerability associated with each indicator, regardless of any other scale on which an indicator could simultaneously exist. The EVI scale was defined as ranging between a value of 1 (indicating high resilience / low vulnerability) and 7 (indicating low resilience / high vulnerability). The EVI scale was determined separately for each indicator, is designed to be policy- elevant, and is based on the best available scientific information.

Each indicator is classified into a range of sub-indices including the three aspects of hazards; resistance and damage and into policy-relevant sub-indices including: Climate Change = CC , Biodiversity = CBD, Water = W, Agriculture and fisheries = AF, Human health aspects = HH, Desertification = CCD, Exposure to Natural disasters = D. EVI reports for countries are organised as a single-page, information- dense report card. The information available on the report includes overall EVI score in points, with percent of data over which it was calculated and a classification of overall vulnerability. Vulnerability classification:

Extremely vulnerable 365+

Composite Indicators and Rankings: Inventory 2011 158 Highly Vulnerable 315+ Vulnerable 265+ At risk 215+ Resilient < 215 Resilient <215 The EVI is unlike other environmental indices that describe the relative position of a country in relation to worldwide observed values. The EVI has been designed using thresholds which have been built in to the 1- 7 EVI scale to create a link or anchor between what conditions are observed in countries and those that are environmentally sustainable. Using this approach, indicators are scaled independently of the observed values, providing an in-built mechanism by which countries can immediately assess their vulnerability, rather than identifying their position in relation to others. Resilient <215

Composite Indicators and Rankings: Inventory 2011 159

132. European Green City Index

Developer 1 Siemens Developer 2 Economist Intelligence Unit (EIU) Year launched 2010 Latest Edition 2010 Field Environment Number of Main Dimensions 8 Description of Main Dimensions 1. CO2 Emissions, 2. Energy, 3. Buildings,4. Transportation, 5. (Weights in Parenthesis) Water,6. Air, 7. Waste/Land Use, and8. Environmental Governance. Number of Underlying Indicators 30 Number of units ranked 30 Type of units ranked European cities Link to report http://www.siemens.com/innovation/en/publications/publications_p of/pof_spring_2010/green_cities/egc_index.htm Link to data http://www.siemens.com/innovation/en/publications/publications_p of/pof_spring_2010/green_cities/egc_index.htm

It compares the environmental performance of 30 major cities in 30 European countries. From Athens to Zagreb, from Ljubljana to Istanbul, and from Oslo to Kiev, the study targeted the largest cities in the countries in question, in most cases their capitals. In order to illustrate their environmental and climate protection performance and objectives, each of the cities was assessed on the basis of 30 indicators divided into eight categories: CO2 Emissions, Energy, Buildings, Transportation, Water, Air, Waste/Land Use, and Environmental Governance. The methodology for the study was developed by the EIU in cooperation with independent urban experts and Siemens.

Composite Indicators and Rankings: Inventory 2011 160 133. FEEM Sustainability Index (FEEM SI)

Developer 1 Fondo Eni Enricco Mattei Developer 2 Year launched 2009 Latest Edition 2009 Field Environment Number of Main Dimensions 3 Description of Main Dimensions 1. Economy 2. Environment 3. Social (Weights in Parenthesis) Number of Underlying Indicators 12 Number of units ranked 40 Type of units ranked Countries Link to report http://www.feemsi.org/ Link to data http://www.feemsi.org/

The FEEM SI is an index aimed at providing future projections of sustainability of countries, allowing for comparisons not only across countries, but also through time. The index is built within a dynamic computable general equilibrium model, which allows to project different scenarios in the future. The model output can then be used to assess sustainability according to the different characteristics of the scenarios. The model is based on a database relative to 2001 and then projected up to 2020. A database depicting the state of the different regional economies is produced for each year and used to build the set of indicators that compose the FEEM SI. The model used is the ICES-SI, an extended version of the Intertemporal Computable Equilibrium System (ICES) tailored for the construction of the sustainability indicators. Industries are modelled through a representative cost-minimizing firm. Total output is produced using all available inputs, which include natural resources, land, labour, capital, energy and a set of intermediate goods. A representative consumer in each region receives an income in exchange for labour and for the rent on land, natural resources, and capital. This income is then used to finance three types of expenditure, namely aggregate household consumption, public consumption and savings. The model accounts for main GHG emissions CO2, CH4 and N2O. Policies to restrict GHG emissions can be imposed in the model in order to compare sustainability with and without climate policies. The dynamic of the model is driven by two sources: one exogenous and the other endogenous. The first stems from exogenously imposed growth paths for some key variables - population, labour stock, labour productivity, land productivity. The values for these variables are taken from available statistics or projections from other modelling exercises. The second concerns the process of capital accumulation. Capital stock is updated over time in order to take into account endogenous investment decision. The current model aggregation allows us to calculate the FEEM SI sustainability indicators for 40 world regions. Indicators are constructed from variables obtained from the output of the ICES-SI model for each of the three main components of sustainability, namely economic, social, and environmental.

In order to proceed with the creation of the FEEM SI a normalisation step is necessary to reduce all indicators to a common scale. The FEEM SI indicators have been translated into a 0-1 scale using an indicator-specific normalisation grid defined either starting from relevant sustainability policies or on an average-based criterion. This method is called benchmarking and is very appropriate especially in the case of those indicators for which an agreed target of some kind (at EU level, or global) exists. Normally, the benchmarking procedure assigns only two values, 1 and 0, according to the correspondence to a chosen reference level. In the case of the FEEM SI the purpose was not only to identify best and worst practices, but also to provide a measure of a distance from a given target. That is why the FEEM SI indicators are normalised according to a benchmarking function passing through five reference levels that define a step function with four closed and two open, each one has “linearised”, taking the mean values of two subsequent intervals and interpolating, thereby creating a continuous step function.

Composite Indicators and Rankings: Inventory 2011 161 Each one of the five reference levels corresponds to a given level of sustainability, like a series of steps that go from unsustainable to fully sustainable, while values inside any of the intervals defined by these five values corresponds to an intermediate level in between two steps: 0 extremely unsustainable situation 0.25 indicator is still not sustainable but not as severely as in the previous case 0.50 a discrete level of sustainability, but still far from target 0.75 satisfactory level in the sustainability, yet not on target 1 target level, fully sustainable

Sustainability is characterised by very different indicators and countries can exhibit better values for some indicators, and worse for others, thus requiring an aggregation methodology able to deal effectively with all the information contained in the different indicators. The FEEM SI optimizes the trade-off between simplicity and effectiveness in representing preference by focusing specifically on the interrelations across indicators. In order to assess the degree of interaction across criteria, two extreme performance levels have been defined for each indicator. Next, a weight (or measure) is assigned not to a single criterion only, but to any coalitions of criteria for each node in the decision tree. In so doing, the importance of two benefits is not necessarily the weighted sum of the (single) importance of two benefits alone, but can be greater (in the case of positive interaction) or lower (in the case of negative interaction). A suitable algorithm based on the Choquet integral aggregates the criteria into a single one taking all the coalition weights into account.

Interaction among criteria can be measured by the tendency of the respondent's preference toward more or less “pessimistic” (conservative) behaviour. That is, a “conservative” decision maker prefers that all (or many of) the criteria are fulfilled in order to give a positive evaluation, while an “optimistic” one is satisfied if an excellent performance is observed in at least one criterion independently on the level of the other criteria. This kind of behaviour is a characteristic of the set of weights, only and can be summarized into a numerical index. In order to exploit all the interactions across indicators, the aggregation approach proposed for the FEEM SI requires a respondent (or a group of respondents) to define all the coalition weights (measures). These measures are not randomly given, but are the result of a careful reconstruction of individual preferences using a specifically built questionnaire.

Economic Social Environmental Weights Worst Worst Worst 0 Best Worst Worst 20 Worst Best Worst 50 Worst Worst Best 30 Best Best Worst X ≥ 50 Best Worst Best X ≥ 30 Worst Best Best X ≥ 50 Best Best Best 100

Any indicator is evaluated in two possible states “worst” and “best”, which indicate two extreme levels of performance. All possible combinations of these two states are presented to the respondent of the questionnaire, which must provide an evaluation respecting a monotonicity criterion. A “representative” decision maker has been used to define the measure sets for each node of the FEEM SI tree, characterised by a pessimistic behaviour when evaluating different performances in groups of indicators.

Sensitivity analysis: The subjective weights provided by the decision maker are crucial in the aggregation methodology of the FEEM SI, therefore a sensitivity analysis has been carried out in order to assess the effects of variations in the degree of pessimism of the simulated decision maker. In order to introduce some variability in the determination of subjective weights, three other (fictitious and simulated) decision makers have been determined, each one featuring a different degree of pessimism, and a weighted average of the subjective evaluations provided by all of them has been computed using weights that are randomly generated. This procedure was repeated 50 times thus generating a distribution whose main characteristics - mean, minimum, and maximum - have been used to determine whether countries are statistically equivalent in raking for a given year.

Composite Indicators and Rankings: Inventory 2011 162 134. Global Adaptation Atlas

Developer 1 Resources for the Future Developer 2 Year launched 2009 Latest Edition 2009 Field Environment Number of Main Dimensions 5 Description of Main Dimensions 1. Food, 2. Water, 3. Land, 4. Health and 5. Livelihood (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 170 Type of units ranked Countries Link to report http://adaptationatlas.org/about.cfm Link to data http://adaptationatlas.org/about.cfm

The Adaptation Atlas is a dynamic mapping tool bringing together diverse sets of data on the human impacts of climate change and adaptation activities across the themes of food, water, land, health and livelihood to help researchers, policymakers, planners and citizens to establish priorities and act on adaptation.

Composite Indicators and Rankings: Inventory 2011 163 135. Global Climate Change Policy Tracker

Developer 1 Deutsche Bank Developer 2 Year launched 2009 Latest Edition 2009 Field Environment Number of Main Dimensions 8 Description of Main Dimensions 1.Incentives 2. Public Financing 3. Enforcement 4. Monitoring 5. (Weights in Parenthesis) Sovereign credit risk 6. Integrated plan 7. Implementation capacity 8. Historical Achievement Number of Underlying Indicators 270 Number of units ranked 109 Type of units ranked Countries Link to report http://www.dbcca.com/dbcca/EN/investment- research/investment_research_1780.jsp Link to data http://www.dbcca.com/dbcca/EN/investment- research/investment_research_1780.jsp

This Global Climate Change Policy Tracker provides investors with an analysis of climate change policies and assigns a risk rating to 109 countries, states and regions based on key government mandates and supporting policy frameworks. It incorporates results of a model prepared by Columbia Climate Center researchers that estimates the impacts on carbon emissions of each of 270 major climate policies, and aggregates them at country, regional and global levels. The "Climate Tracker" provides a risk rating of countries and regions based on their relative attractiveness to investors. It is designed to help investors identify the best risk-adjusted returns in climate change investment opportunities around the world.

From this database we have: 1. Analyzed each mandated target to assess its risk level and ability to deliver its goal; 2. Developed an investor risk assessment of country policy regimes by aggregating these individual mandates; 3. Modeled the impact of all the targets on emissions through 2020. The modeling was conducted by researchers at the Columbia Climate Center at Columbia University’s Earth Institute.

We have developed a robust, qualitative assessment framework to rate each target, which is in turn fed into a quantitative risk rating score. Each target is assessed against 8 key criteria, which are then used collectively to develop a composite risk rating. As already discussed, incentives are particularly important. Given the importance of these, we use five sub-criteria to assess them. While these evaluations are qualitative in nature, we have attempted to be as methodical as possible in our assessment.

8 criteria:1.Incentives 2. Public Financing 3. Enforcement 4. Monitoring 5. Sovereign credit risk 6. Integrated plan 7. Implementation capacity 8. Historical Achievement

In the overall assessment, each of the criteria has been given equal weighting. This results in a composite score of between 8 and 24 points, with lower scores indicating a relatively lower-risk policy environment: • For all targets with a score of 12 points or less, the composite score is 1 – lower risk; • for all targets with a score of between 13 and 20, the composite score is 2 – moderate risk; • and for all targets with a score of 21 and above, the composite score is 3 – higher risk.

We have developed a view of the most attractive geographies for investment, based on the strength of the policy regime in place. Where multiple targets are rated in a single geography, we have weighted their ratings (based on the emissions impact) for the average rating for the region.

Composite Indicators and Rankings: Inventory 2011 164 136. Global Climate Risk Index (CRI)

Developer 1 Germanwatch Developer 2 Year launched 2006 Latest Edition 2011 Field Environment Number of Main Dimensions 4 Description of Main Dimensions 1. Number of deaths, 2. Number of deaths per 100 000 inhabitants, (Weights in Parenthesis) 3. Sum of losses in US$ in purchasing power parity (PPP) as well as 4. Losses per unit of Gross Domestic Product (GDP). Number of Underlying Indicators 4 Number of units ranked 173 Type of units ranked Countries Link to report http://www.germanwatch.org/klima/cri.htm Link to data http://www.germanwatch.org/klima/cri2011.pdf

The Global Climate Risk Index (CRI) analyses the quantified impacts of extreme weather events2 - both in terms of fatalities as well as economic losses that occurred - based on data from Munich Re NatCatSERVICE which is worldwide one of the most reliable and complete data bases on this matter. The CRI looks both at absolute and relative impacts, and results in an average ranking of countries in four indicators, with a stronger weighting of the relative indicators. The countries ranking highest are the ones most impacted and should see the CRI as a “warning signal” that they are at risk either from frequent events or rare, but extraordinary catastrophes.

The Climate Risk Index does not provide an all-encompassing analysis of the risks from anthropogenic climate change to countries, but should be seen as one analysis informing countries´ exposure and vulnerability to climate-related risks along with other analyses, based on the most reliable quantified data.

Analysed indicators: For this examination the following indicators were analysed in this paper: 1. Number of deaths, 2. Number of deaths per 100 000 inhabitants, 3. Sum of losses in US$ in purchasing power parity (PPP) as well as 4. Losses per unit of Gross Domestic Product (GDP). For the indicators 2. to 4., economic and population data primarily by the International Monetary Fund was taken into account. However, it has to be added that especially for small (e.g. Pacific small island states) or politically extremely instable countries (e.g. Somalia), the required data is not always available in sufficient quality for the whole observed time period. Those countries have to be left out of the analyses.

Composite Indicators and Rankings: Inventory 2011 165

137. Happy Planet Index

Developer 1 Friends of the Earth - New Economics Foundation Developer 2 Year launched 2006 Latest Edition 2009 Field Environment Number of Main Dimensions 3 Description of Main Dimensions 1. Ecological footprint, 2. life-satisfaction and 3. life (Weights in Parenthesis) expectancy. Number of Underlying Indicators 3 Number of units ranked 143 Type of units ranked Countries Link to report http://www.happyplanetindex.org/public-data/files/happy- planet-index-2-0.pdf Link to data http://www.happyplanetindex.org/

The HPI reflects the average years of happy life produced by a given society, nation or group of nations, per unit of planetary resources consumed. Put another way, it represents the efficiency with which countries convert the earth’s finite resources into well-being experienced by their citizens. The Global HPI incorporates three separate indicators: ecological footprint, life-satisfaction and life expectancy.

Conceptually the HPI is straightforward. It is an efficiency measure: well-being delivered per unit of environmental impact. However, a couple of statistical adjustments are made to ensure that no single component dominates the overall indicator:

Composite Indicators and Rankings: Inventory 2011 166

138. Human Sustainable Development Index (HSDI)

Developer 1 Chuluun Togtokh and Owen Gaffney Developer 2 UNEP Year launched 2010 Latest Edition 2010 Field Environment Number of Main Dimensions 4 Description of Main Dimensions Same as HDI but with GHG emissions per capita (Weights in Parenthesis) Number of Underlying Indicators 5 Number of units ranked 163 Type of units ranked Countries Link to report http://ourworld.unu.edu/en/the-2010-human-sustainable- development-index/ Link to data http://owe.6.co.ua/2608/2010-Human-Sustainable- Development-Index.pdf

The HSDI includes carbon emissions in the recalculation of the HDI, to get an indication of the cost of one country’s quality of life to another’s. If a country has a very high HDI but also high carbon emissions, we can say that the high quality of life enjoyed by this nation comes at a price to the quality of life in other countries, particularly developing nations, and to future generations.

Composite Indicators and Rankings: Inventory 2011 167

139. Index of Social Vulnerability to Climate Change (Africa)

Developer 1 Tyndall Centre for Climate Change Research (Katharine Vincent) Developer 2 Year launched 2004 Latest Edition 2004 Field Environment Number of Main Dimensions 5 Description of Main Dimensions 1. Economic well-being and stability (20%), 2. Demographic (Weights in Parenthesis) structure (20%), 3. Institutional stability and strength of public infrastructure (40%), 4. global interconnectivity (10%) and 5. dependence on natural resources (10%). Number of Underlying Indicators 9 Number of units ranked 22 Type of units ranked African countries Link to report http://www.tyndall.uea.ac.uk/content/creating-index-social- vulnerability-climate-change-africa Link to data Page 23-24 of http://www.tyndall.uea.ac.uk/sites/default/files/wp56.pdf

The SVI is an index that empirically assesses relative levels of social vulnerability to climate change- induced variations in water availability which allows cross-country comparison in Africa. A theory-driven aggregate index of social vulnerability was formed through the weighted average of five composite sub- indices: economic well-being and stability (20%), demographic structure (20%), institutional stability and strength of public infrastructure (40%), global interconnectivity (10%) and dependence on natural resources (10%). Countries are ranked from highest to lowest social vulnerability, depending of the score of the Social Vulnerability Index (SVI) with 1 being highest vulnerability and 0 lowest in a comparative basis.

Composite Indicators and Rankings: Inventory 2011 168

140. Living Planet Index

Developer 1 WWF Developer 2 Year launched 1998 Latest Edition 2010 Field Environment Number of Main Dimensions 3 Description of Main Dimensions A. Tropical index (50%) 2. Temperate index (50%) ( (Weights in Parenthesis) Terrestrial species, Freshwater species and Marine species) Number of Underlying Indicators 2500 Number of units ranked 200 Type of units ranked Countries Link to report http://wwf.panda.org/about_our_earth/all_publications/living _planet_report/ Link to data http://wwf.panda.org/about_our_earth/all_publications/living _planet_report/health_of_our_planet/tropical_temperate/

The Living Planet Index (LPI) is an indicator of the state of the world’s biodiversity. The LPI is based on population data for mammal, bird, reptile, amphibian and fish species from around the world. In the latest LPI, data from nearly 8,000 populations of over 2,500 animal species were used – many more than ever before. The LPI first calculates the annual rate of change for each population. Next, the average change across all populations is calculated for each year from 1970, when data collection began, to 2007, the latest date for which data is available. The global Living Planet Index is the aggregate of two indices – the temperate and tropical LPIs – each of which is given equal weight. The temperate and tropical LPIs include land, freshwater and marine species, each of which is given equal weight.

Composite Indicators and Rankings: Inventory 2011 169 141. Low Carbon Competitiveness Index

Developer 1 The Climate Institute Developer 2 E3G Year launched 2009 Latest Edition 2009 Field Environment Number of Main Dimensions 3 Description of Main Dimensions (Weights 1. Sectoral composition (0.349), 2. Early preparation in Parenthesis) (0.194) and 3. Future prosperity (0.457) Number of Underlying Indicators 36 Number of units ranked G-20 Type of units ranked Countries Link to report http://www.e3g.org/images/uploads/G20_Low_Carbon_Co mpetitiveness_Report.pdf Link to data http://www.e3g.org/images/uploads/G20_Low_Carbon_Co mpetitiveness_Report.pdf

This index seeks to provide a comparative, data-driven analysis of the progress countries are making to carry out this transition now and over time. There are three elements to assessing overall low carbon competitiveness: where countries are positioned now, the rate at which this is changing, and the scale of the challenge they face. This report therefore compares the performance of the G20 countries along three key metrics:  the low carbon competitiveness index: measuring the current capacity of each country to be competitive and generate material prosperity to its residents in a low carbon world, based upon each country’s current policy settings and indicators;  the low carbon improvement index: the extent to which countries are demonstrating an ability to improve their carbon competitiveness as they grow;  the low carbon gap index: the difference between this rate of improvement and the rate required if that country, given its projected economic growth, is to succeed in meeting its share of the required carbon reductions for atmospheric concentrations of greenhouse gases to be stabilised at 450 ppm (parts per million) CO2e.

Low carbon competitiveness index: An initial data collection exercise provided 36 variables which were considered likely to be linked to a country’s low carbon competitiveness and which had sufficient coverage across all countries and across a sufficient number of years. These variables reflected the fact that a country’s low carbon competitiveness can be improved either by reducing its carbon emissions for any given level of output (e.g. by switching from „dirty‟ to „clean‟ electricity generation) or by increasing its level of output for any given level of emissions (e.g. by improving the education opportunities for its residents). The variables were assigned to one of three categories that were chosen to represent different, although clearly related, elements which will determine performance in a low carbon future: sectoral composition, early preparation and future prosperity.

- The sectoral composition category captures how well, or otherwise, the composition of the economy is currently structured towards less emissions intensive activities. - Early preparation variables include indicators reflecting the steps that countries have already taken to move towards a low carbon economy. - The final category consists of variables which will determine future prosperity through their impact on the level of production of goods and services (broadly defined) per capita. The future level of production will be determined by the future level of capital in the economy.

With this data, statistical techniques were used to establish which of these variables, in the recent past, has had the strongest association with low carbon competitiveness - defined as GDP per tonne of emissions in

Composite Indicators and Rankings: Inventory 2011 170 this report. It should be emphasized that association does not necessarily imply causation: in many cases the variables should be considered as proxies for the underlying, but more difficult to measure, driver of carbon productivity; the efficiency of oil refining can be seen as a proxy for the efficiency of the industrial sector as a whole, while the percentage of electricity distribution losses is a proxy for the overall sophistication of the electricity grid (necessary if decentralized clean electricity generation is to be effectively harnessed).

Those variables which were both deemed to be positively associated with a good performance and reached a certain threshold of significance were then selected. In order to translate these criteria into a single index, weights need to be assigned to each component. The approach taken by this report is to use the econometric analysis to understand the relative importance of each individual variable within the index. As each individual variable is allocated to one of the three categories, the appropriate weight for each category can be ascertained as the sum of the individual weights of its component indicators. Then, within each category, all indicators have been weighted equally. Due to the econometric approach taken to the weightings the index is cardinal; that is, the size of the gap between countries provides information on the relative distance between them. Because the values of the indicators were all transformed to be between zero and one, a difference of 0.01 in the index could be interpreted as the distance a country would move if all of its indicators moved one per cent closer to best practice.

Category Early Preparation Sectoral Composition Future Prosperity Weight 0.194 0.349 0.457

The low carbon improvement and low carbon gap indices: The low carbon competitiveness index is designed to explain how well countries are currently positioned to generate material prosperity to their residents in a low carbon future. The capacity of countries to generate material prosperity in this context is not static, however, and will be changing over time. This section considers the speed at which countries are making these improvements and whether it is currently quick enough to meet the given targets for emissions reductions.

The low carbon competitiveness index gives insight into what policies or other factors might be leading a country to have a particularly strong or weak performance. In this section, the rate of improvement in carbon productivity, and its relationship with economic growth, is assessed directly rather than through examination of a series of indicators. This approach gives the ability to assess a country’s performance compared to its directly measured outcomes and allows for an assessment of performance against policy goals. As an intermediate step for framing the analysis on the rate of improvement, this section begins by considering the existing relationship between carbon productivity and GDP per capita levels (rather than their growth rates) in the G20 countries. GDP per capita is a reasonable proxy for conventional measures of productivity.

Following this, the relationship of carbon productivity and GDP growth will be used to construct the low carbon improvement index. In this index, countries are ranked according to how much their carbon productivity changes as their economies grow.

The low carbon gap index considers whether countries are improving their carbon productivity quickly enough if they are to meet their share of the required emissions reductions for atmospheric concentrations of carbon dioxide emissions to be stabilised at 450 ppm. This takes account of the recent historical relationship between economic growth and carbon productivity, projected future economic and population growth rates, and differentiated responsibilities for emissions reductions between Annex 1 and Non-Annex 1 countries.

Composite Indicators and Rankings: Inventory 2011 171 142. Social Vulnerability Index (SOVI)

Developer 1 Hazards and Vulnerability Research Institute -University of South Carolina Developer 2 Year launched 1990 Latest Edition 2003 Field Environment Number of Main Dimensions 9 Description of Main Dimensions 1. Class and property 2. Age 3. Rural, special needs 4. Wealth (Weights in Parenthesis) 5. Race and gender 6. Female 7. Service workers 8. Ethnicity and unemployment 9. Migrants Number of Underlying Indicators 32 Number of units ranked 1 Type of units ranked US Link to report http://webra.cas.sc.edu/hvri/products/sovi.aspx Link to data http://webra.cas.sc.edu/hvri/products/sovi.aspx

The Social Vulnerability Index (SOVI) measures the social vulnerability of U.S. counties to environmental hazards. The index is a comparative metric that facilitates the examination of the differences in social vulnerability among counties. The index synthesizes 32 socioeconomic variables, which the research literature suggests contribute to reduction in a community’s ability to prepare for, respond to, and recover from hazards. The data were culled from national data sources, primarily those from the United States Census Bureau.

The data were compiled and processed by the Hazards and Vulnerability Research Institute at the University of South Carolina. The data were standardized and placed into a principal components analysis to reduce the initial set of variables into a smaller set of statistically optimized components. Adjustments were made to the components’ cardinality (positive (+), negative (-), or absolute value (ll)) to insure that positive component loadings were associated with increasing vulnerability, and negative component loadings with decreasing vulnerability. Once the cardinalities of the components were determined, the components were added together to determine the numerical social vulnerability score for each county. For SOVI 2000, there are 9 significant components explaining 76% of the variance in the data. Among them are socioeconomic status, elderly and children, rural agriculture, housing density, black female-headed households, gender, service industry employment, unemployed Native Americans, and infrastructure employment. To visually compare the SOVI scores at a national level, they are mapped using quantiles. Scores in the top 20% of the United States are more vulnerable counties (red) and scores in the bottom 20% of the United States indicate the least vulnerable counties (blue).

Composite Indicators and Rankings: Inventory 2011 172

143. National Biodiversity Index (NBI)

Developer 1 UNEP Developer 2 CBD Year launched 2001 Latest Edition 2001 Field Environment Number of Main Dimensions N/A Description of Main Dimensions (Weights in Parenthesis) N/A Number of Underlying Indicators N/A Number of units ranked 195 Type of units ranked Countries Link to report N/A Link to data N/A

The NBI is based on estimates of country richness and endemism in four terrestrial vertebrate classes and vascular plants. Vertebrates and plants are ranked equally with index values ranging between 1.000 (maximum) and 0.000 (minimum). The NBI includes some adjustment allowing for country size. Countries with land area less than 5,000 sq km are excluded. Countries are not ranked; just the NBI score is presented.

Composite Indicators and Rankings: Inventory 2011 173

144. Sustainability Rating

Developer 1 Zurich Cantonal Bank (ZKB) Developer 2 Year launched 1999 Latest Edition 2009 Field Environment Number of Main Dimensions 2 Description of Main Dimensions Social (50%) and Environment (50%) (Weights in Parenthesis) Number of Underlying Indicators 100 Number of units ranked 30 Type of units ranked OECD Countries Link to report http://www.zkb.ch/etc/ml/repository/textdokumente/english/corporat e/kurzfassung_nachhaltigkeitsrating_2009_en_pdf.File.pdf Link to data http://www.zkb.ch/etc/ml/repository/textdokumente/english/corporat e/kurzfassung_nachhaltigkeitsrating_2009_en_pdf.File.pdf

The sustainability ratings intend to fill a gap left by traditional credit ratings, which include only minimal information on the environmental situation and on social factors. For many investors, a key factor when deciding to make a sustainable investment is the conviction that in the end sustainable business practices pay off, since risks can be recognized at an early stage and new opportunities can be exploited. Both natural resources and stable political and social conditions are key preconditions for a healthy economy. The evaluation of sustainability is based on 100 largely quantitative, but in part also qualitative, environmental and social aspects. Environmental and social aspects each receive a 50 % weighting in the rating. The sustainability rating is based on a scale of 1 to 10 points and is calculated using the arithmetic mean of the environmental and social ratings. The sub-areas include the following: 1) Environment: energy, water, resources, greenhouse effect, air quality, biodiversity, mobility and environmental policy 2) Social Area: security and stability, human rights, standard of living, health, education and culture, progress, equality, international commitments, In each area, the country with the poorest performance receives 1 point and that with the best performance 10 points.

Composite Indicators and Rankings: Inventory 2011 174 145. Sustainable Society Index (SSI)

Developer 1 Geurt van de Kerk and Arthur Manuel - Nederlandduurzaam Developer 2 Year launched 2006 Latest Edition 2010 Field Wellbeing Number of Main Dimensions 24 Description of Main Dimensions 1. Sufficient Food 2. Sufficient to Drink 3. Safe Sanitation 4. (Weights in Parenthesis) Healthy Life 5. Education Opportunities 6. Gender Equality 7. Good Governance 8. Income Distribution 9.Population Growth 10. Air Quality (humans) 11. Air Quality (nature) 12. Surface Water Quality 13. Consumption of Renew. Energy 14. Emission of Greenhouse Gases 15. Energy Consumption 16. Use of Renewable Water Resources 17. Forest Area 18. Biodiversity 19. Consumption 20. Organic Farming 21. Genuine Savings 22. GDP 23. Employment 24. Public Debt Number of Underlying Indicators 24 Number of units ranked 151 Type of units ranked Countries Link to report http://www.sustainablesocietyindex.com/ Link to data http://www.sustainablesocietyindex.com/maps/

The SSI shows the level of sustainability of each of the 151 assessed countries. The SSI comprises four levels: 24 indicators; 8 categories; 3 wellbeing dimensions;1 Overall index SSI. The first two editions of the SSI, in 2006 and 2008, were based on a framework of 22 indicators. In the process of preparing the 2010 update we have thoroughly evaluated the structure of the SSI. This resulted in a new framework, even more balanced and transparent than the previous one.

In view of the objectives of the SSI – among others to show at a glance the level of sustainability of a country – an aggregation has been made from indicators into categories and from categories into wellbeing dimensions and finally into one single figure for the SSI. We do realise the objections one may have, one of these being a possible trade-off between the indicators. However, since all 24 indicators must receive a score of 10 (on a scale of 0 to 10) to achieve full sustainability, a trade-off will not be sufficient to achieve full sustainability.

Calculation methodology: For lack of a scientific basis for the attribution of different weights to the indicators, every indicator has received the same weight for the aggregation into categories. The same applies for the aggregation into the three wellbeing dimensions. Since there is an inequality among the three dimensions – two comprising three categories and one comprising two categories – the overall index SSI has been calculated directly as the unweighted average of the 24 indicators.

Note that the calculation of world totals is based on the unweighted average of 151 countries. Should one use a calculation based on weighting of population size per country, the results would be different.

Composite Indicators and Rankings: Inventory 2011 175 146. Water Poverty Index (WPI)

Developer 1 Lawrence, Meigh and Sullivan - CEH Wallingford Developer 2 Year launched 2002 Latest Edition 2002 Field Environment Number of Main Dimensions 5 Description of Main Dimensions 1) Resources 2) Access 3) Capacity 4) Use and 5) (Weights in Parenthesis) Environment (equal weights) Number of Underlying Indicators 17 Number of units ranked 147 Type of units ranked Countries Link to report http://129.3.20.41/eps/dev/papers/0211/0211003.pdf Link to data http://129.3.20.41/eps/dev/papers/0211/0211003.pdf

The WPI is a measure, which links household welfare with water availability and indicates the degree to which water scarcity impacts on human populations. Such an index makes it possible to rank countries (and communities within countries) taking into account both physical and socio-economic factors associated with water scarcity. The index is constructed with five major components, each with several subcomponents. The five components are 1) Resources 2) Access 3) Capacity 4) Use and 5) Environment.

The basic calculation is based on the following formula: (xi – xmin) / (xmax – xmin) where xi , xmax and xmin are the original values for country i, the highest value country, and the lowest value country respectively. The indices therefore show a country’s relative position and for any one indicator this lies between 0 and 1. The maximum and minimum values are usually adjusted so as to avoid values of more than 1. Any remaining values above 1 or below zero are fixed at 1 and 0, respectively. Within each of the five components, sub-component indices are averaged to get the component index. Each of the five component indices is multiplied by 20 and then added together to get the final index score for the WPI, which is in the range 0 to 100.

Composite Indicators and Rankings: Inventory 2011 176 Governance

147. Active Citizenship Composite Indicator (ACCI)

Developer 1 European Commission Joint Research Centre (EC -JRC) Developer 2 Centre for Research On Lifelong learning Year launched 2006 Latest Edition 2006 Field Governance Number of Main Dimensions 4 Description of Main Dimensions Participation in 1. Political Life, 2. Civil Society, 3. Community Life (Weights in Parenthesis) and the 4. Values needed for active citizenship (equal weights) Number of Underlying Indicators 63 Number of units ranked 19 Type of units ranked EU countries http://composite- indicators.jrc.ec.europa.eu/Document/EUR%2022530%20EN_Active_

Link to report Citizenship.pdf http://composite- indicators.jrc.ec.europa.eu/Document/EUR%2022530%20EN_Active_

Link to data Citizenship.pdf

The Active Citizenship Composite Indicator (ACCI) covers 19 European countries and is based on a list of 63 basic indicators for which the data has been principally drawn from the European Social Survey of 2002. In order to build the composite indicator of active citizenship in a systematic manner it was necessary to operationalise the definition of the concept. Towards this end we identified measurable and distinctive elements in the definition of active citizenship, which we designated “dimensions of active citizenship.” The dimensions are: participation in Political Life, Civil Society, Community Life and the Values needed for active citizenship (recognition of the importance of human rights, democracy and intercultural understanding). Then each dimension was divided into a number of sub-dimensions. The sub-dimensions and basic indicators are obviously influenced by current data availability. When forthcoming surveys provide wider data coverage for active citizenship then the sub-dimensions and base indicators could be refined and improved. The report summarises the concept of active citizenship into one number that encompasses different dimensions.

The structure of the Active Citizenship Composite Indicator is a weighted sum of the indices computed for the four dimensions Di (Political Life, Civil Society, Community, Values):

w and 0 ≤ ≤ 1 i w for all i=1,..4, and c=1,..,19, where c indicates the number of countries.

Then, each dimension index, Di, is computed as a linear weighted aggregation of the sub-dimension indices SDij. with weights wj*

where Σ = = k j w j 1

Composite Indicators and Rankings: Inventory 2011 177 * 1 and 0 ≤ ≤ 1 j w for all j=1,..ki, and again the country index c=1,..,19. The value of ki varies among the different domains Di, and it corresponds to the number of sub-dimensions encompassed by that domain. So, for instance, for the Civil Society domain (i=1), K1 is equal to 4 and for the Community Life Domain (i=2), k2 is equal to 7.

Finally, each sub-dimension index SDij is a linear weighted sum of the sij normalised sub-indicators hi jc I , with weights #hi , j

Aggregating the different equations into one gives the general formula for the Active Citizenship Composite Indicator:

Having defined the structure, the construction and evaluation of the composite indicator (CI) involve several steps. The first step is the data selection and, if necessary, the imputation of missing data. In the next step the variables must be standardised and the weighting scheme for the indicators specified. Finally, the calculation of the CI and an analysis of its robustness must be performed to improve the transparency of the process.

Due to the fact that the 63 basic indicators have been constructed using different scales, a standardisation process is needed before the data for the different indicators can be aggregated. Different standardisation techniques are available for this (Nardo et al., 2005). The basic standardisation technique that has been applied is the Min-Max approach. Each indicator, q, was standardised based on the following rule:

Using this method, all the indicators have been rescaled and the standardised values lie between 0 (laggard xqc=minc(xq)) and 1 (leader, xqc=minc(xq)). In order to assess the robustness of the composite indicator, the alternative Z-score standardization method has also been used.

After the standardisation process, the data have then been transformed to ensure that for each indicator a higher score would point to a better performance. This step was clearly necessary to make a meaningful aggregation of the different indicators. Based on the Active Citizenship Composite Indicator structure an equal weights scheme was applied within each dimension and within each sub-dimension. The assignment of equal weights to dimensions prevents rewarding dimensions with more indicators (e.g. communities) as compared to dimensions with fewer (e.g. political life). This means that participation in political life, participation in civil society, participation in the community and “values” have the same weights for calculating the Active Citizenship Composite Indicator. In a similar way, all indicators within a sub- dimension were assigned the same weight. For example, the sub-domains of participation in protest activities, human rights, trades union, and environmental organisations would have equal weights when calculating the index for the domain “participation in Civil Society.” Therefore, as a result of the structure in which there are different numbers of indicators for the different sub-dimensions, the basic indicators will not have equal weights in the composite indicator. Following this approach, the basic indicators receiving the highest weights, 0.027, are those of the dimension of political life, while most of the indicators for the dimension of community life only have a weight of 0.009.

Composite Indicators and Rankings: Inventory 2011 178 148. African Governance Indicators

Developer 1 United Nations Economic Commission for Africa Developer 2 Year launched 2005 Latest Edition 2005 Field Governance Number of Main Dimensions 7 Description of Main Dimensions 1. Political representation 2. Institutional effectiveness and (Weights in Parenthesis) accountability 3. Executive's effectiveness 4. Human rights and rule of law 5. Civil society organisations and media independence 6. Economic management 7. Control of corruption - Weighted average but didn't understand - to revisit Number of Underlying Indicators 83 Number of units ranked 28 Type of units ranked African countries Link to report http://www.uneca.org/agr2005/ Link to data Annex to http://www.uneca.org/agr2005/

A research instrument with three components was designed to obtain information on the state of governance in Africa, as reflected by the political, economic and social affairs in each country. The three research components consist of: • An opinion-based study using a national expert panel comprising a group of 70–150 national experts across project countries. • A national sample survey using a stratified two-stage probability sample ranging from some 1,300–3,000 households across Africa • Desk-based research of factual information and hard data to supplement and complement the expert panel perceptions and national household surveys.

The indices are based only on the data from the expert panel study, which contains 83 indicators clustered by ECA subject matter professionals. Some subindices are not mutually exclusive. The overall index is calculated using all 83 indicators for each project country. There is no input from other countries in the overall index of any one country. Each reflects the perceptions of opinion leaders in each country. Each governance index is constructed using average scores which are put together and rescaled to bring each of them to a common range of 0–100 using the following approach:

Let Ti = sum of the mean scores of the indicators in cluster i, i= 0, 1, 2, ...,C, where C is the total number of clusters in the study. Ki = the number of indicators in cluster i, i= 1, 2, ...,C Gi = Index of governance based on cluster i, i= 0, 1, 2, ...,C.

Composite Indicators and Rankings: Inventory 2011 179

The weighted average formula is valid only if the C clusters are strictly mutually exclusive and exhaustive. An index that is close to 100 is perceived to reflect good governance; almost all indices in this African Governance Report relate to 2002. The data from the expert panel study are used to construct 23 subindices of governance for clusters of indicators. Each governance index is constructed using average scores, which are put together and rescaled to bring each of them to a common range of 0–100. An index that is close to 100 reflects good governance as perceived by the respective national opinion leaders of the country concerned. Cross-country comparisons should be avoided since there are serious factors that negate the validity of such comparisons.

Composite Indicators and Rankings: Inventory 2011 180 149. Bribe Payers Index (BPI)

Developer 1 Transparency International Developer 2 Year launched 1999 Latest Edition 2008 Field Governance Number of Main Dimensions 2 Description of Main Dimensions 1. “In your principal lines of business in this country, do you have (Weights in Parenthesis) business relationships (for example as a supplier, client, partner or competitor) with companies whose headquarters are located in these countries listed above.” 2. “How often do firms headquartered in (country name) engage in bribery in this country?” Number of Underlying Indicators 2 Number of units ranked 26 Type of units ranked Countries Link to report http://www.transparency.org/policy_research/surveys_indices/bpi Link to data http://www.transparency.org/news_room/in_focus/2008/bpi_2008

Data for the BPI is drawn from the Bribe Payers Survey. Survey respondents, who are senior business executives, are first asked a filter question: “In your principal lines of business in this country, do you have business relationships (for example as a supplier, client, partner or competitor) with companies whose headquarters are located in these countries listed above.” Respondents are presented a list of 22 countries.

For each country selected, respondents then had to score the country on a 5-point scale system (from 1=never, to 5=almost always), by answering the question: “How often do firms headquartered in (country name) engage in bribery in this country?”

The results of these questions provide an assessment of the views held by senior business executives on the prevalence of bribery exported from many of the world’s strongest economies.

To facilitate the creation of the index, the 5-point scale is then converted into a 10-point scale system. Since the BPI is meant to reflect views on foreign bribery, assessments of a respondent’s own country (12 countries total) have not been included. The countries are then ranked based on the mean scores obtained for each country.

The standard deviation is provided to give an indication of the degree of agreement among respondents in relation to each country: the smaller the standard deviation, the broader the consensus. The confidence intervals at 95 percent confidence are also provided: these show the range of minimum and maximum values where with 95 percent of confidence the true value of the index lies.

Composite Indicators and Rankings: Inventory 2011 181 150. CIFP Governance Index

Developer 1 Carleton University Developer 2 Year launched 2007 Latest Edition 2007 Field Governance Number of Main Dimensions 6 Rule of Law, Human Rights, Government Transparency and Description of Main Dimensions Accountability; Government and Market Efficiency; Democratic (Weights in Parenthesis) Participation; and Political Stability and Violence. Number of Underlying Indicators N/A Number of units ranked 192 Type of units ranked Countries Link to report http://www.carleton.ca/cifp/ Link to data http://www.carleton.ca/cifp/app/gdp_ranking.php

CIFP Governance and Democratic Processes reports are based on three analytical elements, adapted from CIFP’s fragile states methodology. First, structural indicators are grouped into six clusters capturing different facets of democratic processes and governance: rule of law, human rights, government transparency and accountability, government and market efficiency, political stability and violence, and democratic participation. The structural data in this preliminary report constitute a limited set of leading indicators of democracy and governance; later versions of the document will include up to 75 separate structural indicators providing a detailed quantitative baseline portrait of the country. Second, the analysis draws on event monitoring data compiled by CIFP researchers over a six month period extending from November 2006 to May 2007. Collected from a variety of web-based sources, including both international and domestic news sources in English and Spanish, the events are quantitatively evaluated and systematically assessed to identify general trends of relevance to democratic processes and governance. Highly significant events are also qualitatively analyzed to highlight their specific causes and consequences. Third, the report includes a series of analytical exercises, including stakeholder analysis and scenario generation.

Like the CIFP fragility index, the governance index employs a methodology of relative structural assessment. The analysis begins with a structural profile of the country, a composite index that measures overall country performance along six dimensions listed above. Each of these clusters is based on a number of indicators. This multidimensional assessment methodology is a direct response to the multi-dimensional nature of governance and democratic processes. CIFP thus adopts what might be termed an inductive approach, identifying areas of relative strength and weakness across a broad range of measures related to governance and democratic processes.

In ranking state performance on a given indicator, global scores are distributed across a nine-point index. The best performing state receives a score of one, the worst a score of nine, and the rest are continuously distributed between these two extremes based on relative performance. As country performance for some types of data can vary significantly from year to year - as in the case of economic shocks, natural disasters, and other externalities - averages are taken for global rank scores over a five-year time frame. Once all indicators have been indexed using this method, the results for a given country are then averaged in each subject cluster to produce the final scores for the country. In general, a high score - 6.5 or higher - indicates that a country is performing poorly relative to other states. Such a score may be indicative of an arbitrary and autocratic government, a history of non-transparent government, the presence of significant barriers to political participation, the absence of a consistently enforced legal framework, or a poor human rights record. A low score - in the range of 1 to 3.5 - indicates that a country is performing well relative to others, or that a country’s structural conditions present little cause for concern. Values in the moderate 3.5 to 6.5 range indicate performance approaching the global mean.

Composite Indicators and Rankings: Inventory 2011 182 151. Cingranelli-Richards Human Rights Dataset

Developer 1 CIRI Human Rights Data Project Developer 2 Year launched 1981 Latest Edition 2009 Field Governance Number of Main Dimensions 4 Description of Main Dimensions 1. Physical integrity rights 2. Civil liberties 3. Workers’ (Weights in Parenthesis) rights 4. Rights of women Number of Underlying Indicators 20 Number of units ranked 195 Type of units ranked Countries Link to report http://www.humanrightsdata.org Link to data http://ciri.binghamton.edu/myciri/my_ciri_login.asp

The CIRI dataset contains information about government respect for a wide range of human rights. The selection of the particular rights in the CIRI dataset does not imply that these rights are considered to be more important than other human rights. Rather, these are the rights for which we have reliable and systematically available information across time and space. Indeed, we hope to grow CIRI over time to ever-include more human rights as resources allow. CIRI currently includes measures of the practices of governments that allow or impede citizens who wish to exercise their:

 Physical integrity rights--the rights not to be tortured, summarily executed, disappeared, or imprisoned for political beliefs. The scores of these variables can be summed to form a statistically valid cumulative scale  Civil liberties such as free speech, freedom of association and assembly, freedom of movement, freedom of religion, and the right to participate in the selection of government leaders. The scores of some of these variables can be summed to form a statistically valid cumulative scale (Richards, Gelleny, and Sacko, 2001).  Workers’ rights  Rights of women to equal treatment politically, economically, and socially.

Composite Indicators and Rankings: Inventory 2011 183

152. Corruption Perception Index (CPI)

Developer 1 Transparency International Developer 2 Year launched 1995 Latest Edition 2010 Field Governance Number of Main Dimensions 1 Description of Main Dimensions Overall extent of corruption (frequency and/or size of corrupt (Weights in Parenthesis) transactions) in the public and political sectors Number of Underlying Indicators 13 Number of units ranked 200 Type of units ranked Countries Link to report http://www.transparency.org/policy_research/surveys_indices/ cpi Link to data http://www.transparency.org/policy_research/surveys_indices/

cpi/2010/results

The Corruption Perceptions Index (CPI) is an aggregate indicator calculated using data from 13 sources by 10 independent institutions. All sources measure the overall extent of corruption (frequency and/or size of bribes) in the public and political sectors, and all sources provide a ranking of countries, i.e. include an assessment of multiple countries. Evaluation of the extent of corruption in countries/territories is done by two groups: country experts, both residents and non-residents, and business leaders.

Steps to calculate the CPI: 1. The first step to calculate the CPI is to standardise the data provided by the individual sources (that is, translate them into a common scale). We use what is called a matching percentiles technique that takes the ranks of countries reported by each individual source. This method is useful for combining sources that have different distributions. While there is some information loss in this technique, it allows all reported scores to remain within the bounds of the CPI, i.e. to remain between 0 and 10. 2. The second step consists of performing what is called a beta-transformation on the standardized scores. This increases the standard deviation among all countries included in the CPI and makes it possible to differentiate more precisely countries that appear to have similar scores. 3. Finally, the CPI scores are determined by averaging all of the standardised values for each country.

The CPI score and rank are accompanied by the number of sources, the highest and lowest values given to every country by the data sources, the standard deviation and the confidence range for each country. The confidence range is determined by what is called a bootstrap (non-parametric) methodology, which allows inferences to be drawn on the underlying precision of the results. A 90 percent confidence range is then established, where there is only a five percent probability that the value is below and a five per cent probability that the value is above this confidence range.

Composite Indicators and Rankings: Inventory 2011 184 153. Countries at the Crossroads

Developer 1 Freedom House Developer 2 Year launched 2004 Latest Edition 2010 Field Governance Number of Main Dimensions 4 Description of Main Dimensions 1. Accountability and Public Voice, 2. Civil Liberties, 3. Rule (Weights in Parenthesis) of Law, and 4. Anticorruption and Transparency. Number of Underlying Indicators 75 methodology questions Number of units ranked 70 Type of units ranked Countries

Link to report http://freedomhouse.org/template.cfm?page=139&edition=9 Link to data http://freedomhouse.org/template.cfm?page=139&edition=9

Countries at the Crossroads is an annual analysis of government performance in 70 strategically important countries worldwide that are at a critical crossroads in determining their political future. The in-depth comparative analyses and quantitative ratings—examining government accountability, civil liberties, rule of law, and anticorruption and transparency efforts—are intended to help international policymakers identify areas of progress, as well as to highlight areas of concern that could be addressed in diplomatic efforts and reform assistance. In cooperation with a team of methodology experts, Freedom House designed a methodology that includes a questionnaire used both to prepare analytical narratives and for numerical ratings for each government. The final result is a system of comparative ratings accompanied by narratives that reflect governments’ commitment to passing good laws and also their records on upholding them. Freedom House enlisted the participation of prominent scholars and analysts to author the publication’s country reports. Each country narrative report is approximately 7,000 words long. Expert regional advisers reviewed the draft reports, providing written comments and requests for revisions, additions, or clarifications. Authors were asked to respond as fully as possible to all of the questions posed when composing the analytical narratives.

Authors produced a first round of ratings by assigning scores on a scale of 0-7 for each of the 75 methodology questions, where 0 represents weakest performance and 7 represents strongest performance. The scores were then aggregated into seventeen subcategories and four main thematic areas. The regional advisers and Freedom House staff systematically reviewed all country ratings on a comparative basis to ensure accuracy and fairness. All final ratings decisions rest with Freedom House.

In devising a framework for evaluating government performance, Freedom House sought to develop a scale broad enough to capture degrees of variation so that comparisons could be made between countries in the current year, and also so that future time series comparisons might be made to assess a country’s progress in these areas relative to past performance. Narrative essays and scoring were applied to the following main areas of performance, which Freedom House considers to be key to evaluating the state of democratic governance within a country:

ACCOUNTABILITY AND PUBLIC VOICE: •Free and fair electoral laws and elections •Effective and accountable government •Civic engagement and civic monitoring •Media independence and freedom of expression CIVIL LIBERTIES: •Protection from state terror, unjustified imprisonment, and torture •Gender equity •Rights of ethnic, religious, and other distinct groups •Freedom of conscience and belief •Freedom of association and assembly RULE OF LAW: •Independent judiciary •Primacy of rule of law in civil and criminal matters •Accountability of security forces and military to civilian authorities •Protection of property rights

Composite Indicators and Rankings: Inventory 2011 185 ANTICORRUPTION AND TRANSPARENCY: •Environment to protect against corruption •Procedures and systems to enforce anticorruption laws •Enforcement of anticorruption norms, standards, and protections •Governmental transparency

Scoring Range: The analysis rates countries’ performance on each methodology question on a scale of 0-7, with 0 representing the weakest performance and 7 the strongest. The scoring scale is as follows:

Score of 0–2: Countries that receive a score of 0, 1, or 2 ensure no or very few adequate protections, legal standards, or rights in the rated category. Laws protecting the rights of citizens or the justice of the political process are minimal, rarely enforced, or routinely abused by the authorities. Score of 3–4: Countries that receive a score of 3 or 4 provide some adequate protections, legal standards, or rights in the rated category. Legal protections are weak and enforcement of the law is inconsistent or corrupt. Score of 5: Countries that receive a score of 5 provide many adequate protections, legal standards or rights in the rated category. Rights and political standards are protected, but enforcement may be unreliable and some abuses may occur. A score of 5 is considered to be the basic standard of democratic performance. Score of 6–7: Countries that receive a score of 6 or 7 ensure all or nearly all adequate protections, legal standards, or rights in the rated category. Legal protections are strong and are enforced fairly. Citizens have access to legal redress when their rights are violated, and the political system functions smoothly.

Composite Indicators and Rankings: Inventory 2011 186 154. Country Performance Assessments (CPA)

Developer 1 Asian Development Bank Developer 2 Year launched 2001 Latest Edition 2009 Field Governance Number of Main Dimensions 5 Description of Main Dimensions Economic Management, Structural policies, Policies for social (Weights in Parenthesis) inclusion, governance, portfolio performance Number of Underlying Indicators 12 Number of units ranked 26 Type of units ranked Countries Link to report http://www.adb.org/ADF/PBA/fact-sheet.asp Link to data http://www.adb.org/ADF/PBA/annualreport.asp

The CPA is part of ADB's Performance-Based Allocation (PBA) policy guides allocation of the Asian Development Fund (ADF) resources to the eligible developing member countries (DMCs) with access to ADF. The ADF is the concessional lending window of the Asian Development Bank available to member countries that are among the poorest and least developed nations of the Asia Pacific. Under the PBA policy, allocation of ADF resources to a country is determined on the basis of performance as assessed through the country performance assessment (CPA) exercise and country needs (population and per capita income). The ADB’s Country Performance Assessments assesses the quality of a country’s policy and institutional framework. It gauges the extent to which the policy and institutional framework supports sustainable growth, poverty reduction, and the effective use of development assistance. The CPA criteria focus on policies and institutional arrangements, which are the key elements that are within the government’s control, rather than on outcomes that can be influenced by elements beyond the government’s control. Each country’s performance is assessed on seventeen indicators based on:

• Coherence of its macroeconomic and structural policies • Degree to which its policies and institutions promote equity and inclusion • Quality of its governance and public sector management • Portfolio quality

ADB carries out its annual CPAs using the World Bank’s country policy and institutional assessments (CPIA) questionnaire. While ADB employs the CPIA questionnaire in its assessment of country performance, the two institutions’ ratings may differ for the following reasons: the use of different cut-off dates for the information which feeds into assessments, the application of different methodologies in aggregating the scores, and the fact that the CPIA questionnaire allows for differences in professional judgment.

Composite Indicators and Rankings: Inventory 2011 187 155. Country Policy and Institutional Assessment (CPIA) and Country Performance Rating (CPR)

Developer 1 World Bank Developer 2 Year launched 1977 Latest Edition 2009 Field Governance Number of Main Dimensions 3 Description of Main Dimensions CPR = 0.24* (CPIA Clusters A,B,C average) + 0.68* (CPIA Cluster (Weights in Parenthesis) D) + 0.08* (Portfolio Rating). IDA country allocation = f (Country performance rating 5.0, Population1.0, GNI/capita-0.125) Number of Underlying Indicators Number of units ranked 79 Type of units ranked Countries Link to report http://web.worldbank.org/WBSITE/EXTERNAL/EXTABOUTUS/I DA/0,,contentMDK:20948754~menuPK:116699~pagePK:83988~pi PK:84004~theSitePK:73154~isCURL:Y,00.html Link to data http://web.worldbank.org/WBSITE/EXTERNAL/EXTABOUTUS/I DA/0,,contentMDK:20948754~menuPK:116699~pagePK:83988~pi PK:84004~theSitePK:73154~isCURL:Y,00.html

The Country Performance Ratings of IDA countries are assessed annually using the Country Policy and Institutional Assessment (CPIA) ratings. The CPIA assesses each country’s policy and institutional framework and consists of 16 criteria grouped into four equally weighted clusters: (i) economic management; (ii) structural policies; (iii) policies for social inclusion and equity; and (iv) public sector management and institutions. To ensure that the ratings are consistent with performance within and across regions: (i) detailed questions and definitions are provided to country teams for each of the six rating levels for each of the 16 criteria; and (ii) a World Bank-wide process of rating and vetting a dozen “benchmark” countries is carried out to anchor the ratings in all IDA regions. This is followed by a process of institutional review of all country ratings before they are finalized.

The CPIA underpins IDA’s Country Performance Rating but is not its only determinant. Two additional steps are needed. First, to capture the quality of management of IDA’s projects and programs, the World Bank’s Annual Report on Portfolio Performance (ARPP) is used to determine a rating for each country’s implementation performance. During the IDA15 replenishment discussions, three changes in the calculation of portfolio performance ratings were approved by the Deputies to reduce unwarranted volatility. Therefore, starting FY08, the ARPP scores were based on the percentage of actual IDA problem projects instead of actual plus potential problem projects. In addition, a quarterly average of actual problem projects was used instead of an end-year snapshot. Finally a revised conversion scale was used to convert the percent of actual problem projects into a rating. Second, a governance rating was calculated using cluster D of the CPIA. Starting in FY08, the procurement factor was dropped from the calculation of the governance rating because this is obtained from the potential problem projects, which were dropped in the modification of portfolio performance ratings described in the first step.

Starting in IDA15, the calculation of the IDA Country Performance Rating will be simplified to make the weights of the components explicit.

Country Performance Rating = (0.24 * CPIA A-C + 0.68 * CPIA D + 0.08 * Portfolio) IDA country allocation = f (Country performance rating 5.0, Population 1.0, GNI/capita-0.125)

The exponent on Country Performance Ratings went up from 2 to 5 to maintain the same dispersion of ratings and therefore of allocations as before.

Composite Indicators and Rankings: Inventory 2011 188 156. Democracy Score (Nations in Transit Ratings)

Developer 1 Freedom House Developer 2 Year launched 2004 Latest Edition 2010 Field Governance Number of Main Dimensions 7 Description of Main 1. National Democratic Governance 2. Electoral Process. 3. Civil Dimensions (Weights in Society 4. Independent media 5. Local democratic Governance 6. Parenthesis) Judicial Framework and Independence 7. Corruption Number of Underlying 60 Indicators Number of units ranked 29 Type of units ranked Countries Link to report http://www.freedomhouse.hu/index.php?option=com_content&view=a rticle&id=321:nations-in-transit-2010&catid=46:nations-in- transit&Itemid=121 Link to data http://www.freedomhouse.hu/images/nit2010/NIT-2010-Tables1.pdf

Nations in Transit measures progress and setbacks in democratization in 29 countries and administrative areas from Central Europe to the Eurasian region of the Former Soviet Union. The country reports in Nations in Transit follow an essay format that allowed the report authors to provide a broad analysis of the progress of democratic change in their country of expertise. Freedom House provided them with guidelines for ratings and a checklist of questions covering seven categories: electoral process; civil society; independent media; national democratic governance; local democratic governance; judicial framework and independence; and corruption. Starting with the 2005 edition Freedom House introduced separate analysis and ratings for national democratic governance and local democratic governance to provide readers with more detailed and nuanced analysis of these two important subjects. Previous editions included only one governance category. The ratings are based on a scale of 1 to 7, with 1 representing the highest and 7 the lowest level of democratic progress. The ratings follow a quarter-point scale. Minor to moderate developments typically warrant a positive or negative change of a quarter (0.25) to a half (0.50) point. Significant developments typically warrant a positive or negative change of three-quarters (0.75) to a full (1.00) point. It is rare that the rating in any category will fluctuate by more than a full point (1.00) in a single year. As with Freedom in the World, Freedom House’s global annual survey of political rights and civil liberties, Nations in Transit does not rate governments per se. Nor does it rate countries based on governmental intentions or legislation alone. Rather, a country’s ratings are determined by considering the practical effect of the state and nongovernmental actors on an individual’s rights and freedoms. The Nations in Transit ratings, which should not be taken as absolute indicators of the situation in a given country, are valuable for making general assessments of how democratic or authoritarian a country is. They also allow for comparative analysis of reforms among the countries surveyed and for analysis of long-term developments in a particular country.

The ratings process involved four steps: 1. Authors of individual country reports suggested preliminary ratings in all seven categories covered by the study. 2. The U.S. and Central Europe & Eurasia academic advisers evaluated the ratings and made revisions. 3. Report authors were given the opportunity to dispute any revised rating that differed from the original by more than 0.50 point. 4. Freedom House refereed any disputed ratings and, if the evidence warranted, considered further adjustments. Final editorial authority for the ratings rested with Freedom House.

Composite Indicators and Rankings: Inventory 2011 189 157. E-Government Development Index

Developer 1 United Nations (UN) Developer 2 Year launched 2003 Latest Edition 2010 Field Governance Number of Main Dimensions 3 1. Scope and quality of online services (0.34), 2. Description of Main Dimensions Telecommunication connectivity (0.33), and 3. human capacity (Weights in Parenthesis) (0.33) Number of Underlying Indicators N/A Number of units ranked 192 Type of units ranked Countries Link to report http://www2.unpan.org/egovkb/global_reports/10report.htm http://unpan1.un.org/intradoc/groups/public/documents/un- Link to data dpadm/unpan038858.pdf

The United Nations e-government development index (EGDI) is a comprehensive scoring of the willingness and capacity of national administrations to use online and mobile technology in the execution of government functions. It is based on a comprehensive survey of the online presence of all 192 Member States. The results are tabulated and combined with a set of indicators embodying a country’s capacity to participate in the information society, without which e-government development efforts are of limited immediate utility.

The e-government development index is not designed to capture e-government development in an absolute sense. Rather, the index rates the performance of national governments relative to one another. The maximum possible value is one and the minimum is zero. Though the basic model has remained constant, the precise meaning of these values varies from one survey to the next as understanding of the potential of e government. Mathematically, the EDGI is a weighted average of three normalized scores on the most important dimensions of egovernment, namely: scope and quality of online services, telecommunication connectivity, and human capacity. Each of these sets of indexes is itself a composite measure that can be extracted and analysed independently:

EGDI = (0.34 × online service index) + (0.33 × telecommunication index) (0.33 × human capital index)

Composite Indicators and Rankings: Inventory 2011 190 158. E-Government Index

Developer 1 Brookings Developer 2 Year launched 2001 Latest Edition 2008 Field Governance Number of Main Dimensions 6 Description of Main Dimensions 1. Online Services 2. Publications Databases 3. Privacy Policy 4. (Weights in Parenthesis) Security Policy 5. W3C Disability 6. Accessibility Number of Underlying Indicators N/A Number of units ranked 198 Type of units ranked Countries Link to report http://www.brookings.edu/reports/2008/0817_egovernment_west.as px Link to data http://www.brookings.edu/~/media/Files/rc/reports/2008/0817_egov ernment_west/0817_egovernment_west.pdf

This report reviews the current condition of electronic government and makes practical suggestions for improving the delivery of information and services over the Internet. Using a detailed analysis of 1,667 national government websites in 198 nations around the world undertaken in Summer 2008, this report studies the types of features available online, the variation that exists across countries, and how current e- government trends compare to previous years, as far as 2001.

To evaluate the state of digital government, this study examines 18 different features. Four points are awarded to each website for the presence of the following features: publications, databases, audio clips, video clips, foreign language access, not having ads, not having premium fees, not having user fees, disability access, having privacy policies, security policies, allowing digital signatures on transactions, an option to pay via credit cards, email contact information, areas to post comments, option for email updates, option for website personalization and PDA accessibility. These features provide a maximum of 72 points for particular websites.

Each site then qualifies for up to 28 points based on the number of online services executable on that site (one point for one service, two points for two services, three points for three services and on up to 28 points for 28 or more services). The overall e-government index runs along a scale from zero (having none of these features and no online services) to 100 (having all features plus at least 28 online services). Totals for each website within a country were averaged across all of that nation's websites to produce a zero to 100 overall rating for that nation.

Composite Indicators and Rankings: Inventory 2011 191 159. EIU Political Instability Index

Developer 1 Economist Intelligence Unit (EIU) Developer 2 Year launched 2007 Latest Edition 2010 Field Governance Number of Main Dimensions 2 Description of Main Dimensions 1. Index of underlying vulnerability and 2. an economic (Weights in Parenthesis) distress index (simple average of both) Number of Underlying Indicators 15 Number of units ranked 165 Type of units ranked Countries Link to report http://viewswire.eiu.com/site_info.asp?info_name=social _unrest_table&page=noads&rf=0 Link to data http://viewswire.eiu.com/site_info.asp?info_name=social _unrest_table&page=noads&rf=0

The Political Instability Index shows the level of threat posed to governments by social protest. The index scores are derived by combining measures of economic distress and underlying vulnerability to unrest. The final PITF model that had the greatest predictive power is a simple model that is based on only four factors: the level of development as measured by the infant mortality rate; extreme cases of economic or political discrimination against minorities (according to assessments and codings by the Minorities at Risk Project); "a bad neighbourhood" (if a country has at least four neighbours that suffered violent conflicts); and regime type (intermediate regimes that are neither consolidated democracies nor autocratic regimes combined with the existence in these regimes of intense factionalism in domestic politics, as coded by the Polity Project on democracy). Although over 80% of outbreaks of instability could be predicted (a very high "hit rate"), the model cannot predict the intensity or duration of the instability, or its exact timing. We also look and measure other factors associated with instability that have been identified in the literature, such as inequality, a prior history of instability, ethnic fragmentation, poor governance, a proclivity to labour unrest, the level of provision of public services and state strength.

We define social and political unrest or upheaval as those events or developments that pose a serious extra- parliamentary or extra-institutional threat to governments or the existing political order. The events will almost invariably be accompanied by some violence as well as public disorder. These need not necessarily be successful in the sense that they end up toppling a government or regime. Even unsuccessful episodes result in turmoil and serious disruption. The assessment of what constitutes a "serious threat" still requires judgment and can be arbitrary, but this is a step forward from having no definition at all.

The overall index on a scale of 0 (no vulnerability) to 10 (highest vulnerability) has two component indexes—an index of underlying vulnerability and an economic distress index. The overall index is a simple average of the two component indexes. There are 15 indicators in all—12 for the underlying vulnerability and 3 for the economic distress index.

I. Underlying vulnerability: 1. Inequality 2. State history 3. Corruption 4. Ethnic fragmentation 5. Trust in institutions 6. Status of minorities 7. History of political instability 8. Proclivity to labour unrest 9. Level of social provision 10. A country's neighbourhood 11. Regime type 12. Regime type and factionalism

II. Economic distress: 1. Growth in incomes 2. Unemployment 3. Level of income per head In the compilation of the economic distress sub-index, growth in GDP per head and unemployment have weights of 40% each, and GDP per head has a weight of 20%.

Composite Indicators and Rankings: Inventory 2011 192 160. Failed States Index

Developer 1 Foreign Policy Developer 2 Fund for Peace Year launched 2005 Latest Edition 2010 Field Governance Number of Main Dimensions 3 Description of Main Dimensions (Weights in Parenthesis) 1. Social 2. Economic 3. Political Number of Underlying Indicators 12 Number of units ranked 177 Type of units ranked Countries Link to report N/A http://www.fundforpeace.org/web/index.php?option=com_co Link to data ntent&task=view&id=99&Itemid=140

The index assesses violent internal conflicts and measures the impact of mitigating strategies. In addition to rating indicators of state failure that drive conflict, it offers techniques for assessing the capacities of core state institutions and analyzing trends in state instability. The Fund for Peace methodology triangulates data from three primary sources and subjects them to critical review to obtain final scores for the Failed States Index. The main data collection methods are content analysis (electronic scanning), quantitative data, and qualitative input. First, we download millions of documents, including a variety of digitized news articles, essays, magazine pieces, speeches, and government and non-government reports (we do not use blogs, twitter, or other social media.) Then, we apply our content analysis software to scan the documents using Boolean phrases on indicators within our CAST framework. The data used in each index are collected from the preceding year and stored on our servers so that we can go back to them when needed. Our search landscape has expanded from 90,000 to 115,000 online English-language publications worldwide, giving us a wide variety of data sources upon which to base our findings. Filters built into the software extract irrelevant or erroneous documents so the search can zero in on the specific subject matter defined in the Boolean phrases, and correct for false positives, pack journalism, and media drift. Second, we incorporate quantitative data from reputable institutions and other reliable sources. Third, the results are compared with insights from a separate qualitative review of each indicator for each country. Taken together, the three methods serve as internal checks. Aggregated data are normalized and scaled from 0-10 to obtain final scores for 12 social, economic and political/military indicators for 177 countries. These results are then critically reviewed by analysts different from those who conducted the original research.

This multi-stage process has several layers of scrutiny to ensure the highest standards of methodological rigor, the broadest possible information base including both quantitative and qualitative expertise, and the greatest accuracy. The rank order of the states is based on the total scores of the 12 indicators. For each indicator, the ratings are placed on a scale of 0 to 10, with 0 being the lowest intensity (most stable) and 10 being the highest intensity (least stable). The total score is the sum of the 12 indicators and is on a scale of 0-120. Countries in the Index are divided into three equal parts for easy reference: Critical (red), In Danger (orange), and Borderline (yellow). On the index's global map, additional countries that ranked higher than 60 are colored yellow. Countries with scores between 30 and 59.9 are considered Stable (dark grey). Countries that have scores lower than 30 are categorized as Most Stable (light grey). This coloring scheme differs slightly from the original FfP methodology, which it still employs in its reports, such as the Iraq Reports and Country Profiles. FfP's original methodology breaks the countries into four colored zones based on their aggregate scores. A country in the "Alert" zone has an aggregate score between 90 and 120. A country that is colored orange, the "Warning" zone, scores between 60 and 89.9. A country colored yellow, the "Monitoring" zone, has an aggregate score between 30 and 59.9. A country colored green, the "Sustainable" zone, has an aggregate score of 29.9 or less.

Composite Indicators and Rankings: Inventory 2011 193 161. Freedom of the Net Index

Developer 1 Freedom House Developer 2 Year launched 2010 Latest Edition 2010 Field Governance Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 15 Type of units ranked Countries Link to report http://www.freedomhouse.org/uploads/specialreports/NetFree dom2009/FreedomOnTheNet_FullReport.pdf Link to data http://www.freedomhouse.org/uploads/specialreports/NetFree dom2009/FreedomOnTheNet_FullReport.pdf

Freedom on the Net aims to measure each country’s level of internet and new media freedom on the basis of two key components – access to the relevant technology and the free flow of information through it without fear of repercussions. Our assessments reflect not just government actions and policies, but also the impact that actions by non-state actors or foreign governments may have on the user experience within the geographical boundaries of a country. It also reflects the behavior of users themselves in testing boundaries, even in more restrictive environments. Each country receives a numerical score from 0 (the most free) to 100 (the least free), which serves as the basis for an internet freedom status designation of Free (0-30 points), Partly Free (31-60 points), or Not Free (61-100). The methodology aims to capture the wide variety of possible factors that could affect levels of internet freedom, as well as providing a way to assess the particular dynamics within each country, both in terms of changing methods of restriction as well as changes over time.

Composite Indicators and Rankings: Inventory 2011 194 162. Freedom of the Press Index

Developer 1 Freedom House Developer 2 Year launched 1980 Latest Edition 2010 Field Governance Number of Main Dimensions 3 Description of Main Dimensions 1. The legal environment (30pts), 2. The political environment (Weights in Parenthesis) (40pts), and 3. The economic environment (30pts) Number of Underlying Indicators 109 Number of units ranked 196 Type of units ranked Countries Link to report http://www.freedomhouse.org/template.cfm?page=16 Link to data http://www.freedomhouse.org/template.cfm?page=16

The index provides analytical reports and numerical ratings for 196 countries and territories, continues a process conducted since 1980 by Freedom House. The findings are widely used by governments, international organizations, academics, and the news media in many countries. Countries are given a total score from 0 (best) to 100 (worst) on the basis of a set of 23 methodology questions divided into three subcategories. Assigning numerical points allows for comparative analysis among the countries surveyed and facilitates an examination of trends over time. The degree to which each country permits the free flow of news and information determines the classification of its media as “Free,” “Partly Free,” or “Not Free.” Countries scoring 0 to 30 are regarded as having “Free” media; 31 to 60, “Partly Free” media; and 61 to 100, “Not Free” media. The criteria for such judgments and the arithmetic scheme for displaying the judgments are described in the following section. The ratings and reports included in Freedom of the Press 2010 cover events that took place between January 1, 2009, and December 31, 2009.

Our examination of the level of press freedom in each country currently comprises 23 methodology questions and 109 indicators divided into three broad categories: the legal environment, the political environment, and the economic environment. For each methodology question, a lower number of points is allotted for a more free situation, while a higher number of points is allotted for a less free environment. Each country is rated in these three categories, with the higher numbers indicating less freedom. A country’s final score is based on the total of the three categories: A score of 0 to 30 places the country in the Free press group; 31 to 60 in the Partly Free press group; and 61 to 100 in the Not Free press group.

Composite Indicators and Rankings: Inventory 2011 195 163. Global Corruption Barometer

Developer 1 Transparency International Developer 2 Year launched 2010 Latest Edition 2010 Field Governance Number of Main Dimensions 8 Description of Main Dimensions 8 corruption questions (Weights in Parenthesis) Number of Underlying Indicators 8 Number of units ranked 86 Type of units ranked Countries Link to report http://www.transparency.org/policy_research/surveys_indice s/gcb/2010 Link to data http://www.transparency.org/policy_research/surveys_indice s/gcb/2010/results

It is the only worldwide public opinion survey on views and experiences of corruption. As a poll of the general public, it provides an indicator of how corruption is viewed at national level and how efforts to curb corruption around the world are assessed on the ground. It also provides a measure of people’s experience of corruption in the past year. The 2010 Barometer, the seventh edition, reflects the responses of 91,781 people in 86 countries, and offers the greatest country coverage to date.

The Barometer asks general questions about people’s perceptions of corruption and experiences with bribery. It asks which institutions people trust to curb corruption and whether they believe their government’s efforts to fight corruption are working. For the first time, the 2010 Barometer asks the general public about their personal willingness to engage in the fight against corruption. Questions change year to year, with some cycling in and out, allowing for comparisons of results over time.

Timing of fieldwork: Fieldwork for the survey was conducted between 1 June 2010 and 30 September 2010. The demographic variables captured in the questionnaire are: age, education, household income, employment and religion. For comparability purposes these variables were recoded from their original form. In each country the sample is probabilistic and was designed to represent the general adult population. General coverage of the sample is as follows: 83 per cent national and 17 per cent urban only. The interviews were conducted either face-to-face, using self-administered questionnaires, by telephone, internet or computer-assisted telephone interviewing (CATI) (mostly in developed countries), with both male and female respondents aged 16 years and above.

Weighting: The data were weighted in two steps to obtain representative samples by country and worldwide. The data were first weighted to generate data representative of the general population for each country. A second weight, according to the size of the population surveyed, was then applied to obtain global and regional totals.

Data entry and consistency checks: The final questionnaire, which was reviewed and approved by Transparency International, was marked with columns, codes, and with indications of single or multi- punching. Local survey agencies followed this layout when entering data and sent an ASCII data file to the Gallup International Association’s Coordination Center following these specifications. The data was processed centrally by analysing different aspects such as whether all codes entered were valid and if filters were respected and bases consistent. If any inconsistency was found, this was pointed out to the local agency so they could evaluate the issue and send back the revised and amended data. Data for all countries was finally consolidated and weighted as specified above. All data analysis and validation was done using SPSS software.

Composite Indicators and Rankings: Inventory 2011 196 164. Global Integrity Index

Developer 1 Center for Public Integrity Developer 2 Year launched 2004 Latest Edition 2009 Field Governance Number of Main Dimensions 6 Description of Main Dimensions 1- Civil Society, Public Information and Media 2 - Elections (Weights in Parenthesis) 3- 3 Government Accountability 4 - Administration and Civil Service 5- Oversight and Regulation and 6-Anti-Corruption and Rule of Law. Number of Underlying Indicators 300 Number of units ranked 38 Type of units ranked Countries Link to report http://report.globalintegrity.org/globalIndex.cfm Link to data http://report.globalintegrity.org/globalindex/results.cfm

The Integrity Scorecard for each country examines three concepts: 1. The existence of public integrity mechanisms, including laws and institutions, which promote public accountability and limit corruption. 2. The effectiveness of those mechanisms. 3. The access that citizens have to those mechanisms.

More specifically, indicators of existence assess the laws, regulations, and agencies/entities or equivalently functioning mechanisms that are in place in a particular country. Indicators of effectiveness assess such aspects of public integrity as protection from political interference; appointments that support the independence of an agency; professional, full-time staff and funding; independently initiated investigations; and imposition of penalties. Indicators of citizen access assess the ready availability of public reports to citizens, or publicly available information, within a reasonable time period and at a reasonable cost.

The Integrity Indicators are a unique instrument designed to provide a quantitative assessment of anticorruption safeguards in a particular country at the national level. Carefully selected from a comprehensive review of the anti-corruption literature and other democratic governance sources, including Transparency International's National Integrity Systems framework, the Integrity Indicators are used to "score" the institutional framework that exists at the national level to promote public integrity and accountability and prevent abuses of power. For 2009, the Integrity Indicators were organized into six main categories and 23 sub-categories.

Each Integrity Indicator is scored directly by the lead researcher and substantiated as far as possible with relevant references and additional comments. The data is relayed from the field to HQ via the internet using MAGIC. There are two types of indicators: "in law" and "in practice." All indicators, regardless of type, are scored on the same ordinal scale of 0 to 100 with zero being the worst possible score and 100 perfect.

"In law" indicators provide an objective assessment of whether certain legal codes, fundamental rights, government institutions, and regulations exist. These "de jure" indicators are scored with a simple "yes" or "no" with "yes" receiving a 100 score and "no" receiving a zero.

"In practice" indicators address "de facto" issues such as implementation, effectiveness enforcement, and citizen access. As these usually require a more nuanced assessment, these "in practice" indicators are scored along an ordinal scale of zero to 100 with possible scores at 0, 25, 50, 75 and 100.

Composite Indicators and Rankings: Inventory 2011 197 Lead researchers are required to provide a reference to substantiate each of their scores. This may be an interview conducted with a knowledgeable individual, a website link to a relevant report, or the name of a specific law or institution, depending on the particular indicator. Lead researchers are also offered the opportunity to include additional comments to support their score and reference for a particular indicator. These are particularly useful in capturing the nuances of a particular situation, namely the "Yes, but…" phenomenon which is often the reality in undertaking this type of research.

Personality, language, and culture can all affect the interpretation of a particular indicator and the score assigned to it. To minimize this effect and maximize inter-coder reliability, Global Integrity provides researchers and peer reviewers with scoring criteria for every single Integrity Indicator. The scoring criteria anchor each indicator and sub-indicator to a predefined set of criteria. In essence, the scoring criteria guide the lead researcher by suggesting, "If you see X on the ground, score this indicator in the following way." For binary yes/no "in law" indicators, scoring criteria are provided for both "yes (100)" and "no (0)" responses. For "in practice" indicators, scoring criteria are defined for each of the 100, 50, and 0 scores with 25 and 75 deliberately left undefined to serve as in between scoring options. Scoring criteria for each indicator can be accessed via any of our online Integrity Scorecards by "hovering" one's mouse over a given indicator's scoring scale.

In summary, a given indicator or sub-indicator has the following elements:  Indicator question, provided by Global Integrity  Indicator scoring criteria, provided by Global Integrity  Indicator score (either yes (100)/no (0) or ordinal scale of 0 - 100 with steps at 25, 50, and 75), assigned by the lead researcher based on: - References, provided by the lead researcher - Comments (optional), provided by the lead researcher - Peer review comments (optional), as provided through a double blind peer review process

Composite Indicators and Rankings: Inventory 2011 198

165. Global Peace Index (GPI)

Developer 1 Institute for Economics and Peace Developer 2 Economist Intelligence Unit (EIU) Year launched 2007 Latest Edition 2010 Field Governance Number of Main Dimensions 3 Description of Main Dimensions 1. Internal Peace (60%) 2. External Peace (40%) (Weights in Parenthesis) Number of Underlying Indicators 23 Number of units ranked 149 Type of units ranked Countries Link to report http://www.visionofhumanity.org/wp- content/uploads/PDF/2010/2010%20GPI%20Results%20Report.pdf Link to data http://www.visionofhumanity.org/gpi-data/#/2010/scor

It ranks nations according to their relative peacefulness. It is composed of 24 indicators, ranging from a nation’s level of military expenditure to its relations with neighbouring countries and the level of respect for human rights. The index has been tested against a range of potential “drivers” or determinants of peace—including levels of democracy and transparency, education and material wellbeing. The 24 indicators of the existence or absence of peace are divided into three key thematic categories. Many of the indicators have been “banded” on a scale of 1-5 and any gaps in the quantitative data have been filled by estimates from the Economist Intelligence Unit’s Country Analysis team. Some indicators have been scored on a qualitative basis exclusively by our extensive team of country analysts and network of in-field researchers. Indicators of quantitative data such as military expenditure or jailed population have been normalised on the basis of: x = (x- Min(x)) / (Max (x)—Min (x))

Where Min (x) and Max (x) are respectively the lowest and highest values in the 121 countries for any given indicator. The normalised value is then transformed from a 0-1 value to a 1-5 score to make it comparable with the other indicators. Twenty-three indicators of the existence or absence of peace were chosen by the panel (see page 9), which are divided into three broad categories: 1. Ongoing domestic and international conflict 2. Safety and security in society 3. Militarisation

All scores for each indicator are “banded”, either on a scale of 1-5 (for qualitative indicators) or 1-10 (for quantitative data, such as military expenditure or the jailed population, which have then been converted to a 1-5 scale for comparability when compiling the final index). Qualitative indicators in the index have been scored by the Economist Intelligence Unit’s extensive team of country analysts, and gaps in the quantitative data have been filled by estimates by the same team. Indicators consisting of quantitative data such as military expenditure or jailed population have been measured on the basis of the distribution of values across all countries between the maximum and minimum values (we assume that the 149 countries measured for the Global Peace Index (GPI) are a representative sample of all countries).

Two sub-component weighted indices were then calculated from the GPI group of indicators: 1) a measure of how at peace internally a country is; 2) a measure of how at peace externally a country is (its state of peace beyond its borders). The overall composite score and index was then formulated by applying a weight of 60% to the measure of internal peace and 40% for external peace. The heavier weight applied to internal peace was agreed within the advisory panel, following robust debate. The decision was based on the innovative notion that a greater level of internal peace is likely to lead to, or at least correlate with, lower external conflict.

Composite Indicators and Rankings: Inventory 2011 199 166. Global Political Risk Index (GPRI)

Developer 1 Eurasia Group Developer 2 Year launched 2001 Latest Edition 2010 Field Governance Number of Main Dimensions 4 Description of Main Dimensions Four equally weighted subcategories: government, society, (Weights in Parenthesis) security, and economy. Number of Underlying Indicators 20 Number of units ranked 24 Type of units ranked Countries Link to report http://blogs.reuters.com/andrew- marshall/files/2010/08/GPRI.pdf Link to data N/A

The GPRI is an index of country stability ratings for 24 emerging market countries. Its unique methodology measures a country’s ability to absorb political shocks. The GPRI evaluates political, social, economic, and security factors, using a combination of quantitative and qualitative data that is collected on the ground and through open source methods. Ratings are expressed on a scale of 0 to 100. Clear and concise analysis ac- companies the index to illustrate what events impacted each country’s stability rating and make forecasts for the coming month. Each country’s score is based on 20 indicators in four equally weighted subcategories: government, society, security, and economy.

Composite Indicators and Rankings: Inventory 2011 200 167. Governance Indicators

Developer 1 World Bank Institute (Kaufmann, Kraay and Mastruzzi) Developer 2 Year launched 1996 Latest Edition 2009 Field Governance Number of Main Dimensions 6 Description of Main Dimensions 1. Voice and Accountability 2. Political Stability and absence (Weights in Parenthesis) of Violence 3. Government Effectiveness 4. Regulatory Quality 5. Rule of Law 6. Control of Corruption Number of Underlying Indicators 30 Number of units ranked 213 Type of units ranked Countries Link to report N/A Link to data http://info.worldbank.org/governance/wgi/index.asp

The Worldwide Governance Indicators (WGI) project reports aggregate and individual governance indicators for 213 economies over the period 1996–2009, for six dimensions of governance: 1. Voice and Accountability 2. Political Stability and absence of Violence 3. Government Effectiveness 4. Regulatory Quality 5. Rule of Law 6. Control of Corruption.

The aggregate indicators combine the views of a large number of enterprise, citizen and expert survey respondents in industrial and developing countries. The individual data sources underlying the aggregate indicators are drawn from a diverse variety of survey institutes, think tanks, non-governmental organizations, and international organizations.

In the WGI we draw together data on perceptions of governance from a wide variety of sources, and organize them into six clusters corresponding to the six broad dimensions of governance listed above. For each of these clusters we then use a statistical methodology known as an Unobserved Components Model to (i) standardize the data from these very diverse sources into comparable units, (ii) construct an aggregate indicator of governance as a weighted average of the underlying source variables, and (iii) construct margins of error that reflect the unavoidable imprecision in measuring governance.

Composite Indicators and Rankings: Inventory 2011 201 168. Human Rights Commitment Index

Developer 1 Danish Institute for Human Rights (Sano and Lindhotl) Developer 2 Year launched 2000 Latest Edition 2000 Field Governance Number of Main Dimensions 4 Description of Main Dimensions 1. Formal commitment to international and regional human (Weights in Parenthesis) rights standards by governments 2. civil and political human rights violations by governments 3. commitment to fulfillment of economic, social and cultural rights 4. commitment to gender equality by Governments Number of Underlying Indicators N/A Number of units ranked 42 Type of units ranked Countries Link to report http://menneskeret.dk/files/pdf/Engelsk/Research/indicator-

full.pdf Link to data http://menneskeret.dk/files/pdf/Engelsk/Research/indicator-

full.pdf

The Human Rights Commitment Indicators include indicators of conduct. They focus attention on government formal and actual behaviour in relation to human rights. The focus is on four dimensions of Human Rights Commitment. Four sets of indicators were chosen:

Formal Commitment measures acceptance of human rights instruments including regional human rights conventions and incorporation of human rights in national constitutions. The formal commitment indicator has four components: Ratification of fundamental international and regional human rights instruments, ratification of other UN human rights conventions, reservations to international or regional conventions, and national Bills of Rights.

Commitment to civil and political rights measures whether governments violate eight human rights standards, which can all, be found in the key international and regional conventions. These are: 1. Extra- judicial killings /disappearances, 2. Torture and ill-treatment, 3. Detention without trial, 4. Unfair trial, 5. Participation in the political process, 6. Freedom of association, 7. Freedom of expression, and 8. Discrimination except gender discrimination which is measured separately.

Commitment to Economic, Social and Cultural Rights measures the degree to which governments fulfill their obligations on economic, social rights and cultural rights. Two components have been included as regards this indicator, i.e., the proportion of government expenditure spent on health and education as a percentage of the gross domestic production, and the gross national income in combination with achievements of progress in the human development indicators health and education.

Commitment to eradication of gender discrimination measures degrees of gender discrimination and not whether it occurs or not. It should be noted that gender discrimination prevails in any country examined. The two components included in this index intend to flag the issue rather than define it precisely. This indicator measures government employment of women at all levels together with achievements of progress in the UNDP defined Gender Development Indicators.

Composite Indicators and Rankings: Inventory 2011 202 169. Human Rights Risk Atlas

Developer 1 Maplecroft Developer 2 Year launched 2006 Latest Edition 2011 Field Governance Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators 30 Number of units ranked 196 Type of units ranked Countries Link to report http://www.maplecroft.com/portfolio/human_rights/atlas/ Link to data N/A

The Human Rights Risk Atlas 2011 includes interactive maps and indices for 30 human rights categories and scorecards for 196 countries. It also features sub-national mapping of human rights violations and human security incidents down to site-specific levels worldwide. It is supported by sector specific country human rights risk reports

Composite Indicators and Rankings: Inventory 2011 203 170. Ibrahim Index of African Governance

Developer 1 Mo Ibrahim Foundation Developer 2 Year launched 2007 Latest Edition 2010 Field Governance Number of Main Dimensions 4 Description of Main Dimensions 1. Safety and Rule of Law; 2. Participation and Human Rights; 3. (Weights in Parenthesis) Sustainable Economic Opportunity; and 4. Human Development as proxies for the quality of the processes and outcomes of governance – (Equal weights) Number of Underlying Indicators 89 Number of units ranked 48 Type of units ranked African countries Link to report http://www.moibrahimfoundation.org/en/section/the-ibrahim-index Link to data http://www.moibrahimfoundation.org/en/section/the-ibrahim-index

The Ibrahim Index explicitly ranks sub-Saharan African countries according to governance quality. It provides both a new definition of governance, as well as a comprehensive set of governance measures. Based on five categories of essential political goods, each country is assessed against 58 individual measures (SSC), capturing clear, objective outcomes. 1- Safety and Security 2- Rule of Law, Transparency and Corruption 3- Participation and Human Rights 4- Sustainable Economic Development 5- Human Development. In calculating this composite score, raw data is normalized, putting it on a common scale so that the many different measures included in the Index could be compared and combined to calculate a single overall score. The raw data are re-scaled such that the minimum value across all years of the Index (2000, 2002, and 2005) receives a score of “0” and the maximum value across all years of the Index a score of “100.” For each SSC in each country in each year, the score is calculated as follows:

t where x c is the raw value for that SSC for country c in year t and X describes all raw values across all countries for that SSC across all years 2000, 2002, and 2005. For the final overall rankings each category was weighted equally in developing a country score. Countries are ranked from highest score (better governance) to lowest score.

Composite Indicators and Rankings: Inventory 2011 204 171. Index of Democracy

Developer 1 Economist Intelligence Unit (EIU) Developer 2 Year launched 2007 Latest Edition 2010 Field Governance Number of Main Dimensions 5 Description of Main Dimensions 1. Electoral process and pluralism; 2. Civil liberties; 3. Functioning (Weights in Parenthesis) of government; 4. Political participation; and 5. Political culture. Number of Underlying Indicators 60 Number of units ranked 165 Type of units ranked Countries Link to report http://graphics.eiu.com/PDF/Democracy_Index_2010_web.pdf Link to data Page 4-6 of http://graphics.eiu.com/PDF/Democracy_Index_2010_web.pdf

The index provides a snapshot of the state of democracy worldwide for 165 independent states and two territories—this covers almost the entire population of the world and the vast majority of the world’s independent states (micro states are excluded). The Economist Intelligence Unit’s index of democracy, on a 0 to 10 scale, is based on the ratings for 60 indicators grouped in five categories: electoral process and pluralism; civil liberties; the functioning of government; political participation; and political culture. Each category has a rating on a 0 to 10 scale, and the overall index of democracy is the simple average of the five category indexes. The category indexes are based on the sum of the indicator scores in the category, converted to a 0 to 10 scale. The index values are used to place countries within one of four types of regimes: 1. Full democracies--scores of 8-10 2. Flawed democracies--score of 6 to 7.9 3. Hybrid regimes--scores of 4 to 5.9 4 Authoritarian regimes--scores below 4

The scoring system: We use a combination of a dichotomous and a three-point scoring system for the 60 indicators. A dichotomous 1-0 scoring system (1 for a yes and 0 for a no answer) is not without problems, but it has several distinct advantages over more refined scoring scales (such as the often-used 1-5 or 1-7). For many indicators, the possibility of a 0.5 score is introduced, to capture ‘grey areas’ where a simple yes (1) of no (0) is problematic, with guidelines as to when that should be used. Thus for many indicators there is a three-point scoring system, which represents a compromise between simple dichotomous scoring and the use of finer scales. The problems of 1-5 or 1-7 scoring scales are numerous. For most indicators under such a system, it is extremely difficult to define meaningful and comparable criteria or guidelines for each score. This can lead to arbitrary, spurious and non-comparable scorings. For example, a score of 2 for one country may be scored a 3 in another and so on. Or one expert might score an indicator for a particular country in a different way to another expert. This contravenes a basic principle of measurement, that of so- called reliability—the degree to which a measurement procedure produces the same measurements every time, regardless of who is performing it. Two and three-point systems do not guarantee reliability, but make it more likely. Second, comparability between indicator scores and aggregation into a multi-dimensional index appears more valid with a two or three-point scale for each indicator (the dimensions being aggregated are similar across indicators). By contrast, with a 1-5 system, the scores are more likely to mean different things across the indicators (for example a 2 for one indicator may be more comparable to a 3 or 4 for another indicator, rather than a 2 for that indicator). The problems of a 1-5 or 1-7 system are magnified when attempting to extend the index to many regions and countries.

Composite Indicators and Rankings: Inventory 2011 205 172. Index of State Weakness in the Developing World

Developer 1 Brookings Institution Developer 2 Year launched 2008 Latest Edition 2008 Field Governance Number of Main Dimensions 4 Description of Main Dimensions 1. Economic, 2. Political, 3. Security, and 4. Social welfare (EQUAL (Weights in Parenthesis) weights) Number of Underlying Indicators 20 Number of units ranked 141 Type of units ranked Countries Link to report http://www.brookings.edu/reports/2008/02_weak_states_index.aspx Link to data http://www.brookings.edu/~/media/Files/rc/reports/2008/02_weak_st ates_index/02_weak_states_index_world_map.pdf

The Index ranks developing countries according to their relative performance in four critical spheres: economic, political, security, and social welfare. Weak states are defined as countries that lack the essential capacity and/or will to fulfill four sets of critical government responsibilities: fostering an environment conducive to sustainable and equitable economic growth; establishing and maintaining legitimate, transparent, and accountable political institutions; securing their populations from violent conflict and controlling their territory; and meeting the basic human needs of their population.

The Index relies on four “baskets,” each of which contains five indicators. Each of the four baskets consists of indicators that are proxies for one core aspect of state function: 1. Indicators in the economic basket assess a state’s ability to provide its citizens with a stable economic environment that facilitates sustainable and equitable growth. They take into account recent economic growth, the quality of existing economic policies, whether the environment is conducive to private sector development, and the degree to which income is equitably distributed. 2. Political indicators assess the quality of a state’s political institutions and the extent to which its citizens accept as legitimate their system of governance. They seek to measure government accountability to citizens, the rule of law, the extent of corruption, the extent of democratization, freedom of expression and association, and the ability of the state bureaucracy and institutions to function effectively, independently, and responsively. 3. Security indicators evaluate whether a state is able to provide physical security for its citizens. They measure the occurrence and intensity of violent conflict or its residual effects (e.g., population displacement), illegal seizure of political power, widespread perceptions of political instability, territory affected by conflict, and state-sponsored political violence and gross human rights abuses. 4. Indicators in the social welfare basket measure how well a state meets the basic human needs of its citizens, including nutrition, health, education, and access to clean water and sanitation.

Taken together, the 20 indicators yield a balanced picture of how developing countries perform or fail to perform along multiple dimensions. Within each basket, the indicator scores are standardized and aggregated, creating individual indicator and basket scores ranging from 0.0 (worst) to 10.0 (best). The 4 basket scores are then averaged to obtain an overall score for state weakness, ranging from just above 0 to just short of a perfect 10, to produce a ranking of states on the basis of their relative weakness. We term countries in the bottom quintile “critically weak states” and deem the 3 weakest states in the world “failed states.” Failed states perform markedly worse than all others—even those in their critically weak cohort. Failed and critically weak states are those least capable of fulfilling most, if not all, of the four critical functions of government. We term the second quintile “weak states.” In addition, we note that a number of countries that perform better overall than those in the bottom two quintiles are nonetheless “states to watch,” because they score notably poorly in at least one of the four core areas of state function.

Composite Indicators and Rankings: Inventory 2011 206 173. International Property Rights Index (IPRI)

Developer 1 Property Rights Alliance Developer 2 Year launched 2007 Latest Edition 2010 Field Governance Number of Main Dimensions 3 Description of Main Dimensions 1. Legal and Political Environment (LP), 2. Physical Property (Weights in Parenthesis) Rights (PPR), and 3. Intellectual Property Rights (IPR) Number of Underlying Indicators 11 Number of units ranked 125 Type of units ranked Countries Link to report http://www.internationalpropertyrightsindex.org/ Link to data http://www.internationalpropertyrightsindex.org/userfiles/Result s.pdf

The International Property Rights Index (IPRI) is an international comparative study that measures the significance of both physical and intellectual property rights and their protection for economic well-being. The 2010 IPRI is comprised of a total of 10 variables, which are divided into the three main components: Legal and Political Environment (LP), Physical Property Rights (PPR), and Intellectual Property Rights (IPR). Despite a large number of property rights related variables considered by the authors, the final IPRI study focuses only on core factors that directly relate to the strength and protection of property rights. The final ranking is very similar to the alternative rankings calculated with other factors included. Finally, preference was given to the variables that were available for a greater number of countries and were updated on a regular basis to ensure that the resulting scores were comparable across countries and years. Of the 10 variables incorporated into the index, the Registering Property variable is made up of two sub- variables. In sum, the IPRI comprises 11 data points for each country.

The overall grading scale of the IPRI ranges from 0 to 10, with 10 representing the strongest level of property rights protection and 0 reflecting the non-existence of secure property rights in a country. Similarly, each component and variable is placed on the same 0 to 10 scale. For the calculation of the final index score, the variables within each component are averaged to derive the score for each of the three components. The final overall IPRI score is itself the average of the component scores. During construction of the index, a number of weighting methods for the components were tried. These were based on the authors’ subjective views as well as to account for the different variances within each variable. However, the choice of the weighting method had little impact on the final rating and ranking of the countries. Thus, for reasons of simplicity and objectivity, the final numbers presented in this report are the result of a simple average calculation. The 10 variables included in the IPRI stem from different sources. Most of them can be easily normalized to the IPRI’s 0-10 scale. To combine variables that did not come in an indexed form, we applied the following standardization formula:

Xi represents the individual country’s value of the factor involved, while Xmax and Xmin were set at the maximum value for that factor within the original sample of countries in 2007 and zero, respectively. This method was used to standardize the Registering Property variables in the PPR component. Previously, the maximum value for each of the factors was allowed to change with changes in the sample of countries. This year, it was anchored to the benchmark value in the sample of countries in the 2007 IPRI report. This change allows for a more objective comparison of countries from year to year. Previous years’ data were rescaled, and scores were recalculated to account for this change. It is important to note that the recalculation of previous years’ scores for PPR as well as IPRI had a very minor effect on rankings for those years.

Composite Indicators and Rankings: Inventory 2011 207 174. Latin American Index of Budget Transparency

Developer 1 DFID - Peru Developer 2 International Budget Project Year launched 2001 Latest Edition 2003 Field Governance Number of Main Dimensions 3 Description of Main Dimensions 1. Process 2. Stages 3. Transparency (no weights provided) (Weights in Parenthesis) Number of Underlying Indicators 49 Number of units ranked 10 Type of units ranked Latin American Countries Link to report http://www.internationalbudget.org/themes/BudTrans/LA03.htm Link to data See report: http://www.internationalbudget.org/themes/BudTrans/English.pdf

In general transparency implies that the reasons for all governmental and administrative decisions, as well as the costs and resources committed in the application of these decisions, are accessible, clear, and communicated to the general public. Transparency in public spending is particularly relevant given the central character of the budget of any government. The true objectives, commitments, and priorities of those in control of the government are tangibly expressed in the budget. Applied budget analysis therefore allows evaluation of who truly wins and loses with the distribution of public resources. In addition, this type of analysis reveals the degree of efficiency and effectiveness of public spending, by revealing potential cases of corruption.

The index is based on a questionnaire containing 70 questions measuring budget transparency. The questionnaire is distributed to the following budget experts: 1. Legislators (Representatives and/or Senators) participating in the budget commission 2. Communications media: Journalists who write about the budget in newspapers and magazines with national coverage were chosen. 3. Academics or researchers that are experts on the subject 4. Civil society organizations (CSOs) working on issues related to the budget, accountability, transparency, corruption, and public resource monitoring were chosen. The questionnaire contained 70 questions grouped into three categories: 1. Scores of budget transparency at different levels: an assessment of budget transparency conditions in general and assessments of the specific processes or topics of budget formulation, approval, execution, oversight, citizen participation, and access to information. 2. Assessments of the importance of each of the budget stages or related topics (formulation, approval, execution, oversight, citizen participation, and access to information 3. Specific questions on the level of transparency in the budget. These questions are built as Likert scales in a range of 1 to 5, to simultaneously measure agreement and its degree.

The results are reported with two units or scales. The score of general transparency conditions and scores by stage or process are the averages obtained in the experts survey using a scale of 1 to 100. The Budget Transparency General Index is given by a score of this type. On the other hand, the percentage is reported of positive or “agreement” responses for specific variables and questions. This percentage is the sum of the “agree” and “totally agree” responses (values 4 and 5) among the total of valid responses, in the following scale: 1 Do not agree 2- 3 Neither agree 4 -5 Totally at all nor disagree agree.

A total of 14 variables were built from 49 specific questions as follows: Citizen participation in the budget 5, Authority and participation of the legislature in the budget 3, Information on macroeconomic criteria of the budget 2, Changes in the budget 1, Budget allocation 4, Budget oversight 5, Evaluation of the internal comptroller 1, Capacities of the institutions of external oversight 3, Accountability7 , Control over federal officials 5, Responsibilities among governmental levels 1, Information on federal debt 4, Quality of information and statistics in general 4, Timeliness of budget information 4.

Composite Indicators and Rankings: Inventory 2011 208 175. Media Sustainability Index

Developer 1 International Research and Exchanges Board (IREX) Developer 2 Year launched 2000 Latest Edition 2010 Field Other Number of Main Dimensions 5 Description of Main Dimensions 1. Legal and social norms 2. Standards of quality 3. News sources (Weights in Parenthesis) 4. Independence 5. Supporting institutions (no weights) Number of Underlying Indicators 38 Number of units ranked 80 Type of units ranked Countries Link to report http://www.irex.org/project/media-sustainability-index-msi Link to data http://www.irex.org/project/media-sustainability-index-msi

The Media Sustainability Index provides in-depth analysis of the conditions for independent media in 20 countries across Europe and Eurasia. The MSI is designed to assist policymakers and implementers in these and other fields by analyzing the various elements of a media system and pointing to areas where assistance can be most effective in developing a sustainable and professional media system. The MSI assesses five objectives in shaping a successful media system: 1. Legal and social norms protect and promote free speech and access to public information. 2. Journalism meets professional standards of quality. 3. Multiple news sources provide citizens with reliable and objective news. 4. Independent media are well-managed businesses, allowing editorial independence. 5. Supporting institutions function in the professional interest of independent media.

The scoring is done in two parts. First, a panel of experts is assembled in each country, drawn from representatives of local media, NGOs, professional associations, international donors, and media- development implementers. The panelists meet to discuss the objectives and indicators and to devise combined scores and analyses. In the second stage of the scoring process the panelists’ scores are reviewed by IREX in country staff and Washington DC, media staff, which then score the countries independently of the MSI panel. Using the combination of scores, the final scores are determined. This method allowed the MSI scores to reflect both local media insiders’ views and the views of international media- development professionals. A score was attained for each objective by rating seven to nine indicators, which determine how well a country meets that objective. Each indicator is scored on a 0-4 scale with 4 being the best. The averages of all the indicators are then averaged to obtain a single, overall score for each objective. Then, objective scores are averaged to provide an overall score for each country. Interpretation of final scores:

Unsustainable, Anti-Free Press (0-1): Country does not meet or only minimally meets objectives. Government and laws actively hinder free media development, professionalism is low, and media-industry activity is minimal. Unsustainable Mixed System (1-2): Country minimally meets objectives, with segments of the legal system and government opposed to a free media system. Evident progress in free-press advocacy, increased professionalism, and new media businesses may be too recent to judge sustainability. Near Sustainability (2-3): Country has progressed in meeting multiple objectives, with legal norms, professionalism, and the business environment supportive of independent media. Advances have survived changes in government and have been codified in law and practice. However, more time may be needed to ensure that change is enduring and that increased professionalism and the media business environment are sustainable. Sustainable (3-4): Country has media that are considered generally professional, free, and sustainable, or to be approaching these objectives. Systems supporting independent media have survived multiple governments, economic fluctuations, and changes in public opinion or social conventions.

Composite Indicators and Rankings: Inventory 2011 209 176. Millennium Challenge Corporation Country Scorecards

Developer 1 US Government - MCC Developer 2 Year launched 2003 Latest Edition 2011 Field Governance Number of Main Dimensions 3 Description of Main Dimensions Ruling justly, investing in people, economic freedom (no (Weights in Parenthesis) weights provided) Number of Underlying Indicators 17 Number of units ranked 95 Type of units ranked Countries Link to report http://www.mcc.gov/pages/selection Link to data http://www.mcc.gov/pages/selection/scorecards

To select countries as eligible for Millennium Challenge Account (“MCA”) compact funding, the Millennium Challenge Corporation (“MCC”) assesses the degree to which the political, social, and economic conditions in a country promote broad-based sustainable economic growth. In making its determinations, MCC’s Board of Directors considers three factors: performance on the defined policy criteria, the opportunity to reduce poverty and generate economic growth in the country, and the funds available to MCC. To assess policy performance, MCC uses third-party indicators to identify countries with policy environments that will allow MCA funding to be effective in reducing poverty and promoting economic growth. MCC evaluates performance in three areas— Ruling Justly, Investing in People, and Encouraging Economic Freedom. The Selection Process has four major steps:

Candidate countries for the fiscal year are identified based on their per capita income and whether they are legally eligible to receive U.S. economic assistance. MCC submits a report to Congress with a list of candidate countries prior to the selection of countries eligible for MCA assistance. For Fiscal Year 2011 (FY11), a “candidate country” must meet one of the following income criteria and cannot be statutorily ineligible to receive U.S. economic assistance under the Foreign Assistance Act or any other provision of law. •• Low Income Category: countries with a per capita income less than or equal to $1,905; or •• Lower Middle Income Category: countries with a per capita income between $1,906 and $3,945.

When evaluating countries for eligibility, the Board considers whether countries perform above the median score of their income peer group (either the low income country group or the lower middle income country group) on at least half of the indicators in each of the three policy categories, as well as above the median on the Control of Corruption indicator. The Board may also take into consideration if a country performs substantially below the median on any indicator (i.e. the bottom 25th percentile) and has not taken appropriate measures to address the shortcoming.

To evaluate policy performance, MCC uses, to the maximum extent possible, objective and quantifiable policy indicators in three broad policy categories: Ruling Justly, Investing in People, and Encouraging Economic Freedom. MCC favors policy indicators developed by independent third party institutions that rely on objective, publicly available data and have an analytically rigorous methodology. MCC seeks indicators that have broad country coverage, cross-country comparability, and broad consistency in results from year to year. MCC also seeks indicators that are linked to economic growth, poverty reduction, and government policies.

Composite Indicators and Rankings: Inventory 2011 210 177. Opacity Index (O-Factor)

Developer 1 Milken Institute Developer 2 Year launched 2001 Latest Edition 2009 Field Governance Number of Main Dimensions 5 1. Corruption, 2. Legal system inadequacies, 3. Economic Description of Main Dimensions Enforcement policies, 4. Accounting standards and corporate (Weights in Parenthesis) governance, and 5. Regulation - no weights provided Number of Underlying Indicators 65 Number of units ranked 48 Type of units ranked Countries Link to report http://kurtzmangroup.com/pdf/InstituteOpacityIndex_Apr8.pdf Link to data http://kurtzmangroup.com/pdf/InstituteOpacityIndex_Apr8.pdf

The index aims to measure “opacity”, defined as the lack of clear, accurate, formal, easily discernible, and widely accepted practices in the world's capital markets. A composite "O-Factor" score for each country is based on opacity data in five different areas that affect capital markets: a) corruption, b) legal system, c) government macroeconomic and fiscal policies, d) accounting standards and practices (including corporate governance and information release), and e) regulatory regime. The index draws upon 65 objective variables from 41 sources. The countries are ranked from lowest score (more transparent conditions) to higher score (more opaque conditions).

Composite Indicators and Rankings: Inventory 2011 211 178. Open Budget Index (OBI)

Developer 1 Center on Budget and Policy Priorities - International Budget Project Developer 2 Year launched 2006 Latest Edition 2010 Field Governance Number of Main Dimensions 8 Description of Main Dimensions 1. Pre-Budget Statement 2. Executive’s Budget Proposal 3. (Weights in Parenthesis) Enacted Budget 4. In-Year Reports 5. Mid-Year Review 6. Year-End Report 7. Audit Report 8.Citizens Budget Number of Underlying Indicators 92 Number of units ranked 94 Type of units ranked Countries Link to report http://www.internationalbudget.org/what-we-do/open-budget- survey/ Link to data http://www.internationalbudget.org/files/2010_Full_Report-

English.pdf

The OBI rates countries on how open their budget books are to their citizens. It is intended to provide citizens, legislators, and civil society advocates with the comprehensive and practical information needed to gauge a government’s commitment to budget transparency and accountability. It is based on the Open Budget Questionnaire, which consists of 122 multiple-choice questions, and four tables covering the manner in which budget documents are disseminated. The questionnaire groups questions into three sections: 1) tables to elicit information on the dissemination of budget information 2) the executive’s annual budget proposal to the legislature and the availability of other information that would contribute to analysis of budget policies and practices 3) the four phases of the budget process. The questions evaluate publicly available information issued by the central government, and do not cover the availability of information at the sub-national level. The majority of the questions ask about what occurs in practice, rather than about the requirements that may be in law. The Open Budget Index consists of the average of the responses to those questions. Most of the questions require the researcher to choose among five responses. Letter “a” or “b” is considered as describing a situation or condition that represents good practice regarding the subject matter of the question. The responses “c” or “d” correspond to practices that are considered poor. The fifth response is “e,” or not applicable. Researchers were also asked to provide a citation as well as enrich their questionnaire responses with comments, as appropriate. For the purposes of aggregating the responses, the numeric score of 100 percent was awarded for an “a” response, 67 percent for a “b” response, 33 percent for a “c” response, and 0 for a “d” response. The response of “e” caused the question not to be counted as part of the aggregated category. Some questions have three possible responses: “a,” “b,” or “c” (not applicable). For these questions, a score of 100 percent was awarded for the “a” response, and 0 for the “b” response. The “c” response caused the question not to be included in the aggregated category. For purposes of describing the performance of a country on the index, a country with a score of 81 to 100 percent indicates that the government “provides extensive information to citizens,” country scores of 61 to 80 percent indicate that the government “provides significant information to citizens,” country scores of 41 to 60 percent indicate that the government “provides some information to citizens,” and country scores of 21 to 40 percent indicate that the government “provides minimal information to citizens.” Finally, country scores below 20 percent indicate that the government “provides scant, or no information to citizens.” Each of the questions used is assigned the same weight when calculating the OBI score for a country. The number of questions for each of the eight documents assessed, however, is different. As a result of this scoring system, some budget documents carry a greater weight than others. For example, many questions used to construct the OBI are related to the Executive’s Budget Proposal, so if a country does not publish this document it receives a zero score on all those questions and its OBI score is likely to be very low. For each of the remaining documents, there are between one and 10 questions.

Composite Indicators and Rankings: Inventory 2011 212 179. Peace and Conflict Instability Ledger

Developer 1 Center for International Development and Conflict Management Developer 2 Year launched 2008 Latest Edition 2010 Field Governance Number of Main Dimensions 5 Description of Main Dimensions 1. Regime consistency 2. Economic openness 3. Infant mortality (Weights in Parenthesis) rates 4. Militarization 5. Neighborhood security (no weights) Number of Underlying Indicators 5 Number of units ranked 186 Type of units ranked Countries Link to report http://www.cidcm.umd.edu/pc/ Link to data http://www.cidcm.umd.edu/pc/

It is a ranking of countries in terms of their risk of future state instability. The risk estimate for each country was obtained using a statistical model based on several variables known to be strongly related to the onset of instability events (or armed civil conflict). These include the incoherence of the governing regime, high infant mortality rates, lack of integration with the global economy, the militarization of society, and the presence of armed conflict in neighboring states. For each country, the ledger presents a single score that captures the overall risk of future instability. In addition, the ledger gives information about the level of statistical confidence corresponding to the risk estimate. The analysis draws from four domains, identifying five factors that are closely related to the onset of political instability. 1- From the political domain, the ledger accounts for the impact of institutional consistency. Regimes lacking institutional consistency— possessing a mix of both democratic and autocratic features—are more likely to experience instability. 2- The ledger accounts for the impact of the economic domain by accounting for economic openness, which is the extent to which a country’s economy is integrated with the global economy. Countries that are more tightly connected to global markets have been found to experience less instability. 3- For the social domain, the ledger examines the impact of infant mortality rates, an indicator that serves as a proxy for a country’s overall economic development and the level of advancement in social welfare policy. 4- To account for the security domain, the ledger focuses on a country’s level of militarization and neighborhood security. Instability is most likely in countries with higher levels of militarization. Also, the likelihood of instability increases substantially when a neighboring state is currently experiencing armed conflict. For each country, the ledger presents an array of information about the risks of future instability. The score for each country’s likelihood of future instability is presented as a risk ratio. The risk ratio gives the relative risk of instability in a country compared to the average estimated likelihood of instability for 28 member countries of the Organization for Economic Cooperation and Development (OECD). For example, Guatemala’s score of 7.3 should be interpreted as meaning that the risk of instability in that country is more than seven times greater than the average country in the OECD. Countries with scores in the top 25th percentile are categorized as high risk (denoted with a red circle in the ledger). Countries with scores falling below the global median are denoted as low risk (denoted with a green circle). The remaining countries are classified as moderate risk (denoted with a gold circle). Finally, the ledger reports a confidence range for every country’s estimate. Statistically speaking, the “true” risk of instability lies within this range with a 95 percent probability.

Composite Indicators and Rankings: Inventory 2011 213 180. Political and Economic Risk Map

Developer 1 AON Developer 2 Oxford Analytica Year launched 2006 Latest Edition 2010 Field Governance Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 200 Type of units ranked Countries Link to report http://www.oxan.com/About/Media/News/AONRiskMap2010.aspx Link to data http://www.oxan.com/About/Media/News/AONRiskMap2010.aspx

It rates the economic and political risks in more than 200 territories worldwide, and includes a table of key supply chain disruption events and threats, and a list of 2006’s most significant global stress points. Political, economic and social environments can shift at a moment’s notice, disrupting business operations for anyone involved in international commerce. Companies can be subjected to discriminatory action – or inaction – of foreign governments and third parties, potentially leading to forced shutdowns, relocations and other unforeseen expenses. It classifies countries into low risk, medium-low risk, medium risk, medium-high risk and high risk.

Composite Indicators and Rankings: Inventory 2011 214 181. Political Rights and Civil Liberties Ratings

Developer 1 Freedom House Developer 2 Year launched 1972 Latest Edition 2011 Field Governance Number of Main Dimensions 2 Description of Main Dimensions 1. Political rights (40%) 2. Civil liberties (60%) (Weights in Parenthesis) Number of Underlying Indicators 25 Number of units ranked 193 Type of units ranked Countries Link to report http://www.freedomhouse.org/template.cfm?page=15 Link to data http://www.freedomhouse.org/template.cfm?page=15

The ratings are determined by a checklist of 25 questions, 10 addressing political rights and 15 addressing civil liberties. Each country or territory is awarded a raw score for each of the questions on a 0 to 4 scale, where 0 points represents the smallest degree and 4 points the greatest degree of rights or liberties present.

The 10 political rights questions (a total of 40 points) are grouped into three sub-categories:  Electoral Process: 3 questions (a total of 12 points)  Political Pluralism and Participation: 4 questions (16 points)  Functioning of Government: 3 questions (12 points) The 15 civil liberties questions (60 points) are grouped into four sub-categories:  Freedom of Expression and Belief: 4 questions (16 points)  Associational and Organizational Rights: 3 questions (12 points)  Rule of Law: 4 questions (16 points)  Personal Autonomy and Individual Rights: 4 questions (16 points)

Freedom House measures freedom according to two broad categories: political rights and civil liberties. Political rights enable people to participate freely in the political process, including through the right to vote, compete for public office, and elect representatives who have a decisive impact on public policies and are accountable to the electorate. Civil liberties allow for the freedoms of expression and belief, associational and organizational rights, rule of law, and personal autonomy without interference from the state. Each country and territory is assigned a numerical rating on a scale of 1 to 7. A rating of 1 indicates the highest degree of freedom and 7 the least amount of freedom. The ratings process is based on a checklist of 10 political rights questions (grouped into three subcategories) and 15 civil liberties questions (grouped into four subcategories) done by a group of experts and academics. Raw points are awarded to each of these questions on a scale of 0 to 4, where 0 points represents the smallest degree and 4 points the greatest degree of rights or liberties present. The highest number of points that can be awarded to the political rights checklist is 40 (or a total of up to 4 points for each of the 10 questions). The highest number of points that can be awarded to the civil liberties checklist is 60 (or a total of up to 4 points for each of the 15 questions). The total number of points awarded to the political rights and civil liberties checklists determines the political rights and civil liberties ratings. Each pair of political rights and civil liberties ratings is averaged to determine an overall status of “Free,” “Partly Free,” or “Not Free.” Those whose ratings average 1.0-2.5 are considered Free; ratings of 3.0-5.0 are considered Partly Free and 5.5-7.0 are Not Free

Composite Indicators and Rankings: Inventory 2011 215 182. Political Risk Atlas

Developer 1 Maplecroft Developer 2 Year launched 2010 Latest Edition 2011 Field Governance Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators 41 Number of units ranked 196 Type of units ranked Countries Link to report http://www.maplecroft.com/portfolio/political_risk/atlas/ Link to data N/A

The Atlas offers 41 indices and maps, as well as scorecards for each country, sub-national mapping of terrorism and conflict, plus two years of trends.

Composite Indicators and Rankings: Inventory 2011 216 183. Political Terror Scale

Developer 1 Mark Gibney and Matthew Dalton, Purdue University Developer 2 Year launched 1980 Latest Edition 2009 Field Governance Number of Main Dimensions 2 Description of Main Dimensions Political violence from Amnesty International and State (Weights in Parenthesis) Department - no weights provided Number of Underlying Indicators N/A Number of units ranked 187 Type of units ranked Countries Link to report http://politicalterrorscale.org/ Link to data http://politicalterrorscale.org/download.php

The Political Terror Scale is a widely used data set measuring the levels of political violence in various countries. Countries are ranked on a scale of 1-5 according to their level of terror the previous year. A country’s level of terror is based on the descriptions of these countries provided in the Amnesty International and U.S. State Department Country Reports. The levels are as follow:

Level 1: Countries under a secure rule of law, people are not imprisoned for their views, and torture is rare or exceptional. Political murders are extraordinarily rare. Level 2: There is a limited amount of imprisonment for nonviolent political activity. However, few are affected; torture and beatings are exceptional. Political murder is rare. Level 3: There is extensive political imprisonment, or a recent history of such imprisonment. Execution or other political murders and brutality may be common. Unlimited detention, with or without trial, for political views is accepted. Level 4: The practices of the Level 3 are expanded to larger numbers. Murders, disappearances, and torture are a common part of life. In spite of it generality, on this level violence affects primarily those who interest themselves in politics or ideas. Level 5: The violence of Level 4 has been extended to the whole population. The leaders of these societies place no limits or means or thoroughness with which they pursue personal or ideological goals.

Two people are responsible for coding each country. In the case of a disagreement a third party steps in, therefore, employing a rule of majority vote. Coders are asked to provide a score and a few comments rationalizing their decision. Inter-coder reliability between the two original coders is in the range of 70-90 percent. Usually, however, a more informal means of dispute resolution is employed. Oftentimes where there is disagreement the original coders will be asked to re-read certain country reports. After this, it is not unusual for a fair amount of discussion to ensue concerning why certain countries where given the scores they had been given. In nearly every instance, then, there eventually is unanimity. Where the various parties simply cannot agree, the lower score is used.

Composite Indicators and Rankings: Inventory 2011 217 184. Polity Country Scores

Developer 1 Center for Systemic Peace Developer 2 Center for Global Policy Year launched 2003 Latest Edition 2009 Field Governance Number of Main Dimensions 6 Key qualities of executive recruitment, constraints on executive authority, Description of Main Dimensions and political competition. It also records changes in the institutionalized (Weights in Parenthesis) qualities of governing authority Number of Underlying Indicators N/A Number of units ranked 162 Type of units ranked Countries Link to report http://systemicpeace.org/polity/polity4.htm Link to data http://www.systemicpeace.org/inscr/inscr.htm

The Polity IV Country Reports are designed to provide greater transparency in Polity coding decisions. For each of the countries covered in the study, the report provides a summary of Polity codes and a graphic illustration of changes in Polity scores from 1946 (or date of independence) through 2003. In addition, it includes indicators of major episodes of armed civil conflict. The summary information is followed by a narrative description of the quality of regime authority for 2004 on each of the three conceptual categories: executive recruitment, executive constraints, and political competition.

The Polity conceptual scheme examines concomitant qualities of democratic and autocratic authority in governing institutions, rather than discreet and mutually exclusive forms of governance. This perspective envisions a spectrum of governing authority that spans from fully institutionalized autocracies through mixed, or incoherent, authority regimes (termed "anocracies") to fully institutionalized democracies. The "Polity Score" captures this regime authority spectrum on a 21-point scale ranging from -10 (hereditary monarchy) to +10 (consolidated democracy). The Polity scores can also be converted to regime categories: we recommend a three-part categorization of "autocracies" (-10 to -6), "anocracies" (-5 to +5 and the three special values: -66, -77, and -88), and "democracies" (+6 to +10); see "Global Regimes by Type, 1946- 2006" above.

The Polity scheme consists of six component measures that record key qualities of executive recruitment, constraints on executive authority, and political competition. It also records changes in the institutionalized qualities of governing authority. The Polity data include information only on the institutions of the central government and on political groups acting, or reacting, within the scope of that authority. It does not include consideration of groups and territories that are actively removed from that authority (i.e., separatists or "fragments"; these are considered separate, though not independent, polities) or segments of the population that are not yet effectively politicized in relation to central state politics.

Composite Indicators and Rankings: Inventory 2011 218 185. Press Freedom Index

Developer 1 Reporters without Borders Developer 2 Year launched 2002 Latest Edition 2009 Field Governance Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators 40 Number of units ranked 175 Type of units ranked Countries Link to report http://en.rsf.org/press-freedom-index-2009,1001.html Link to data http://en.rsf.org/press-freedom-index-2009,1001.html

The index measures the state of press freedom in the world. It reflects the degree of freedom that journalists and news organizations enjoy in each country, and the efforts made by the authorities to respect and ensure respect for this freedom. A score and a position is assigned to each country in the final ranking. They are complementary indicators that together assess the state of press freedom. A country can change position from year to year even if its score stays the same, and viceversa. This ranking reflects the situation during a specific period. It is based solely on events between 1 September 2008 and 1 September 2009. It does not look at human rights violations in general, just press freedom violations.

To compile this index, Reporters Without Borders prepared a questionnaire with 40 criteria that assess the state of press freedom in each country. It includes every kind of violation directly affecting journalists (such as murders, imprisonment, physical attacks and threats) and news media (censorship, confiscation of newspaper issues, searches and harassment). It includes the degree of impunity enjoyed by those responsible for these press freedom violations. It also measures the level of self-censorship in each country and the ability of the media to investigate and criticize. Financial pressure, which is increasingly common, is also assessed and incorporated into the final score.

The questionnaire takes account of the legal framework for the media (including penalties for press offences, the existence of a state monopoly for certain kinds of media and how the media are regulated) and the level of independence of the public media. It also reflects violations of the free flow of information on the Internet.

Composite Indicators and Rankings: Inventory 2011 219 186. Rule of Law Index

Developer 1 World Justice Project Developer 2 Year launched 2010 Latest Edition 2010 Field Governance Number of Main Dimensions 10 Description of Main Dimensions limited government powers; absence of corruption; clear, publicized, (Weights in Parenthesis) and stable laws; order and security; fundamental rights; open government; regulatory enforcement; access to civil justice; effective criminal justice; and informal justice. Number of Underlying Indicators 49 Number of units ranked 35 Type of units ranked Countries Link to report http://worldjusticeproject.org/rule-of-law-index Link to data http://www.worldjusticeproject.org/sites/default/files/WJP%20Rule%20

of%20Law%20Index%202010_2.pdf

The WJP’s Rule of Law Index is based on the premise that it is necessary to use different but complementary data sources to best approximate the concept of the rule of law. Currently, there is no comparable data that fully covers all dimensions of the rule of law. The WJP Rule of Law Index addresses this gap by constructing a new set of indicators drawn from two novel data sources:

1. A general population poll (GPP) conducted by leading local polling companies using a probability sample of 1,000 respondents in the three largest cities of each country. 2. Qualified respondents' questionnaire (QRQ) completed by in-country experts in civil and commercial law, criminal justice, labor law, and public health. The WJP methodology anchors expert opinion on rigorous polling of the general public, thus ensuring that the findings reflect the conditions experienced by the population, including marginalized sectors of society.

The Index provides new data on the following 10 dimensions of the rule of law: limited government powers; absence of corruption; clear, publicized, and stable laws; order and security; fundamental rights; open government; regulatory enforcement; access to civil justice; effective criminal justice; and informal justice. These ten factors are further disaggregated into forty nine sub-factors. The Index’s rankings and scores are the product of a rigorous data collection and aggregation process. Data comes from a global poll of the general public and detailed questionnaires administered to local experts. To date, over 900 experts and 35,000 other individuals from around the world have participated in this project.

No single question can tap all of the dimensions of the concepts described by the different factors and subfactors, therefore, the WJP’s Rule of Law Index measures each of the concepts with several variables. All variables included in the Rule of Law Index were normalized using the Max-Min method, so that all variables are expressed in a scale from 0 (low rule of law) to 1 (high rule of law). Individual variables tapping the same concept were averaged and then aggregated into sub-factors, and factors, using simple averages. These scores are the basis of the final rankings. In all cases, the base level of aggregation for each sub-factor is calculated with a weight of 50% for the QRQ variables, and 50% for the GPP variables.

Composite Indicators and Rankings: Inventory 2011 220 187. The Observer Human Rights Index

Developer 1 Guardian Unlimited Developer 2 Year launched 1999 Latest Edition 1999 Field Governance Number of Main Dimensions 10 Description of Main Dimensions EJE=Extrajudicial executions, DIS=Disappearances, (Weights in Parenthesis) T/IT=Torture/inhuman treatment, DIC=Deaths in custody, POC=Prisoners of conscience, UFT=Unfair trials, DWC=Detention without charge or trial, EXE=Executions (death penalty), SOD=Sentence of death, AOG=Abuses by armed opposition groups Number of Underlying Indicators 10 Number of units ranked 100 Type of units ranked Countries Link to report http://www.guardian.co.uk/rightsindex/0%2C2759%2C201749%2C 00.html Link to data http://www.guardian.co.uk/Tables/4_col_tables/0,5737,94911,00.ht ml

The index monitors human rights abuses. There are two rankings: first is a simple ranking of incidence of abuse by head of population, under 10 general headings. These comprise: the incidence of extra-judicial executions; disappearances; torture and inhumane treatment; deaths in custody; prisoners of conscience; unfair trials; detention without charge or trial; existence of the death penalty; sentences of death; and abuses by armed opposition groups. Another ranking, doubles the score for the first three so-called 'non- derogable' human rights (extra-judicial executions, disappearances and torture/inhuman treatment) and factors in each country's Human Development Index. The use of the HDI has the effect of scoring wealthy abusers of human rights more harshly than countries with deep economic and social problems.

Composite Indicators and Rankings: Inventory 2011 221 188. World Governance Assessment (WGA)

Developer 1 ODI Developer 2 Year launched 2002 Latest Edition 2006 Field Governance Number of Main Dimensions 6 Description of Main Dimensions 1- Civil Society 2- Political Society 3- Government 4- (Weights in Parenthesis) Bureaucracy 5- Economic Society 6- Judiciary Number of Underlying Indicators 30 Number of units ranked 10 Type of units ranked Countries Link to report http://www.odi.org.uk/work/projects/00-07-world- governance-assessment/ Link to data http://www.odi.org.uk/work/projects/00-07-world- governance-assessment/

The WGA is a global, collaborative effort to improve the assessment and analysis of governance. The focus on the rules that guide the political process and the way issues are transacted from one arena to another within this regime led to the following definition of each arena: 1- Civil Society, where the rules for political participation, socialisation and articulation of demands are the main focus 2- Political Society, where the rules for aggregating policy is the principal focus through an assessment of the rules for electing political representatives and their own role both vis-à-vis government and the public 3- Government, where we are interested in the norms guiding its role as steward of societal or public interests 4- Bureaucracy, where we are interested in the rules that influence the operations of the civil service and its interaction with society 5- Economic Society, where our interest centres on the rules that shape state-market interactions in a global economy 6- Judiciary, where our interest is foremost in the rules that guide the operations of dispute and conflict resolving institutions. Each arena has 5 indicators. The first WGA questionnaire was comprised of thirty items, each using a five-point response scale. Informants are asked to rate various issues concerning governance as either very high, high, moderate, low, or very low. The items are equally divided into six sections covering the six arenas mentioned above. The WGA is a scale, not an index. It is a dedicated theoretically based scale that employs the same indicators and methodology in each country. The range of the WGA scale is from a low of 36 to a possible high of 180 for the overall scale and 6 to 30 for the six societal arenas and the six principles.

Composite Indicators and Rankings: Inventory 2011 222 Health

189. Ageing Vulnerability Index

Developer 1 CSIS Developer 2 Watson Wyatt Worldwide Year launched 2003 Latest Edition 2003 Field Health Number of Main Dimensions 4 Description of Main Dimensions 1. Public burden (1/3) 2. Fiscal Room (1/3) 3.Benefit (Weights in Parenthesis) dependence 4. Elder affluence (3 + 4 to combined 1/3) Number of Underlying Indicators 11 Number of units ranked 12 Type of units ranked Industrial countries Link to report http://csis.org/files/media/csis/pubs/aging_index.pdf Data Appendix to Link to data http://csis.org/files/media/csis/pubs/aging_index.pdf

The Index is calculated by combining country scores on eleven separate indicators. The indicators are grouped into four categories, each dealing with a distinct dimension of the problem: The first and most important category is public burden. It contains three indicators that measure the sheer magnitude of each country’s projected public old-age dependency burden. ■ The second category is fiscal room. It contains three indicators that measure each country’s ability to accommodate the growth in its public old-age dependency burden via higher taxes, cuts in other spending, or government borrowing. ■ The third category is benefit dependence. It contains three indicators that measure how dependent the elderly in each country are on public benefits and thus how politically difficult it may be to reduce those benefits beneath current law — or even to carry out reductions in benefits that are already scheduled to take place. ■ The fourth category is elder affluence. It contains two indicators that measure per capita elderly income in each country relative to nonelderly income — another factor that could critically affect the future politics of reform.

The Index is constructed as follows. For each of the indicators, we generate an indicator ranking, from one (best) to twelve (worst). We also transform the indicator results into an index and generate an index score for each country. For each indicator, the mean result is set to an index value of 50; results that lie above and below the mean by one standard deviation are set, respectively, to index values of 100 and zero. The index scores thus preserve the indicator rankings while also reflecting the relative distance of each ranked country, positively or negatively, from the “center of the pack.” For each of the four categories, a category score is then calculated as an average of the indicator index scores. The category score determines the overall category rankings. Finally, the category scores themselves are averaged as follows: A weight of one-third is given to the first public-burden category, one-third to the second fiscal-room category, and one- third to the third and fourth “policy-climate” categories combined. A country’s final combined average for the four categories determines its ranking in the overall Index.

Composite Indicators and Rankings: Inventory 2011 223 190. AIDS Program Effort Index (API)

Developer 1 UNAIDS Developer 2 USAID, WHO and the Policy project Year launched 2000 Latest Edition 2003 Field Health Number of Main Dimensions 10 Description of Main Dimensions 1. Political support 2. Policy and planning 3. Organizational structure (Weights in Parenthesis) 4. Program resources 5. Evaluation, monitoring and research 6. Legal and regulatory environment 7. Human rights 8. Prevention programs 9. Care and treatment services 10. Mitigation programs. (NO INDEX created, thus no weights) Number of Underlying 47 Indicators Number of units ranked 54 Type of units ranked Countries Link to report http://www.policyproject.com/pubs/monographs/API2003.pdf Link to data Appendix A to: http://www.policyproject.com/pubs/monographs/API2003.pdf

The index contains 10 components corresponding to key boxes in the conceptual framework. The components are: • Political support • Policy and planning • Organizational structure • Program resources • Evaluation, monitoring, and research • Legal and regulatory environment • Human rights • Prevention programs • Care and treatment services • Mitigation programs.

There were 100 individual items grouped into these components. Respondents scored each item on a scale of 0 to 5, where 0 indicated the complete lack of effort (e.g., no policy), 5 indicated the maximum score (e.g., a well designed policy in place and being implemented), and scores in between indicated various degrees of quality and implementation. This system was designed to provide evaluations of the quality of effort in addition to the existence of a policy or program. However, analysis of the 2000 results indicated that respondents in different countries used different frames of reference in rating the items. As a result, it was difficult to compare scores across countries. To address this problem, the API was redesigned for the 2003 round. The same 10 components are used, but the contents have been revised. Instead of asking respondents to rate the national policy on a scale of 0–5, the revised questionnaire asks for “Yes/No” responses to questions about the existence of a policy and a number of characteristics of the policy. This removes some of the judgment from the scores and makes them more easily compared across countries. The revised questionnaire contains 167 of these specific items.

Since these “Yes/No” items cannot capture all the elements of program effort, respondents are asked to provide a summary rating, on a scale of 0–10, for each component. This captures some of the elements that are hard to quantify and provides a score that can be compared with the previous round. In order to gauge progress since 2000, respondents were asked to score each item twice, once for 2003 and once for 2001. The final score for each component is the average of the qualitative summary score and the quantitative item score. The qualitative summary score is divided by 10 to adjust the range to 0–1.

The API scores are based on responses that are a mixture of fact and judgment. While the API scores do not provide a precise ranking of countries, they are useful as profiles of effort at the regional and global levels. These profiles can indicate to international agencies and donors where past efforts have led to improvements and where greater emphasis may be required in the future.

Composite Indicators and Rankings: Inventory 2011 224 191. Alcohol Policy Index

Developer 1 European Commission Joint Research Centre (EC -JRC) Developer 2 Year launched 2007 Latest Edition 2007 Field Other Number of Main Dimensions 5 Description of Main Dimensions 1.Physical availability of alcohol, 2.drinking context, 3.alcohol (Weights in Parenthesis) prices, 4.alcohol advertising, and 5. operation of motor vehicles (weights depend on effectiveness on each policy) Number of Underlying Indicators 16 Number of units ranked 30 Type of units ranked Countries Link to report http://composite- indicators.jrc.ec.europa.eu/Document/Brand,Saisana,%20Rynn,% 20Pennoni,%20Lowenfels.pdf Link to data http://composite- indicators.jrc.ec.europa.eu/Document/Brand,Saisana,%20Rynn,% 20Pennoni,%20Lowenfels.pdf

To assist public health leaders and policymakers, the authors developed a composite indicator—the Alcohol Policy Index—to gauge the strength of a country’s alcohol control policies.

The index generated scores with a potential range of 0 to 100 points, and used to assign a score to each country. The scoring system weighted different topics according to the effectiveness of regulations aimed at reducing adverse effects of alcohol as reported in the World Health Organization’s recent alcohol policy study. Based on the available scientific evidence, that report assigned a ‘‘star’’ rating to each topic, using one, two, or three stars (‘‘*’’ ‘**’’ or ‘‘***’’) to indicate limited, moderate, or high effectiveness. A weight of 1, 2, or 3 was assigned to each topic according to its star rating, then determined that the proportionate point values 2.6, 5.3, and 7.9 would yield a total of 100 points when summed over the 16 topics (2.6 points32 topics þ 5.3 points 3 6 topics þ 7.9 points 3 8 topics ¼ 100 points). These point values have been rounded to the nearest decimal point in this report, but exact values were used in the analysis. For a given topic, a country received credit based on the strictness of the country’s own policy relative to that topic: no points for the most lenient policy option, full points for the most restrictive option, and partial points for intermediate options. For example, legal alcohol purchase ages of 16, 17, 18, 19, or 20þ y generate 0, 2.0, 3.9, 5.9, or 7.9 points, respectively, corresponding to 0%, 25%, 50%, 75%, or 100% credit for this three-star topic. Summing the points credited to a country over all topics in a given domain yields the domain score; summing the domain scores yields the country’s overall alcohol policy score.

The ‘‘price index’’ for an alcoholic beverage refers to the retail price (including alcohol taxes) for a standard size beverage container (0.5-l beer, 0.75-l wine, or 0.75-l spirits) adjusted for a country’s standard of living. The adjustment consists of dividing the retail price by the per capita share of a country’s gross domestic product (GDP), and multiplying the result by 10,000 to produce a price index with an approximate range of 0 to 20. That is,

Of the 480 policies of interest (16 topics 330 countries), we were able to ascertain information about 453 policies (94.4%). In the analysis, we handled missing policy data by substituting the mean point value credited to countries with known policies for the topic in question.

Composite Indicators and Rankings: Inventory 2011 225

Weighting. We tested four different weighting schemes: baseline weighting (weights 1, 2, and 3 applied to one-star, two-star, and three-star topics, respectively), heavy weighting (weights 1, 3, and 5 used instead of 1, 2, and 3), equal weighting (same weight for all topics), and ‘‘country-specific weighting.’’ The last alternative, also known as data envelopment analysis, involved choosing a set of weights for each country in a manner that maximized that country’s performance relative to all other countries. This best-case scenario was included to discourage countries from rejecting the Alcohol Policy Index on grounds that a given weighting scheme might not be fair to a particular country. In applying a country-specific method, it is essential to place reasonable bounds on the weights; otherwise, a country could achieve a perfect score simply by assigning zero weight to all topics for which the government had not implemented the strictest policy option. To preclude this possibility, we required minimum and maximum weights to differ by no more than a factor of 12—that is, four times the spread of the weights used in the baseline model.

Imputation. The baseline model uses mean-value substitution to impute missing policy data (5.6% of all items). In the sensitivity analysis, we used a more refined approach, known as ‘‘nearest-neighbor’’ imputation. This method computes the mathematical ‘‘distance’’ between every pair of countries based on all shared (nonmissing) policy data. Each missing item is then replaced by the value of the corresponding item from the country’s nearest neighbor; that is, the country that is mathematically closest (most similar with respect to its policies) to the one with the missing item. If a country has more than one nearest neighbor, the mode (most frequent value) from those neighbors is used as the replacement.

Aggregation. The Alcohol Policy Index generates a score by adding together weighted contributions from each of 16 policy topics to permit the ranking of countries based on their aggregate scores.

Composite Indicators and Rankings: Inventory 2011 226 192. Australian Federal Police Drug Harm Index

Developer 1 Australian Federal Police Developer 2 Year launched 2008 Latest Edition 2010 Field Health Number of Main Dimensions N/A Description of Main Dimensions (Weights in Parenthesis) N/A Number of Underlying Indicators N/A Number of units ranked 1 Type of units ranked Australia Link to report http://www.afp.gov.au/policing/drug-crime/risks.aspx Link to data N/A

The AFP Drug Harm Index was developed to provide a single measure that encapsulates the potential value to the Australian community of AFP drug seizures. The index represents the dollar value of harm that would have occurred had the seized drugs reached the community.

In the five years to June 2009, the AFP and its partners saved the Australian community approximately $883.3 million in drug-related harm through its disruption of illicit drug importations. Previous research has shown that the AFP's Drug Harm Index shows a return of approximately $5 to the Australian community for every $1 invested in federal drug investigations.

Composite Indicators and Rankings: Inventory 2011 227 193. Early Motherhood Risk Ranking

Developer 1 Save the Children Developer 2 Year launched 2004 Latest Edition 2004 Field Health Number of Main Dimensions 3 Description of Main Dimensions 1. Early marriage (30 percent) 2. Early motherhood (40 (Weights in Parenthesis) percent) and 3. Risk to children (30 percent) Number of Underlying Indicators 3 Number of units ranked 119 Type of units ranked Countries Link to report N/A – It was taken off the website Link to data N/A

It focuses on the prevalence of early marriage and early childbearing, as well as the increased risk to babies that early motherhood often creates. Data were gathered for three indicators of risks associated with early motherhood: 1. Early marriage: Percent of women aged 15 to 19 ever married 2. Prevalence of early motherhood status: Births per 1,000 women aged 15 to 19 and 3. Risk to babies: Infant Mortality Rate (IMR) for mothers under age 20. Standard scores, or Z-scores, were created for each of the indicators. Z- scores were divided by the range of Z-scores for each variable in order to control for differences in the range of possible scores. These percentage scores (i.e., actual score as percent of range of scores) were then averaged to create the index scores. The indexed risk score was calculated as a weighted average of early marriage (30 percent), early motherhood (40 percent) and risk to children (30 percent). The index scores were scaled on a scale of 0 to 100, where 100 represents the country in the sample with the highest level of risk to young mothers. Scaled scores were then ranked.

Composite Indicators and Rankings: Inventory 2011 228 194. EIU Quality of Death Index

Developer 1 Economist Intelligence Unit (EIU) Developer 2 LIEN Foundation Year launched 2010 Latest Edition 2010 Field Health Number of Main Dimensions 4 Description of Main Dimensions 1. Basic End-of-Life Healthcare Environment (20%) 2. (Weights in Parenthesis) Availability of End-of-Life Care (25%) 3. Cost of End-of-Life Care (15%) and 4. Quality of End-of-Life Care (40%) Number of Underlying Indicators 24 Number of units ranked 40 Type of units ranked Countries Link to report http://graphics.eiu.com/upload/QOD_main_final_edition_Jul12_to print.pdf Link to data http://www.lifebeforedeath.com/qualityofdeath/index.shtml

The Quality of Death Index measures the current environment for end-of-life care services across 40 countries: 30 OECD nations and 10 select others for which data was available. The Economist Intelligence Unit’s research team devised the Index, collated data and built the model from a wide range of indicators. They interviewed a variety of doctors, specialists and other experts to compile and verify the data. The Index scores countries across four categories: Basic End-of-Life Healthcare Environment; Availability of End-of-Life Care; Cost of End-of-Life Care; and Quality of End-of-Life Care.

Twenty-four individual indicators fall into three broad categories: Quantitative indicators: Eleven of the Index’s 24 indicators are based on quantitative data, such as life expectancy and healthcare spending as a percentage of GDP. Qualitative indicators: Ten of the indicators are qualitative assessments of end-of-life care in individual countries, for example “Public awareness of end-of-life care”, which is assessed on a scale of 1-5 where 1=little or no awareness and 5=high awareness. Status indicators: Three of the indicators describe whether something is or is not the case, for example, “Existence of a government-led national palliative care strategy”, for which the available answers are Yes, No and In Progress.

The Index is an aggregate score of all of the underlying indicators, normalised to make the data comparable. Data is first aggregated by category and then overall, based on the composite of the underlying category scores. To create the category scores, each underlying indicator was aggregated according to an assigned weighting, determined by the EIU’s research team following consultation with experts interviewed for the research.

Each category is also accorded a weighting within the overall score. Quality is given the largest weighting, accounting for 40% of the overall score; Availability accounts for 25%, Basic End-of-Life Healthcare Environment 20% and Cost 15%. Although the index scores were calculated to two decimal places, they have been rounded to one decimal place in the charts in this white paper. For this reason, countries with different rankings may nonetheless display the same score.

Composite Indicators and Rankings: Inventory 2011 229 195. Global Burden of Disease (GBD)

Developer 1 WHO Developer 2 Year launched 1990 Latest Edition 2011 Field Health Number of Main Dimensions 24 Description of Main Dimensions 1. Childhood and maternal under nutrition: Underweight, Iron (Weights in Parenthesis) deficiency, Vitamin A deficiency, Zinc deficiency, Suboptimal breastfeeding, 2. Other nutrition-related risk factors and physical activity: High blood pressure, High cholesterol, High blood glucose, Overweight and obesity, Low fruit and vegetable intake, Physical inactivity 3. Addictive substances: Tobacco use, Alcohol use, Illicit drug use, 4. Sexual and reproductive health, Unsafe sex, Unmet contraceptive need 5. Environmental risks: Unsafe water, sanitation, hygiene, Urban outdoor air pollution , Indoor smoke from solid fuels, Lead exposure, Global climate change, 6. Occupational risks: Risk factors for injuries, Carcinogens, Airborne particulates, Ergonomic stressors, Noise 7. Other selected risks: Unsafe healthcare injections, Child sexual abuse Number of Underlying Indicators 69 Number of units ranked 190 Type of units ranked Countries Link to report http://www.who.int/topics/global_burden_of_disease/en/ Link to data http://www.globalburden.org/

The global burden of disease (GBD) measures burden of disease using the disability-adjusted life year (DALY). This time-based measure combines years of life lost due to premature mortality and years of life lost due to time lived in states of less than full health. The DALY metric assesses the burden of disease consistently across diseases, risk factors and regions. The principle guiding the burden of disease approach is that the best estimates of incidence, prevalence, and mortality can be generated by carefully analyzing all available sources of information in a country or region, and correcting for bias. The disability-adjusted life year (DALY), a time-based measure that combined years of life lost due to premature mortality and years of life lost due to time lived in health states less than ideal health, was developed to assess the burden of disease.

DALYs are a common currency by which deaths at different ages and disability may be measured. One DALY can be thought of as one lost year of “healthy” life, and the burden of disease can be thought of as a measurement of the gap between current health status and an ideal situation where everyone lives into old age, free of disease and disability. DALYs for a disease or injury are calculated as the sum of the years of life lost due to premature mortality (YLL) in the population and the years lost due to disability (YLD) for incident cases of the disease or injury. YLL are calculated from the number of deaths at each age multiplied by a global standard life expectancy of the age at which death occurs. YLD for a particular cause in a particular time period are estimated as follows:

YLD = number of incident cases in that period × average duration of the disease × disability weight

The disability weight reflects the severity of the disease on a scale from 0 (perfect health) to 1 (death). In the standard DALYs in recent WHO reports, calculations of YLD used an additional 3% time discounting and non-uniform age weights that give less weight to years lived at young and older ages. Using discounting and age weights, a death in infancy corresponds to 33 DALYs, and deaths at ages 5– 20 years to around 36 DALYs.

Composite Indicators and Rankings: Inventory 2011 230 196. Health Utilities Index (HUI)

Developer 1 HUInc Developer 2 Year launched 2010 Latest Edition 2010 Field Health Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators N/A Number of units ranked 1 Type of units ranked US Link to report http://www.healthutilities.com/ Link to data http://www.healthutilities.com/

The Health Utilities Index (HUI) is a family of generic preference-based systems for measuring comprehensive health status and health-related quality of life (HRQL). HUI provides descriptive evidence on multiple dimensions of health status, a score for each dimension of health, and a HRQL score for overall health. Health dimensions include vision, hearing, speech, ambulation/mobility, pain, dexterity, self-care, emotion and cognition. Each dimension has 3- 6 levels. HUI® systems describe almost a million unique health states.

HUI scoring functions are based on preference measurements from random samples of the general population and represent mean community utilities. The utility scores have interval-scale properties. Overall HRQL scores are on the conventional dead = 0.00 to perfect health = 1.00 scale and are appropriate for calculating quality-adjusted life years (QALYs) in cost-effectiveness and cost-utility analyses.

Composite Indicators and Rankings: Inventory 2011 231 197. Index of Social Health

Developer 1 Institute for Innovation in Social Policy Developer 2 Year launched 1987 Latest Edition 2008 Field Health Number of Main Dimensions N/A Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators 16 Number of units ranked 1 Type of units ranked US Link to report http://iisp.vassar.edu/ish.html Link to data http://iisp.vassar.edu/ish.html

The Index of Social Health monitors the social well-being of American society. It has been released annually by the Institute (formerly the Fordham Institute for Innovation in Social Policy) since 1987. Like the Index of Leading Economic Indicators or the Gross Domestic Product, it is a composite measure that combines multiple indicators to produce a single number.

The Index of Social Health is based on sixteen social indicators. These are: infant mortality, child poverty, child abuse, teenage suicide, teenage drug abuse, high school dropouts, unemployment, wages, health insurance coverage, poverty among the elderly, out-of-pocket health costs among the elderly, homicides, alcohol-related traffic fatalities, food insecurity, affordable housing, and income inequality.

The Index of Social Health is composed of sixteen indicators. Grouped by stage of life, they are as follows:

Children Adults All Ages Infant mortality Unemployment Child abuse Average weekly wages Homicides Child poverty Health insurance coverage Alcohol-related traffic fatalities Youth Elderly Food insecurity Teenage suicide Affordable housing Poverty, ages 65 and over Teenage drug abuse Income inequality Out-of-pocket health costs, ages 65 and over High school dropouts

Composite Indicators and Rankings: Inventory 2011 232 198. Mother's Index

Developer 1 Save the Children Developer 2 Year launched 2000 Latest Edition 2010 Field Health Number of Main Dimensions 5 1. Children’s well-being (30 percent), 2. women’s health status (20 Description of Main Dimensions percent), 3. women’s educational status (20 percent), 4. women’s (Weights in Parenthesis) economic status (20), and 5. women’s political status (10 percent). Number of Underlying Indicators 12 Number of units ranked 143 Type of units ranked Countries

Link to report http://www.savethechildren.net/alliance/what_we_do/every_one/news.html

Link to data http://www.savethechildren.net/alliance/what_we_do/every_one/news.html

The Mothers’ Index aims to assess where it is best and worst to be a mother. It is based on a composite of separate indices for women’s and children’s well-being. The Index relies on information published by governments, research institutions and international agencies.

The Mothers’ Index was calculated as a weighted average of children’s well-being (30 percent), women’s health status (20 percent), women’s educational status (20 percent), women’s economic status (20), and women’s political status (10 percent). The scores on the Mothers’ Index were then ranked.

The Z-scores of the four indicators related to women’s health were averaged to create an index score of women’s health status. In Tier I, an index score of women’s economic status was similarly calculated as a weighted average of the ratio of female to male earned income (75 percent), length of maternity leave (12.5 percent) and percent of wages paid (12.5 percent). An index of child well-being – the Children’s Index – was also created by first averaging indicators of education, then averaging across all Z-scores. At this stage, cases (countries) missing more than one indicator on either index were eliminated from the sample. Countries missing any one of the other indicators (that is educational, economic or political status) were also eliminated. A Women’s Index was then calculated as a weighted average of health status (30 percent), educational status (30 percent), economic status (30 percent) and political status (10 percent).

Composite Indicators and Rankings: Inventory 2011 233 199. New Zealand Illegal Drugs Harm Index (NZ-DHI)

Developer 1 New Zealand Ministry of Health Developer 2 Year launched 2006 Latest Edition 2006 Field Health Number of Main Dimensions 3 Description of Main Dimensions (Weights in Parenthesis) 1. Direct costs, 2. Indirect costs and 3. Intangible costs Number of Underlying Indicators N/A Number of units ranked 1 Type of units ranked New Zealand http://www.moh.govt.nz/moh.nsf/pagescm/559/$File/mcdp-illegal- Link to report drug-harm-index-28apr08.pdf http://www.atkearney.com/index.php/Publications/making-offshore- Link to data decisions.html?q=offshore

The objectives for the NZDHI are to:

• Quantify drug related costs, which will not just identify how expensive the problem is, but also identify where the avoidable costs lie, and what could be done to minimise them. • Help to answer questions about the benefit-to-cost ratio of current illicit drug strategies and policies, in particular the effectiveness of supply reduction efforts by enforcement agencies. • Offer insights into the impact of supply side interventions. The NZDHI will contribute significantly to current understandings about the balance of investment between drug demand reduction and drug supply reduction initiatives. Using the Index will assist key decision makers and enforcement agencies to better gauge the cost-effectiveness of drug supply reduction efforts. It will enable improvements to be made to multi-agency and cross-sector approaches, encourage consensus about the value of certain types of interventions, and identify opportunities for synergies between interventions. • Provide a means to potentially benchmark our performance in this area against overseas jurisdictions, particularly Australia, and, having set the benchmark, begin to track New Zealand’s progress over time.

The New Zealand Drug Harm Index has been broadly modelled on the Australian Drug Harm Index developed by the Australia Federal Police, which was based on the Collins and Lapsley (2002) study of substance abuse in Australia1. However, the NZDHI differs in that estimates are built from the bottom up where possible, rather than working from aggregate estimates or data from other countries. The NZDHI uses NZ data on drugs and drug user behaviour. It demonstrates a more comprehensive range of impacts, including a wider range of crime, work and health service consequences.

Three broad categories of cost are considered: direct costs, indirect costs and intangible costs. These categories contain further disaggregated costs such as crime costs, road accident costs, health care costs, lost production costs and reduced quality of life. The work involved three stages. First, it estimated the total harm from illicit drug consumption in the base year of 2006. Second it determined the harm per kilogram of particular illicit drug types. The harm per kilogram estimates indicates the gross economic benefit of drug seizures. Third, it developed a metric called the New Zealand Drug Harm Index based on illicit drug seizures between 2000 and 2006. Validity checks were carried out using a selection of dummy scenarios to generate index numbers, which were scrutinized to ensure that the calculated values satisfied the 'common sense' tests and were in line with expectations. Separate tests were carried out to ensure consistency and comparability with the Australian DHI.

Composite Indicators and Rankings: Inventory 2011 234 200. Overall Health System Achievement Index

Developer 1 WHO Developer 2 Year launched 2000 Latest Edition 2000 Field Health Number of Main Dimensions 5 1. Level of health (25%) 2. distribution of health (25%) 3. Description of Main Dimensions Level of responsiveness (12.5%) 4. distribution of (Weights in Parenthesis) responsiveness and 5. fairness of financial contribution (25%) Number of Underlying Indicators 5 Number of units ranked 191 Type of units ranked Countries Link to report http://www.who.int/healthinfo/paper28.pdf Link to data http://www.who.int/healthinfo/paper28.pdf

Composite Indicators and Rankings: Inventory 2011 235 201. Overall Health System Performance Index

Developer 1 WHO Developer 2 Year launched 2000 Latest Edition 2000 Field Health Number of Main Dimensions 5 1. Level of health (25%) 2. distribution of health (25%) 3. Level of Description of Main Dimensions responsiveness (12.5%) 4. distribution of responsiveness and 5. (Weights in Parenthesis) fairness of financial contribution (25%) Number of Underlying Indicators 5 Number of units ranked 191 Type of units ranked Countries

Link to report http://www.who.int/healthinfo/paper30.pdf

Link to data http://www.who.int/healthinfo/paper30.pdf

How well a health system does its job requires two inquiries: 1) how to measure the outcomes of interest – that is, to determine what is achieved with respect to the three objectives of good health, responsiveness and fair financial contribution (attainment) And 2) how to compare those attainments with what the system should be able to accomplish – that is, the best that could be achieved with the same resources (performance). Health performance measures how that health outcome compares to what might have been achieved with the resources available in the country. The index of performance on the level of health reports how efficiently health systems translate expenditure into health as measured by disability-adjusted life expectancy (DALE). Performance on the level of health is defined as the ratio between achieved levels of health and the levels of health that could be achieved by the most efficient health system. More specifically, the numerator of the ratio is the difference between observed DALE in a country and the DALE that would be observed in the absence of a functioning modern health system given the other non- health system determinants that influence health, which are represented by education. The denominator of the ratio is the difference between the maximum possible DALE that could have been achieved for the observed levels of health expenditure per capita in each country and the DALE in the absence of a functioning health system. Econometric methods have been used to estimate the maximum DALE for a given level of health expenditure and other non-health system factors using frontier production analysis. The relationship between life expectancy and human capital at the turn of the century was used to estimate the minimum DALE that would have been expected in each country (at current levels of educational attainment) in the absence of an effective health system. Overall performance of health systems was measured using a similar process relating overall health system achievement to health system expenditure. Maximum attainable composite goal achievement was estimated using a frontier production model relating overall health system achievement to health expenditure and other non-health system determinants represented by educational attainment.

Composite Indicators and Rankings: Inventory 2011 236 202. Reproductive Risk Index

Developer 1 Population Action International Developer 2 Year launched 2001 Latest Edition 2001 Field Health Number of Main Dimensions 9 Description of Main Dimensions 1. adolescent fertility 2. contraceptive prevalence 3. antenatal care 4. (Weights in Parenthesis) skilled attendance at delivery 5. anemia among pregnant women 6. HIV/AIDS prevalence among adult females 7. HIV/AIDS prevalence among adult males 8. abortion policy 9. L Lifetime risk of death from Pregnancy and CHildbirth (total fertility rate (TFR), and maternal mortality ratio (MMR) Number of Underlying Indicators 10 Number of units ranked 133 Type of units ranked Countries Link to report http://www.populationaction.org/Publications/Reports/A_World_of_Di fference/Trends_in_Reproductive_Health_Worldwide.shtml Link to data http://www.populationaction.org/Publications/Reports/A_World_of_Di fference/The_Reproductive_Risk_Index.shtml

The index is composed of 10 indicators of reproductive health. The ten indicators of reproductive health composing the Reproductive Risk Index are: adolescent fertility, contraceptive prevalence, antenatal care, skilled attendance at delivery, anemia among pregnant women, HIV/AIDS prevalence among adult females, HIV/AIDS prevalence among adult males, abortion policy, total fertility rate (TFR), and maternal mortality ratio (MMR). Reproductive Risk Index combines TFR and MMR into the indicator Lifetime Risk of Death from Pregnancy and Childbirth (LTR) to which a logarithmic function is applied. LTR indicates the risk associated with each pregnancy and the number of times a woman becomes pregnant. The observed range for seven of the resulting nine indicators is then transformed into a range of 0 to 100. For each of these seven indicators, each country is located in the new range, giving the country at the top of the range for each indicator a score of 100 and the country at the bottom of the range a score of zero. For the construction of the Reproductive Risk Index, LTR is given a weight of two to reflect the importance of the two indicators from which it is derived. The final composite index score is derived by dividing the sum of the eight-scaled values and the two assigned scores by 10. The maximum value of the index a country can have is 95 because the maximum scores assigned to prevalence of anemia and abortion policies are 70 and 80 respectively.

Composite Indicators and Rankings: Inventory 2011 237 Wellbeing

203. African Gender and Development Index (AGDI)

Developer 1 UNECA Developer 2 Year launched 2004 Latest Edition 2010 Field Wellbeing Number of Main Dimensions 2 Description of Main Dimensions Gender Status Index (GSI) and the African Women's Progress (Weights in Parenthesis) Scoreboard (AWPS) Number of Underlying Indicators 42 Number of units ranked 12 Type of units ranked African countries Link to report http://www.uneca.org/eca_resources/publications/books/awr/index.htm Link to data http://www.uneca.org/eca_resources/publications/books/awr/index.htm

The African Gender and Development Index (AGDI) is designed to measure the gap in the status of women and men in Africa and to assess the progress made by African governments in implementing the gender policies they have developed. The AGDI is a composite index consisting of two parts, a Gender Status Index (GSI) and the African Women’s Progress Scoreboard (AWPS), rather than a collection of individual statistics. The index is in two main parts.

The GSI is a quantitative measure of relative gender equality in various spheres, computed using a set of 41 indicators. These indicators are classified within three blocks: social power representing ‘capabilities’; economic power representing ‘opportunities’; and political power representing ‘agency’. The social power block focuses on education and health; the economic power block pays attention to gender inequalities in income, time use, employment and access to resources, while the political power block measures representation in decision-making across public and Civil Society Organizations (CSOs). A fourth block, women’s rights is restricted to the African Women’s Progress Scoreboard subcomponent of the AGDI, uses qualitative indicators to review performance with respect to global and regional treaty obligations affecting women. Each block of the GSI is divided into various components, which in turn are subdivided into a number of sub-components and finally, indicators/variables respectively. Only variables amenable to comparison between women and men are included. To meet the objective of democratizing statistics, the index is based on the use of simple indicators which compare women’s achievement to men’s, and thus ignores population-weighed harmonic means as a basis of computation.

The AWPS assesses progress being made by African governments in the qualitative areas of legal reform, policy, planning, implementation and monitoring of international treaties, declarations, and decisions affecting women. The AWPS is a double entry table composed of two axes: a vertical axis (horizontal lines) listing selected conventions, charters, resolutions, and issues included in the assessment; and a horizontal axis comprised of a range of indicators for measuring government performance. Similar to the GSI, the AWPS functions under the three blocks of social, economic and political. However, in view of its unique objective of also assessing the human rights of women, it also possesses a women’s rights block as an additional (fourth) block. The inclusion of a rights assessment in the AGDI framework is not to suggest that the other blocks (social, economic and political) are not sensitive to women’s rights. This rights block rather reinforces the other three by providing a special window of opportunity for investigating country performance of treaty obligations in fields that are social, economic and political.

Composite Indicators and Rankings: Inventory 2011 238 204. American Human Development Index

Developer 1 American Human Development Project Developer 2 Year launched 2009 Latest Edition 2011 Field Wellbeing Number of Main Dimensions 3 Description of Main Dimensions 1. Health 2. Education 3. Income (equal weights) (Weights in Parenthesis) Number of Underlying 4 Indicators Number of units ranked 50 Type of units ranked US States Link to report http://www.measureofamerica.org/the-measure-of-america-2010- 2011-book/ Link to data http://www.measureofamerica.org/maps/

The Measure of America presents a modified American Human Development Index. The American HD Index measures the same three basic dimensions as the standard HD Index, but it uses different indicators to better reflect the U.S. context and to maximize use of available data. For example, while the standard index measures access to knowledge using the average number of years that students spend in school, we have chosen instead to use educational attainment, a more demanding indicator.

The American Human Development (HD) Index is calculated using a simple methodology that is replicated for each state, congressional district, metro area, and population group. First, a sub-index for each of the three components of the overall index—health, education, and income—is calculated, and each of the three components is weighted one-third in the index. This equal weighting is not arbitrary, but rather reflects a belief that these three basic building blocks of a life of freedom and opportunity are equally essential. Performance in each dimension is expressed as a value between 0 and 10 by applying the following general formula:

For each of the three indices, goalposts are determined based on the range of the indicator observed for all possible groupings and also taking into account possible increases and decreases in years to come. In order to make the HD Index comparable over time, the health and education indicator goalposts do not change from year to year. The earnings goalposts are adjusted for inflation. Because earnings data and the goalposts are presented in dollars of the same year, these goalposts reflect a constant amount of purchasing power regardless of the year, making Income Index results comparable over time.

Indicator Max Min Life expectancy at birth (years) 90 66 Educational attainment score 2.0 0.5 Combined gross enrollment ratio (%) 100 70 Median personal earnings (2009 dollars)* $60,429 $14,283 * Earnings goalposts were originally set at $55,000 and $13,000 in 2005 dollars.

The American HD Index results from taking the simple average of the health, education, and income indices. Since all three components range from 0 to 10, the HD Index itself also varies from 0 to 10, with 10 representing the highest level of human development.

Composite Indicators and Rankings: Inventory 2011 239 205. Assessing the Achievement of the Millennium Development Goals (MDGs)

Developer 1 UNDP Developer 2 World Bank Year launched 2002 Latest Edition 2009 Field Wellbeing Number of Main Dimensions 8 Description of Main Dimensions Goal 1: Eradicate extreme poverty and hunger. Goal 2: Achieve (Weights in Parenthesis) universal primary education. Goal 3: Promote gender equality and empower women Goal 4: Reduce child mortality Goal 5: Improve maternal health Goal 6: Combat HIV/AIDS, malaria and other diseases Goal 7: Ensure environmental sustainability Goal 8: Develop a Global Partnership for Development Number of Underlying 60 Indicators Number of units ranked 223 Type of units ranked Countries Link to report N/A Link to data http://unstats.un.org/unsd/mdg/Data.aspx

It assesses the prospects of countries, aggregated by region, for reaching six of the targets of the Millennium Development Goals. Progress toward the MDGs for selected indicators is calculated using the latest available data point and comparing it to the contemporaneous point on a reference path connecting the 1990 value to the MDG target. The reference path was calculated assuming a constant, annual or geometric rate of change. The countries are then classified into a set of colors: green represents countries that made progress in the 1990s fast enough to attain the target value in the specified time period (by 2005 for gender equality and by 2015 for all others). They are “likely" to achieve the goals. Countries in light green made progress, but too slowly to reach the goals in the time specified. Continuing at the same rate, they will need as much as twice the time as the “likely" countries to reach the goals – they are rated “possible". Countries in orange made slower progress and are “unlikely" to reach the goals. Countries in red are “very unlikely" to reach the goals. Lastly, gray countries lack adequate data to measure progress.

Composite Indicators and Rankings: Inventory 2011 240 206. Basic Capabilities Index (BCI)

Developer 1 Social Watch Developer 2 Year launched 200 0 Latest Edition 2010 Field Wellbeing Number of Main Dimensions 3 1. Education 2. Mortality among children under five 3. The Description of Main Dimensions percentage of births attended by skilled health personnel. (equal (Weights in Parenthesis) weights) Number of Underlying Indicators 4 Number of units ranked 161 Type of units ranked Countries Link to report http://www.socialwatch.org/node/12257 Link to data http://www.socialwatch.org/node/12259

The Basic Capabilities Index (BCI) was designed by Social Watch as an alternative way to monitor the situation of poverty in the world. It is based instead on a person’s capability of accessing a series of services that are indispensable for survival and human dignity. The indicators that make up the BCI are among the most basic of those used to measure the Millennium Development Goals. The BCI is the average of three indicators: 1) mortality among children under five, 2) reproductive or maternal-child health, and 3) education (measured by a combination of enrolment in primary education and the proportion of children reaching fifth grade). All the indicators are expressed in percentages and they range from 0 to 100. Under five mortality, which is usually expressed in number of deaths per thousand children born alive, is expressed as 100 minus that value. So that, for example, a value of 20 deaths per thousand becomes 2 per cent and, when deducted from 100, a basic index value of 98. Thus, the theoretical maximum value in infant mortality is 100, which would mean that all children born alive survive until they are five years old. Reproductive health takes the maximum value 100 when all women giving birth are attended by skilled health personnel. Similarly, the education indicator registers 100 when all school age children are enrolled in education and they all attain five years of schooling. These three indicators are then averaged, so the total value of the index will vary between 0% and 100%. Thus, the BCI of a country approaches 100 when there is universal access to the three minimum levels of social coverage mentioned above. Social Watch understands that a BCI value close to the maximum reflects the “dignity for all” proclaimed by the Universal Declaration of Human Rights.

The BCI was calculated for 162 countries for 2009, 163 for 2000 and 163 for 1990. Countries are grouped in various categories. Countries in the most serious situation are those with a Critical BCI (less than 70 points). In the Very Low BCI category (from 70 to 79 points) there are countries facing major obstacles to achieving well-being for the population. The countries with Low BCI (from 80 to 89 points) are at an intermediate level as regards the satisfaction of basic needs, and their performance varies in some dimensions of development. The countries that have progressed and now satisfy most or all the population’s basic capabilities are in the two categories with the highest values: Medium BCI (from 90 to 96) and Acceptable (97 points and more).

Composite Indicators and Rankings: Inventory 2011 241 207. Canadian Index of Wellbeing (CIW)

Developer 1 Institute of Wellbeing Developer 2 Year launched 2011 Latest Edition 2011 Field Wellbeing Number of Main Dimensions 8 Description of Main Dimensions Culture and recreation, community vitality, democratic (Weights in Parenthesis) engagement, education, environment, healthy populations, living standards and time use Number of Underlying Indicators N/A Number of units ranked 1 Type of units ranked Canada Link to report http://www.ciw.ca/Libraries/Documents/FirstReportOfTheCIW. sflb.ashx Link to data Not released yet.

The CIW is a new way of measuring wellbeing. It will provide unique insights into the quality of life of Canadians – overall, and in specific areas that matter: our standard of living, our health, the quality of our environment, our education and skill levels, the way we use our time, the vitality of our communities, our participation in the democratic process, and the state of our arts, culture and recreation. In short, the CIW is the only national index that measures wellbeing in Canada across a wide spectrum of domains.

Composite Indicators and Rankings: Inventory 2011 242 208. Child and Youth Wellbeing Index (CWI)

Developer 1 Foundation for Child Development Developer 2 Year launched 2004 Latest Edition 2010 Field Wellbeing Number of Main Dimensions 7 Description of Main Dimensions 1. Economic wellbeing, 2. Safe/risky behavior, 3. Social (Weights in Parenthesis) relationships, 4. Emotional/ spiritual well-being, 5. Community engagement, 6. Educational attainment and 7. Health. (Equal weights) Number of Underlying Indicators 28 Number of units ranked 1 Type of units ranked US Link to report http://www.fcd-us.org/resources/2010-child-well-being-index-cwi Link to data http://www.fcd-us.org/our-work/child-well-being-index-cwi

The objective of the overall CWI is to give a view of changes over time in the overall well-being of children and youth in the United States. The composite CWI, an equally-weighted average of the seven Well-Being Domains, provides a sense of the overall direction of change in well-being, as compared to a base year of the indicators, 1975. For this reason, the focus of the Index is not primarily on specific indicators, but rather on the way in which they interact and change over time. As a composite index of changes over time, the important information in the CWI pertains to its directions of change over sequences of years. The CWI is based on a composite of 28 Key Indicators of well-being that are grouped into seven Quality-of- Life/Well-Being Domains. These domains are economic wellbeing, safe/risky behavior, social relationships, emotional/ spiritual well-being, community engagement, educational attainment, and health. This year’s overall CWI is an updated measure of trends over the 33-year period from 1975 to 2008, with projections for 2009.

To calculate the CWI, each of the time series of the indicators is indexed by a base year (1975). The base year value of the indicator is assigned a value of 100 and subsequent values of the indicator are taken as percentage changes in the CWI. The directions of the indicators are oriented so that a value greater (lesser) than 100 in subsequent years means the social condition measured has improved (deteriorated). The indexed Key Indicator time series then are grouped into the seven Domains of Well-Being by equal weighting to compute the Domain-Specific Index values for each year. The seven Domain-Specific Indices then are grouped into an equally-weighted Child and Youth Well-Being Index value for each year. The CWI Project uses an equal-weighting strategy for constructing its composite indices for two reasons. First, it is the simplest and most transparent strategy and can easily be replicated by others. Second, statistical research done in conjunction with the CWI Project has demonstrated that, in the absence of a clear ordering of the indicators of a composite index by their relative importance to the composite and on which there is a high degree of consensus in the population, an equal weighting strategy is privileged in the sense that it will achieve the greatest level of agreement among the members of the population. In statistical terminology, the equal-weighting method is a minimax estimator.

Composite Indicators and Rankings: Inventory 2011 243 209. Child Development Index

Developer 1 Save the Children Developer 2 Year launched 2008 Latest Edition 2008 Field Wellbeing Number of Main Dimensions 3 Description of Main Dimensions (Weights in Parenthesis) 1. Health 2. Nutrition 3. Education Number of Underlying Indicators 3 Number of units ranked 140 Type of units ranked Countries Link to report http://www.savethechildren.org.uk/en/7129.htm Link to data http://www.savethechildren.org.uk/en/7129.htm

Save the Children UK has introduced the first ever globally representative, multi-dimensional tool to monitor and compare the wellbeing of children. We have used it in more than 140 developed and developing countries across the world. The Child Development Index is made up of three indicators of three areas of child wellbeing. The indicators were chosen because they are easily available, commonly understood, and clearly indicative of child wellbeing. The three indicators are:

• Health: the under-five mortality rate (the probability of dying between birth and five years of age, expressed as a percentage on a scale of 0 to 340 deaths per 1,000 live births17) • Nutrition: the percentage of under-fives who are moderately or severely underweight • Education: the percentage of primary school-age children who are not enrolled in school.

These three indicators are aggregated by simply calculating the average score between them for each period under review, meaning that they each have equal weighting in the index scores. Because the data are not collected annually, they are grouped into three time periods, and are available for 88 countries in the first period (1990–94), 118 countries in the second period (1995–99), and 137 countries in the third period (2000–06).

Increasing country coverage across these periods reflects improvements in data collection. Countries are then ranked: Japan is ranked first, scoring 0.41, representing the highest level of child wellbeing – through to the country with the lowest level, Niger, which scored 58. It is important to stress that a low score is best as it represents a low level of child deprivation, whereas a high score represents a high level of child deprivation and poverty. A zero score would mean that all children survive beyond their fifth birthday, all under-fives are well-nourished, and all primary school-age children are enrolled in primary school. Conversely, a maximum score of 100 would represent a situation where all children under five were underweight, all primary school children were out of school, and under-fives were dying at the highest possible rate on the scale – that is, at a rate of 340 per 1,000 live births.

Composite Indicators and Rankings: Inventory 2011 244 210. Child Well Being Index

Developer 1 UK Department for Communities and Local Government Developer 2 Year launched 2007 Latest Edition 2009 Field Wellbeing Number of Main Dimensions 7 Description of Main Dimensions 1. Material well-being 2. Health 3. Education 4. Crime 5. (Weights in Parenthesis) Housing 6. Environment 7. Children in need. Number of Underlying Indicators 29 Number of units ranked 1 Type of units ranked UK Link to report http://www.communities.gov.uk/publications/communities/chil dwellbeing2009 Link to data http://www.communities.gov.uk/publications/communities/chil dwellbeing2009

The Child Well-being Index (CWI) represents the first attempt to create a small area index exclusively for children in England. Unlike the Index of Multiple Deprivation (IMD), the CWI was restricted by the availability of data as many datasets are not disaggregated by age group. Data on children is largely collected through surveys which are not robust enough to be broken down to small area level

The Child Well-being Index (CWI) is produced at Lower Super Output Area level (LSOAs) and is made up of seven domains. Summary measures of the CWI are presented at local authority district and county council levels. The CWI is based on the approach, structure and methodology that were used in the construction of the ID 2007. The seven domains included in the CWI are: 1. Material well-being 2. Health 3. Education 4. Crime 5. Housing 6. Environment 7. Children in need.

Each of the 32,482 LSOAs in England has been assigned a score and rank for the CWI index; the seven domain indices; and the two sub domains. Each local authority district is assigned a score and a rank using a population weighted average of the score and rank for each LSOA within the local authority. Each (social service authority) is assigned a score and rank based on the population weighted score and rank for each LSOA within the social service authority.

Composite Indicators and Rankings: Inventory 2011 245 211. Cochise County Quality of Life Index

Developer 1 Cochise County - Arizona Developer 2 Year launched 2006 Latest Edition 2006 Field Wellbeing Number of Main Dimensions 4 Description of Main Dimensions 1. Health, Safety & Security 2. Economic Health 3. Environmental (Weights in Parenthesis) Health 4. Education & Community Health Number of Underlying Indicators 24 Number of units ranked 1 Type of units ranked Cochise County -Arizona Methodology On a Separate Word Doc Link to report http://cochise.az.gov/qolwebsite/default.htm Link to data http://cochise.az.gov/qolwebsite/default.htm

The Cochise County Quality of Life Index is a project sponsored by the Cochise Community Foundation, the Cochise College Center for Economic Research and Cochise County. It is a summary of weighted indicators used to: Baseline current conditions, Benchmark progress over time, Educate the public, Develop consensus, Compare ourselves with others. Continued pressure on public budgets challenge government’s ability to address the needs of residents. A burden shift is taking place as private and non- profit sectors are being engaged in new ways. The QOL Index can help strengthen these relationships by providing a context for looking at different issues in an integrated way. The Index is comprised of 24 indicators, each with its own separate analysis. They are organized into 4 categories of 6 indicators each: 1. Health, Safety & Security 2. Economic Health 3. Environmental Health 4. Education & Community Health

Indicator Average Rating Weight in QOL Index Safe roads and highways 8.09 4.41% Crime rate 7.99 4.35% Availability of healthcare 7.88 4.29% Quality of county government services 7.78 4.24% Quality of elementary and secondary education 7.78 4.24% Water conservation 7.77 4.24% Cost of living 7.77 4.23% Availability of higher education opportunities 7.73 4.21% Availability of law enforcement protection 7.72 4.20% Level of illegal immigration 7.71 4.20% Affordable housing 7.71 4.20% Preserving the natural habitat for plant and wildlife 7.68 4.18% Wage and salary levels 7.61 4.15% Preservation of dark skies 7.61 4.14% Level of health insurance coverage in the county 7.60 4.14% Level of unemployment 7.59 4.13% Preserving open spaces 7.57 4.13% Level of economic growth countywide 7.54 4.11% Survival of the San Pedro River 7.52 4.10% Local tax burden 7.50 4.09% Availability of recycling services 7.48 4.07% Availability of public parks 7.47 4.07% Availability of community events and activities 7.28 3.97% Availability of arts and heritage organizations 7.19 3.92%

Composite Indicators and Rankings: Inventory 2011 246 212. Crime Index

Developer 1 Intelligent Direct Developer 2 Year launched 1995 Latest Edition 2010 Field Wellbeing Number of Main Dimensions N/A Description of Main Dimensions (Weights in Parenthesis) N/A Number of Underlying Indicators N/A Number of units ranked 1 Type of units ranked US Methodology N/A Link to report http://www.crimeindex.com/ Link to data http://www.crimeindex.com/

CrimeINDEX.com offers Crime Risk Analysis and Mapping to companies throughout the United States. - Total Crime - Personal Crime - Murder - Rape - Robbery - Assault - Property Crime - Burglary - Larceny - Motor Vehicle Theft

Composite Indicators and Rankings: Inventory 2011 247 213. Development Web Model

Developer 1 Ophelia M. Yeung and John A. Mathieson Developer 2 Year launched 1998 Latest Edition 1998 Field Wellbeing Number of Main Dimensions 6 Description of Main Dimensions economic performance, competitiveness, education, health, environment, and (Weights in Parenthesis) democracy and freedom Number of Underlying Indicators 6 Number of units ranked 100 Type of units ranked Countries Global Benchmarks: Comprehensive Measures of Development Brookings, Link to report SRI. http://www.brookings.edu/press/Books/1998/bench.aspx Link to data In the Publication

It presents a unique and innovative measurement system for country progress in six aspects of development: economic performance, competitiveness, education, health, environment, and democracy and freedom. The authors scored over 100 countries individually and plotted their development performance along six vectors, allowing them to be benchmarked against one another. They illustrate at a glance whether the country's development is balanced and allows the country's progress to be monitored over time.

Composite Indicators and Rankings: Inventory 2011 248 214. EU Regional Human Development Index

Developer 1 European Commission Developer 2 Year launched 2010 Latest Edition 2010 Field Wellbeing Number of Main Dimensions 3 Description of Main Dimensions 1. Health 2. Education 3. Income (equal weights) (Weights in Parenthesis) Number of Underlying 3 Indicators Number of units ranked 27 Type of units ranked EU Countries Link to report http://ec.europa.eu/regional_policy/sources/docoffic/official/reports/

cohesion5/index_en.cfm Link to data Page 114 - http://ec.europa.eu/regional_policy/sources/docoffic/official/reports/ cohesion5/pdf/5cr_en.pdf

To gain a better perspective on human development diversity within the EU, an EU regional HDI has been calculated, which includes healthy life expectancy, net adjusted household income16 and low and high educational attainment for people aged 25–64. This indicator is less closely correlated to GDP than the UN one and provides a complementary perspective.

Composite Indicators and Rankings: Inventory 2011 249 215. EU Regional Poverty Index

Developer 1 European Commission Developer 2 Year launched 2010 Latest Edition 2010 Field Wellbeing Number of Main Dimensions 4 Description of Main Dimensions 1. The probability at birth of not reaching 65, 2. the at-risk-of- (Weights in Parenthesis) poverty rate, 3. long term unemployment and 4. the share of population aged 25–64 with only basic schooling. Number of Underlying 4 Indicators Number of units ranked 27 Type of units ranked EU Countries Link to report http://ec.europa.eu/regional_policy/sources/docoffic/official/reports/

cohesion5/index_en.cfm Link to data Page 114 - http://ec.europa.eu/regional_policy/sources/docoffic/official/reports/ cohesion5/pdf/5cr_en.pdf

The UN has also created a Human Poverty Index, which allows for the fact that averages can hide large disparities. The Index has one version for less developed countries and one for developed countries (HPI 2). This latter index was also calculated for all EU regions based on the probability at birth of not reaching 65, the at-risk-of-poverty rate, long term unemployment and the share of population aged 25–64 with only basic schooling..

Composite Indicators and Rankings: Inventory 2011 250 216. Famine Early Warning System (FEWSNet)

Developer 1 USAID, Chemonics International, Inc., United States Geological Survey (USGS), National Aeronautics and Space Administration (NASA), National Oceanographic and Atmospheric Administration (NOAA), United States Department of Agriculture (USDA)

Developer 2 Year launched 1985 Latest Edition 2010 Field Wellbeing Number of Main Dimensions 5 Description of Main Dimensions Crude mortality rate (# deaths per 10,000 people per day), (Weights in Parenthesis) Acute malnutrition (weight/height ‹ - 2 z-scores), Food access/ availability, Coping, Livelihood assets (5 capitals: human, social, financial, natural, physical) Number of Underlying Indicators 5 Number of units ranked 29 Type of units ranked Countries Link to report http://www.fews.net/Pages/default.aspx Link to data http://www.fews.net/Pages/default.aspx

The primary purpose of the FEWS NET Food Insecurity Severity Scale is to provide a common classification of the severity of food insecurity, which can be used to highlight priority areas and populations in need of emergency response that have been identified based on food security analysis. Achieving statistically comparable measures of food insecurity is not currently possible, even with a major investment – nor necessarily required for early warning purposes. Therefore, the FEWS NET Food Insecurity Severity Scale aims to support the development of the most comparable analysis possible to support decision making and planning at different levels. FEWS NET fully recognizes the significant amount of judgment that underlies this type of analysis. FEWS NET uses the latest available assessment and monitoring data, as well as baseline and historical data, to inform its scenario analysis. A consensus- based process engaging relevant experts in each country is conducted to determine the appropriate level of food insecurity to assign to each area.

Since FEWS NET performs food security outlook analyses regularly over the course of the year, FEWS NET has designed this food security classification to be dynamic. For example, an area or population may be classified by FEWS NET as no acute food insecurity, moderately food insecure, or highly food insecure at different times over the course of the year depending on seasonality and the timing of specific shocks, coping strategies, and other factors. Also, in the interest of highlighting key areas of concern for decision- makers, FEWS NET explicitly incorporates assumptions about likely humanitarian assistance in its analysis of food security outcomes.

The FEWS NET Food Insecurity Severity Scale utilizes reference thresholds for acute malnutrition, mortality and food deficits that are similar to those developed as part of the FAO-led Integrated Phase Classification (IPC) process, of which FEWS NET is a partner.

FEWS NET Food Insecurity Severity Scale

No Acute Food Moderately Food Highly Food Extremely Food Famine Insecurity Insecure Insecure Insecure

Summary HH able to meet Able to meet their Although Households face Destitution and Description basic food basic food households may substantial or starvation become

Composite Indicators and Rankings: Inventory 2011 251 requirements requirements, but be receiving prolonged prominent, and without depending to do so, they are external shortfalls in their populations face on external relying on assistance and ability to meet high mortality assistance. There is external employing basic food risk, due to an adequate food assistance and/or coping requirements. extreme lack of available and that coping strategies strategies, Reduced food access to food and households have that begin to modest shortfalls intake is other basic needs. adequate resources erode their asset in meeting basic widespread, to obtain sufficient base. Levels of food resulting in food. No major acute malnutrition requirements significantly deficiencies exist in remain within remain. Negative increased rates the diet. Households typical seasonal household of acute may face less severe norms. response malnutrition and manifestations of strategies are increasing food insecurity that prominent, and mortality. reflect poor chronic more extreme Significant conditions. These coping, erosion of assets may include less including is occurring, and than ideal dietary liquidation of households are diversity, inability productive gradually to consume assets, may be moving towards preferred foods, present. The destitution. chronic prevalence of malnutrition, and/or acute anxiety about future malnutrition is food security. above normal.

Corresponding IPC Reference Indicators

Crude mortality CMR ‹ 0.5 CMR ‹ 0.5 CMR 0.5-1, CMR 1-2, U5MR › 4 rate U5MR ‹ =1 increasing; increasing, or › CMR › 2 (# deaths per U5MR 1-2 2x reference rate 10,000 people per day)

Acute ‹ 3% › 3% but ‹ 10% ; 10-15% ; › usual, › 15%; > usual, > 30% malnutrition usual range, increasing increasing (weight/height ‹ stable - 2 z-scores)

Food access/ Usually adequate, Borderline Lack of Severe Extreme availability stable (2,100 kcal adequate, unstable entitlement entitlement gap, entitlement gap; pppd) (2,100 kcal pppd) (2,100 kcal unable to meet much below 2,100 pppd), meeting minimum needs kcal pppd minimum needs through asset stripping

Coping NDC Insurance Crisis strategies; Distress NDC strategies CSI › reference, strategies; CSI increasing significantly ‹ reference

Livelihood Generally sustained Stressed Accelerated and Near complete Effectively assets (5 utilization unsustainable critical depletion and irreversible complete loss; capitals: utilization or loss of access depletion or loss collapse human, social, of access financial, natural, physical) Note: NDC = not a defining characteristic; pppd = per person per day; ltrs = liters; CSI = Coping Strategies Index developed by CARE and WFP.

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217. Food Insecurity

Developer 1 FAO Developer 2 Year launched 1996 Latest Edition 2010 Field Wellbeing Number of Main Dimensions 1 Description of Main Dimensions Progress World Food Summit (WFS) goal of halving (Weights in Parenthesis) undernourished people Number of Underlying Indicators 1 Number of units ranked 200 Type of units ranked Countries Link to report http://www.fao.org/publications/sofi/en/ Link to data http://www.fao.org/hunger/en/

FAO reports on global and national efforts to reach the goal set by the 1996 World Food Summit: to reduce by half the number of undernourished people in the world by the year 2015. It monitors progress in hunger reduction based on accurate, reliable and timely methods that measure the prevalence of hunger, food insecurity and vulnerability and that also illustrate changes over time. FAO presents the latest estimates of the number of undernourished people and the proportion by country. It also presents the countries with food emergencies and their causes (“hunger hotspots”).

Composite Indicators and Rankings: Inventory 2011 253 218. Food Security Risk Index

Developer 1 Maplecroft Developer 2 Year launched 2010 Latest Edition 2010 Field Wellbeing Number of Main Dimensions 12 Description of Main Dimensions N/A (Weights in Parenthesis) Number of Underlying Indicators 12 Number of units ranked 163 Type of units ranked Countries Link to report http://www.maplecroft.com/about/news/food- security.html Link to data N/A

The Food Security Risk Index 2010, released by risk analysis and rating firm Maplecroft, evaluates the risks to the supply of basic food staples for 163 countries. It uses 12 criteria developed in collaboration with the World Food Programme, to calculate the ranking including: the nutritional and health status of populations, cereal production and imports, GDP per capita, natural disasters, conflict, and the effectiveness of government.

Composite Indicators and Rankings: Inventory 2011 254 219. Gallup-Healthways Well-Being Index

Developer 1 Gallup Developer 2 Healthways Year launched 2008 Latest Edition 2010 Field Wellbeing Number of Main Dimensions 6 Description of Main Dimensions Life Evaluation, Emotional Health, Physical Health, (Weights in Parenthesis) Healthy Behavior, Work Environment and Basic Access Number of Underlying Indicators 6 Number of units ranked 1 Type of units ranked US Link to report http://well-beingindex.com/files/2011PressKitFinal.pdf Link to data http://well-beingindex.com/

The Gallup-Healthways Well-Being Index is the first-ever daily assessment of U.S. residents' health and well-being. By interviewing at least 1,000 U.S. adults every day, the Well-Being Index provides real-time measurement and insights needed to improve health, increase productivity, and lower healthcare costs. Public and private sector leaders use data on life evaluation, physical health, emotional health, healthy behavior, work environment, and basic access to develop and prioritize strategies to help their communities thrive and grow. Journalists, academics, and medical experts benefit from this unprecedented resource of health statistics and behavioral economic data to inform their research and reporting.

To compile the Well-Being Index, Gallup obtains completed interviews from 1,000 U.S. adults nationally, seven days a week, excluding only major holidays. Based on their response, individuals and communities receive an overall well-being composite score and score of each of six sub-indices including life evaluation, emotional health, physical health, healthy behavior, work environment and basic access. Changes in condition can be tracked over time, and the introduction of both controlled and uncontrolled variable considered. Discrete populations can also be ranked one against another for a stratified view of their relative well-being.

The survey methods for Gallup-Healthways Well-Being Index relies on live (not automated) interviewers, dual-frame random-digit-dial (RDD) sampling (which includes landlines as well as wireless phone sampling to reach those in wireless-only households), and a random selection method for choosing respondents within a household. Additionally, daily tracking includes Spanish-language interviews for respondents who speak only Spanish, includes interviews in Alaska and Hawaii. The data are weighted daily to compensate for disproportional ties in selection probabilities and non-response. The data are weighted to match targets from the U.S. Census Bureau by age, sex, region, gender, education, ethnicity and race. The Gallup-Healthways Well-Being Index Composite Score is comprised of six sub-indices: Life Evaluation, Emotional Health, Physical Health, Healthy Behavior, Work Environment and Basic Access. The Life Evaluation Sub-Index is partially based on the Cantril Self-Anchoring Striving Scale and combines the evaluation of one’s present life situation with one’s anticipated life situation five years from now. The Emotional Health Sub-Index is primarily a composite of respondents’ daily experiences, asking respondents to think about how they felt yesterday along nine dimensions. The Physical Health Sub-Index is comprised of questions related to: Body Mass Index, disease burden, sick days, physical pain, daily energy, history of disease and daily health experiences.

The Healthy Behavior Sub-Index includes items measuring life style habits with established relationships to health outcomes. The Work Environment Sub-Index surveys workers on several factors to gauge their feelings and perceptions about their work environment. The Basic Access Sub-Index is based on thirteen items measuring resident’s access to food, shelter, healthcare and a safe and satisfying place to live.

Composite Indicators and Rankings: Inventory 2011 255 220. Gender Empowerment Measure (GEM)

Developer 1 UNDP Developer 2 Year launched 1995 Latest Edition 2008 Field Wellbeing Number of Main Dimensions 3 Description of Main Dimensions 1. Parliamentary participation (1/3) 2. Economic Participation (Weights in Parenthesis) (1/3) and 3. Power over economic resources (1/3) Number of Underlying Indicators 4 Number of units ranked 109 Type of units ranked Countries Link to report http://hdr.undp.org/en/reports/global/hdr2007-8/ Link to data http://hdr.undp.org/en/statistics/indices/gdi_gem/

The GEM examines whether women and men are able to actively participate in economic and political life and take part in decision-making. It captures gender inequality in three key areas: 1) Political participation and decision-making power, as measured by women’s and men’s percentage shares of parliamentary seats 2) Economic participation and decision-making power, as measured by two indicators— women’s and men’s percentage shares of positions as legislators, senior officials and managers and women’s and men’s percentage shares of professional and technical positions 3) Power over economic resources, as measured by women’s and men’s estimated earned income (PPP US$).

For each of these three dimensions, an equally distributed equivalent percentage (EDEP) is calculated, as a population weighted average, rewarding gender equality and penalizing inequality. It is calculated as the harmonic mean of the two components. The EDEP for “economic participation” is the unweighted average of the EDEP for each of its sub-components. The EDEP for “income” is computed from gender sub-values that are indexed to a scale from 100 to 40,000 (PPP US$). The GEM is the unweighted average of the three EDEPs.

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Composite Indicators and Rankings: Inventory 2011 257