10412-05_Ch05.qxd 8/16/07 2:55 PM Page 90 5 The Poverty Mapping Exercise in Bulgaria BORYANA GOTCHEVA ACRONYMS AND ABBREVIATIONS BIHS Bulgaria Integrated Household Survey EU European Union Eurostat Statistical Office of the European Communities IDF Institutional Development Fund Lev lev (plural leva), the Bulgarian currency MLSP Ministry of Labor and Social Policy MTHS multitopic household survey NSI National Statistical Institute OECD Organisation for Economic Co-operation and Development SIF Social Investment Fund ulgaria is a well-performing middle-income country that joined the European BUnion (EU) on January 1, 2007. After a difficult transition from central planning that culminated in a severe crisis in 1996–97, the country has made impressive progress toward long-term stability and sustained growth. Macroeconomic stability has been reestablished and maintained through prudent fiscal policies and strict discipline in income policy anchored on the currency board arrangement adopted in 1997. A broad structural reform agenda has contributed to solid economic performance. Continued growth since the 1996–97 crisis has led to poverty reduction and improvements in living standards generally, although deep pockets of poverty persist. Per capita income increased from US$1,200 in 1997 to US$2,740 in 2004 (gross national income, Atlas method). Nonetheless, per capita gross domestic product, at the purchasing power stan- dard in 2003, was only 30 percent of the EU average, so that continued growth and the 90 10412-05_Ch05.qxd 8/16/07 2:55 PM Page 91 THE POVERTY MAPPING EXERCISE IN BULGARIA 91 convergence of living conditions toward EU standards remain a core policy goal. Poverty fell sharply from 1997 to 2001 and more slowly thereafter.1 The most recent assessment of poverty in the country indicates that, measured at two-thirds of median consumption, relative poverty fell by 2.1 percentage points between 2001 and 2003 (Tes¸liuc 2005). Indicators of the depth and severity of poverty also improved. Extreme poverty remained low, at 4.8 percent of households in 2003, while food poverty (a proxy for malnutrition) was virtually nonexistent. Even as poverty has fallen, the profile of poverty has been changing. Poverty is increasingly concentrated among certain vulner- able groups, especially single-parent families with children, households where the head is long-term unemployed or disabled, and the Roma ethnic minority. In the beginning of the decade of the 2000s, the government of Bulgaria and the World Bank reinstated their dialogue on poverty issues, starting with a high-level work- shop opened by the prime minister. The participants—cabinet ministers, the Bank country and social sector teams, the ambassador of the EU delegation to Bulgaria, and the United Nations resident coordinator and the United Nations teams—discussed the findings of the Bank poverty assessment and analytical and advisory work on poverty and living standards in the 1990s. The joint agenda they set for actions focused on the following: Ⅲ Strengthening the social development impact of macroeconomic and sectoral polices Ⅲ Responding to the needs of the vulnerable Ⅲ Establishing institutional arrangements for antipoverty policy development and implementation; ex ante and ex post poverty impact analysis and poverty monitoring and evaluation for antipoverty policy design emerged as one of the main cross-cutting agenda items and one of the main areas of Bank support for the government in the following years In Bulgaria, the poverty mapping methodology and related concepts were first intro- duced by the World Bank in the beginning of the decade of the 2000s in the context of the Bank’s poverty-related analytical work. The Bank’s aim was to advance the policy dialogue with the government based on solid knowledge of poverty at the level of districts (oblasts) and municipalities. The Bank team tasked with the poverty work in Bulgaria conducted a multitopic household survey (MTHS) in April and May 2001, and the National Statistical Institute (NSI) conducted a methodologically similar sur- vey in October and November 2003. The two surveys were used in the preparation of two poverty assessments that were carried out in 2001–02 and 2003–05 (World Bank 2002 and NSI 2006, respectively). Both poverty assessments pointed to the clear regional dimension of poverty in Bulgaria and showed that poverty is a spatially heterogeneous phenomenon with concentration in rural areas. However, aggregated national-level poverty data, as well as an urban-rural breakdown of poverty, obscured considerably the subnational variations at the level of the 28 districts (oblasts) and, most importantly, the 262 municipalities. At the same time, policies and programs to reduce poverty required 10412-05_Ch05.qxd 8/16/07 2:55 PM Page 92 92 GOTCHEVA solid and detailed information about where the poor live and what resources they need to improve their welfare. Because the 2001 MTHS data were representative at the national and district levels, the Bank’s analytical team first suggested, in 2002, testing the small area estimation methodology in the measurement of poverty at the district and municipal levels. In par- allel, the team started engaging the government, the Ministry of Labor and Social Policy (MLSP) in particular, with ideas and proposals about using the results achieved with the small area estimation methodology to design geographically targeted antipoverty policies and to allocate resources for poverty reduction interventions tailored to conditions in the municipalities.2 The MLSP approved the concept of using poverty maps in targeting policies and resource allocations and requested consultancy support in the application of the small area estimation methodology to produce poverty maps because the in-house capacity did not exist at that time. As a result, an international consultant developed the first poverty and inequality maps on Bulgaria in 2003. These maps measured and illustrated mean per capita consumption by municipality, the poverty headcount index and the poverty depth index using upper (two-thirds of the median consumption) and lower (one-half of the median consumption) relative poverty lines, and the Theil mean log deviation index and the Theil entropy index by municipality (see Ivaschenko 2004). After the collection of more recent household consumption data at the end of 2003, the poverty mapping exercise was replicated in 2004–05. The objective of this chapter is twofold. First, it aims to introduce and to discuss the Bulgarian experience in the development of poverty maps and to reflect on the use of the maps in policy making and on the range of policy decisions influenced by the maps. Second, it aims at drawing lessons with regard to process (what is involved in prepar- ing the maps and understanding how to apply them) and with regard to the areas of application and the effective use of the maps in taking policy decisions. The chapter is organized as follows. The next section provides background on how the idea to produce poverty maps evolved in Bulgaria. The subsequent section reviews the technical aspects of the elaboration of poverty maps, but without considering method- ological and technical issues in detail. The following section summarizes the main find- ings of the analysis of the spatial distribution of poverty. The section thereafter describes the users of poverty map, the ways in which the poverty mapping results have been applied in the country, and the impact of the maps on policy. The penultimate section examines the determinants of the long-term sustainability of poverty mapping in Bulgaria. The chapter concludes with a brief outline of the lessons learned. Background The first poverty maps in Bulgaria were developed on the initiative of the World Bank in 2003 using the data collected in April and May 2001 through the Bulgaria Integrated Household Survey (BIHS), the first MTHS. The desire to improve the quality of the 10412-05_Ch05.qxd 8/16/07 2:55 PM Page 93 THE POVERTY MAPPING EXERCISE IN BULGARIA 93 analysis of the regional dimensions of poverty drove that effort. The World Bank hired an international consultant to apply the methodology developed by Elbers, Lanjouw, and Lanjouw (2002) to obtain accurate estimates of consumption-based poverty and inequality at the disaggregated district level by combining census and household (con- sumption) survey information. The NSI provided access to the anonymized household- unit data from the 2001 Population and Housing Census, as well as support with data processing during the preparation of the maps. The consultant linked the 2001 census data to the household-unit data from the 2001 BIHS. For the data processing, the con- sultant applied the special-purpose World Bank software developed in SAS (originally known as Statistical Analysis System software) by Gabriel Demombynes. A report sum- marized the estimated poverty and inequality indicators at the district (28) and munic- ipal (262) levels for 2001, together with the set of corresponding maps. It also provided sufficient technical details on the process of poverty mapping to allow the mapping steps to be replicated (see Ivaschenko 2004). Policy makers recognized the analytical value of the first municipal-level poverty maps, and these maps were included among the crite- ria for ranking municipalities by poverty status in assessing the eligibility of municipali- ties for social infrastructure project financing through the Social Investment Fund (SIF). The development of the second set of poverty maps became a joint effort of the World Bank and the government. The effort was driven by the desire to update the analysis of the regional dimensions of poverty using more recent household consump- tion data and to test whether a team of national experts would be able to apply the small area estimation methodology. For this purpose, a joint team composed of staff at the MLSP, the NSI, and the World Bank, along with representatives of academic institu- tions (the Institute of Economics of the Bulgarian Academy of Sciences, the University of National and World Economy, and the University of Sofia), was set up under the leadership of Mariana Kotzeva, a statistician and econometrician.