Calculating the Human Development Indices
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EPAU HDI Comparative Assessment Technical Note December 2011 Docx
Economic and Policy Analysis Unit UNDP Maputo December 2011 Mozambique’s Performance in the HDI . A comparative Assessment Author: Thomas Kring Technical Note Mozambique’s Performance in the HDI Published by The Economic and Policy Analysis Unit (EPAU) UNDP Mozambique Av. Kenneth Kaunda 931 Maputo, Mozambique Technical Notes from EPAU are intended to be informal notes on economic and technical issues relevant for the work of the UNDP in Mozambique. The views expressed are those of the author and may not be attributed to the UNDP. 1 Technical Note Mozambique’s Performance in the HDI Introduction Since 1990 the UNDP has published the Human Development Report (HDR) on an annual basis. One significant component of the HDR has traditionally been advanced statistics seeking to measure economic and human development in more comprehensive and informative ways. One of the best known measures in the HDR is the Human Development Index (HDI). The HDI provides a broad overview of human progress and the complex relationship between income and well-being. The HDI looks beyond the GDP to a broader definition of well-being by including health and knowledge. By doing so it corrects, to some extent, for the inherent weaknesses in traditional measurements of growth and wealth (see Annex 2 for more detail). The recently released Global HDR 2011 provides, as in previous years, a HDI value for a 187 countries in the world. Mozambique’s performance this year, as in previous years, continues to baffle observers. The country has made significant progress in the past ten years or more. It is among the five highest performers in the world measured in terms of average annual increase in the HDI since 2000 in relative terms, and among the top 25 in absolute terms (see Annex 1). -
Ethnolinguistic Diversity and Education. a Successful Pairing
sustainability Article Ethnolinguistic Diversity and Education. A Successful Pairing Mª Ángeles Caraballo 1,* and Eva Mª Buitrago 2 1 Dpto. Economía e Historia Económica and IUSEN, Universidad de Sevilla, 41018 Sevilla, Spain 2 Dpto. Economía Aplicada III and IAIIT, Universidad de Sevilla, 41018 Sevilla, Spain; [email protected] * Correspondence: [email protected]; Tel.: +34-954-557-535 Received: 22 October 2019; Accepted: 19 November 2019; Published: 23 November 2019 Abstract: The many growing migratory flows render our societies increasingly heterogeneous. From the point of view of social welfare, achieving all the positive effects of diversity appears as a challenge for our societies. Nevertheless, while it is true that ethnolinguistic diversity involves costs and benefits, at a country level it seems that the former are greater than the latter, even more so when income inequality between ethnic groups is taken into account. In this respect, there is a vast literature at a macro level that shows that ethnolinguistic fragmentation induces lower income, which leads to the conclusion that part of the difference in income observed between countries can be attributed to their different levels of fragmentation. This paper presents primary evidence of the role of education in mitigating the adverse effects of ethnolinguistic fractionalization on the level of income. While the results show a negative association between fragmentation and income for all indices of diversity, the attainment of a certain level of education, especially secondary and tertiary, manages to reverse the sign of the marginal effect of ethnolinguistic fractionalization on income level. Since current societies are increasingly diverse, these results could have major economic policy implications. -
Income and Poverty in the United States: 2018 Current Population Reports
Income and Poverty in the United States: 2018 Current Population Reports By Jessica Semega, Melissa Kollar, John Creamer, and Abinash Mohanty Issued September 2019 Revised June 2020 P60-266(RV) Jessica Semega and Melissa Kollar prepared the income section of this report Acknowledgments under the direction of Jonathan L. Rothbaum, Chief of the Income Statistics Branch. John Creamer and Abinash Mohanty prepared the poverty section under the direction of Ashley N. Edwards, Chief of the Poverty Statistics Branch. Trudi J. Renwick, Assistant Division Chief for Economic Characteristics in the Social, Economic, and Housing Statistics Division, provided overall direction. Vonda Ashton, David Watt, Susan S. Gajewski, Mallory Bane, and Nancy Hunter, of the Demographic Surveys Division, and Lisa P. Cheok of the Associate Directorate for Demographic Programs, processed the Current Population Survey 2019 Annual Social and Economic Supplement file. Andy Chen, Kirk E. Davis, Raymond E. Dowdy, Lan N. Huynh, Chandararith R. Phe, and Adam W. Reilly programmed and produced the historical, detailed, and publication tables under the direction of Hung X. Pham, Chief of the Tabulation and Applications Branch, Demographic Surveys Division. Nghiep Huynh and Alfred G. Meier, under the supervision of KeTrena Phipps and David V. Hornick, all of the Demographic Statistical Methods Division, conducted statistical review. Lisa P. Cheok of the Associate Directorate for Demographic Programs, provided overall direction for the survey implementation. Roberto Cases and Aaron Cantu of the Associate Directorate for Demographic Programs, and Charlie Carter and Agatha Jung of the Information Technology Directorate prepared and pro- grammed the computer-assisted interviewing instrument used to conduct the Annual Social and Economic Supplement. -
The Human Development Index (HDI) Has Been Criticized for Not Incorporating Distributional Issues
Using Census Data to Explore the Spatial Distribution of Human Development Iñaki Permanyer1 Abstract: The human development index (HDI) has been criticized for not incorporating distributional issues. We propose using census data to construct a municipal-based HDI that allows exploring the distribution of human development with unprecedented geographical coverage and detail. Moreover, we present a new methodology that allows decomposing overall human development inequality according to the contribution of its subcomponents. We illustrate our methodology for Mexico‘s last three census rounds. Municipal-based human development has increased over time and inequality between municipalities has decreased. The wealth component has increasingly accounted for most of the existing inequality in human development during the last twenty years. Keywords: Human Development Index, Measurement, Spatial Distribution, Inequality, Census, Mexico. 1 Contact person: [email protected], +345813060, Centre d‘Estudis Demogràfics, Campus UAB, Bellaterra, 08193, Barcelona, Spain. 1 1. INTRODUCTION Since it was first introduced in the 1990 Human Development Report, the Human Development Index (HDI) has attracted a great deal of interest in policy-making and academic circles alike. As stated in Klugman et al (2011): ―Its popularity can be attributed to the simplicity of its characterization of development – an average of achievements in health, education and income – and to its underlying message that development is much more than economic growth‖. Despite its acknowledged shortcomings (see Kelley 1991, McGillivray 1991, Srinivasan 1994), the HDI has been very helpful to widen the perspective with which academics and policy-makers alike approached the problem of measuring countries development levels (see Herrero et al 2010). -
Technical Notes
Technical notes Calculating the human development indices—graphical presentation Human Development DIMENSIONS Long and healthy life Knowledge A decent standard of living Index (HDI) INDICATORS Life expectancy at birth Expected years Mean years GNI per capita (PPP $) of schooling of schooling DIMENSION Life expectancy index Education index GNI index INDEX Human Development Index (HDI) Inequality-adjusted DIMENSIONS Long and healthy life Knowledge A decent standard of living Human Development Index (IHDI) INDICATORS Life expectancy at birth Expected years Mean years GNI per capita (PPP $) of schooling of schooling DIMENSION Life expectancy Years of schooling Income/consumption INDEX INEQUALITY- Inequality-adjusted Inequality-adjusted Inequality-adjusted ADJUSTED life expectancy index education index income index INDEX Inequality-adjusted Human Development Index (IHDI) Gender Development Female Male Index (GDI) DIMENSIONS Long and Standard Long and Standard healthy life Knowledge of living healthy life Knowledge of living INDICATORS Life expectancy Expected Mean GNI per capita Life expectancy Expected Mean GNI per capita years of years of (PPP $) years of years of (PPP $) schooling schooling schooling schooling DIMENSION INDEX Life expectancy index Education index GNI index Life expectancy index Education index GNI index Human Development Index (female) Human Development Index (male) Gender Development Index (GDI) Gender Inequality DIMENSIONS Health Empowerment Labour market Index (GII) INDICATORS Maternal Adolescent Female and male Female -
The US Education Innovation Index Prototype and Report
SEPTEMBER 2016 The US Education Innovation Index Prototype and Report Jason Weeby, Kelly Robson, and George Mu IDEAS | PEOPLE | RESULTS Table of Contents Introduction 4 Part One: A Measurement Tool for a Dynamic New Sector 6 Looking for Alternatives to a Beleaguered System 7 What Education Can Learn from Other Sectors 13 What Is an Index and Why Use One? 16 US Education Innovation Index Framework 18 The Future of US Education Innovation Index 30 Part Two: Results and Analysis 31 Putting the Index Prototype to the Test 32 How to Interpret USEII Results 34 Indianapolis: The Midwest Deviant 37 New Orleans: Education’s Grand Experiment 46 San Francisco: A Traditional District in an Innovation Hot Spot 55 Kansas City: Murmurs in the Heart of America 63 City Comparisons 71 Table of Contents (Continued) Appendices 75 Appendix A: Methodology 76 Appendix B: Indicator Rationales 84 Appendix C: Data Sources 87 Appendix D: Indicator Wish List 90 Acknowledgments 91 About the Authors 92 About Bellwether Education Partners 92 Endnotes 93 Introduction nnovation is critical to the advancement of any sector. It increases the productivity of firms and provides stakeholders with new choices. Innovation-driven economies I push the boundaries of the technological frontier and successfully exploit opportunities in new markets. This makes innovation a critical element to the competitiveness of advanced economies.1 Innovation is essential in the education sector too. To reverse the trend of widening achievement gaps, we’ll need new and improved education opportunities—alternatives to the centuries-old model for delivering education that underperforms for millions of high- need students. -
State Income Limits for 2021
STATE OF CALIFORNIA - BUSINESS, CONSUMER SERVICES AND HOUSING AGENCY GAVIN NEWSOM, Governor DEPARTMENT OF HOUSING AND COMMUNITY DEVELOPMENT DIVISION OF HOUSING POLICY DEVELOPMENT 2020 W. El Camino Avenue, Suite 500 Sacramento, CA 95833 (916) 263-2911 / FAX (916) 263-7453 www.hcd.ca.gov April 26, 2021 MEMORANDUM FOR: Interested parties FROM: Megan Kirkeby, Deputy Director Division of Housing Policy Development SUBJECT: State Income Limits for 2021 Attached are briefing materials and State Income Limits for 2021 that are now in effect, replacing the 2020 State Income Limits. Income limits reflect updated median income and household income levels for extremely low-, very low-, low-, and moderate-income households for California’s 58 counties. The 2021 State Income Limits are on the Department of Housing and Community Development (HCD) website at http://www.hcd.ca.gov/grants-funding/income- limits/state-and-federal-income-limits.shtml. State Income Limits apply to designated programs, are used to determine applicant eligibility (based on the level of household income) and may be used to calculate affordable housing costs for applicable housing assistance programs. Use of State Income Limits are subject to a particular program’s definition of income, family, family size, effective dates, and other factors. In addition, definitions applicable to income categories, criteria, and geographic areas sometimes differ depending on the funding source and program, resulting in some programs using other income limits. The attached briefing materials detail California’s 2021 Income Limits and were updated based on: (1) changes to income limits the U.S. Department of Housing and Urban Development (HUD) released on April 1, 2021 for its Public Housing, Section 8, Section 202 and Section 811 programs and (2) adjustments HCD made based on State statutory provisions and its 2013 Hold Harmless (HH) Policy. -
Human Development Paper
HUMAN DEVELOPMENT PAPER HUMAN DEVELOPMENT PAPER ON INCOME INEQUALITY IN THE REPUBLIC OF SERBIA 1 HUMAN DEVELOPMENT PAPER ON INCOME INEQUALITY IN THE REPUBLIC OF SERBIA Reduced inequality as part of the SDG agenda August 2018 2 HUMAN DEVELOPMENT PAPER ON INCOME INEQUALITY IN THE REPUBLIC OF SERBIA FOREWORD “People are the real wealth of a nation. The basic objective of development is to create an enabling environment for people to enjoy long, healthy and creative lives. This may appear to be a simple truth. But it is often forgotten in the immediate concern with the accumulation of commodities and financial wealth.” (UNDP, Human Development Report, 1990). When the first Human Development Report was published in 1990, the UNDP firmly set out the concepts of dignity and a decent life as the essential to a broader meaning of human development. Ever since, the organization has been publishing reports on global, regional and national levels addressing the most pressing development challenges. In recent years, UNDP initiated a new product - Human Development Papers – that focus on a selected development issue with the aim to contribute to policy dialogue and policy-making processes. It is my pleasure to introduce the first Human Development Paper for Serbia, focusing on inequality. The Agenda 2030 for Sustainable Development places a special emphasis on eradicating poverty worldwide while reducing inequality and exclusion, promoting peaceful, just and inclusive societies and leaving no one behind. The achievement of Sustainable Development Goals requires new approaches to how we understand and address inter-related challenges of poverty, inequality and exclusion. The paper analyses and sets a national baseline for SDG10 leading indicator 10.1.1 - Growth rates of household expenditure or income per capita among the bottom 40 per cent of the population and the total population and the related target 10.1. -
Household Income and Wealth
HOUSEHOLD INCOME AND WEALTH INCOME AND SAVINGS NATIONAL INCOME PER CAPITA HOUSEHOLD DISPOSABLE INCOME HOUSEHOLD SAVINGS INCOME INEQUALITY AND POVERTY INCOME INEQUALITY POVERTY RATES AND GAPS HOUSEHOLD WEALTH HOUSEHOLD FINANCIAL ASSETS HOUSEHOLD DEBT NON-FINANCIAL ASSETS BY HOUSEHOLDS HOUSEHOLD INCOME AND WEALTH • INCOME AND SAVINGS NATIONAL INCOME PER CAPITA While per capita gross domestic product is the indicator property income may never actually be returned to the most commonly used to compare income levels, two country but instead add to foreign direct investment. other measures are preferred, at least in theory, by many analysts. These are per capita Gross National Income Comparability (GNI) and Net National Income (NNI). Whereas GDP refers All countries compile data according to the 1993 SNA to the income generated by production activities on the “System of National Accounts, 1993” with the exception economic territory of the country, GNI measures the of Australia where data are compiled according to the income generated by the residents of a country, whether new 2008 SNA. It’s important to note however that earned on the domestic territory or abroad. differences between the 2008 SNA and the 1993 SNA do not have a significant impact of the comparability of the Definition indicators presented here and this implies that data are GNI is defined as GDP plus receipts from abroad less highly comparable across countries. payments to abroad of wages and salaries and of However, there are practical difficulties in the property income plus net taxes and subsidies receivable measurement both of international flows of wages and from abroad. NNI is equal to GNI net of depreciation. -
Global Urban Indicators Database Version 2
GLOBAL URBAN INDICATORS DATABASE Version 2 Global Urban Observatory United Nations Human Settlements Programme (UN - Habitat) NOTE The designation and presentation of material in this publication do not imply the expression of any opinion whatsoever on the part of the secretariat concerning the legal status of any country, city, or territory concerning the delimitation of its frontiers or boundaries. UNITED NATIONS PUBLICATION HS/637/01E ISBN 92-1-131627- 8 Any questions or comments concerning this product should be addressed to: Coordinator Global Urban Observatory United Nations Human Settlements Programme (UN - Habitat) P. O. Box 30030 - Nairobi, Kenya Tel: (254 02) 623050 - Fax: (254 02) 623080 Email: [email protected] http://www.unhsp.org/guo TABLE OF CONTENTS Page List of Acronyms ......................................................................................... iv 1. INTRODUCTION ........................................................................................1 Overview .......................................................................................................1 Databases .....................................................................................................1 Data collection ..............................................................................................2 2. THE CITY DEVELOPMENT INDEX ......................................................3 3. REGIONAL DATA ANALYSIS ...............................................................4 Tenure ............................................................................................................4 -
Nber Working Paper Series Income Growth and Its
NBER WORKING PAPER SERIES INCOME GROWTH AND ITS DISTRIBUTION FROM EISENHOWER TO OBAMA: THE GROWING IMPORTANCE OF IN-KIND TRANSFERS (1959-2016) James Elwell Kevin Corinth Richard V. Burkhauser Working Paper 26439 http://www.nber.org/papers/w26439 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 November 2019 The views in this paper reflect those of the authors and should not be attributed to the Joint Committee on Taxation, the Council of Economic Advisers, their staffs, or the National Bureau of Economic Research. Elwell’s work on this research was funded by The Lynde and Harry Bradley Foundation while he was a graduate student at Cornell University. Part of this work was undertaken while Burkhauser was employed by the Council of Economic Advisers. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. © 2019 by James Elwell, Kevin Corinth, and Richard V. Burkhauser. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. Income Growth and its Distribution from Eisenhower to Obama: The Growing Importance of In-Kind Transfers (1959-2016) James Elwell, Kevin Corinth, and Richard V. Burkhauser NBER Working Paper No. 26439 November 2019 JEL No. D31,H24,J3 ABSTRACT Using Census Bureau estimates of the market value of in-kind transfers and Current Population Survey (ASEC-CPS) data over the period 1979 to 2007, Burkhauser et al. -
2014 Mastercard African Cities Growth Index Understanding Inclusive Urbanization
Knowledge Leadership 2014 MasterCard African Cities Growth Index Understanding Inclusive Urbanization By Dr Yuwa Hendrick-Wong & Professor George Angelopulo Acknowledgements The authors thank Rodger George (Deloitte Consulting (PTY) LTD.) for his advice when designing the MasterCard African Cities Growth Index and Desmond Choong (The Quiet Analyst LTD.) for technical support during data gathering and analysis. Copyright MasterCard 2014 Table of Contents Foreword 4 Introduction 5 ONE | ABOUT THE 2014 MASTERCARD AFRICAN CITIES GROWTH INDEX 7 TWO | THE CITIES OF THE 2014 INDEX 8 Illustration 2.1: The six international comparison cities of the 2014 MasterCard African Cities Growth Index 8 Illustration 2.2: The 74 African cities reviewed by the 2014 MasterCard African Cities Growth Index 9 THREE | DATA AND RANKING 10 Lagging Indicators 10 Illustration 3.1: Lagging indicators 10 Figure 3.1: Lagging indicator ranking by city 12 Leading Indicators 13 Illustration 3.2: Leading indicators 13 Figure 3.2: Leading indicator ranking by city 14 FOUR | CITY RANKING 15 International Comparison Cities 15 Table 4.1: International comparison cities 15 Figure 4.1: Inclusive growth potential - comparison city array 16 Large Cities 17 Table 4.2: Large cities of more than 1 000 000 inhabitants 18 Figure 4.2: Inclusive growth potential - large city array 19 Figure 4.3: 2014 MasterCard African Cities Growth Index - large cities by rank 20 Medium Cities 21 Table 4.3: Medium cities of 500 000 to 1 000 000 inhabitants 21 Figure 4.4: Inclusive growth potential - medium