Poverty and Inequality Mapping in

Final Report

Oleksiy Ivaschenko January 2004

Acknowledgements:

I am very grateful to people from the National Statistical Institute (NSI) of Bulgaria for their help in producing the poverty and inequality maps. I am especially thankful to Rositza Balakova, Dora Mircheva, Svetla Liamova, and Lilia Miteva. The NSI director Alexander Hadjiiski played an instrumental role in providing access to the Census data. I would also like to acknowledge very useful comments provided by a referee (Mr. Petkov) on an earlier version of this report. My special thanks go to Gero Carletto and Peter Lanjouw from the World Bank for their guidance during all stages of this work. Table of Contents:

I. Introduction II. Zero Stage work: looking for a set of common variables in the Census and the BIHS II. a) Explaining zero stage work II. b) The results of zero stage work III. First stage: estimating the model of household per capita consumption using BIHS data IV. Second Stage: Predicting household per capita consumption using the Census data V. Poverty and inequality estimates for various geographical units VI. Conclusions References

Appendix A. Establishing the comparability of variables in the Census and the BIHS Appendix B. Modeling heteroscedasticity in the household component of the residual Appendix C. Poverty and Inequality measures Appendix D. Estimates of poverty and inequality for districts and municipalities

Appendix E. Poverty and Inequality Maps

1 I. Introduction

The lack of reliable information about the welfare of population at the level of districts and municipalities in Bulgaria has been a constraining factor in the design, implementation and evaluation of economic and social programs that would be targeted at regional development. Although the Population and Housing Census (PHC), that was successfully conducted by the National Statistics Institute of Bulgaria (NSI) in 2001, provides comprehensive information on the household socio-demographic conditions, dwelling conditions, and individual characteristics of household members (such as age, education, employment status, etc.), it does not have the information necessary to construct the consumption or income aggregate. At the same time, the Bulgaria Integrated Household Survey (BIHS), conducted by the Gallup International during the period of April-May 2001 using the pre-census listing to draw a nationally-representative sample of 2,500 households, made it possible to construct a reliable consumption-based welfare measure. However, due to a relatively small sample size this survey does not allow one to obtain reliable welfare estimates at a more disaggregated level than city (capital), other urban, and rural. The main objective of the poverty and inequality mapping in Bulgaria is to produce the estimates of poverty and inequality that would be representative at the level of 28 districts and 262 municipalities. The poverty mapping work is based on a methodology developed by C. Elbers, J. Lanjouw and P. Lanjouw (2002a), which allows one to get accurate estimates of the consumption-based poverty and inequality at the disaggregated regional level by combing the information from the Census and the household (consumption) survey. This methodology involves three major steps. The main purpose of zero stage work is to select a set of variables that are common to the Census and the BIHS. In the first stage the subset of variables that are found to match (contain the same information) between the Census and the BIHS is used to estimate the regression model of per capita consumption using the BIHS data. In the second stage, the obtained set of parameter estimates from the consumption model is applied to the similarly defined variables in the Census to obtain the predicted per capita consumption for each census household. Based on the estimated level of per capita consumption, the estimates of poverty and inequality, as well as their standard errors, are calculated for any geographical unit which has sufficient number of households to obtain the reliable estimates. As mentioned above, in this report we focus on the estimates of welfare at the level of districts (with urban/rural disaggregation) and municipalities. However, we also provide estimates for Sofia city, other urban and rural strata (as well as for the whole country) to compare them with those estimates that are obtained directly from the BIHS.

2 The remainder of the report is structured in the following way. Section II describes in a greater detail zero stage work, and presents its findings. Section III is devoted to the estimation of household per capita consumption using the household survey data. Section IV discusses how the welfare estimates are calculated using the Census data. Section V presents the results of estimating poverty and inequality for districts and municipalities of Bulgaria. Section VI concludes.

II. Zero Stage work: looking for a set of common variables in the Census and the BIHS

II. a) Explaining zero stage work

The zero stage work aims at identifying a set of comparable variables in the Census and the BIHS. The high degree of comparability of selected variables is crucial for getting the accurate estimates of welfare. Even when the household survey and the Census have what seem to be identically worded questions, subtle differences in the way the questions are asked, or different ordering of questions may cause the information content of the answers to differ between the two data sources. The comparability assessment essentially involves determining whether the variables are statistically similarly distributed over the households in the Census and the household survey samples. We perform this comparability procedure at the national level, as well as separately for urban (including Sofia city) and rural areas, at which the BIHS was designed to be representative of the population. A set of about 30 candidate common variables covering the household socio-demographic conditions, quality of dwelling, and the characteristics of the household head was initially identified by systematically comparing the Census and BIHS questionnaires, and studying the interviewer manuals for both surveys when necessary (see Table A1, Appendix A for the list of those variables). Initially, the following qualitative criteria were used to select a set of candidate variables: (a) Are the questions identically worded? (b) Are the criteria pertaining to the questions and answers identical (e.g., children are defined as those of age under 15 in both data sets)? (c) Are the answer options identical? (d) Are the interviewer instructions pertaining to the questions identical? In those cases where the number of the answer options differ between the Census and the BIHS (e.g., the construction material of the dwelling), we check whether several categories in one data source could be combined in a way that would make them comparable with a certain category in the other data source. The descriptive statistics (mean, standard deviation, minimum

3 and maximum values) for the selected (or constructed from those) variables that we expect to match between the Census and BIHS is then produced. The next step of the analysis involves the comparison of the descriptive statistics for the set of candidate variables using the Census and the BIHS data to investigate whether the initially selected variables are statically similarly distributed over households in these two data sources. As the main criteria for the extent of the overlap between the two data sources, we test whether the Census mean for a variable lies within the 95% confidence interval around the BIHS mean for the same variable. In those cases where the BIHS mean is found to be outside of the 95% confidence interval, we make every possible effort to understand the sources of discrepancies by going back to the data, and verifying the definitions of the variables by using the questionnaire instructions for both surveys, and talking to the NSI experts who could provide additional explanation on the content of the questions and answer options. In several cases, it was found that with some justifiable adjustments (e.g., re-grouping of the answer categories for the question in the BIHS to get a better fit with a particular category in the Census) the comparability of the variable in the two data sources could be established.1 There have also been identified several variables which due to a different wording (or meaning) of the questions in the two data sources are clearly not comparable. Such variables are excluded from the subsequent analysis.

II. b) The results of zero stage work

The analysis of the comparability of the set of candidate variables between the Census and the BIHS suggests that there is a good match for most of them. The descriptive statistics for the list of common variables in both the Census and BIHS at the national level, and separately for urban and rural areas is presented in Tables A2, A3 and A4, Appendix A. For several variables we have found the comparability to be better at the urban level as compared to the rural one, and vice versa. The main problem identified during the analysis is under-representation of one-person households in the BIHS as compared to the Census (17.7% vs. 22.7% of the total number of households, respectively).2 When analyzing the age structure of one-person households, we have

1 As an example of such an adjustment, it was found that the self-reported ethnicity in the BIHS matches better the ethnicity status in the Census (which is also self-reported) than the verified by the interviewer ethnicity status available in the BIHS data. 2 The main reason for this seems to be driven by the fact that in the BIHS the replacement procedure for households that could not be interviewed due to absence or refusal required that the replacement household would come from the dwelling of the same size (such as a 1 BR apartment), but would not necessarily have the same number of household members. Since one-person households are less likely to be present during the time of the visit, they are under-represented in the BIHS.

4 discovered that the BIHS under-represents young people (age 16-24), and over-represents elderly people (the percentages of single persons in the age group of above 55 are 76.1% and 64.2% in the BIHS and the Census, respectively). The fact that the Census-based means for some variables (e.g., age of the household head) are somewhat outside of the 95% confidence interval around the BIHS means is likely to be driven in part by such an under-representation of one-person households in the BIHS. The found discrepancies for several variables between the Census and BIHS do not represent a problem for the purpose of the poverty mapping work as soon as they are not driven by the differences in the definitions of the variables, and hence do not affect the accuracy of the parameter estimates. The problem is that when the structure of the BIHS in terms of the household size does not perfectly match that of the Census, it might be difficult to judge whether the found discrepancies in the means of some variables (other than household size) are due to this “structural” problem, or because the information content of the variables indeed differs across data sources. As an additional check of variables’ comparability we also calculate the BIHS means using the weights designed to make the household size structure of the BIHS sample to be identical to that of the Census.3 The results of these calculations for urban and rural areas are presented in Tables A5 and A6, Appendix A. Noteworthy, reweighing the BIHS data makes the census mean start falling within the 95% confidence interval of the BIHS mean for 5 variables (beside household size variables) in the urban sample, and 8 variables in the rural samples. The number of variables that after reweighing start falling slightly outside of the confidence interval is 2 and 1 for urban and rural samples, respectively. A good comparability for most variables between the Census and the BIHS provides a basis for the selection of variables that are included in the household per capita consumption regression. It is worth noting that for dummy variables that will be used in the regression analysis we require that their means are not smaller than 3% and not larger than 97%, so that the constructed variables have some variation across households.4 The availability of the extensive data at the level of location points and municipalities should allow for capturing the region- specific effects when estimating the model.

3 See Hoogeveen (2003) for the discussion of the issue of reweighing the data for Uganda to improve the comparability of the survey and the census in dimensions other than household size. 4 The variables with low variation across households (such as the availability of electricity, which is reported by almost all households) generate observations with high leverage in the first stage regressions.

5 III. First stage: estimating the model of household per capita consumption using BIHS data

The first stage work involves modeling household per capita consumption at the level of three domains: Sofia city, other urban, and rural. The number of the domains for the estimation is driven by a relatively small size of the BIHS sample. Estimating the consumption model separately for these areas allows for the differences in the coefficients across domains. The first stage begins with the regression model of household per capita consumption for a household h in location c, where the explanatory variables are restricted to those variables which are found during zero stage work to be the same in the census and the BIHS (and are of course defined in the same way in both data sources), as well as the variables from other data sources (such as the municipality-level variables from the GIS data) which can be linked to both data sources. The regression equation takes the following form:

= ′ + (1) ln ych xch β uch ; where ych is household per capita consumption for household h in location c, xch is the vector of

explanatory variables, and uch is an error term. Noteworthy, since we are interested in the prediction of ych, the potential endogeneity of explanatory variables is not of a concern. We first estimate equation (1) by OLS separately for each of the three domains using the available pool of variables comparable between the census and the BIHS to select a subset of variables specific for each domain that best explains variation in household per capita consumption. Since the BIHS data are self-weighted, no sample weights are used in the estimation. We model the residual term uch as:

= η + ε (2) uch c ch ;

η ε where c is a location component, and ch is a household component of the residual. The η location component c reflects the part of an error term which is due to some location characteristics common to all households in the location. The household component of the ε residual ch reflects unobserved household characteristics which are not correlated with the location effect. It is important to introduce among the explanatory variables in the model some factors which diminish the relative importance of the location effect in order to get as accurate prediction of household per capita consumption as possible. In our analysis we model the location effect at the level of census cluster. To reduce the location effect the means of several variables have been

6 calculated at the level of location point (and the city district for Sofia) using census data, and those of them which best explain the location effect have been added as the explanatory variables to the model.5 To capture the location effect, we have also added to the model a few municipality- level variables which are correlated with the location effects. These variables have been obtained from the administrative data on municipalities. After estimating equation (1) with the variables capturing the location effect the final specification of the model has been decided upon, and the error component diagnostics has been performed. The results of the error diagnostics tests are presented in Table 1. Noteworthy, the importance of the location effect is the lowest for Sofia city. It is significantly higher for other urban, and rural areas. The inclusion in the model of the location means of certain variables from the census, as well as of several municipality characteristics from other data sources (see Table 2 for the list of those variables) helped reduce the location effects somewhat, although they are still considerable in rural and, especially, other urban areas. In the next step of the analysis we have tested for normality in the distribution of the location and household components of the residual. The knowledge of the residuals’ distribution is important when deciding on the form of the distribution from which to draw the simulated errors for the final stage of the estimation. The results of the normality tests are reported in Table η 1. We observe that in terms of the location component c the hypothesis of normality can be rejected for rural area, but cannot be rejected for Sofia city and other urban areas. In terms of the ε household-specific component ch the hypothesis of normality can be rejected for all strata. Since the household component of the model is likely to be heteroskedastic, we allow for 2 heteroskedasticity in the household component of the error by modeling ech as a function of variables that best explain its variation. We choose variables, zch, that best explain variation in

2 ech out of all potential explanatory variables, their squares, and interactions. We estimate a logistic model of the variance of εch conditional on zch, bounding the prediction between zero and

2 a maximum, A, set equal to (1.05) * max{ech }:

e 2 (3) ln[ ch ] = z T αˆ + r ; − 2 ch ch A ech

The results of modeling heteroscedasticity are presented in Table B1, Appendix B.

5 Location point (village, town) and the city district (for Sofia) is the lowest administrative level at which we could link the population census to the BIHS. Since the location effect within a town/village in Bulgaria is likely to be small, the means for the location points should be good proxies for the location effects.

7 T α = ε Letting exp{zch ˆ} B and using the delta method, the variance of ch is estimated as:

− 2 AB 1 AB(1 B) (4) σˆ ε = [ ] + Var(r)[ ] ; ,ch 1+ B 2 (1+ B)3

η ε The variance of c is estimated non-parametrically, allowing for heteroscedasticity in ch (see Appendix 2 of Elbers, Lanjouw and Lanjouw, 2002b). The two variance components are

combined in order to calculate the estimated variance covariance matrix ( Σˆ ) of the overall

residual of the original model. Once Σˆ is calculated the original model is estimated by GLS. We report the results of these GLS estimations in Table 2. Examining the results presented in Table 2, we find that the regression model for rural strata is more successful in explaining the variation in per capita consumption that the one for Sofia city and other urban areas. The adjusted R2 varies from 0.42 for Sofia city to 0.54 for rural strata. In general, age and education of household head, household size and the number of children, as well as the procession of durable goods by the household emerge as strong correlates of per capita consumption. In rural areas the percent of irrigated land as a % of total cultivated land in the municipality is positively related to household welfare. In urban areas the abundance of water resources (which also captures the proximity to the sea) in the municipality is positively related to per capita consumption.

IV. Second Stage: Predicting household per capita consumption using Census data

In the second stage of the analysis the parameter estimates from the regression model estimated above are applied to the census data to generate predicted log per capita consumption for each household in the census. We conduct a series of 100 simulations, where for each ~ simulation we draw a vector of the first stage parameters β from the multivariate normal distribution described by the first stage point estimates (the coefficients of the GLS estimation) and the associated variance-covariance matrix. In each simulation the location component of the η~ ε~ error term c and the household component ch are also drawn. Since for Sofia city and other η urban areas we could not reject the hypothesis of normality in the distribution of c , the location

8 component for these strata is drawn from the respective normal distributions.6 The household components for these strata are drawn from the corresponding empirical distributions since the η hypothesis of normality is rejected. For rural strata the normality of the distributions of both c ε and ch is rejected, and hence for this strata these components are drawn from their empirical

7 ~ η~ distributions using two-stage draws. Having in hand the resulting from each draw values β , c , ε~ and ch , the value of per capita consumption yˆ ch is estimated for each simulation (thus for a set of 100 simulations we have 100 estimated values of per capita consumption) as:

= ()′ ~ + η~ + ε~ (5) yˆ ch exp x ch β c ch ;

Finally, the full vector of simulated per capita consumption, yˆ ch , is used to calculate the mean and standard deviation of each welfare measure (per capita consumption, poverty and inequality) for each spatial subgroup.8 For any given location, the means constitute the point estimates of the welfare measures, while the standard deviations are the standard errors of these estimates.9

V. Poverty and inequality estimates for various geographical units

The imputed values of per capita consumption for each household in the Census are used to calculate poverty and inequality measures for various administrative levels. The main objective of this report is to obtain the estimates of poverty and inequality for 262 municipalities and 28 districts (which consist of municipalities) of Bulgaria, although other levels of aggregation (and not necessarily geographical) are possible. In particular, we obtain the welfare estimates for the three strata (Sofia city, other urban, and rural) at which the modeling of per capita consumption is performed to compare them with the estimates that come directly from the BIHS. To measure poverty, we use the class of Foster-Greer-Thorbecke indices, P(α), with the poverty aversion parameter, α, equal to 0, 1, and 2. These poverty indices are also known as poverty headcount, poverty depth and poverty severity, respectively. To estimate inequality, we

6 Note that drawing the location component for these strata from the empirical distribution (based on the limited number of observations) increases the standard errors of the estimates. 7 For the description of two-stage draws see Demombynes (2002). 8 All estimations have been conducted using a SAS module (July 9, 2003 version) developed by Gabriel Demombynes from the University of California at Berkeley. 9 Because we are interested in measures based on individual-level consumption, these calculations are performed using household size as weights. We thus implicitly assume that consumption is distributed uniformly within households.

9 calculate two measures belonging to the Generalized Entropy class of decomposable inequality measures, GE(0) and GE(1). The methodology of calculating of these poverty and inequality measures is described in detail in Appendix C. To estimate poverty, we use two poverty lines – the lower poverty line which is equal to 46.1 Bulgarian Leva (BLG) per capita per month, and the higher poverty line equal to 61.5 BLG.10 These poverty lines correspond to respectively 1/2 and 2/3 of the mean per capita consumption in the 1997 BIHS expressed in 2001 prices. These poverty lines are used in the Bulgarian Poverty Assessment, and thus provide a basis for comparison of our estimates to those obtained from the BIHS data.11 The use of two poverty lines also allows us to investigate the sensitivity of the poverty rates to the poverty line chosen. However, it is worth noting that the main purpose of the poverty mapping work is not to get the absolute numbers per se (as any poverty line is in a way arbitrary), but to understand which regions are the poorest, and which are the richest (at a given poverty line). Table 3 shows the estimates of the poverty headcount calculated from the census data for Sofia city, other urban, and rural areas, and compares them to the estimates obtained from the BIHS data.12 We observe that the poverty headcount calculated using the Census data falls within the 95% confidence interval of the poverty estimate from the BIHS data for all strata considered. In other words, the census-based predictions are quite comparable to those from the BIHS. Not surprisingly, the share of poor people is the lowest in Sofia city. The poverty headcount in rural areas is twice as high as the poverty headcount in other (without Sofia) urban areas. We report next the census-based estimates of poverty and inequality for 28 districts of Bulgaria where for each district we calculate poverty and inequality for urban and rural areas. Table 4 reports the estimates of per capita consumption, poverty (using the poverty line of 61.5 BGL), GE(0) and GE(1). Table 5 reports the estimates of per capita consumption, poverty (using the poverty line of 46.1 BGL), and the Gini coefficient. Several interesting findings emerge out of these tables. Noteworthy, we observe a substantial variation in the standards of living across Bulgaria. Interestingly, the differences in average per capita consumption and poverty rates are not entirely due to the gap between urban and rural areas, although the poverty indeed is mostly concentrated in the latter. A substantial heterogeneity exists within both urban and rural areas. For

10 Please note that in this preliminary report we report only the estimates that use the higher poverty line of 61.5 BGL. 11 The lower poverty line of 46.1 BGL is also close to other poverty benchmarks used in Bulgaria, such as the guaranteed minimum income (37.4 BGL), minimum social pension (43 BGL), 2.15$ PPP per day (47.9 BGL per month), and MLSP/ILO/UNDP poverty line (54 BGL). 12 The BIHS data are weighted using weights that make the household size structure of the BIHS sample to be identical to that of the Census.

10 instance, in the rural areas of , and districts, 28% of population is found to be poor, while in the rural areas of and only 8% of population is poor. Among urban areas, the districts of Sofia city, and Varna with the poverty headcounts of respectively 3.1%, 5.6% and 5.8% stand out as the most prosperous, while the urban area of Pazardgik with a headcount ratio of 13.2% is the poorest. Nevertheless, it is obvious that the poverty across urban areas does not vary as much as it does across rural ones. Noteworthy, looking at the estimates of inequality we observe that consumption inequality within rural areas is higher than within urban areas, even for the same district. The estimates of poverty (using the poverty line of 61.5 BGL) and inequality for 262 municipalities of Bulgaria are reported in Table D1, Appendix D. At the district level (now we aggregate welfare measures across rural and urban areas within the district), (poverty headcount of 19.5%), (19.3%), Targovishte (18.6%), and (18.1%) are the poorest. Kaynardzha municipality in Silistra district has the lowest welfare among all municipalities. The estimated share of people below the poverty line there reaches 43.8%. The headcount ratios are the lowest for Sofia city (3.2%) and Sofia district (5.3%). They are followed by (7.5%), Ruse (8.9%), Kyustendil (9.3%), (9.1%), Varna (9.2%), Pernik (9.4%), (9.9%), and (9.9%). The estimates of poverty using the poverty line of 46.1 BGL are reported in Table D2, Appendix D. The estimates of per capita consumption and poverty indicate a remarkable heterogeneity in the standards of living across municipalities within a given district. For example, while the average monthly per capita consumption in Burgas municipality (mostly the city of Burgas) is 182.8 BGL, in Ruen municipality it is 96.6 BGL. While only one out of every twenty people in Varna and municipalities of Varna district are poor, one out of every five people are poor in Byala, and municipalities. Noteworthy, a lot of within variation in welfare is observed for almost all districts. Analyzing inequality, we find that inequality is more pronounced in rural areas for all districts of the country (Tables 4 and 5). However, the levels of inequality in Bulgaria are generally not very high. The results of decomposing inequality, measured by the Theil mean log deviation index, into its within and between components at various levels of aggregation are presented in Table 6. Before analyzing these results it is worth noting that, by definition, the contribution of the between component to the total inequality increases with the number of groups. In other words, for the country as a whole all inequality is due to within inequality, while for the individuals all inequality is due to between inequality. Table 6 indicates that GE(0) is equal to 13.2% and 18.1% for urban and rural areas, respectively. The differences in mean levels

11 of consumption between urban and rural areas constitute only 3% of total inequality. Hence, it is inequalities within urban and rural areas that contribute most to explaining total inequality. Inequality between municipalities makes up only 8.7% of total inequality in the country, indicating that, on average, there is a lot of heterogeneity within municipalities.13 Looking separately at urban and rural areas, we discover that inequalities between municipalities account for only about 10% of total inequality. The maps of poverty and inequality at the municipality level are presented in Tables E1-E7, Appendix E. 14

VI. Conclusions

This report describes the recently developed methodology of the small area poverty and inequality estimation, and presents the welfare estimates obtained for the 28 districts and 262 municipalities of Bulgaria using the 2001 Bulgarian Integrated Household Survey (BIHS) and the 2001 Population and Housing Census (PHC). The census-based predictions of the poverty headcount are found to be close to the actually observed in the BIHS levels of poverty (for Sofia city, other urban and rural areas – the level of disaggregation at which the comparison was possible between the two data sources). The findings of this report indicate that: 1) there are substantial differences in poverty levels across the districts and municipalities of Bulgaria -- looking at the districts we find that, when using the poverty line of 61.5 BGL, the poverty headcount varies from a mere 3% in Sofia city to 19% in Razgrad and Kardzhali, while focusing on municipalities we estimate that the share of poor varies from 3% in Sofia city and (Pleven district) to above 40% in Kaynardzha (Silistra district) and Nikola Kozlevo (Shumen district); 2) although poverty is mostly concentrated in rural areas, where on average the share of poor is almost twice as large as in urban areas (excluding Sofia city), there are remarkable differences in welfare within both rural and urban areas; for instance, at the district level the percentage of poor in rural areas differs from about 8% in Pernik and Kyustendil to 28% in Dobrich, Shumen and Targovishte, and the share of poor in urban areas fluctuates from 3% in Sofia city to 13% in and ; 3)

13 This does not preclude the possibility that while some municipalities may have very high levels of inequality, others may have very low levels of it. For example, as Table D1, Appendix D illustrates, while GE(0) reaches 19.13% and 19.98% in municipalities of (Ruse district) and (Pleven district), it equals 10.47% and 11.11% in municipalities of Gabrovo and (both in Gabrovo district), respectively. 14 The produced estimates of poverty and inequality for municipalities are put on the map of Bulgaria using the ARCVIEW 3.2 software. The Geographical Systems Unit at the NSI has this software and the capacity to produce the additional poverty and inequality maps, if necessary.

12 the standards of living are found to vary a lot even across the municipalities of the same district – for example, within Silistra district the poverty headcount differs from 10% in to 44% in Kaynardzha, and within Shumen district it varies from 8.8% in Shumen municipality to 42% in Nikola Kozlevo; 4) Consumption inequality is higher in rural areas for all districts of the country. Measured by the Theil mean log deviation index, inequality reaches 16.3% and 12.6% in rural and urban areas, respectively. The poverty and inequality maps presented in this report have several applications with regard to the potential policy options. First of all, it would be extremely useful to consider the obtained welfare estimates for municipalities as an input in a detailed analysis of specific regional factors associated with poverty and inequality. It is advisable to do some survey work (either qualitative or quantitative), especially in the municipalities identified as the poorest by this report, to see which geographical factors make the regions more likely to be poor. In the context of Bulgaria, where rural areas are found to be both more poor and less equal compared to urban areas, special attention should be paid to identifying the sources of disparities for rural population. The understanding of what makes various geographic areas of the country poor should clearly facilitate the design of more effective poverty reduction efforts. Second, by identifying the pockets of poverty in the country this report provides policy makers with an opportunity of improving the targeting of poverty reduction programs. The finding of substantial spatial variations in poverty across the municipalities of even the same district points out at the importance of looking beyond the district picture for successful targeting. In the districts with very unequal, in terms of welfare levels, municipalities, the projects tailored at addressing, first of all, the needs of a particular municipality (rather than of the whole district) are expected to result in a more efficient use of funds, and the higher rates of poverty reduction. However, when spatial disparities within the district are less pronounced, the emphasis on large scale projects at the district level can also be well warranted. Importantly, no matter which geographical level is chosen for the policy intervention, the estimates of the poverty gap (how far on average the poor are below the poverty line) combined with the population numbers at the municipality or district level, allow policy makers to estimate fairly accurately the costs of various poverty reduction incentives. Third, among the specific policy options utilizing the poverty maps presented in this report would be to set up social funds in the poorest municipalities to improve geographic targeting, as it has already been done in several other countries (The World Bank, 2001, p. 156). Social funds help finance small projects identified and implemented by poor communities, which usually provide cofinancing. They can be used to support income generation projects, upgrade

13 infrastructure, and improve quality of social services available to communities. Microfinance programs can also use geographic targeting based on poverty maps to reach people in need. Also, in municipalities where poverty is linked primarily to high unemployment, some self-targeting schemes, such as public work programs, can be a solution. Finally, the poverty maps can be used to identify where the households in need of cash transfers are most likely to be located. To conclude, this report provides a geographic profile of poverty and inequality in Bulgaria, and this information about the spatial distribution of welfare is believed to be of paramount importance in improving the targeting of various poverty reduction efforts.

References:

Demombynes, G. 2002. “A Manual for the Poverty and Inequality Mapper Module”, Memo. Elbers, Chris, Jean O. Lanjouw, and Peter Lanjouw. 2002a. “Micro-Level Estimation of Poverty and Inequality”, Econometrica, 71(1): 355-64. Elbers C., Lanjouw J. O., Lanjouw P. 2002b. “Micro-level Estimation of Welfare.” Working Paper N. 2911, The World Bank, Washington, D.C. Hoogeveen, H. 2003. “Survey Non-response and Household Size: Implications for Uganda’s Poverty Estimates”, Working Paper, submitted to Economic Letters Journal. Mistianen, J. A., B. Ozler, T. Razafimanantena, J. Razafindravonona, 2002. “Putting Welfare on the Map in Madagascar”, Working Paper.

World Development Report 2000/01: Attacking Poverty. 2001. The World Bank, Oxford University Press: New York.

14 Table 1. Diagnostics of the error component Sofia city Other urban Rural I. Importance of the location effect Without Location Means

Variance of the location effect ηc 0.015 0.037 0.034

Variance of the total residual uch 0.134 0.169 0.168 Relative importance of the location effect 0.108 0.221 0.204 With Location Means

Variance of the location effect ηc 0.012 0.035 0.027

Variance of the total residual uch 0.134 0.169 0.160 Relative importance of the location effect 0.090 0.208 0.168 Number of clusters 76 264 160 II. Test for Normality

Distribution of ηc Shapiro-Wilk 0.986 0.994 0.983 (PrD) (0.150) (0.150) (0.138) Cramer-von Mises 0.046 0.030 0.146 (Pr>W-Sq) (0.025) (0.250) (0.027) Number of clusters 76 264 160

Distribution of εch Shapiro-Wilk 0.984 0.993 0.982 (PrD) (0.121) (<0.010) (<0.010) Cramer-von Mises 0.105 0.186 0.507 (Pr>W-Sq) (0.098) (0.008) (<0.005) Number of observations 380 1320 800

15 Table 2. The results of GLS estimation of the log per capita consumption regression for Sofia, other urban & rural strata Sofia Other urban Rural Signif. Signif. Signif. Variable coefficient level coefficient level coefficient level Constant 6.187 *** 4.647 *** 4.715 *** 0.185 0.227 0.133 Household head characteristics Age of HH head -0.006 *** -0.005 *** -0.003 *** 0.001 0.001 0.001 Male HH head * age of HH head 0.002 *** 0.001 HH head is widowed 0.129 *** 0.043 HH head is single (never married) 0.097 ** 0.050 HH head is Bulgarian 0.146 *** 0.038 HH head has primary education 0.131 *** 0.051 HH head has middle education 0.176 *** 0.051 HH head has secondary general education 0.262 *** 0.066

HH head has secondary technical education 0.199 *** 0.064

HH head has secondary vocational education 0.249 *** 0.062 HH head has secondary technical/vocational education 0.101 *** 0.081 *** 0.041 0.023 HH head has university education 0.123 *** 0.081 *** 0.271 *** 0.037 0.028 0.075 HH head is employed on own farm/land 0.240 *** 0.089 Household demographic characteristics HH size -0.426 *** -0.320 *** -0.262 *** 0.050 0.026 0.024 HH size squared (/100) 0.043 *** 0.024 *** 0.012 *** 0.007 0.003 0.003 Number of children (age 15 and below) -0.079 *** 0.026 Number of children under age 7 -0.041 ** -0.051 ** 0.022 0.031 Number of children above age 7 0.043 ** 0.024 HH has 1 pensioner 0.028 0.033 HH has 2+ pensioners 0.063 *** 0.099 *** 0.028 0.041 Share of adult HH members not working -0.187 *** -0.277 *** -0.207 *** 0.050 0.032 0.042 Share of adult HH members engaged in private business 0.249 *** 0.068 Household living conditions and availability of durables Number of rooms 0.026 *** 0.064 *** 0.010 0.009 Dwelling is built of concrete 0.025

16 0.030 HH uses electricity as a main source of heating in the winter -0.083 *** 0.022 Phone availability 0.192 *** 0.162 *** 0.032 0.026 Freezer availability 0.103 *** 0.056 *** 0.023 0.027 Automatic washing machine availability 0.068 *** 0.116 *** 0.034 0.023 Color TV availability 0.165 *** 0.156 *** 0.200 *** 0.071 0.033 0.027 Video-Recorder availability 0.101 *** 0.096 *** 0.134 *** 0.036 0.023 0.038 Stereo system availability 0.194 *** 0.058 Personal computer availability 0.269 *** 0.163 *** 0.655 *** 0.046 0.047 0.126 Car availability 0.228 *** 0.152 *** 0.150 *** 0.037 0.022 0.029 Location point characteristics Average HH size -0.243 *** 0.063 Share of households living in dwellings built during 1971-1990 0.328 *** 0.097 Share of households living in dwellings built of prefabricated materials/panels -0.207 *** 0.101 Share of households which have phone 0.316 0.197 Share of households which have freezer 0.536 *** 0.244 Share of Roma households -0.186 0.184 Share of households which have no books -0.181 ** 0.100 Municipality characteristics % of rural area (log) 0.074 ** 0.040 % of area under water resources (log) 0.095 *** 0.024 % of area under extraction of natural resources (log) 0.161 *** 0.094 0.060 0.060

% of irrigated land in total cultivated land (log) 0.042 *** 0.012 R-squared adj. 0.420 0.435 0.541 F-value 20.63 38.64 33.46 Pr > F <0.0001 <0.0001 <0.0001 Number of observations 380 1320 800 Note: standard errors are provided in italics; for Sofia city location point refers to city district *** - denotes significance at 1% level; ** - 5% level; * - 10% level

17 Table 3. Poverty headcount by strata (poverty line = 61.5 BGL per month in 2001 prices), % Poverty Poverty headcount, headcount, Strata BIHS Std. Err. 95% Conf. Interval, BIHS Census

Sofia city 2.34 0.78 0.81 3.86 3.12 Other urban 9.25 0.80 7.69 10.81 7.95 Rural 17.72 1.36 15.06 20.39 17.54 Total (all country) 10.85 0.62 9.63 12.07 10.24

18 Table 4. Poverty and inequality in districts, urban/rural (poverty line = 61.5 BGL per months in 2001 prices), % District Population Rural Urban per capita poverty poverty poverty per capita poverty poverty poverty rural urban total consumption headcount, % depth, % severity, % GE(0), % GE(1), % consumption headcount, % depth, % severity, % GE(0), % GE(1), % Burgas 122,832 295,046 417,878 112.47 22.22 6.60 2.9117.72 17.53 173.125.571.24 0.43 14.57 14.76 3.12 1.38 0.54 0.29 1.03 1.12 18.08 1.31 0.30 0.11 1.15 1.21 146,318 189,710 336,028 123.6117.72 4.86 2.02 17.59 17.92 134.91 9.78 2.11 0.72 13.0113.35 4.67 1.66 0.59 0.30 1.24 1.44 10.43 2.54 0.63 0.24 1.03 1.08 Dobrich 70,949 142,315 213,264 99.46 28.69 9.36 4.37 17.80 16.77 130.77 12.03 2.68 0.92 13.29 13.78 2.96 1.84 0.84 0.49 1.20 1.72 17.74 6.24 1.61 0.61 1.23 1.51 Gabrovo 29,170 112,872 142,042 136.42 11.36 3.03 1.26 14.59 14.21143.87 6.52 1.25 0.39 11.35 11.65 5.07 1.54 0.53 0.28 1.22 1.22 18.90 3.09 0.64 0.21 1.08 1.12 81,077 192,824 273,901 123.37 16.91 4.79 2.05 16.3115.89 140.12 9.47 2.07 0.70 13.36 13.66 3.95 1.31 0.49 0.26 1.17 1.25 13.77 2.96 0.75 0.28 1.39 1.45 52,681 101,081 153,762 123.98 15.98 4.82 2.18 15.95 15.18 147.63 9.12 2.08 0.73 13.50 13.68 4.86 1.57 0.57 0.32 1.27 1.31 22.67 4.54 1.23 0.48 0.96 1.14 Kyustendil 54,855 104,832 159,687 140.75 8.81 2.07 0.78 13.84 14.34 134.98 9.62 2.06 0.69 12.25 12.52 5.99 1.43 0.41 0.19 1.26 1.47 15.74 4.38 1.09 0.41 1.24 1.30 Kardzhali 98,055 63,622 161,677 99.61 26.13 7.27 3.05 15.55 15.55 138.38 8.87 1.79 0.57 11.93 12.12 4.11 2.33 0.81 0.40 1.17 1.23 21.90 4.11 0.99 0.36 1.14 1.14 65,910 99,388 165,298 121.8117.10 5.09 2.27 15.94 15.02 148.06 7.94 1.73 0.59 13.40 13.62 3.91 1.67 0.64 0.34 1.19 1.14 13.97 2.18 0.53 0.20 1.06 1.09 Montana 70,680 108,778 179,458 120.86 17.71 5.49 2.53 16.36 15.25 146.189.432.100.72 14.10 14.22 3.92 1.48 0.58 0.34 1.11 1.08 17.91 2.96 0.79 0.31 1.61 1.65 Pazardzhik 131,240 175,908 307,148 130.32 17.58 5.00 2.12 19.4119.87 133.42 13.24 3.12 1.10 14.74 14.70 5.70 1.81 0.66 0.34 1.38 1.64 13.64 3.23 0.93 0.38 1.30 1.27 Plovdiv 202,689 505,917 708,606 144.53 13.50 4.05 1.82 19.15 19.29 148.98 8.49 1.93 0.68 14.46 14.75 5.54 1.27 0.47 0.25 1.42 1.69 9.25 1.76 0.55 0.25 1.17 1.21 Pernik 35,757 113,296 149,053 139.64 8.39 1.91 0.70 12.85 13.16 132.67 9.68 2.03 0.67 11.00 11.06 6.87 1.56 0.42 0.18 1.25 1.38 24.19 5.84 1.43 0.52 1.14 1.13 Pleven 111,904 194,930 306,834 132.28 15.04 4.73 2.20 16.98 15.98 163.86 5.65 1.180.39 13.7114.08 4.68 1.29 0.51 0.29 1.15 1.13 19.36 1.80 0.38 0.13 1.06 1.06 Note: standard errors are reported in italics

19 Table 4. Poverty and inequality in districts, urban/rural (poverty line = 61.5 BGL per months in 2001 prices), %, continued District Population Rural Urban per capita poverty poverty poverty per capita poverty poverty poverty rural urban total consumption headcount, % depth, % severity, % GE(0), % GE(1), % consumption headcount, % depth, % severity, % GE(0), % GE(1), % Razgrad 83,112 67,074 150,186 100.10 27.34 8.11 3.55 16.73 16.43 138.78 9.85 2.150.73 13.37 13.64 4.42 2.48 0.96 0.52 1.36 1.36 16.69 3.23 0.80 0.30 1.40 1.36 Ruse 79,629 182,313 261,942 137.42 14.85 4.33 1.90 18.68 18.78 153.75 6.26 1.29 0.43 12.22 12.59 6.13 1.54 0.58 0.32 1.76 2.04 25.13 3.05 0.65 0.22 0.76 0.88 Sofia district 111,627 158,127 269,754 135.97 11.28 3.11 1.34 14.86 14.89 139.71 9.29 1.99 0.66 13.27 13.46 5.16 1.39 0.45 0.23 1.13 2.14 8.34 1.83 0.50 0.20 0.99 1.08 Shumen 76,958 123,986 200,944 101.11 28.19 8.53 3.78 17.95 17.86 144.94 9.07 2.04 0.7113.28 13.35 3.20 2.18 0.87 0.47 1.36 1.50 22.36 3.45 0.86 0.32 1.03 0.98 Silistra 77,757 62,595 140,352 102.19 25.85 7.88 3.53 16.5115.79 146.158.351.81 0.62 13.26 13.49 5.43 2.59 0.98 0.52 1.38 1.39 18.25 3.31 0.81 0.30 1.05 1.12 Sliven 71,316 141,777 213,093 121.18 24.99 9.10 4.63 23.82 21.87 134.50 12.69 3.00 1.07 14.02 14.03 3.86 1.64 0.93 0.64 1.73 1.60 18.62 5.14 1.51 0.63 1.01 1.14 65,779 71,347 137,126 111.97 16.01 3.77 1.39 12.11 11.97 122.25 11.68 2.36 0.75 11.43 11.66 4.67 2.24 0.65 0.28 1.03 1.05 12.24 3.66 0.89 0.32 1.12 1.13 Sofia city 54,038 1,103,900 1,157,938 184.134.601.08 0.4116.89 18.43 155.87 3.120.530.16 11.18 12.08 11.96 1.22 0.36 0.16 1.84 2.22 6.07 0.82 0.17 0.06 0.84 1.07 115,792 249,426 365,218 123.52 19.30 6.29 2.97 18.93 18.03 143.01 8.34 1.81 0.6112.58 12.81 3.53 1.12 0.46 0.27 1.17 1.31 15.66 3.13 0.78 0.30 1.26 1.31 Targovishte 64,719 71,380 136,099 100.34 28.63 8.58 3.76 17.6117.28 139.94 9.51 2.06 0.70 13.14 13.42 3.39 1.96 0.80 0.44 1.31 1.34 18.83 3.84 0.96 0.36 1.25 1.28 Varna 93,970 361,256 455,226 116.93 22.106.873.11 18.84 18.15 158.80 5.811.180.38 13.3113.75 4.91 1.62 0.71 0.41 1.54 1.56 14.55 1.79 0.39 0.14 1.33 1.41 52,207 76,298 128,505 129.20 13.94 4.02 1.77 15.45 14.89 155.00 7.47 1.59 0.53 13.60 13.95 4.97 1.56 0.53 0.27 1.22 1.30 22.13 4.58 1.19 0.45 1.05 1.19 101,619 138,346 239,965 117.02 18.62 5.50 2.43 16.16 15.66 148.84 7.86 1.67 0.56 13.66 13.98 4.03 1.71 0.63 0.33 1.20 1.29 15.83 2.81 0.65 0.23 1.14 1.28 Veliko Tarnovo 100,792 188,116 288,908 132.76 16.09 4.95 2.24 18.10 17.43 154.91 6.50 1.37 0.45 13.40 13.79 4.09 1.13 0.48 0.28 1.09 1.14 15.84 1.94 0.43 0.15 1.25 1.36 Note: standard errors are reported in italics

20

Table 5. Poverty and inequality in districts, urban/rural (poverty line = 46.1 BGL per months in 2001 prices), % District Population Rural Urban per capita poverty poverty poverty per capita poverty poverty poverty rural urban total consumption headcount, % depth, % severity, % Gini, % consumption headcount, % depth, % severity, % Gini, % Burgas 122,832 295,046 417,878 112.47 11.60 3.22 1.36 31.84 173.72 1.81 0.35 0.11 28.45 3.12 0.97 0.34 0.18 0.92 22.48 0.68 0.15 0.05 1.32 Blagoevgrad 146,318 189,710 336,028 123.61 8.47 2.180.8831.96 131.59 3.180.580.1726.61 4.67 1.06 0.35 0.17 1.08 11.22 1.06 0.22 0.07 1.12 Dobrich 70,949 142,315 213,264 99.46 16.58 4.95 2.1931.57 131.35 4.53 0.90 0.29 28.25 2.96 1.47 0.59 0.32 1.01 17.86 2.89 0.67 0.24 1.30 Gabrovo 29,170 112,872 142,042 136.42 5.22 1.35 0.55 28.53 143.87 1.97 0.35 0.1026.18 5.07 0.92 0.33 0.17 1.14 18.90 1.06 0.20 0.06 1.23 Haskovo 81,077 192,824 273,901 123.37 8.39 2.23 0.92 30.51140.12 3.49 0.68 0.21 28.19 3.95 0.88 0.31 0.16 1.10 13.77 1.34 0.30 0.10 1.41 Yambol 52,681 101,081 153,762 123.98 8.35 2.43 1.07 29.82 147.63 3.59 0.72 0.23 28.24 4.86 0.95 0.37 0.21 1.18 22.67 2.23 0.52 0.19 0.99 Kyustendil 54,855 104,832 159,687 140.75 3.44 0.80 0.30 28.48 134.98 3.46 0.66 0.20 27.08 5.99 0.74 0.21 0.09 1.27 15.74 1.95 0.43 0.14 1.36 Kardzhali 98,055 63,622 161,677 99.6112.74 3.29 1.33 30.12 138.38 2.92 0.53 0.1626.75 4.11 1.49 0.46 0.22 1.10 21.90 1.76 0.37 0.12 1.24 Lovech 65,910 99,388 165,298 121.81 8.85 2.511.09 29.87 148.06 2.92 0.57 0.1828.23 3.91 1.13 0.40 0.21 1.08 13.97 0.94 0.21 0.07 1.05 Montana 70,680 108,778 179,458 120.87 9.57 2.83 1.26 30.09 146.18 3.59 0.71 0.22 28.90 3.92 1.02 0.40 0.22 1.00 17.91 1.43 0.33 0.12 1.53 Pazardzhik 131,240 175,908 307,148 130.33 8.82 2.32 0.94 33.47 133.42 5.52 1.100.3529.58 5.70 1.20 0.40 0.20 1.17 13.64 1.75 0.43 0.16 1.24 Plovdiv 202,689 505,917 708,606 144.53 7.05 2.02 0.88 32.84 148.98 3.32 0.67 0.22 29.28 5.54 0.81 0.29 0.15 1.25 9.25 1.02 0.29 0.12 1.14 Pernik 35,757 113,296 149,053 139.64 3.160.71 0.26 27.45 132.67 3.36 0.63 0.1925.67 6.87 0.77 0.20 0.09 1.33 24.19 2.55 0.53 0.17 1.27 Pleven 111,904 194,930 306,834 132.28 8.23 2.47 1.11 30.51163.86 1.93 0.37 0.1228.62 4.68 0.87 0.35 0.19 1.01 19.36 0.63 0.13 0.04 1.02 Note: standard errors are reported in italics

21 Table 5. Poverty and inequality in districts, urban/rural (poverty line = 46.1 BGL per months in 2001 prices), %, continued District Population Rural Urban per capita poverty poverty poverty per capita poverty poverty poverty rural urban total consumption headcount, % depth, % severity, % Gini, % consumption headcount, % depth, % severity, % Gini, % Razgrad 83,112 67,074 150,186 100.10 14.32 3.911.64 31.07 138.78 3.62 0.71 0.22 28.23 4.42 1.73 0.61 0.31 1.20 16.69 1.42 0.31 0.11 1.35 Ruse 79,629 182,313 261,942 137.42 7.57 2.09 0.89 32.57 153.75 2.11 0.40 0.1227.01 6.13 1.01 0.38 0.20 1.51 25.13 1.07 0.21 0.07 0.81 Sofia district 111,627 158,127 269,754 135.97 5.33 1.45 0.62 29.03 139.71 3.36 0.63 0.1928.16 5.16 0.77 0.26 0.13 1.08 8.34 0.94 0.22 0.07 1.02 Shumen 76,958 123,986 200,944 101.11 15.154.19 1.76 32.19 144.94 3.49 0.70 0.23 28.04 3.20 1.57 0.55 0.29 1.20 22.36 1.53 0.34 0.12 0.96 Silistra 77,757 62,595 140,352 102.19 13.90 3.93 1.68 30.63 146.15 3.05 0.60 0.1928.12 5.43 1.77 0.61 0.31 1.26 18.25 1.41 0.31 0.11 1.06 Sliven 71,316 141,777 213,093 121.18 15.81 5.33 2.57 35.89 134.50 5.29 1.08 0.34 28.83 3.86 1.44 0.77 0.49 1.19 18.63 2.79 0.71 0.26 1.04 Smolyan 65,779 71,347 137,126 111.97 6.411.41 0.50 26.76 122.25 3.84 0.68 0.20 26.30 4.67 1.20 0.31 0.13 1.11 12.24 1.59 0.34 0.11 1.25 Sofia city 54,038 1,103,900 1,157,938 184.13 1.81 0.42 0.1531.60 155.87 0.75 0.13 0.04 26.07 11.96 0.65 0.19 0.08 1.67 6.07 0.27 0.06 0.02 0.97 Stara Zagora 115,792 249,426 365,218 123.52 11.04 3.36 1.51 32.32 143.01 3.07 0.59 0.18 27.30 3.53 0.78 0.32 0.19 1.02 15.66 1.40 0.31 0.11 1.31 Targovishte 64,719 71,380 136,099 100.34 15.30 4.16 1.73 31.95 139.94 3.48 0.67 0.21 28.00 3.39 1.48 0.53 0.28 1.13 18.83 1.71 0.37 0.13 1.27 Varna 93,970 361,256 455,226 116.93 12.173.48 1.49 32.61158.80 1.93 0.36 0.11 28.20 4.91 1.24 0.49 0.27 1.32 14.55 0.67 0.14 0.04 1.42 Vidin 52,207 76,298 128,505 129.20 6.92 1.95 0.84 29.50 155.00 2.64 0.50 0.16 28.52 4.97 0.93 0.32 0.16 1.16 22.13 2.15 0.48 0.17 1.08 Vratsa 101,619 138,346 239,965 117.02 9.59 2.69 1.1530.18 148.84 2.77 0.53 0.1728.61 4.03 1.13 0.38 0.19 1.12 15.83 1.12 0.23 0.08 1.20 Veliko Tarnovo 100,792 188,116 288,908 132.77 8.71 2.511.08 31.75 154.92 2.25 0.43 0.13 28.29 4.09 0.83 0.34 0.19 0.95 15.84 0.73 0.15 0.05 1.30

Note: standard errors are reported in italics

22 Table 6. Decomposition of the Theil Mean Log Deviation Index (GE(0)) Number of Level of geographic Within-group Between-group % between-group decomposition units inequality, % inequality, % inequality Bulgaria (total) 1 14.73 0.00 0 Urban/rural 2 14.28 0.45 3.1 District 28 14.47 0.26 1.8 Municipality 262 13.47 1.26 8.7 Urban 1 13.20 0.00 0 District 28 12.93 0.27 2.0 Municipality 213 11.94 1.26 9.7 Rural 1 18.14 0.00 0 District 28 17.28 0.86 4.7 Municipality 255 16.23 1.91 11.1

23 Appendix A. Establishing the comparability of variables in the Census and the BIHS

Table A1. The set of candidate common variables in the Census and the BIHS CENSUS HOUSEHOLD SURVEY Household (HH) head characteristics 1 Age of HH head (Section “Population”, Q. 2 & Q. 8) Age of HH head (Section 1, Q. 2 & Q. 4) 2 Sex of HH head (Section “Population”, Q. 2 & Q. Sex of HH head (Section 1, Q. 2 & Q. 3) 10) Dummy variable (1 – male, 0 – female) 3 Education of HH head (Section “Population”, Q. 2 Education of HH head (Section 1, Q. 2 & Section 3, & Q. 18a & Q. 18b) Q. 3) Dummy variable for each education level in Q.18a and Q. 18b (1- if a given level of education, 0 – otherwise); except code 13 (child)

No education: codes 12 No education: codes 00, 01 Primary: 10, 11 Primary: 31-34 Middle: 08,09 Middle: 41-44 Secondary general: 07 Secondary general: 51-53 Secondary technical: 05 Secondary technical: 61-65 Secondary vocational: 06 Secondary vocational: 71-75 University+: 01, 02, 03, 04 University+:81-93 4 Marital Status of HH head (Section “Population”, Q. Marital Status of HH head (Section 1, Q. 5) 12 & Q. 13) Dummy variable for each marital status (1- if a given marital status, 0 – otherwise); Single [p.1, Q. 13)] Single (Never Married) – p.6, Q. 5 Cohabiting (p.2 + p.3, Q. 13) Cohabiting - p.2, Q. 5 Married (p.2, Q. 12) Married - p.1, Q. 5 Widowed (p.3, Q. 12) Widowed - p.5, Q. 5 Divorced (p.4, Q. 12) Divorced/Separated - p.3 + p.4, Q. 5 5 Ethnicity of HH head (Section “Population”, Q.2 & Ethnicity of HH head (Section 1, Q. 2 & Section 11, Q. 14) Q. 1) Dummy variable for each ethnicity (1- if a given Bulgarian – p.1, Q.1 ethnicity, 0 – otherwise): Bulgarian, Turkish, Roma Turkish – p.2, Q.1 (Gypsy), Other Roma – p.3, Q.1 Other – p.4+, Q.1 6 Mother tongue of HH head (Section “Population”, Mother tongue of HH head (Section 1, Q. 2 & Section Q.2 & Q. 15) 3, Q. 1) Dummy variable for each mother tongue (1- if a Bulgarian - p.1, Q.1 given mother tongue, 0 – otherwise): Bulgarian, Turkish – p.2, Q.1 Turkish, Roma (Gypsy), Other Roma – p.3, Q.1 Other - p.4+, Q.1 7 Religion of HH head (Section “Population”, Q.2 & Religion of HH head (Section 1, Q. 2 & Section 11, Q. 16) Q. 7) Dummy variable for each religion (1- if a given Christian Orthodox – p.1, Q.17 religion, 0 – otherwise Catholic - p.2+p.3, Q. 17 Christian Orthodox – p.1, Q.16 Protestant - p.4+p.5, Q. 17 Christian Catholic – p.2, Q.16 Muslim – p.6, Q. 16 Protestant – p.3, Q.16 Other – p. 7+p.8+p.9, Q.16 Muslim – p.4+p.5, Q. 16 Other – p. 6+p.99, Q.16 8 Employment Status of HH Head (Section Employment Status of HH head (Section 1, Q. 2 & “Population”, Q. 2 & Q. 19) Section 6.1, Q. 1); Dummy variable for working or not working (1 – if Dummy variable for working or not working (1 – if working, 0 – not working); working, 0 – not working); Working – pp. 1-5, Q. 19 Not working – p. 6, Q. 19

24 9 Type of employment of HH head (Section Type of employment of HH head (Section 1, Q. 2 & “Population”, Q. 2 & Q. 19) Section 6.1, Q. 3); Dummy variable for each type of employment (1 – if this type, 0 – otherwise); Wage employment – p.1, Q.19; Wage (hired) employment – pp.1-3, Q.3 Own farm (own production for the market or self- Own farm (agricultural worker) – p.5, Q. 3 consumption) – p.2 & p.4, Q. 19; Own business – p. 4, Q. 3 Own business – p. 3, Q. 19; Helping family/friends – p6, Q.3 Not working – p.6, Q. 19; Not working – “No”, Q. 1 Household (HH) socio-demographic characteristics 10 HH size (Section “Population”, Q. 2a); HH size (Section 1, Q. 11, p. 1) Note: it may be necessary to exclude individuals who are “temporarily” absent for more than 3 months (use Section “Population”, Q. 5 to identify those) to make the HH definition comparable to that in the Household Survey 11 Number of pre-school children (age <8) (Section Number of pre-school children ( age <8) (dummies “Population”, Q. 8) for 0, 1, 2, >2 children) (Section 1, Q. 4) Dummy variable for the number of children (0, 1, 2, >2 children) Example: 0 children – 1 if yes, and 0 otherwise; and the same for all other categories 12 Number of children of school age (8 to 15 incl.) Number of children of school age (8 to 15 incl.) (Section “Population”, Q. 8) (dummies for 0, 1, 2, >2 children) (Section 1, Q. 4) Dummy variable for the number of children (0, 1, 2, >2 children) 13 Number of (not employed) old-age pensioners Number of (not employed) old-age pensioners (Section “Population”, Q. 19b, p. 3) (Section 6.1, Q. 6, p. 7) (dummies for 0, 1, 2 , >2) Dummy variable for the number of pensioners (0, 1, 2, >2) Note: may need to exclude here disability pensioners (Section “Population”, Q. 28) 14 Presence of a disabled person (Section “Population”, Presence of a disabled person (Section 6.1, Q. 6, p. 3; Q. 28) or Section 8.4, p.1) Dummy variable for having a disabled person (1 - Dummy variable for having a disabled person (1 - yes, 0 – no) yes, 0 – no) Yes – pp. 2-4, Q. 28; No - pp. 1, Q. 28; 15 The highest level of education achieved by anyone The highest level of education achieved by anyone in in a household (Section “Population”, Q. 18a and a household (a dummy variable for each level of Q.18b) education) (Section 3, Q. 3) 12 categories (in Q. 18a and Q.18b, except “child”) should be grouped into 7 categories as follows: No education: codes 00, 01 1,2,3:1; 4:2; 5,6,8:3; 7:4; 9:5; 10,11:6; 12:7 Primary: 31-34 Dummy variable if anyone in a HH achieved a given Middle: 41-44 level of education (1-yes, 0-no) (construct a dummy Secondary general: 51-53 for each category above) Secondary technical: 61-65 Secondary vocational: 71-75 University+:81-93 16 Number of non-working HH members (Section Number of non-working HH members (Section 6.1, “Population”, Q. 19) Q. 1) Not working – p.6, Q. 19 HH Dwelling Conditions and Assets 17 Material of which the building was constructed What is the main material of the walls of the (Section “Building”, Q. 4) dwelling? (Section 4, Q. 21) 8 categories should be grouped into 6 as follows 1:1, 7 categories grouped into 6: 1:1, 2:2, 3:3, 4:4, 5:5, 2:2, (3,4,5):3, 6:4, 7:5, 8:6) (6,7):6 Dummy variable for each construction material (1 – Dummy variable for each construction material (1 – if if this material, 0 – otherwise) this material, 0 – otherwise) Example: Category 3 (bricks or stones – pp. 3-5, Q. (prefabricated elements, concrete, stone/bricks, wood, 4) – 1 if built of those, 0 – otherwise; and similarly adobe, other) for each category

25 18 Age of the building (2001-year of construction) What is the approximate age of the dwelling? (Section (Section “Building”, Q. 3) 4, Q. 20) 19 Number of rooms (excl. entrance hall) (Section How many rooms (excluding toilets, hallway and “Dwelling”, Q. 4) – 1 (kitchen) – 1 (toilet); kitchen) are used by your household? (Section 4, Q. Note: the work with data would be needed to see if 5) this adjustment works in terms of comparability with the variable in the BIHS 20 Total residential area (Section “Dwelling”, Q. 5, p. What is the area used by your HH? (Section 4, Q. 4); 10) Note: one needs to check whether there is a significant difference in the answers to Q.4 and Q.3) 21 Does the dwelling have electricity supply? (Section How many hours a day was electricity available on an “Dwelling”, Q. 9) average day this past week in this dwelling? (Section Dummy variable (1 – yes, 0 –no) 4, Q. 34) Dummy variable (0 – if 0 hours, 1- if otherwise) 22 Does the dwelling have water supply? (dummy) How many hours a day was water available on an (Section “Dwelling”, Q. 10) average day this past week in this dwelling? (Section Dummy variable (1 – yes, 0 –no) 4, Q. 35) Dummy variable (0 – if 0 hours, 1- if otherwise) 23 Does the dwelling have sewage system? (Section What is the waste disposal system in this dwelling? (3 “Dwelling”, Q. 11) categories) (Section 4, Q. 37) 3 categories should be grouped into 2 as follows: 3 categories grouped into 2 as follows: 1:1, (2,3):2 1:1, (2,3):2 Dummy variable for availability of public sewage Dummy variable for availability of public sewage system (1 – if public sewage, 0 – otherwise) system (1 – yes, 0 –no) 24 What does the household use for heating? (Section What is your main source of energy for heating in the “Dwelling”, Q. 15) winter? (Section 4, Q. 33) 7 categories (except category 8) should be grouped Dummy variable for 5 categories (1 – if this source of into 5 as follows 1:1, 3:2, 4:3, 5:4, 6,7, 2:5) heating, 0 – otherwise): district heating, electric Dummy variable for each heating category (1 – if heating, wood/coal fire, oil, other (gas) this category, 0 – otherwise) 25 Is there a lavatory inside the dwelling? (Section Is the toilet inside or outside the dwelling? (Section 4, “Dwelling”, Q. 12); Q. 24) Dummy variable (1 – yes, 0 –no) 3 categories grouped into 2 as follows: (1,2):1, 3:2 Dummy variable for having a toilet inside the dwelling (1 – yes, 0 – no) 26 Availability of telephone (Section “Dwelling”, Q. Is there a telephone in your dwelling? (Section 4, Q. 16, telephone) 42) Dummy variable (1 – yes, 0 –no) Dummy variable for availability of telephone (1 – yes, 0 – no) 27 Availability of durable goods (Section “Dwelling”, Possession of durable goods (Section 9.1, Q.1) Q. 16) Dummy variable (1 – yes, 0 – no) for availability of: Color TV, VCR, Stereo, Computer, Electric/Gas Color TV, VCR, Stereo system, Personal computer, stove, Automatic Washing Machine, Dish Washer, Electric Gas stove, Automatic Washing Machine, Refrigerator, Freezer, Car Dish Washer, Refrigerator, Freezer, Car Dummy variable for each of those (1 – yes, 0 – no) Notes: Q. – question, p. – point (answer option); Example: Age of HH head (Section 1, Q. 2 & Q. 4) means that HH head status can be identified from Section 1, Q. 2, and age can be identified from Section 1, Q. 4; the same for other variables.

26

Table A2. Descriptive statistics of the variables from the BIHS and Census National level BIHS Census

Variable Mean Std. Dev. l95b u95b Mean Characteristics of the household (HH) head Age, years 54.479 15.762 53.861 55.097 52.950 Gender (1 - male, 0 - female) 0.752 0.432 0.735 0.769 0.751 Marital status (dummies): married 0.680 0.467 0.661 0.698 0.628 cohabiting 0.023 0.151 0.017 0.029 0.027 divorced/separated 0.068 0.252 0.058 0.078 0.071 widowed 0.185 0.388 0.170 0.200 0.180 never married 0.044 0.205 0.036 0.052 0.081 Ethnicity (dummies): Bulgarian 0.873 0.333 0.860 0.886 0.879 Turk 0.062 0.234 0.053 0.072 0.076 Roma/Gypsy 0.044 0.224 0.036 0.052 0.030 Other 0.016 0.126 0.011 0.021 0.015 Mother tongue/native language (dummies): Bulgarian 0.891 0.312 0.879 0.903 0.883 Turk 0.061 0.240 0.052 0.071 0.077 Roma/Gypsy 0.040 0.196 0.032 0.048 0.027 Other 0.008 0.089 0.005 0.011 0.013 Education: No education 0.016 0.126 0.011 0.021 0.015 Incomplete Primary 0.019 0.136 0.013 0.024 0.012 Primary 0.075 0.264 0.065 0.086 0.095 Middle 0.285 0.451 0.281 0.317 0.301 Secondary general 0.140 0.347 0.102 0.127 0.098 Secondary technical 0.180 0.385 0.165 0.195 0.195 Secondary vocational 0.117 0.322 0.102 0.127 0.119 University+ 0.186 0.389 0.161 0.191 0.166 Employment status (1 - employed, 0 - not employed) 0.402 0.490 0.383 0.421 0.405 Employment type: not employed 0.598 0.490 0.579 0.617 0.595 hired employment 0.333 0.471 0.315 0.352 0.320 self-employed, own business 0.048 0.215 0.040 0.057 0.057 self-employed in farming, own farm 0.019 0.137 0.014 0.025 0.030 helping relatives, friends 0.001 0.035 0.000 0.003 0.001 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean.

27 Table A2. Descriptive statistics of the variables from the BIHS and Census (continued) National level BIHS Census

Variable Mean Std. Dev. l95b u95b Mean Household socio-demographic characteristics Urban/Rural Location 0.680 0.466 0.662 0.699 0.683

HH size 2.930 1.583 2.870 2.990 2.686 HH size (dummies): 1 person 0.177 0.382 0.162 0.192 0.227 2 person 0.295 0.456 0.277 0.313 0.284 3 person 0.202 0.402 0.187 0.218 0.216 4 person 0.180 0.384 0.165 0.195 0.180 5 person 0.087 0.282 0.076 0.098 0.058 6 person 0.031 0.174 0.024 0.038 0.024 7+ 0.016 0.163 0.011 0.021 0.012

No. of children age<16 (dummies): No children 0.673 0.469 0.655 0.692 0.705 1 child age 0.193 0.395 0.177 0.208 0.180 2 children 0.110 0.313 0.098 0.123 0.100 3+ children 0.006 0.080 0.003 0.010 0.015

No. of non-working household members 1.566 1.112 1.522 1.609 1.450 No. of (non-working) pensioners (dummies): No pensioners 0.462 0.499 0.443 0.482 0.498 1 pensioner 0.293 0.455 0.275 0.311 0.298 2 pensioners 0.231 0.421 0.214 0.247 0.192 3+ pensioners 0.014 0.118 0.009 0.019 0.012 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean.

28 Table A2. Descriptive statistics of the variables from the BIHS and Census (continued) National level BIHS Census

Variable Mean Std. Dev. l95b u95b Mean Household dwelling conditions and assets (durables) a) dwelling conditions Number of rooms (excl. toilet, hallway and kitchen) 2.714 1.198 2.667 2.761 2.799 Age of the dwelling, years 32.976 18.388 32.243 33.710 33.684 The main material of the dwelling's walls: Prefabricated elements (1-yes, 0-no) 0.243 0.429 0.226 0.260 0.230 Concrete (1-yes, 0-no) 0.169 0.375 0.154 0.184 0.139 Stone, bricks (1-yes, 0-no) 0.530 0.499 0.510 0.549 0.568 Wood (1-yes, 0-no) 0.002 0.045 0.000 0.004 0.002 Adobe (sun-dried brick) (1-yes, 0-no) 0.053 0.224 0.044 0.062 0.059 Other (1-yes, 0-no) 0.004 0.060 0.001 0.006 0.002 Availability of public sewage (1-yes, 0-no) 0.675 0.469 0.656 0.693 0.656 Location of toilet (1-inside dwelling, 0- outside) 0.649 0.477 0.630 0.668 0.664 Availability of telephone (1-yes, 0-no) 0.752 0.432 0.735 0.769 0.738 Main source of energy for heating in the winter: District heating (1-yes, 0-no) 0.150 0.357 0.136 0.164 0.166 Electric heating (1-yes, 0-no) 0.254 0.435 0.237 0.271 0.251 Wood/coal fire/other (1-yes, 0-no) 0.583 0.493 0.564 0.603 0.568 Oil (1-yes, 0-no) 0.008 0.087 0.004 0.011 0.005 Gas (1-yes, 0-no) 0.006 0.077 0.003 0.009 0.005 b) durable goods Electric/gas stove (1-yes, 0-no) 0.852 0.356 0.838 0.866 0.785 Refrigerator (1-yes, 0-no) 0.882 0.322 0.870 0.895 0.842 Freezer (1-yes, 0-no) 0.262 0.440 0.245 0.279 0.255 Automatic washing machine (1-yes, 0-no) 0.452 0.498 0.432 0.471 0.420 Dish washing machine (1-yes, 0-no) 0.008 0.089 0.005 0.011 0.016 Color TV (1-yes,0-no) 0.796 0.403 0.780 0.812 0.784 VCR (1-yes, 0-no) 0.235 0.424 0.219 0.252 0.236 Stereo system (1-yes, 0-no) 0.113 0.317 0.101 0.126 0.132 Personal computer (1-yes,0-no) 0.041 0.198 0.033 0.049 0.042 Car (1-yes, 0-no) 0.339 0.474 0.321 0.358 0.358 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean.

29 Table A3. Descriptive statistics of the variables from the BIHS and Census Urban BIHS Census

Variable Mean Std. Dev. l95b u95b Mean Characteristics of household (HH) head Age, years 52.730 15.495 51.993 53.466 50.379 Gender (1 - male, 0 - female) 0.740 0.439 0.719 0.761 0.745 Marital status (dummies): married 0.678 0.467 0.656 0.701 0.638 cohabiting 0.021 0.144 0.014 0.028 0.025 divorced/separated 0.079 0.269 0.066 0.092 0.090 widowed 0.169 0.375 0.151 0.187 0.148 never married 0.052 0.223 0.042 0.063 0.100 Ethnicity (dummies): Bulgarian 0.931 0.253 0.919 0.943 0.919 Turk 0.035 0.183 0.026 0.043 0.041 Roma/Gypsy 0.024 0.153 0.017 0.031 0.025 Other 0.010 0.099 0.005 0.015 0.015 Mother tongue/native language (dummies): Bulgarian 0.937 0.244 0.925 0.948 0.921 Turk 0.032 0.175 0.023 0.040 0.043 Roma/Gypsy 0.022 0.146 0.015 0.029 0.022 Other 0.010 0.099 0.005 0.015 0.014 Education: No education 0.007 0.084 0.003 0.011 0.010 Incomplete Primary 0.008 0.087 0.003 0.012 0.006 Primary 0.041 0.175 0.031 0.050 0.045 Middle 0.229 0.403 0.209 0.249 0.222 Secondary general 0.135 0.368 0.118 0.151 0.123 Secondary technical 0.215 0.409 0.195 0.234 0.241 Secondary vocational 0.127 0.338 0.111 0.143 0.127 University+ 0.239 0.434 0.219 0.260 0.226

Employment status (1 - employed, 0 - not employed) 0.478 0.500 0.454 0.502 0.460 Employment type: not employed 0.522 0.500 0.498 0.546 0.540 hired employment 0.411 0.492 0.388 0.434 0.386 self-employed, own business 0.056 0.231 0.045 0.067 0.076 self-employed in farming, own farm 0.009 0.097 0.005 0.014 0.007 helping relatives 0.001 0.034 0.000 0.003 0.0003 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean.

30 Table A3. Descriptive statistics of the variables from the BIHS and Census (continued) Urban BIHS Census

Variable Mean Std. Dev. l95b u95b Mean Household socio-demographic characteristics HH size 2.902 1.423 2.830 2.970 2.715 HH size (dummies): 1 person 0.169 0.009 0.151 0.187 0.216 2 person 0.275 0.011 0.254 0.296 0.260 3 person 0.226 0.010 0.206 0.246 0.242 4 person 0.203 0.010 0.184 0.222 0.200 5 person 0.087 0.007 0.074 0.100 0.055 6 person 0.026 0.004 0.019 0.034 0.019 7+ 0.013 0.003 0.008 0.018 0.008

No. of children age<16 (dummies): No children 0.664 0.473 0.641 0.686 0.680 1 child age 0.213 0.409 0.193 0.232 0.207 2 children 0.110 0.313 0.095 0.125 0.101 3+ children 0.002 0.048 0.000 0.005 0.012

No. of non-working household members 1.416 1.036 1.367 1.465 1.311

No. of (non-working) pensioners (dummies): No pensioners 0.526 0.499 0.503 0.550 0.570 1 pensioner 0.269 0.443 0.248 0.290 0.264 2 pensioners 0.196 0.397 0.177 0.215 0.158 3+ pensioners 0.009 0.094 0.004 0.013 0.008 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean.

31 Table A3. Descriptive statistics of the variables from the BIHS and Census (continued) Urban BIHS Census

Variable Mean Std. Dev. l95b u95b Mean Household dwelling conditions and assets (durables) a) dwelling conditions Number of rooms (excl. toilet, hallway and kitchen) 2.539 1.038 2.489 2.588 2.594 Age of the dwelling, years 29.522 17.706 28.667 30.378 28.658 The main material of the dwelling's walls: Prefabricated elements (1-yes, 0-no) 0.352 0.478 0.329 0.375 0.325 Concrete (1-yes, 0-no) 0.205 0.404 0.186 0.224 0.188 Stone, bricks (1-yes, 0-no) 0.416 0.493 0.393 0.440 0.464 Wood (1-yes, 0-no) 0.001 0.024 -0.001 0.002 0.001 Adobe (sun-dried brick) (1-yes, 0-no) 0.024 0.152 0.016 0.031 0.021 Other (1-yes, 0-no) 0.002 0.048 0.000 0.005 0.000 Availability of public sewage (1-yes, 0-no) 0.889 0.314 0.875 0.904 0.886 Location of toilet (1-inside dwelling, 0- outside) 0.867 0.340 0.850 0.883 0.869 Availability of telephone (1-yes, 0-no) 0.827 0.379 0.809 0.845 0.816 Main source of energy for heating in the winter: District heating (1-yes, 0-no) 0.220 0.414 0.200 0.240 0.245 Electric heating (1-yes, 0-no) 0.354 0.479 0.332 0.377 0.358 Wood/coal fire/other (1-yes, 0-no) 0.408 0.492 0.385 0.431 0.380 Oil (1-yes, 0-no) 0.009 0.097 0.005 0.014 0.006 Gas (1-yes, 0-no) 0.008 0.090 0.004 0.013 0.006 b) durable goods Electric/gas stove (1-yes, 0-no) 0.928 0.259 0.915 0.940 0.917 Refrigerator (1-yes, 0-no) 0.924 0.266 0.911 0.936 0.923 Freezer (1-yes, 0-no) 0.270 0.444 0.249 0.291 0.267 Automatic washing machine (1-yes, 0-no) 0.561 0.496 0.537 0.584 0.558 Dish washing machine (1-yes, 0-no) 0.012 0.108 0.007 0.017 0.023 Color TV (1-yes,0-no) 0.863 0.344 0.847 0.879 0.867 VCR (1-yes, 0-no) 0.288 0.453 0.267 0.310 0.307 Stereo system (1-yes, 0-no) 0.145 0.352 0.128 0.161 0.180 Personal computer (1-yes,0-no) 0.057 0.232 0.046 0.068 0.061 Car (1-yes, 0-no) 0.380 0.485 0.357 0.403 0.423 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean.

32 Table A4. Descriptive statistics of the variables from the BIHS and Census Rural BIHS Census

Variable Mean Std. Dev. l95b u95b Mean Characteristics of household (HH) head Age, years 58.203 15.690 57.113 59.292 58.493 Gender (1 - male, 0 - female) 0.777 0.416 0.748 0.806 0.763 Marital status (dummies): married 0.682 0.466 0.650 0.714 0.628 cohabiting 0.028 0.164 0.016 0.039 0.031 divorced/separated 0.046 0.210 0.032 0.061 0.041 widowed 0.218 0.413 0.189 0.246 0.258 never married 0.026 0.160 0.015 0.037 0.042 Ethnicity (dummies): Bulgarian 0.760 0.428 0.730 0.789 0.793 Turk 0.121 0.327 0.099 0.144 0.151 Roma/Gypsy 0.086 0.281 0.067 0.106 0.043 Other 0.033 0.178 0.020 0.045 0.013 Mother tongue/native language (dummies): Bulgarian 0.793 0.405 0.765 0.822 0.802 Turk 0.124 0.330 0.101 0.147 0.152 Roma/Gypsy 0.079 0.270 0.060 0.098 0.037 Other 0.004 0.061 0.000 0.008 0.010 Education: No education 0.035 0.184 0.022 0.048 0.028 Incomplete Primary 0.043 0.202 0.029 0.057 0.024 Primary 0.166 0.374 0.141 0.192 0.202 Middle 0.447 0.498 0.412 0.481 0.469 Secondary general 0.071 0.295 0.053 0.089 0.043 Secondary technical 0.108 0.315 0.086 0.129 0.097 Secondary vocational 0.088 0.283 0.068 0.107 0.099 University+ 0.043 0.208 0.029 0.057 0.038 Employment status (1 - employed, 0 - not employed ) 0.240 0.428 0.211 0.270 0.275 Employment type: not employed 0.760 0.428 0.730 0.789 0.715 hired employment 0.168 0.374 0.142 0.194 0.177 self-employed, own business 0.031 0.174 0.019 0.043 0.077 self-employed in farming, own farm 0.040 0.196 0.026 0.054 0.030 helping relatives 0.001 0.035 -0.001 0.004 0.001 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean.

33 Table A4. Descriptive statistics of the variables from the BIHS and Census (continued) Rural BIHS Census

Variable Mean Std. Dev. l95b u95b Mean Household socio-demographic characteristics HH size 2.990 1.878 2.860 3.120 2.623 HH size (dummies): 1 person 0.194 0.396 0.167 0.221 0.250 2 person 0.338 0.473 0.305 0.371 0.337 3 person 0.151 0.359 0.127 0.176 0.158 4 person 0.130 0.337 0.107 0.154 0.135 5 person 0.088 0.283 0.068 0.107 0.066 6 person 0.041 0.199 0.027 0.055 0.034 7+ 0.058 0.233 0.041 0.074 0.019

No. of children age<16 (dummies): No children 0.693 0.461 0.661 0.725 0.759 1 child age 0.150 0.357 0.125 0.175 0.123 2 children 0.111 0.315 0.090 0.133 0.096 3+ children 0.015 0.122 0.007 0.023 0.023

No. of non-working household members 1.885 1.197 1.802 1.968 1.711

No. of (non-working) pensioners (dummies): No pensioners 0.325 0.469 0.293 0.358 0.343 1 pensioner 0.344 0.475 0.311 0.377 0.372 2 pensioners 0.305 0.461 0.273 0.337 0.267 3+ pensioners 0.025 0.156 0.014 0.036 0.019 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean.

34 Table A4. Descriptive statistics of the variables from the BIHS and Census (continued) Rural BIHS Census

Variable Mean Std. Dev. l95b u95b Mean Household dwelling conditions and assets (durables) a) dwelling conditions Number of rooms (excl. toilet, hallway and kitchen) 3.086 1.414 2.988 3.185 3.137 Age of the dwelling, years 40.388 17.630 39.139 41.637 41.987 The main material of the dwelling's walls: Prefabricated elements (1-yes, 0-no) 0.010 0.100 0.003 0.017 0.009 Concrete (1-yes, 0-no) 0.093 0.290 0.072 0.113 0.027 Stone, bricks (1-yes, 0-no) 0.771 0.420 0.742 0.800 0.806 Wood (1-yes, 0-no) 0.005 0.071 0.000 0.010 0.005 Adobe (sun-dried brick) (1-yes, 0-no) 0.115 0.319 0.093 0.137 0.146 Other (1-yes, 0-no) 0.006 0.079 0.001 0.012 0.006 Availability of public sewage (1-yes, 0-no) 0.218 0.413 0.189 0.246 0.170 Location of toilet (1-inside dwelling, 0- outside) 0.185 0.389 0.158 0.212 0.237 Availability of telephone (1-yes, 0-no) 0.594 0.491 0.560 0.629 0.612 Main source of energy for heating in the winter: District heating (1-yes, 0-no) 0.000 0.000 0.000 0.000 0.001 Electric heating (1-yes, 0-no) 0.039 0.193 0.025 0.052 0.065 Wood/coal fire/other (1-yes, 0-no) 0.956 0.205 0.942 0.970 0.961 Oil (1-yes, 0-no) 0.004 0.061 0.000 0.008 0.002 Gas (1-yes, 0-no) 0.001 0.035 -0.001 0.004 0.002 b) durable goods Electric/gas stove (1-yes, 0-no) 0.690 0.463 0.657 0.722 0.592 Refrigerator (1-yes, 0-no) 0.795 0.404 0.767 0.823 0.759 Freezer (1-yes, 0-no) 0.245 0.431 0.215 0.275 0.255 Automatic washing machine (1-yes, 0-no) 0.219 0.414 0.190 0.248 0.177 Dish washing machine (1-yes, 0-no) 0.000 0.000 0.000 0.000 0.004 Color TV (1-yes,0-no) 0.653 0.476 0.620 0.686 0.649 VCR (1-yes, 0-no) 0.123 0.328 0.100 0.145 0.114 Stereo system (1-yes, 0-no) 0.046 0.210 0.032 0.061 0.045 Personal computer (1-yes,0-no) 0.006 0.079 0.001 0.012 0.005 Car (1-yes, 0-no) 0.253 0.435 0.223 0.283 0.258 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean.

35 Table A5. Descriptive statistics of the variables from the BIHS and Census (reweighing BIHS data to perfectly match the household size structure of the Census) Urban BIHS Census mean Variable Mean Std. Dev. l95b u95b (census) Characteristics of household (HH) head Age, years 53.105 0.383 52.353 53.856 50.379 Gender (1 - male, 0 - female) * 0.715 0.011 0.694 0.737 0.745 Marital status (dummies): married** 0.641 0.012 0.618 0.663 0.638 cohabiting 0.019 0.003 0.013 0.026 0.025 divorced/separated 0.087 0.007 0.074 0.101 0.090 widowed 0.192 0.010 0.173 0.211 0.148 never married 0.061 0.006 0.049 0.072 0.100 Ethnicity (dummies): Bulgarian 0.937 0.006 0.925 0.948 0.919 Turk 0.032 0.004 0.023 0.040 0.041 Roma/Gypsy 0.021 0.003 0.014 0.028 0.025 Other 0.011 0.002 0.006 0.015 0.015 Mother tongue/native language (dummies): Bulgarian** 0.942 0.006 0.931 0.953 0.921 Turk 0.029 0.004 0.021 0.037 0.043 Roma/Gypsy 0.019 0.003 0.012 0.025 0.022 Other 0.010 0.002 0.006 0.015 0.014 Education: No education 0.008 0.002 0.003 0.012 0.010 Incomplete Primary 0.008 0.002 0.004 0.012 0.006 Primary 0.042 0.005 0.032 0.051 0.045 Middle 0.230 0.010 0.210 0.250 0.222 Secondary general 0.134 0.008 0.118 0.151 0.123 Secondary technical 0.212 0.010 0.192 0.231 0.241 Secondary vocational 0.125 0.008 0.109 0.141 0.127 University+ 0.242 0.010 0.222 0.263 0.226

Employment status (1 - employed, 0 - not employed) 0.464 0.012 0.441 0.488 0.460 Employment type: not employed 0.533 0.012 0.509 0.556 0.540 hired employment 0.402 0.012 0.379 0.426 0.386 self-employed, own business** 0.055 0.006 0.044 0.066 0.057 self-employed in farming, own farm 0.009 0.002 0.005 0.014 0.007 helping relatives 0.001 0.001 -0.001 0.002 0.000 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean. **(*) - denotes variables for which the Census mean started (stopped) to fall within the 95% confidence interval of the BIHS mean after reweighing.

36 Table A5. Descriptive statistics of the variables from the BIHS and Census (continued) (reweighing BIHS data to perfectly match the household size structure of the Census) Urban BIHS Census mean Variable Mean Std. Dev. l95b u95b (census) Household socio-demographic characteristics HH size 2.710 0.030 2.650 2.780 2.715 1 person 0.216 0.010 0.196 0.236 0.216 2 person 0.260 0.011 0.239 0.281 0.260 3 person 0.242 0.010 0.222 0.262 0.242 4 person 0.200 0.010 0.181 0.219 0.200 5 person 0.055 0.006 0.044 0.066 0.055 6 person 0.019 0.003 0.013 0.025 0.019 7+ 0.008 0.002 0.004 0.012 0.008

No. of children (dummies): No children 0.696 0.011 0.674 0.718 0.680 1 child age 0.199 0.010 0.180 0.218 0.207 2 children 0.097 0.007 0.083 0.111 0.101 3+ children 0.002 0.001 0.000 0.003 0.012

No. of non-working household members** 1.341 0.024 1.294 1.388 1.311 No. of (non-working) pensioners (dummies): No pensioners 0.528 0.012 0.505 0.552 0.570 1 pensioner 0.283 0.011 0.262 0.304 0.264 2 pensioners 0.181 0.009 0.162 0.199 0.158 3+ pensioners 0.008 0.002 0.004 0.012 0.008 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean. **(*) - denotes variables for which the Census mean started (stopped) to fall within the 95% confidence interval of the BIHS mean after reweighing.

37 Table A5. Descriptive statistics of the variables from the BIHS and Census (continued) (reweighing BIHS data to perfectly match the household size structure of the Census) Urban BIHS Census mean Variable Mean Std. Dev. l95b u95b (census) Household dwelling conditions and assets (durables) a) dwelling conditions Number of rooms (excl. toilet, hallway and kitchen) 2.486 0.025 2.438 2.535 2.594 Age of the dwelling, years 29.626 0.438 28.767 30.485 28.658 The main material of the dwelling's walls: Prefabricated elements (1-yes, 0-no) 0.360 0.012 0.337 0.382 0.325 Concrete (1-yes, 0-no) 0.204 0.010 0.184 0.223 0.188 Stone, bricks (1-yes, 0-no) 0.412 0.012 0.388 0.435 0.464 Wood (1-yes, 0-no) 0.001 0.001 -0.001 0.002 0.001 Adobe (sun-dried brick) (1-yes, 0-no) 0.022 0.004 0.015 0.029 0.021 Other (1-yes, 0-no) 0.002 0.001 0.000 0.005 0.000 Availability of public sewage (1-yes, 0-no) 0.895 0.007 0.881 0.910 0.886 Location of toilet (1-inside dwelling, 0- outside) 0.871 0.008 0.855 0.887 0.869 Availability of telephone (1-yes, 0-no) 0.823 0.009 0.805 0.841 0.816 Main source of energy for heating in the winter: District heating (1-yes, 0-no)** 0.226 0.010 0.206 0.246 0.245 Electric heating (1-yes, 0-no) 0.363 0.012 0.340 0.386 0.358 Wood/coal fire/other (1-yes, 0-no) 0.393 0.012 0.370 0.416 0.380 Oil (1-yes, 0-no) 0.010 0.002 0.005 0.015 0.006 Gas (1-yes, 0-no) 0.008 0.002 0.004 0.013 0.006 b) durable goods Electric/gas stove (1-yes, 0-no) 0.928 0.006 0.916 0.941 0.917 Refrigerator (1-yes, 0-no) 0.922 0.007 0.909 0.934 0.923 Freezer (1-yes, 0-no) 0.259 0.011 0.238 0.280 0.267 Automatic washing machine (1-yes, 0-no) 0.544 0.012 0.520 0.568 0.558 Dish washing machine (1-yes, 0-no) 0.011 0.003 0.006 0.016 0.023 Color TV (1-yes,0-no) 0.856 0.009 0.839 0.873 0.867 VCR (1-yes, 0-no)* 0.279 0.011 0.257 0.300 0.307 Stereo system (1-yes, 0-no) 0.141 0.008 0.125 0.158 0.180 Personal computer (1-yes,0-no) 0.056 0.006 0.045 0.067 0.061 Car (1-yes, 0-no) 0.362 0.012 0.339 0.385 0.423 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean. **(*) - denotes variables for which the Census mean started (stopped) to fall within the 95% confidence interval of the BIHS mean after reweighing.

38 Table A6. Descriptive statistics of the variables from the BIHS and Census (continued) (reweighing BIHS data to perfectly match the household size structure of the Census) Rural BIHS Census mean Variable Mean Std. Dev. l95b u95b (census) Characteristics of household (HH) head Age, years 59.019 0.558 57.923 60.115 58.493 Gender (1 - male, 0 - female) 0.744 0.015 0.714 0.774 0.763 Marital status (dummies): married** 0.632 0.017 0.599 0.666 0.628 cohabiting 0.027 0.006 0.016 0.038 0.031 divorced/separated 0.053 0.008 0.037 0.068 0.041 widowed** 0.257 0.015 0.227 0.287 0.258 never married** 0.031 0.006 0.019 0.043 0.042 Ethnicity (dummies): Bulgarian** 0.783 0.015 0.754 0.811 0.793 Turk 0.117 0.011 0.094 0.139 0.151 Roma/Gypsy 0.071 0.009 0.053 0.089 0.043 Other 0.029 0.006 0.018 0.041 0.013 Mother tongue/native language (dummies): Bulgarian 0.816 0.014 0.789 0.843 0.802 Turk 0.118 0.011 0.096 0.141 0.152 Roma/Gypsy 0.063 0.009 0.046 0.080 0.037 Other 0.003 0.002 -0.001 0.007 0.010 Education: No education 0.034 0.006 0.021 0.046 0.028 Incomplete Primary 0.045 0.007 0.030 0.059 0.024 Primary 0.167 0.013 0.141 0.193 0.202 Middle 0.442 0.018 0.408 0.477 0.469 Secondary general 0.072 0.009 0.054 0.090 0.043 Secondary technical 0.108 0.011 0.087 0.130 0.097 Secondary vocational 0.088 0.010 0.069 0.108 0.099 University+ 0.044 0.007 0.030 0.058 0.038

Employment status (1 - employed, 0 - not employed ) 0.219 0.015 0.190 0.248 0.275 Employment type: not employed 0.768 0.015 0.738 0.797 0.715 hired employment 0.163 0.013 0.137 0.188 0.177 self-employed, own business 0.030 0.006 0.018 0.042 0.077 self-employed in farming, own farm 0.039 0.007 0.025 0.052 0.030 helping relatives 0.001 0.001 -0.001 0.004 0.001 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean. **(*) - denotes variables for which the Census mean started (stopped) to fall within the 95% confidence interval of the BIHS mean after reweighing.

39 Table A6. Descriptive statistics of the variables from the BIHS and Census (continued) (reweighing BIHS data to perfectly match the household size structure of the Census) Rural BIHS Census mean Variable Mean Std. Dev. l95b u95b (census) Household socio-demographic characteristics

HH size 2.630 0.060 2.520 2.730 2.623 1 person 0.250 0.015 0.220 0.280 0.250 2 person 0.337 0.017 0.304 0.370 0.337 3 person 0.158 0.013 0.133 0.184 0.158 4 person 0.135 0.012 0.111 0.159 0.135 5 person 0.066 0.009 0.049 0.083 0.066 6 person 0.034 0.006 0.021 0.047 0.034 7+ 0.019 0.005 0.010 0.029 0.019

No. of children (dummies): No children** 0.750 0.015 0.720 0.780 0.759 1 child age 0.137 0.012 0.113 0.161 0.123 2 children 0.091 0.010 0.071 0.111 0.096 3+ children 0.006 0.003 0.001 0.012 0.023

No. of non-working household members** 1.717 0.037 1.645 1.789 1.711

No. of (non-working) pensioners (dummies): No pensioners 0.310 0.016 0.278 0.342 0.343 1 pensioner 0.379 0.017 0.345 0.412 0.372 2 pensioners** 0.291 0.016 0.259 0.322 0.267 3+ pensioners 0.021 0.005 0.011 0.031 0.019 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean. **(*) - denotes variables for which the Census mean started (stopped) to fall within the 95% confidence interval of the BIHS mean after reweighing.

40 Table A6. Descriptive statistics of the variables from the BIHS and Census (continued) (reweighing BIHS data to perfectly match the household size structure of the Census) Rural

Variable Household dwelling conditions and mean assets (durables) Mean Std. Dev. l95b u95b (census) a) dwelling conditions Number of rooms (excl. toilet, hallway and kitchen)* 3.013 0.049 2.917 3.109 3.137 Age of the dwelling, years** 40.963 0.645 39.698 42.229 41.987 The main material of the dwelling's walls: Prefabricated elements (1-yes, 0-no) 0.010 0.004 0.003 0.018 0.009 Concrete (1-yes, 0-no) 0.094 0.010 0.074 0.115 0.027 Stone, bricks (1-yes, 0-no) 0.773 0.015 0.744 0.803 0.806 Wood (1-yes, 0-no) 0.006 0.003 0.000 0.011 0.005 Adobe (sun-dried brick) (1-yes, 0-no) 0.111 0.011 0.089 0.133 0.146 Other (1-yes, 0-no) 0.005 0.003 0.000 0.010 0.006 Availability of public sewage (1-yes, 0-no) 0.216 0.015 0.187 0.245 0.170 Location of toilet (1-inside dwelling, 0- outside) 0.187 0.014 0.160 0.214 0.237 Availability of telephone (1-yes, 0-no) 0.596 0.017 0.562 0.630 0.612 Main source of energy for heating in the winter: District heating (1-yes, 0-no) 0.000 0.000 0.000 0.000 0.001 Electric heating (1-yes, 0-no) 0.042 0.007 0.028 0.056 0.065 Wood/coal fire/other (1-yes, 0-no) 0.953 0.008 0.938 0.967 0.961 Oil (1-yes, 0-no) 0.004 0.002 0.000 0.009 0.002 Gas (1-yes, 0-no) 0.001 0.001 -0.001 0.004 0.002 b) durable goods Electric/gas stove (1-yes, 0-no) 0.688 0.016 0.656 0.721 0.592 Refrigerator (1-yes, 0-no) 0.795 0.014 0.767 0.823 0.759 Freezer (1-yes, 0-no) 0.229 0.015 0.200 0.258 0.255 Automatic washing machine (1-yes, 0-no) 0.207 0.014 0.178 0.235 0.177 Dish washing machine (1-yes, 0-no) 0.000 0.000 0.000 0.000 0.004 Color TV (1-yes,0-no) 0.640 0.017 0.606 0.673 0.649 VCR (1-yes, 0-no) 0.111 0.011 0.089 0.133 0.114 Stereo system (1-yes, 0-no) 0.045 0.007 0.030 0.059 0.045 Personal computer (1-yes,0-no) 0.005 0.003 0.000 0.010 0.005 Car (1-yes, 0-no) 0.233 0.015 0.204 0.263 0.258 Note: l95b and u95b denote the lower and upper bounds of the 95% confidence interval around the BIHS mean. **(*) - denotes variables for which the Census mean started (stopped) to fall within the 95% confidence interval of the BIHS mean after reweighing.

41 Appendix B. Modeling heteroscedasticity in the household component of the residual

Table B1. The results of modeling heteroscedasticity in the household component of the residual Sofia Other urban Rural signif. signif. signif. Variable coefficient level coefficient level coefficient level Constant -6.537 *** -5.654 *** -5.321 *** 0.565 0.410 0.288 Household head characteristics (Yhat^2) * Age of HH head 0.001 *** 0.000 (Yhat^2) * (HH size^2) 0.002 *** 0.000 (Yhat^2) * Share of households living in dwellings built between 1971 and 1990 0.105 *** 0.026 (Yhat^2) * % of rural area (log) 0.020 *** 0.005 Age of HH head * PC availability -0.043 * 0.026 Age of HH head * Phone availability -0.006 ** 0.003 Age of HH head * HH head has primary education -0.011 *** 0.004 Age of HH head * Share of households in location point which have no books 0.018 *** 0.006 Age of male HH head * CTV availability -0.008 ** 0.003

HH head is Bulgarian * HH head has secondary technical/vocational education -0.924 ** 0.386

HH head has secondary technical/vocational education * PC availability 4.881 *** 1.299 HH head has university education * PC availability 4.137 *** 1.175

HH head has university education * share of HH adults engaged in private business -2.118 *** 0.939 HH head has middle education * Freezer availability -1.234 *** 0.309 HH head has secondary technical education * VCR availability 1.951 *** 0.700 HH head is single * % of rural area (log) -0.132 * 0.085 HH head is widowed * VCR availability 3.703 *** 0.945 (HH size^2) * Share of non-working adults in the HH 0.051 ** 0.022 HH size * Car availability -0.284 ***

42 0.076 Share of non-working adults in the HH * CTV availability 0.560 *** 0.219 Share of non-working adults in the HH * HH uses electricity as a main source of heating in the winter 1.946 *** 0.707 HH uses electricity as a main source of heating in the winter * VCR availability -0.599 *** 0.198

AVM availability * PC availability 4.710 *** 1.338 CTV availability * PC availability -6.971 *** 1.812

CTV availability * Share of households living in dwellings built between 1971 and 1990 -1.873 *** 0.538 CTV availability * % of rural area (log) -0.245 *** 0.065 Car availability * % of irrigated land in total cultivated land (log) 0.466 *** 0.105 R-squared adj. 0.106 0.021 0.069 F-value 6.01 4.49 6.95 Pr > F <0.0001 <0.0001 <0.0001 Number of observations 380 1320 800 Note: standard errors are provided in italics; Yhat refers to predicted consumption from OLS model *** - denotes significance at 1% level; ** - 5% level; * - 10% level

43 Appendix C. Poverty and Inequality measures

FGT Poverty Measures

The FGT class of measures is generally denoted as P(α) and defined as:

N z − y α = 1  i  ()≤ P(α) ∑  I yi z ; N i=1  z 

where N is the population size for which the measure is computed, yi is the level of individual welfare (e.g., real per capita consumption) of the ith individual, z is the poverty line, I(.) is an indicator function that maps a value of 1 when the constraint is satisfied (i.e., per capita consumption is below the poverty line) and 0 otherwise, and α is the poverty sensitivity indicator. When the latter is set equal to zero, the FGT measure becomes what is known as the poverty headcount, the share of people living below the poverty line. The poverty depth, which indicates how far the poor are, on average, below the poverty line, can be measured by letting α=1. The poverty severity, a measure giving a greater weight to poorer people, is computed by setting α=2.

Entropy Class of Decomposable Inequality Measures

The Generalized Entropy class of decomposable inequality measures has been developed by Theil. Within that class, we calculate the Theil mean log deviation index, GE(0), and the Theil entropy index, GE(1):

1 y GE(0) = log i ; N ∑ y

and

1 y y GE(1) = i log i .15 N ∑ y y

where N is the population size for which the measure is computed, yi is the level of individual welfare (e.g., real per capita consumption) of the ith individual, and y is average per capita consumption. Both measures are equal zero for perfect equality. For complete inequality (one person consumes everything), GE(0) goes to infinity while GE(1) reaches n*ln(n). These two inequality measures differ in their sensitivity to inequality in various part of the distribution. GE(0) is most sensitive to inequality in the top range of the distribution, while GE(1) is most sensitive to inequality in the bottom of the distribution.

15 For more details on these inequality measures, please see: http://www.worldbank.org/research/inequality/index.htm

44 Appendix D.D Poverty and inequality in districts and municipalities Table D1. Poverty and. Povertyinequality in districtsand inequality and municipalities in (poverty districts line = 61.5and BGL municipalities per month in 2001 prices) Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % GE(0), % GE(1), % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. Burgas Total 122,832 295,046 417,878 155.29 12.80 10.47 1.01 2.81 0.26 1.16 0.12 16.28 0.86 18.05 0.99 BGS01 9,122 20,969 30,091 124.32 13.18 16.82 4.17 4.45 1.25 1.79 0.54 14.80 0.86 16.48 1.04 Burgas BGS04 14,842 192,296 207,138 182.82 25.47 4.04 1.73 0.90 0.37 0.33 0.13 13.36 0.74 13.94 1.06 BGS06 7,571 9,478 17,049 124.02 10.95 18.04 3.13 5.17 1.10 2.22 0.55 16.13 0.91 16.54 0.91 BGS08 7,141 5,103 12,244 118.56 11.46 20.06 3.70 6.17 1.35 2.81 0.72 16.40 1.38 16.04 1.30 BGS09 9,086 20,206 29,292 146.74 16.08 12.34 2.87 3.36 0.88 1.39 0.39 16.43 0.84 16.58 1.08 BGS12 1,505 2,922 4,427 146.41 15.30 10.22 2.74 2.65 0.87 1.05 0.43 13.90 1.14 14.36 1.24 BGS13 2,913 6,785 9,698 146.82 15.73 9.71 2.90 2.29 0.77 0.85 0.32 13.91 0.96 14.42 1.14 BGS15 8,370 10,549 18,919 150.96 16.95 10.49 2.50 2.96 0.77 1.28 0.39 16.47 1.49 17.22 1.87 BGS17 10,733 16,378 27,111 122.28 12.36 17.18 3.10 4.82 0.97 2.04 0.49 15.19 1.26 16.08 1.45 Ruen BGS18 28,756 28,756 96.60 4.54 27.41 3.10 7.70 1.17 3.24 0.64 15.03 1.63 14.82 1.57 BGS21 9,883 4,330 14,213 140.62 11.95 12.54 2.48 3.53 0.84 1.51 0.43 15.40 1.63 16.34 1.63 BGS23 11,404 3,683 15,087 117.06 6.66 20.57 2.80 5.99 1.06 2.59 0.56 16.77 1.42 16.31 1.51 BGS27 1,506 2,347 3,853 164.73 21.59 9.01 3.70 2.49 1.43 1.05 0.80 15.50 2.17 16.84 2.29 Blagoevgrad Total 146,318 189,710 336,028 129.99 6.23 13.24 1.60 3.31 0.44 1.29 0.19 15.05 0.79 15.36 0.97 BLG01 4,647 8,900 13,547 140.75 16.12 8.51 3.26 1.85 0.81 0.64 0.32 11.97 1.37 12.14 1.80 BLG02 6,290 3,289 9,579 86.48 7.88 34.28 6.21 9.92 2.29 4.20 1.16 13.18 1.43 13.52 1.38 Blagoevgrad BLG03 6,917 69,546 76,463 142.04 21.00 7.44 4.52 1.53 1.02 0.51 0.35 11.77 0.71 12.37 1.09 Gotse Delchev BLG11 12,110 20,288 32,398 127.24 12.93 13.72 3.50 3.42 1.03 1.33 0.49 13.95 1.51 14.61 2.00 Garmen BLG13 14,907 14,907 110.71 8.67 25.05 4.62 7.56 1.80 3.37 0.99 19.35 3.00 19.31 3.15 BLG28 2,315 3,832 6,147 129.67 16.02 11.34 5.27 2.56 1.43 0.92 0.58 12.16 1.62 12.49 2.12 BLG33 27,931 29,198 57,129 140.80 12.53 10.25 2.58 2.43 0.67 0.91 0.26 14.51 1.05 15.03 1.47 BLG37 9,159 12,513 21,672 139.00 14.79 10.07 3.58 2.34 0.96 0.85 0.38 13.21 1.26 13.71 1.73 BLG40 16,124 26,203 42,327 131.53 13.87 11.80 4.38 2.80 1.15 1.04 0.46 13.44 0.99 14.08 1.38 Satovcha BLG42 17,861 17,861 102.29 8.69 24.37 5.30 6.56 1.84 2.67 0.90 14.98 2.31 15.11 2.35 BLG44 8,867 7,020 15,887 120.67 10.27 13.51 3.53 3.27 1.07 1.25 0.50 12.10 1.20 12.05 1.35 Strumyani BLG49 6,304 6,304 118.61 12.43 16.87 4.77 4.75 1.69 2.06 0.90 15.26 3.23 15.12 3.70 BLG52 7,990 2,909 10,899 129.32 11.36 13.28 4.01 3.31 1.28 1.31 0.66 14.62 2.22 14.92 2.42 BLG53 4,896 6,012 10,908 90.74 9.97 31.46 6.34 8.48 2.09 3.36 0.96 12.43 1.19 14.11 1.29 Dobrich Total 70,949 142,315 213,264 120.35 11.87 17.57 4.21 4.90 1.11 2.07 0.44 15.14 0.91 15.72 1.27 DOB03 9,625 12,393 22,018 126.34 14.44 17.52 3.90 5.09 1.19 2.21 0.57 16.17 1.23 16.43 1.43 DOB12 11,184 8,072 19,256 116.74 12.06 18.08 3.15 5.26 0.95 2.29 0.45 14.06 0.93 13.90 0.93 Dobrich DOB15 25,545 25,545 95.13 4.14 31.16 2.54 10.48 1.19 5.00 0.73 17.93 1.68 16.70 3.65 DOB17 4,996 11,290 16,286 134.08 19.51 13.07 4.14 3.44 1.11 1.39 0.44 14.17 0.88 14.45 1.14 Krushari DOB20 5,805 5,805 96.16 8.03 29.90 4.70 9.49 2.14 4.34 1.23 16.62 2.00 15.54 2.01 DOB27 11,446 7,235 18,681 101.73 9.40 28.81 3.78 8.89 1.52 3.96 0.82 16.42 1.27 17.52 1.17 Dobrich DOB28 99,345 99,345 125.54 24.39 12.65 8.85 2.81 2.29 0.96 0.87 11.58 0.73 12.00 0.93 DOB29 2,348 3,980 6,328 172.68 22.89 5.68 2.14 1.28 0.58 0.46 0.24 13.64 1.29 15.03 1.63

45 Table D1. Poverty and inequality in districts and municipalities (poverty line = 61.5 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % GE(0), % GE(1), % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. Gabrovo Total 29,170 112,872 142,042 142.34 15.06 7.52 2.48 1.62 0.52 0.57 0.18 12.02 0.89 12.18 0.96 Gabrovo GAB05 7,739 66,453 74,192 145.60 26.29 6.23 4.11 1.23 0.83 0.40 0.27 10.47 0.52 10.82 0.68 Dryanovo GAB12 2,731 8,601 11,332 137.88 19.22 8.36 4.11 1.76 0.97 0.59 0.35 11.11 0.64 11.18 0.85 GAB29 17,820 24,467 42,287 142.95 17.02 8.94 2.83 2.17 0.67 0.84 0.26 12.60 0.77 12.53 0.89 GAB35 880 13,351 14,231 127.05 18.20 9.29 4.75 1.90 1.06 0.63 0.36 10.27 0.78 10.49 0.91 Haskovo Total 81,077 192,824 273,901 135.16 9.77 11.67 2.12 2.87 0.55 1.10 0.21 14.30 1.04 14.48 1.11 Dimitrovgrad HKV09 16,642 47,634 64,276 135.78 18.29 10.50 4.54 2.49 1.13 0.93 0.43 12.59 0.79 12.69 1.10 HKV11 3,666 4,387 8,053 129.18 15.95 12.33 2.95 3.10 0.78 1.23 0.36 12.34 1.02 13.20 1.09 HKV17 3,201 8,197 11,398 151.40 21.63 8.98 3.42 2.16 0.91 0.81 0.36 13.76 0.97 13.78 1.23 HKV18 1,403 722 2,125 107.13 9.45 20.23 4.45 5.16 1.46 2.03 0.71 12.42 1.55 12.68 1.56 Mineralni Bani HKV19 6,549 6,549 109.39 8.88 21.60 4.72 5.77 1.59 2.32 0.77 15.22 2.58 15.12 2.91 HKV28 6,304 18,833 25,137 154.29 20.96 7.17 3.05 1.64 0.78 0.60 0.30 12.53 0.67 12.75 0.89 HKV29 2,824 7,756 10,580 119.52 16.55 18.81 6.24 4.96 2.03 1.95 0.90 14.89 1.08 14.75 1.57 Stambolovo HKV30 5,776 5,776 110.69 6.23 21.05 3.52 5.70 1.26 2.32 0.63 15.18 1.77 14.72 1.81 HKV32 8,584 6,595 15,179 131.78 14.18 12.64 2.84 3.40 0.82 1.40 0.38 13.20 1.02 13.85 1.04 HKV33 7,450 19,830 27,280 132.51 16.66 13.24 4.19 3.35 1.22 1.30 0.51 14.52 1.09 14.99 2.27 Haskovo HKV34 18,678 78,870 97,548 135.18 22.80 11.10 4.51 2.65 1.11 0.99 0.41 12.74 0.71 12.90 0.95 Yambol Total 52,681 101,081 153,762 139.52 14.99 11.47 3.03 3.02 0.83 1.23 0.34 14.49 0.77 14.59 0.95 JAM03 4,009 1,510 5,519 126.03 9.60 15.40 3.08 4.48 1.08 2.00 0.59 15.34 1.80 14.83 1.76 JAM07 8,120 12,256 20,376 131.41 16.08 13.36 3.35 3.58 0.91 1.47 0.39 13.85 0.87 14.11 1.02 JAM22 9,448 5,804 15,252 122.41 10.24 17.58 3.62 4.90 1.21 2.05 0.57 15.59 1.20 15.17 1.39 Tundzha JAM25 31,104 31,104 127.67 5.96 14.49 1.89 4.38 0.68 2.00 0.38 15.63 1.56 14.87 1.60 Yambol JAM26 81,511 81,511 150.20 28.23 8.43 5.61 1.90 1.51 0.66 0.59 12.75 0.64 13.01 0.81 Kyustendil Total 54,855 104,832 159,687 136.96 10.53 9.34 2.92 2.06 0.73 0.72 0.28 12.81 0.92 13.19 1.06 Bobovdol KNL04 4,751 6,526 11,277 161.63 19.17 4.56 2.49 0.95 0.58 0.32 0.22 10.96 0.89 11.04 1.07 KNL05 2,152 1,489 3,641 136.83 12.94 8.66 3.48 2.00 1.03 0.75 0.51 11.73 1.85 11.82 2.02 KNL27 3,643 2,727 6,370 131.42 13.24 10.75 3.99 2.41 1.10 0.85 0.45 12.06 1.89 12.41 2.24 Kyustendil KNL29 20,432 48,755 69,187 131.71 18.16 10.11 5.32 2.22 1.32 0.77 0.49 11.25 0.59 11.50 0.84 Nevestino KNL31 4,328 4,328 132.28 10.47 11.54 3.27 2.75 0.93 1.04 0.42 14.32 2.68 14.76 3.09 Rila KNL38 621 3,035 3,656 120.04 19.09 12.72 6.84 2.72 1.73 0.92 0.64 10.23 0.95 10.41 1.43 KNL41 4,545 4,407 8,952 154.69 20.59 7.08 3.37 1.65 1.01 0.62 0.47 13.04 2.45 13.45 2.72 KNL48 13,284 37,893 51,177 138.53 20.28 8.96 4.58 1.96 1.14 0.68 0.43 11.85 0.76 12.48 1.12 Treklyano KNL50 1,099 1,099 103.93 11.54 20.25 5.46 5.14 1.79 2.01 0.89 11.75 2.24 11.16 2.19 Kardzhali Total 98,055 63,622 161,677 114.86 8.97 19.34 2.15 5.11 0.62 2.07 0.28 14.70 0.84 15.61 0.90 KRZ02 9,877 3,507 13,384 102.07 8.29 23.19 4.16 6.01 1.24 2.38 0.55 13.25 1.45 13.37 1.52 Dzhebel KRZ08 5,766 2,823 8,589 94.69 7.41 25.28 5.06 6.47 1.45 2.54 0.63 11.70 1.30 11.57 1.41 Kirkovo KRZ14 24,069 24,069 115.26 6.87 19.32 2.97 5.03 1.00 2.01 0.50 16.09 1.88 16.32 2.05 KRZ15 14,563 5,154 19,717 100.37 6.97 25.26 3.09 7.22 1.05 3.11 0.55 14.14 1.06 14.43 1.07 Kardzhali KRZ16 24,085 44,451 68,536 130.07 19.88 14.16 3.70 3.65 0.94 1.46 0.37 13.47 0.68 14.96 0.86 KRZ21 9,184 7,687 16,871 105.86 10.67 19.71 4.66 4.92 1.17 1.91 0.47 11.74 0.88 12.09 0.91 Chernoochene KRZ35 10,511 10,511 89.17 4.84 31.78 3.71 8.99 1.50 3.79 0.84 14.38 1.87 14.19 1.90

46 Table D1. Poverty and inequality in districts and municipalities (poverty line = 61.5 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % GE(0), % GE(1), % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. Lovech Total 65,910 99,388 165,298 137.58 8.54 11.59 1.47 3.07 0.41 1.26 0.18 14.61 0.80 14.72 0.86 LOV02 442 3,543 3,985 148.60 25.40 5.83 4.26 1.09 0.86 0.34 0.28 11.25 0.75 11.99 1.06 LOV17 1,630 3,895 5,525 132.96 17.59 13.99 5.15 3.27 1.43 1.15 0.58 14.70 1.52 14.86 2.02 Lovech LOV18 17,621 42,239 59,860 144.45 18.58 8.29 2.78 2.02 0.65 0.78 0.25 12.20 0.61 12.31 0.77 LOV19 11,125 9,877 21,002 126.73 12.82 18.15 3.84 5.44 1.28 2.44 0.63 17.25 1.46 16.63 1.61 LOV33 12,106 11,025 23,131 116.92 11.61 17.18 4.24 4.40 1.33 1.71 0.61 13.30 1.34 13.44 1.39 LOV34 13,827 22,699 36,526 153.87 17.63 5.95 2.18 1.31 0.47 0.47 0.17 11.61 0.76 12.20 0.98 LOV36 5,370 3,071 8,441 113.07 9.97 20.52 4.95 5.76 1.68 2.43 0.80 15.73 2.28 16.60 2.80 LOV38 3,789 3,039 6,828 121.33 12.79 22.00 3.73 7.52 1.62 3.67 0.99 18.77 1.65 18.23 1.52 Montana Total 70,680 108,778 179,458 136.21 10.96 12.69 1.89 3.44 0.53 1.43 0.23 15.17 1.07 15.15 1.08 MON02 6,962 15,020 21,982 128.48 18.24 12.74 5.88 3.15 1.73 1.22 0.73 12.47 0.78 12.32 0.92 MON04 10,101 1,947 12,048 124.95 8.00 18.72 2.54 5.86 1.03 2.69 0.58 17.41 1.96 16.56 2.01 MON07 5,207 1,594 6,801 133.99 12.60 16.66 3.90 5.18 1.60 2.39 0.90 17.82 2.32 17.03 2.14 MON11 8,272 4,788 13,060 120.60 11.33 21.48 3.99 6.97 1.60 3.28 0.92 18.52 1.92 18.10 1.73 MON12 2,614 7,028 9,642 129.64 21.75 14.16 6.20 3.49 1.92 1.30 0.81 13.51 1.04 13.74 1.62 Georgi Damyanovo MON14 4,217 4,217 129.46 9.64 11.68 3.00 3.07 0.98 1.25 0.50 12.72 1.98 12.11 1.94 Lom MON24 7,138 27,423 34,561 134.75 19.85 12.23 5.64 2.92 1.56 1.08 0.62 13.41 0.94 13.29 1.24 Medkovets MON26 5,585 5,585 116.87 14.16 18.97 5.93 5.98 2.23 2.78 1.20 15.39 3.00 14.03 2.74 Montana MON29 12,143 48,612 60,755 151.17 26.86 8.09 3.38 1.96 0.80 0.76 0.29 12.77 0.71 13.13 1.08 MON36 2,601 2,366 4,967 140.75 15.83 8.50 2.45 2.00 0.69 0.77 0.32 11.64 1.09 12.29 1.11 Yakimovo MON38 5,840 5,840 109.38 12.76 22.18 5.40 6.94 2.00 3.20 1.10 15.80 2.58 14.62 2.36 Pazardzhik Total 131,240 175,908 307,148 132.10 8.18 15.10 2.00 3.92 0.60 1.54 0.26 16.73 0.95 16.89 1.12 Batak PAZ03 3,033 3,998 7,031 115.49 17.49 17.62 7.86 4.47 2.73 1.73 1.31 11.53 1.49 13.73 1.60 Belovo PAZ04 6,489 4,564 11,053 136.69 12.39 9.33 3.96 2.07 1.07 0.73 0.44 12.05 1.45 12.60 1.79 PAZ06 6,686 4,622 11,308 140.69 14.66 11.71 3.85 3.17 1.35 1.32 0.69 14.97 2.51 14.83 2.59 PAZ08 17,887 24,599 42,486 109.35 13.78 21.25 5.33 5.51 1.63 2.13 0.71 13.24 1.26 13.95 1.43 Lesichovo PAZ14 6,521 6,521 119.85 12.22 19.63 5.02 5.52 1.89 2.30 1.00 17.11 3.34 17.17 3.48 Pazardzhik PAZ19 48,956 76,903 125,859 139.47 17.72 13.47 4.12 3.54 1.16 1.41 0.47 16.20 0.93 16.44 1.30 PAZ20 9,799 19,899 29,698 153.70 23.58 7.13 2.73 1.66 0.66 0.61 0.26 11.94 0.81 12.40 0.94 PAZ21 2,619 19,321 21,940 121.70 21.48 17.78 8.50 4.38 2.71 1.59 1.16 13.30 1.04 13.74 1.67 PAZ24 7,382 8,252 15,634 99.26 11.50 28.70 7.87 7.69 3.01 2.97 1.45 14.51 2.49 16.07 3.19 PAZ29 20,640 8,982 29,622 138.84 11.17 14.60 3.30 4.04 1.14 1.68 0.56 17.95 2.07 18.41 2.44 PAZ32 1,228 4,768 5,996 129.86 21.36 11.37 5.75 2.53 1.46 0.87 0.55 11.60 0.82 11.90 1.07

47 Table D1. Poverty and inequality in districts and municipalities (poverty line = 61.5 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % GE(0), % GE(1), % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. Plovdiv Total 202,689 505,917 708,606 147.71 6.79 9.92 1.31 2.54 0.41 1.00 0.19 15.80 0.93 16.03 1.10 PDV01 15,160 51,579 66,739 136.26 18.45 9.56 4.28 2.19 1.02 0.80 0.38 12.00 0.76 12.11 1.01 PDV07 6,658 2,063 8,721 141.11 10.21 12.43 2.32 3.74 0.87 1.69 0.48 15.87 1.71 15.46 1.78 Kaloyanovo PDV12 13,526 13,526 157.12 13.68 9.90 2.14 2.96 0.76 1.33 0.40 17.37 2.94 17.36 3.41 PDV13 29,091 40,415 69,506 122.69 10.19 14.59 3.20 3.98 0.89 1.69 0.39 13.88 1.05 13.48 1.17 Laki PDV15 1,069 2,858 3,927 132.65 17.82 8.43 3.97 1.80 0.87 0.63 0.33 10.49 1.17 10.64 1.56 Maritsa PDV17 32,119 32,119 154.30 10.48 12.22 2.17 3.66 0.79 1.64 0.42 19.79 2.19 20.09 2.58 Plovdiv PDV22 334,005 334,005 150.78 12.50 8.47 2.24 2.01 0.75 0.73 0.35 14.43 1.61 14.60 1.59 PDV23 15,697 15,340 31,037 139.09 13.43 11.62 2.62 3.09 0.77 1.27 0.36 14.49 1.22 14.45 1.39 PDV25 12,084 16,239 28,323 166.42 24.37 10.38 2.76 3.16 1.02 1.44 0.56 17.27 1.92 18.43 2.17 Rodopi PDV26 40,660 40,660 170.27 12.13 7.58 2.20 1.94 0.77 0.78 0.39 18.54 2.69 19.91 3.20 PDV28 13,994 2,582 16,576 131.76 10.70 16.15 3.28 4.84 1.24 2.15 0.65 16.71 2.08 16.36 1.97 Saedinenie PDV33 5,732 6,386 12,118 151.12 15.85 7.81 2.43 1.94 0.64 0.76 0.28 13.19 1.17 13.24 1.44 Hisarya PDV37 7,286 8,153 15,439 185.74 23.41 5.12 1.99 1.28 0.59 0.50 0.27 14.30 1.55 16.00 1.79 PDV39 8,522 8,522 102.43 19.46 22.63 10.83 5.24 3.27 1.78 1.31 10.95 0.89 10.98 0.88 PDV40 5,378 5,378 137.30 28.50 11.26 6.79 2.50 1.77 0.85 0.68 12.65 0.86 12.71 0.96 PDV41 9,613 12,397 22,010 154.68 19.37 10.20 3.11 2.80 0.94 1.18 0.45 15.77 2.04 15.60 2.44 Pernik Total 35,757 113,296 149,053 134.34 18.46 9.37 4.46 2.00 1.09 0.68 0.40 11.45 0.92 11.61 0.98 PER08 4,179 4,312 8,491 120.93 11.61 11.71 3.83 2.52 0.97 0.86 0.38 10.63 0.88 10.77 1.06 PER19 1,882 2,213 4,095 118.17 12.56 13.19 4.32 2.97 1.08 1.07 0.43 10.72 0.87 10.80 0.97 Kovachevtsi PER22 2,128 2,128 130.14 12.27 9.78 4.04 2.19 1.30 0.79 0.67 11.66 2.51 11.63 2.65 Pernik PER32 15,959 88,378 104,337 138.96 25.67 7.97 6.02 1.62 1.44 0.53 0.52 10.30 0.72 10.54 0.90 PER36 8,844 15,642 24,486 127.12 15.65 11.78 6.29 2.67 1.70 0.94 0.67 11.58 0.87 12.36 1.34 Tran PER51 2,765 2,751 5,516 113.40 8.76 18.54 4.97 4.62 1.68 1.73 0.76 13.23 0.95 13.77 1.20 Pleven Total 111,904 194,930 306,834 152.34 12.41 9.08 1.23 2.47 0.30 1.05 0.14 15.13 0.79 15.39 0.85 Belene PVN03 2,563 9,308 11,871 178.05 24.68 3.38 1.83 0.69 0.40 0.24 0.15 11.74 0.84 12.71 1.14 PVN08 12,821 3,825 16,646 151.74 11.17 7.09 2.14 1.66 0.64 0.62 0.30 12.76 1.83 12.88 1.93 Dolna Mitropolia PVN10 16,487 8,655 25,142 139.53 10.91 11.71 2.18 3.33 0.74 1.45 0.39 14.96 1.35 14.79 1.44 Dolni Dabnik PVN11 10,414 4,966 15,380 143.37 13.44 16.51 3.08 5.30 1.22 2.48 0.69 19.98 2.39 20.10 2.49 Levski PVN16 13,747 12,094 25,841 146.42 16.03 10.81 2.61 2.88 0.77 1.19 0.36 14.96 1.21 15.17 1.30 Nikopol PVN21 8,795 4,490 13,285 141.61 11.25 10.90 3.31 2.87 0.97 1.16 0.42 14.27 1.42 14.64 1.71 PVN23 4,976 4,104 9,080 137.18 16.38 11.89 4.41 3.08 1.38 1.24 0.67 13.86 1.67 13.69 1.93 Pleven PVN24 22,213 124,162 146,375 160.69 27.08 6.89 2.41 1.86 0.53 0.80 0.21 13.32 0.72 13.94 0.96 PVN27 5,531 2,329 7,860 140.89 12.31 11.35 3.08 3.08 1.02 1.27 0.51 14.40 1.74 14.22 1.79 PVN37 14,357 20,997 35,354 137.20 14.26 12.67 2.95 3.42 0.86 1.42 0.40 15.35 1.23 15.22 1.38

48 Table D1. Poverty and inequality in districts and municipalities (poverty line = 61.5 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % GE(0), % GE(1), % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. Razgrad Total 83,112 67,074 150,186 117.37 7.84 19.53 1.99 5.45 0.64 2.29 0.31 15.81 0.98 16.69 1.02 RAZ11 8,712 3,493 12,205 92.79 9.31 29.56 6.67 8.46 2.59 3.60 1.36 13.65 2.05 13.70 1.94 RAZ14 15,234 9,762 24,996 104.30 11.54 25.72 4.07 7.46 1.40 3.22 0.71 15.03 1.13 17.12 1.47 RAZ16 14,991 8,896 23,887 116.68 9.39 18.97 4.18 5.20 1.39 2.16 0.68 15.58 1.87 15.55 2.07 RAZ17 12,207 2,596 14,803 113.17 7.95 22.21 3.36 6.53 1.26 2.83 0.68 16.74 1.55 16.60 1.48 Razgrad RAZ26 19,644 38,131 57,775 134.06 18.53 13.18 3.42 3.46 0.92 1.40 0.41 13.80 0.94 15.03 1.04 Samuil RAZ29 7,971 7,971 87.70 7.82 32.59 5.86 9.84 2.21 4.39 1.18 14.68 1.97 14.15 1.97 Tsar Kaloyan RAZ36 4,353 4,196 8,549 114.73 13.67 14.84 6.31 3.35 1.77 1.19 0.76 10.59 1.65 10.50 1.68 Ruse Total 79,629 182,313 261,942 148.79 17.59 8.87 2.17 2.22 0.49 0.87 0.18 14.24 0.75 14.50 1.03 Borovo RSE03 5,131 2,607 7,738 128.54 12.44 16.94 4.60 4.85 1.70 2.08 0.87 16.11 2.08 16.46 2.12 Byala RSE04 6,812 9,910 16,722 145.73 19.36 13.48 2.82 4.07 0.98 1.83 0.53 16.68 1.22 17.73 1.28 RSE05 11,787 6,834 18,621 114.71 9.49 18.79 4.80 4.84 1.68 1.89 0.86 14.48 2.13 14.72 2.27 RSE08 7,215 4,678 11,893 119.47 11.42 17.59 3.99 4.85 1.28 2.02 0.64 14.74 1.46 14.50 1.42 Ivanovo RSE13 11,018 11,018 157.14 14.11 10.11 3.53 3.00 1.33 1.35 0.71 17.53 3.22 17.43 3.28 Ruse RSE27 16,880 158,284 175,164 157.04 26.27 5.49 3.15 1.13 0.67 0.38 0.23 11.88 0.62 12.48 1.02 Slivo Pole RSE33 12,838 12,838 126.94 9.66 19.00 4.28 5.61 1.65 2.45 0.88 19.13 3.14 18.85 3.26 Tsenovo RSE37 7,948 7,948 140.50 12.33 11.34 3.40 3.11 1.15 1.31 0.59 15.41 2.76 15.38 2.99

49 Table D1. Poverty and inequality in districts and municipalities (poverty line = 61.5 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % GE(0), % GE(1), % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. Sofia district Total 111,627 158,127 269,754 138.16 5.33 10.12 1.22 2.46 0.35 0.94 0.15 13.93 0.74 14.05 1.25 SFO06 2,771 5,149 7,920 154.85 17.10 4.67 2.45 0.91 0.54 0.30 0.19 11.19 1.02 11.87 1.45 SFO07 14,004 21,426 35,430 142.68 18.55 9.95 3.10 2.63 0.88 1.08 0.39 13.36 1.08 13.30 1.27 SFO09 1,571 5,012 6,583 137.54 20.75 8.02 3.84 1.66 0.91 0.56 0.34 10.72 0.77 10.91 1.01 Gorna Malina SFO10 6,958 6,958 139.81 11.82 8.97 2.72 2.25 0.83 0.89 0.39 12.37 1.49 12.04 1.52 Dragoman SFO16 2,810 3,732 6,542 136.94 17.32 8.79 3.26 1.94 0.78 0.69 0.30 11.02 0.87 11.12 1.07 SFO17 17,222 6,643 23,865 156.43 13.47 7.17 2.18 1.75 0.62 0.68 0.28 14.27 1.76 14.86 2.11 SFO18 2,223 11,360 13,583 134.12 23.33 10.38 5.31 2.47 1.34 0.93 0.52 11.48 2.05 11.45 4.54 SFO20 5,643 13,466 19,109 129.85 17.60 14.95 5.72 3.71 1.67 1.39 0.68 14.61 1.24 15.13 2.35 SFO24 2,650 2,650 139.61 24.97 8.27 5.04 1.64 1.12 0.52 0.38 11.41 0.84 11.66 0.95 SFO25 5,158 9,926 15,084 123.05 15.38 12.03 5.41 2.85 1.40 1.06 0.56 10.92 1.13 11.05 1.47 SFO26 5,730 12,098 17,828 131.80 17.81 9.06 4.80 1.93 1.12 0.66 0.41 10.50 0.88 10.69 1.12 SFO34 4,027 4,226 8,253 116.85 15.18 20.34 4.04 6.93 1.40 3.44 0.84 16.37 1.31 15.87 1.20 SFO39 14,638 27,230 41,868 133.59 16.51 11.47 4.05 2.71 1.14 0.99 0.45 12.63 0.71 12.56 0.84 SFO43 16,607 8,523 25,130 141.60 14.23 8.08 2.55 1.82 0.61 0.66 0.23 11.70 1.05 11.77 1.13 SFO45 2,440 7,902 10,342 139.99 22.93 7.63 4.32 1.58 0.99 0.53 0.38 10.29 0.81 10.58 0.99 SFO47 885 5,729 6,614 136.27 25.55 9.41 5.13 2.05 1.21 0.70 0.44 10.95 0.78 10.91 1.05 Anton SFO54 1,803 1,803 148.54 30.82 7.82 6.62 1.90 2.06 0.72 0.97 12.24 3.42 13.58 4.62 SFO55 921 8,324 9,245 158.64 29.89 5.70 4.30 1.16 0.99 0.37 0.35 11.13 1.17 11.82 2.77 Mirkovo SFO56 3,095 3,095 130.41 19.95 13.14 5.96 3.44 2.03 1.39 1.01 13.55 2.51 13.35 2.43 Chavdar SFO57 1,420 1,420 128.06 29.41 13.08 8.90 3.46 2.60 1.45 1.22 12.00 4.06 11.94 4.13 Chelopech SFO58 1,701 1,701 139.42 27.96 8.56 7.13 2.00 2.16 0.73 0.98 10.60 3.45 10.83 3.59 SFO59 4,731 4,731 122.62 22.78 14.94 7.72 3.39 2.15 1.16 0.85 12.19 0.77 12.11 0.76 Shumen Total 76,958 123,986 200,944 128.15 13.85 16.40 2.28 4.53 0.63 1.89 0.27 15.71 0.82 16.79 0.93 Venets SHU07 8,012 8,012 85.12 7.78 33.24 7.08 9.51 2.54 4.01 1.29 12.77 2.21 12.22 2.09 SHU10 7,565 3,635 11,200 86.00 6.50 36.82 5.61 10.61 2.28 4.39 1.15 14.76 1.60 15.18 1.87 Hitrino SHU11 7,017 7,017 103.39 7.39 24.04 4.44 6.70 1.65 2.82 0.86 15.33 2.11 15.20 2.26 SHU18 10,929 1,552 12,481 90.81 6.51 30.50 5.26 9.19 2.08 4.08 1.12 14.39 1.71 13.87 1.59 SHU19 4,892 4,805 9,697 124.12 11.54 20.44 3.78 6.25 1.60 2.78 0.91 18.16 2.14 18.53 2.19 Nikola Kozlevo SHU21 7,083 7,083 80.14 7.02 41.79 5.79 14.24 2.60 6.78 1.54 17.29 2.85 16.30 2.61 Novi Pazar SHU22 5,987 13,339 19,326 129.77 18.42 14.05 4.93 3.67 1.43 1.47 0.62 14.07 0.86 14.32 0.99 SHU23 6,904 8,908 15,812 125.80 14.38 16.19 3.76 4.31 1.15 1.75 0.54 14.30 1.27 15.23 1.26 SHU25 3,666 4,398 8,064 114.66 14.17 18.37 5.91 4.66 1.78 1.80 0.77 13.38 1.36 13.37 1.54 Shumen SHU30 14,903 87,349 102,252 147.23 25.99 8.76 3.72 2.10 0.89 0.80 0.33 13.00 0.64 13.25 0.92

50 Table D1. Poverty and inequality in districts and municipalities (poverty line = 61.5 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % GE(0), % GE(1), % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. Silistra Total 77,757 62,595 140,352 121.79 8.68 18.05 2.06 5.17 0.65 2.23 0.32 15.75 0.90 16.65 0.97 SLS01 1,787 2,119 3,906 115.65 13.53 16.90 4.66 4.66 1.44 1.97 0.73 12.73 1.60 13.22 1.62 SLS07 11,710 2,061 13,771 103.32 5.91 24.19 3.54 6.64 1.30 2.72 0.66 14.69 1.37 14.64 1.41 Dulovo SLS10 23,476 6,950 30,426 97.93 7.24 28.11 3.92 8.47 1.48 3.77 0.78 15.16 1.20 15.84 1.07 Kaynardzha SLS15 5,377 5,377 82.90 7.53 43.79 5.70 15.77 3.21 7.72 2.10 20.55 3.64 19.17 3.13 Silistra SLS31 19,795 41,144 60,939 140.22 18.30 10.24 3.50 2.57 0.92 1.01 0.39 12.94 0.99 13.60 1.12 Sitovo SLS32 6,786 6,786 106.65 9.42 21.74 5.32 6.85 2.17 3.23 1.22 15.42 2.75 14.28 2.44 SLS34 8,826 10,321 19,147 131.90 18.04 14.19 4.31 3.69 1.25 1.47 0.55 14.83 1.23 14.94 1.47 Sliven Total 71,316 141,777 213,093 130.04 12.46 16.81 3.47 5.05 1.05 2.26 0.47 17.36 0.89 16.64 1.04 Kotel SLV11 14,483 6,679 21,162 89.45 7.25 36.77 4.66 13.20 2.41 6.70 1.67 19.94 2.65 18.83 2.10 SLV16 19,991 24,307 44,298 148.70 14.71 13.34 2.91 3.88 0.87 1.69 0.38 17.56 0.97 16.61 1.12 Sliven SLV20 31,916 101,413 133,329 131.25 18.57 14.41 5.11 4.03 1.50 1.71 0.64 14.84 0.62 14.38 0.81 Tvarditsa SLV24 4,926 9,378 14,304 121.06 12.72 20.40 4.50 6.00 1.58 2.61 0.77 17.07 1.51 16.74 1.64 Smolyan Total 65,779 71,347 137,126 117.31 6.75 13.76 2.19 3.04 0.56 1.05 0.21 11.80 0.76 11.93 0.81 Banite SML02 6,661 6,661 120.62 9.11 12.04 4.01 2.71 1.15 0.97 0.50 11.26 1.83 11.09 1.87 Borino SML05 4,098 4,098 102.77 13.80 18.86 9.53 4.44 2.69 1.65 1.10 10.64 2.23 10.78 2.42 Devin SML09 7,444 7,476 14,920 107.97 11.93 18.75 6.34 4.40 1.78 1.59 0.71 11.62 1.33 11.66 1.52 SML10 7,504 2,618 10,122 109.56 9.66 18.01 5.45 4.18 1.69 1.50 0.74 11.32 1.39 12.84 1.32 SML11 6,091 7,835 13,926 113.68 15.31 14.22 6.28 3.05 1.59 1.03 0.62 9.89 1.47 10.26 1.63 Madan SML16 7,210 6,516 13,726 105.92 10.32 17.77 6.68 3.94 2.03 1.35 0.87 10.07 0.84 10.19 0.96 SML18 3,567 5,073 8,640 108.75 10.80 15.48 6.06 3.20 1.41 1.05 0.50 10.05 0.87 10.26 1.01 SML27 6,613 4,228 10,841 109.24 10.87 16.13 5.13 3.56 1.37 1.22 0.54 10.44 1.17 10.51 1.31 Smolyan SML31 13,115 32,224 45,339 127.50 16.50 9.79 3.87 2.08 0.85 0.71 0.30 10.52 0.66 10.64 0.80 SML38 3,476 5,377 8,853 135.68 17.17 8.21 3.40 1.69 0.77 0.56 0.28 10.35 0.82 10.30 0.99 Sofia city Total 54,038 1,103,900 1,157,938 157.19 5.82 3.19 0.79 0.56 0.16 0.17 0.05 11.48 0.81 12.51 1.07

51 Table D1. Poverty and inequality in districts and municipalities (poverty line = 61.5 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % GE(0), % GE(1), % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. Stara Zagora Total 115,792 249,426 365,218 136.83 10.75 11.81 2.17 3.23 0.55 1.36 0.22 14.69 0.94 14.61 1.04 Bratya Daskalovi SZR04 10,773 10,773 110.43 5.88 23.29 2.67 8.12 1.34 4.00 0.87 17.87 2.10 15.83 1.90 SZR07 6,953 9,150 16,103 148.73 19.14 8.95 3.12 2.28 0.86 0.91 0.37 13.22 1.11 13.14 1.33 SZR12 26,074 54,596 80,670 135.40 16.71 11.15 5.25 2.75 1.38 1.05 0.54 13.36 0.89 13.73 1.26 SZR22 9,157 3,480 12,637 121.80 11.14 21.49 3.98 6.66 1.48 2.98 0.78 18.64 2.08 17.96 2.23 Opan SZR23 4,103 4,103 175.81 34.24 7.41 3.73 2.09 1.18 0.89 0.56 14.65 2.04 13.97 2.10 SZR24 12,694 3,055 15,749 117.04 8.36 22.91 3.62 6.98 1.42 3.11 0.80 19.10 2.09 18.73 2.09 SZR27 9,669 13,943 23,612 144.69 17.44 9.05 2.34 2.40 0.61 0.99 0.27 12.70 0.88 12.78 1.12 Stara Zagora SZR31 23,723 141,102 164,825 139.84 23.00 9.38 4.23 2.38 1.03 0.95 0.38 11.84 0.77 12.05 0.94 SZR36 8,035 18,116 26,151 135.17 20.21 13.85 4.31 3.85 1.25 1.63 0.53 14.72 0.82 15.30 1.17 SZR37 2,639 3,027 5,666 150.03 23.68 16.12 4.86 5.46 2.09 2.69 1.27 19.69 2.29 19.97 2.43 SZR38 1,972 2,957 4,929 103.45 15.66 29.40 6.45 10.25 2.52 5.01 1.38 18.26 1.73 17.27 1.64 Targovishte Total 64,719 71,380 136,099 121.10 10.00 18.60 2.22 5.16 0.63 2.15 0.28 15.86 0.91 16.78 1.00 TGV02 5,809 1,732 7,541 92.71 6.71 31.85 3.88 9.64 1.54 4.23 0.83 15.58 1.37 16.14 1.51 TGV22 16,387 8,578 24,965 96.16 7.62 29.32 3.83 8.40 1.31 3.55 0.65 14.84 1.23 15.32 1.17 TGV23 4,553 3,177 7,730 105.87 12.16 20.89 6.05 5.28 1.91 2.06 0.88 12.49 1.80 12.94 1.86 Popovo TGV24 18,008 17,703 35,711 130.77 12.06 14.02 2.79 3.80 0.78 1.58 0.37 14.94 1.12 14.95 1.24 Targovishte TGV35 19,962 40,190 60,152 131.23 20.79 14.92 4.30 4.05 1.10 1.67 0.44 14.31 0.64 15.54 0.81 Varna Total 93,970 361,256 455,226 150.16 11.59 9.17 1.46 2.36 0.35 0.95 0.14 14.76 1.10 15.51 1.25 Avren VAR01 8,651 8,651 117.56 7.61 23.02 3.50 7.17 1.60 3.25 0.96 19.72 2.53 19.22 2.57 Aksakovo VAR02 18,840 18,840 126.25 16.62 18.04 4.62 5.34 1.63 2.33 0.83 17.34 3.23 16.75 3.11 Beloslav VAR04 3,042 8,021 11,063 167.70 25.80 5.14 2.96 1.06 0.70 0.35 0.26 12.20 0.94 12.81 1.17 Byala VAR05 1,292 2,062 3,354 119.27 16.15 20.08 4.11 5.88 1.54 2.53 0.86 14.09 1.28 17.41 1.19 Varna VAR06 7,538 307,841 315,379 161.92 16.46 5.04 1.95 1.06 0.42 0.37 0.15 12.90 1.44 13.42 1.57 Vetrino VAR08 6,920 6,920 118.07 10.49 15.90 5.15 4.32 1.63 1.81 0.74 13.51 2.13 12.93 2.17 Valchi Dol VAR09 9,036 3,685 12,721 117.50 9.21 20.94 2.95 6.31 1.09 2.78 0.58 16.37 1.34 16.21 1.25 VAR13 13,087 6,825 19,912 125.35 11.57 19.45 4.51 5.42 1.55 2.28 0.77 18.35 1.90 18.41 2.07 Devnya VAR14 947 8,704 9,651 108.78 16.73 20.01 9.39 4.79 2.92 1.71 1.23 11.87 0.90 12.44 1.35 VAR16 10,434 5,369 15,803 110.51 10.07 22.80 4.68 6.47 1.64 2.75 0.84 16.10 1.89 15.95 1.94 VAR24 11,311 14,024 25,335 123.53 12.67 18.30 3.12 5.47 1.06 2.41 0.55 15.82 0.95 16.06 0.94 VAR26 2,872 4,725 7,597 119.23 16.29 18.53 6.18 5.00 1.98 2.02 0.94 14.51 1.34 14.41 1.50

52 Table D1. Poverty and inequality in districts and municipalities (poverty line = 61.5 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % GE(0), % GE(1), % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. mean std. err. Vidin Total 52,207 76,298 128,505 144.51 13.29 10.10 2.79 2.57 0.74 1.03 0.29 14.52 0.80 14.82 0.96 VID01 2,311 5,725 8,036 140.70 24.18 12.55 5.07 3.16 1.51 1.22 0.64 14.37 0.84 15.05 1.05 Boynitsa VID03 2,190 2,190 110.03 13.61 17.01 7.16 4.17 2.19 1.61 1.04 11.48 2.88 11.12 2.85 VID06 4,144 3,091 7,235 152.93 15.51 8.06 2.75 1.96 0.75 0.76 0.33 14.15 1.54 14.68 1.86 Vidin VID09 16,807 59,998 76,805 151.28 22.31 7.68 4.54 1.71 1.18 0.61 0.45 12.74 0.65 13.01 0.87 Gramada VID15 1,078 2,099 3,177 155.50 24.99 9.69 4.42 2.46 1.32 0.98 0.59 15.01 1.72 15.38 2.01 VID16 7,236 1,500 8,736 113.19 9.46 20.05 4.35 6.06 1.75 2.73 0.97 15.25 2.29 14.39 2.12 Kula VID22 2,761 3,885 6,646 146.76 19.06 8.62 3.06 1.98 0.76 0.74 0.33 12.93 1.20 14.00 1.45 Makresh VID25 2,513 2,513 124.30 13.69 12.86 5.71 3.31 1.78 1.34 0.85 12.41 2.73 11.98 2.87 Novo Selo VID30 4,150 4,150 162.17 19.40 7.36 3.20 1.96 1.03 0.83 0.50 14.89 3.37 14.89 3.65 Ruzhintsi VID33 6,039 6,039 113.67 10.15 22.06 4.27 6.89 1.83 3.18 1.07 17.83 3.04 16.98 3.05 Chuprene VID37 2,978 2,978 115.26 10.63 17.68 3.57 6.24 1.44 3.16 0.87 15.22 2.35 13.33 2.23 Vratsa Total 101,619 138,346 239,965 135.36 9.28 12.42 1.77 3.29 0.46 1.35 0.19 15.02 0.83 15.53 0.99 Borovan VRC05 7,080 7,080 93.91 10.08 29.01 7.98 9.10 3.18 4.14 1.75 14.91 3.04 13.93 3.03 VRC08 17,258 13,660 30,918 128.54 14.40 16.45 3.49 4.53 1.11 1.89 0.53 16.15 1.44 16.39 1.69 Vratsa VRC10 16,128 67,533 83,661 141.58 23.35 8.99 4.23 2.16 0.98 0.83 0.36 12.33 0.62 12.67 0.84 VRC19 4,250 12,776 17,026 148.05 22.00 9.60 3.97 2.27 1.03 0.84 0.42 14.23 1.23 14.58 1.64 VRC20 9,388 14,761 24,149 159.71 22.87 9.75 3.11 2.62 0.96 1.08 0.45 15.47 1.56 16.00 1.88 Krivodol VRC21 8,369 3,805 12,174 113.08 9.32 19.71 3.45 5.89 1.23 2.65 0.66 14.92 1.70 14.67 1.92 VRC27 13,297 12,312 25,609 129.86 12.82 11.06 2.68 2.77 0.68 1.10 0.28 12.00 0.70 12.22 0.74 VRC28 5,527 4,053 9,580 133.28 14.74 12.74 4.38 3.30 1.39 1.34 0.67 14.12 2.17 14.11 2.34 VRC31 8,910 6,073 14,983 129.00 15.14 14.11 4.35 3.73 1.40 1.51 0.67 13.75 1.34 14.08 1.37 Roman VRC32 4,529 3,373 7,902 117.54 10.29 17.86 4.04 5.11 1.35 2.20 0.68 14.51 1.58 13.89 1.66 Hayredin VRC35 6,883 6,883 113.39 11.78 17.03 5.42 4.70 1.80 1.98 0.90 12.86 2.38 12.07 2.29 Veliko Tarnovo Total 100,792 188,116 288,908 147.18 10.41 9.85 1.32 2.62 0.33 1.08 0.14 15.16 0.90 15.29 1.00 Veliko Tarnovo VTR04 15,748 72,759 88,507 156.35 26.27 6.22 2.82 1.39 0.58 0.51 0.20 12.44 0.72 12.79 0.97 VTR06 14,097 38,545 52,642 152.50 20.61 8.05 2.93 2.02 0.71 0.79 0.28 13.67 0.95 13.86 1.32 VTR13 4,787 6,335 11,122 117.93 17.55 20.86 4.29 6.38 1.43 2.87 0.78 15.71 1.25 17.28 1.11 VTR14 2,229 2,651 4,880 102.32 12.04 25.10 7.59 6.72 2.64 2.64 1.21 13.43 1.39 13.29 1.54 VTR20 6,285 9,196 15,481 141.58 17.70 8.74 3.51 2.22 0.91 0.91 0.41 12.16 1.14 12.32 1.23 VTR22 15,299 15,645 30,944 159.84 15.74 10.20 2.13 2.88 0.68 1.23 0.34 16.83 1.33 16.96 1.50 VTR26 13,378 5,156 18,534 136.18 10.60 15.32 2.53 4.74 1.04 2.16 0.61 17.29 1.60 16.42 1.59 VTR28 16,972 30,172 47,144 146.99 17.53 7.46 2.78 1.81 0.66 0.71 0.26 12.05 0.81 12.14 1.03 VTR31 10,996 5,159 16,155 107.19 9.38 24.55 4.51 7.28 1.65 3.17 0.84 16.03 1.38 15.56 1.33 VTR32 1,001 2,498 3,499 149.50 19.02 9.63 3.15 2.35 0.89 0.89 0.42 14.22 1.25 14.33 1.55

53 Table D2. Poverty and inequality in districts and municipalities (poverty line = 46.1 BGL per month in 2001 prices) Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % M unicipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. Burgas Total 122,832 295,046 417,878 155.71 15.89 4.69 0.56 1.19 0.15 0.48 0.06 Aytos BGS01 9,122 20,969 30,091 121.61 15.46 7.50 2.43 1.80 0.60 0.69 0.25 Burgas BGS04 14,842 192,296 207,138 184.43 31.91 1.30 0.77 0.28 0.16 0.10 0.06 Sredets BGS06 7,571 9,478 17,049 123.35 14.61 8.77 2.37 2.32 0.70 0.95 0.33 Kameno BGS08 7,141 5,103 12,244 116.69 13.11 10.66 2.41 3.08 0.83 1.35 0.44 Karnobat BGS09 9,086 20,206 29,292 147.68 23.33 5.61 2.23 1.41 0.58 0.56 0.23 Malko Tarnovo BGS12 1,505 2,922 4,427 145.98 18.65 4.44 1.77 1.07 0.55 0.40 0.25 Tsarevo BGS13 2,913 6,785 9,698 146.24 21.59 3.59 1.33 0.78 0.32 0.27 0.13 Nesebar BGS15 8,370 10,549 18,919 148.97 18.55 4.93 1.31 1.36 0.45 0.57 0.23 Pomorie BGS17 10,733 16,378 27,111 120.81 13.50 8.17 1.89 2.15 0.59 0.88 0.30 Ruen BGS18 28,756 28,756 96.60 4.55 13.53 2.11 3.52 0.75 1.43 0.40 Sozopol BGS21 9,883 4,330 14,213 141.98 13.21 6.06 1.47 1.63 0.50 0.68 0.26 Sungurlare BGS23 11,404 3,683 15,087 116.01 8.52 10.67 2.11 2.85 0.70 1.17 0.35 Primorsko BGS27 1,506 2,347 3,853 167.85 22.47 4.18 2.44 1.09 0.94 0.44 0.50 Blagoevgrad Total 146,318 189,710 336,028 128.12 6.65 5.49 0.76 1.28 0.20 0.48 0.09 Bansko BLG01 4,647 8,900 13,547 138.79 18.81 2.96 1.71 0.59 0.39 0.19 0.15 Belitsa BLG02 6,290 3,289 9,579 84.82 8.55 17.78 4.59 4.53 1.42 1.78 0.68 Blagoevgrad BLG03 6,917 69,546 76,463 139.26 24.82 2.11 1.81 0.39 0.34 0.12 0.11 Gotse Delchev BLG11 12,110 20,288 32,398 125.37 15.34 5.67 2.01 1.33 0.58 0.50 0.29 Garmen BLG13 14,907 14,907 110.71 8.67 13.30 3.19 3.75 1.16 1.60 0.62 Kresna BLG28 2,315 3,832 6,147 124.28 16.01 4.60 3.72 0.94 0.88 0.31 0.33 Petrich BLG33 27,931 29,198 57,129 139.07 11.85 3.78 1.19 0.83 0.28 0.30 0.11 Razlog BLG37 9,159 12,513 21,672 137.92 15.82 3.75 1.86 0.77 0.43 0.25 0.16 Sandanski BLG40 16,124 26,203 42,327 128.67 16.23 4.64 2.70 1.01 0.59 0.36 0.21 Satovcha BLG42 17,861 17,861 102.29 8.69 11.50 3.41 2.85 1.05 1.12 0.49 Simitli BLG44 8,867 7,020 15,887 119.66 12.05 5.38 2.08 1.22 0.58 0.45 0.26 Strumyani BLG49 6,304 6,304 118.61 12.43 8.13 2.93 2.24 1.03 0.97 0.55 Hadzhidimovo BLG52 7,990 2,909 10,899 129.04 11.78 5.48 2.27 1.32 0.78 0.52 0.41 Yakoruda BLG53 4,896 6,012 10,908 89.14 12.29 15.18 4.46 3.49 1.15 1.25 0.48 Dobrich Total 70,949 142,315 213,264 120.73 11.95 8.54 1.99 2.25 0.49 0.92 0.19 Balchik DOB03 9,625 12,393 22,018 125.53 14.74 9.12 2.30 2.48 0.68 1.03 0.33 General Toshevo DOB12 11,184 8,072 19,256 117.59 12.66 9.29 1.82 2.55 0.53 1.07 0.25 Dobrich DOB15 25,545 25,545 95.13 4.14 18.55 2.02 5.70 0.87 2.57 0.50 Kavarna DOB17 4,996 11,290 16,286 134.79 20.88 6.14 2.48 1.54 0.59 0.60 0.22 Krushari DOB20 5,805 5,805 96.16 8.03 16.81 3.82 4.90 1.48 2.11 0.78 Tervel DOB27 11,446 7,235 18,681 102.19 9.32 15.81 2.77 4.40 0.97 1.85 0.50 Dobrich DOB28 99,345 99,345 125.96 24.36 4.63 4.01 0.92 0.93 0.29 0.33 Shabla DOB29 2,348 3,980 6,328 176.04 23.43 2.20 1.06 0.48 0.27 0.16 0.11

54 Table D2. Poverty and inequality in districts and municipalities (poverty line =46.1 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % M unicipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. Gabrovo Total 29,170 112,872 142,042 142.34 15.06 2.64 0.86 0.55 0.17 0.19 0.06 Gabrovo GAB05 7,739 66,453 74,192 145.60 26.29 1.93 1.35 0.37 0.25 0.12 0.08 Dryanovo GAB12 2,731 8,601 11,332 137.88 19.22 2.89 1.70 0.56 0.35 0.18 0.12 Sevlievo GAB29 17,820 24,467 42,287 142.95 17.02 3.66 1.13 0.87 0.28 0.34 0.12 Tryavna GAB35 880 13,351 14,231 127.05 18.20 3.06 1.81 0.59 0.35 0.19 0.11 Haskovo Total 81,077 192,824 273,901 135.16 9.77 4.94 0.98 1.14 0.23 0.42 0.08 Dimitrovgrad HKV09 16,642 47,634 64,276 135.78 18.29 4.24 2.01 0.95 0.45 0.34 0.16 Ivaylovgrad HKV11 3,666 4,387 8,053 129.18 15.95 5.27 1.37 1.29 0.41 0.51 0.20 Lyubimets HKV17 3,201 8,197 11,398 151.40 21.63 3.73 1.65 0.83 0.40 0.30 0.16 Madzharovo HKV18 1,403 722 2,125 107.13 9.45 9.00 2.80 2.14 0.84 0.80 0.39 Mineralni Bani HKV19 6,549 6,549 109.39 8.88 10.20 3.12 2.47 0.90 0.95 0.42 Svilengrad HKV28 6,304 18,833 25,137 154.29 20.96 2.77 1.40 0.60 0.31 0.21 0.11 Simeonovgrad HKV29 2,824 7,756 10,580 119.52 16.55 8.88 3.90 2.07 1.03 0.76 0.41 Stambolovo HKV30 5,776 5,776 110.69 6.23 10.06 2.40 2.49 0.75 0.96 0.34 Topolovgrad HKV32 8,584 6,595 15,179 131.78 14.18 5.88 1.45 1.51 0.43 0.60 0.20 Harmanli HKV33 7,450 19,830 27,280 132.51 16.66 5.84 2.29 1.35 0.57 0.50 0.21 Haskovo HKV34 18,678 78,870 97,548 135.18 22.80 4.51 1.97 1.01 0.42 0.37 0.15 Yambol Total 52,681 101,081 153,762 139.52 14.99 5.22 1.50 1.31 0.37 0.52 0.14 Bolyarovo JAM03 4,009 1,510 5,519 126.03 9.60 7.68 1.86 2.20 0.68 0.96 0.38 Elhovo JAM07 8,120 12,256 20,376 131.41 16.08 6.19 1.58 1.58 0.43 0.63 0.20 Straldzha JAM22 9,448 5,804 15,252 122.41 10.24 8.64 2.28 2.22 0.66 0.90 0.29 Tundzha JAM25 31,104 31,104 127.67 5.96 7.57 1.13 2.23 0.44 0.99 0.25 Yambol JAM26 81,511 81,511 150.20 28.23 3.28 2.73 0.65 0.64 0.21 0.22 Kyustendil Total 54,855 104,832 159,687 136.96 10.53 3.45 1.31 0.71 0.29 0.24 0.10 Bobovdol KNL04 4,751 6,526 11,277 161.63 19.17 1.55 0.99 0.31 0.23 0.10 0.08 Boboshevo KNL05 2,152 1,489 3,641 136.83 12.94 3.31 1.83 0.77 0.60 0.29 0.29 Kocherinovo KNL27 3,643 2,727 6,370 131.42 13.24 4.10 2.04 0.84 0.50 0.28 0.20 Kyustendil KNL29 20,432 48,755 69,187 131.71 18.16 3.70 2.36 0.75 0.51 0.25 0.17 Nevestino KNL31 4,328 4,328 132.28 10.47 4.66 1.77 1.06 0.49 0.39 0.22 Rila KNL38 621 3,035 3,656 120.04 19.09 4.49 3.10 0.88 0.68 0.28 0.23 Sapareva Banya KNL41 4,545 4,407 8,952 154.69 20.59 2.74 1.82 0.63 0.55 0.23 0.25 Dupnitsa KNL48 13,284 37,893 51,177 138.53 20.28 3.30 2.02 0.66 0.45 0.22 0.16 Treklyano KNL50 1,099 1,099 103.93 11.54 8.88 3.40 2.10 1.06 0.80 0.51 Kardzhali Total 98,055 63,622 161,677 114.86 8.97 8.88 1.14 2.20 0.32 0.87 0.14 Ardino KRZ02 9,877 3,507 13,384 102.07 8.29 10.49 2.37 2.51 0.63 0.95 0.27 Dzhebel KRZ08 5,766 2,823 8,589 94.69 7.41 11.24 2.71 2.66 0.72 1.01 0.31 Kirkovo KRZ14 24,069 24,069 115.26 6.87 8.71 1.87 2.13 0.59 0.83 0.29 Krumovgrad KRZ15 14,563 5,154 19,717 100.37 6.97 12.67 1.91 3.39 0.64 1.41 0.33 Kardzhali KRZ16 24,085 44,451 68,536 130.07 19.88 6.26 1.69 1.53 0.39 0.60 0.15 Momchilgrad KRZ21 9,184 7,687 16,871 105.86 10.67 8.41 2.07 1.98 0.50 0.76 0.22 Chernoochene KRZ35 10,511 10,511 89.17 4.84 15.91 2.82 4.11 1.01 1.65 0.53

55 Table D2. Poverty and inequality in districts and municipalities (poverty line = 46.1 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. Lovech Total 65,910 99,388 165,298 137.58 8.54 5.29 0.72 1.34 0.21 0.54 0.10 Apriltsi LOV02 442 3,543 3,985 148.60 25.40 1.65 1.38 0.30 0.26 0.09 0.09 Letnitsa LOV17 1,630 3,895 5,525 132.95 17.59 5.71 2.65 1.15 0.64 0.37 0.24 Lovech LOV18 17,621 42,239 59,860 144.45 18.58 3.42 1.12 0.81 0.27 0.31 0.11 Lukovit LOV19 11,125 9,877 21,002 126.73 12.82 9.50 2.31 2.69 0.72 1.17 0.36 Teteven LOV33 12,106 11,025 23,131 116.92 11.61 7.69 2.47 1.80 0.71 0.66 0.31 Troyan LOV34 13,827 22,699 36,526 153.87 17.63 2.15 0.79 0.47 0.18 0.17 0.07 Ugarchin LOV36 5,370 3,071 8,441 113.07 9.97 10.15 3.09 2.63 0.93 1.08 0.43 Yablanitsa LOV38 3,789 3,039 6,828 121.33 12.79 13.12 2.71 4.18 1.17 1.95 0.69 Montana Total 70,680 108,778 179,458 136.21 10.96 5.95 0.96 1.54 0.26 0.63 0.11 Berkovitsa MON02 6,962 15,020 21,982 128.48 18.24 5.39 3.21 1.27 0.81 0.48 0.32 Boychinovtsi MON04 10,101 1,947 12,048 124.95 8.00 10.33 1.81 3.02 0.69 1.31 0.37 Brusartsi MON07 5,207 1,594 6,801 133.99 12.60 9.01 2.76 2.66 1.06 1.20 0.58 Valchedram MON11 8,272 4,788 13,060 120.60 11.33 12.24 2.81 3.70 1.09 1.67 0.61 Varshets MON12 2,614 7,028 9,642 129.64 21.75 6.17 3.62 1.34 0.92 0.45 0.34 Georgi Damyanovo MON14 4,217 4,217 129.46 9.64 5.32 1.73 1.33 0.58 0.52 0.29 Lom MON24 7,138 27,423 34,561 134.75 19.85 5.03 2.90 1.10 0.67 0.39 0.24 Medkovets MON26 5,585 5,585 116.87 14.16 10.44 3.82 3.12 1.41 1.40 0.73 Montana MON29 12,143 48,612 60,755 151.17 26.86 3.32 1.38 0.78 0.30 0.30 0.11 Chiprovtsi MON36 2,601 2,366 4,967 140.75 15.83 3.31 1.24 0.80 0.37 0.32 0.18 Yakimovo MON38 5,840 5,840 109.38 12.76 12.15 3.44 3.59 1.29 1.59 0.70 Pazardzhik Total 131,240 175,908 307,148 132.10 8.18 6.93 1.12 1.62 0.30 0.60 0.12 Batak PAZ03 3,033 3,998 7,031 115.49 17.49 7.82 5.17 1.82 1.53 0.67 0.68 Belovo PAZ04 6,489 4,564 11,053 136.69 12.39 3.48 1.96 0.72 0.48 0.24 0.19 Bratsigovo PAZ06 6,686 4,622 11,308 140.69 14.66 5.49 2.38 1.42 0.81 0.57 0.41 Velingrad PAZ08 17,887 24,599 42,486 109.35 13.78 9.81 3.07 2.24 0.82 0.81 0.33 Lesichovo PAZ14 6,521 6,521 119.85 12.23 9.81 3.35 2.50 1.19 0.98 0.60 Pazardzhik PAZ19 48,956 76,903 125,859 139.47 17.72 6.20 2.13 1.49 0.52 0.57 0.20 Panagyurishte PAZ20 9,799 19,899 29,698 153.70 23.58 2.80 1.16 0.62 0.28 0.22 0.12 Peshtera PAZ21 2,619 19,321 21,940 121.70 21.48 7.84 5.24 1.62 1.32 0.52 0.48 Rakitovo PAZ24 7,382 8,252 15,634 99.26 11.50 14.10 5.82 3.15 1.74 1.08 0.72 Septemvri PAZ29 20,640 8,982 29,622 138.84 11.17 7.11 2.03 1.82 0.65 0.72 0.31 Strelcha PAZ32 1,228 4,768 5,996 129.86 21.36 4.27 2.65 0.85 0.58 0.28 0.21

56 Table D2. Poverty and inequality in districts and municipalities (poverty line = 46.1 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. Plovdiv Total 202,689 505,917 708,606 147.71 6.79 4.39 0.77 1.06 0.22 0.41 0.09 Asenovgrad PDV01 15,160 51,579 66,739 136.26 18.45 3.64 1.77 0.80 0.39 0.29 0.15 Brezovo PDV07 6,658 2,063 8,721 141.11 10.21 6.50 1.50 1.87 0.56 0.82 0.30 Kaloyanovo PDV12 13,526 13,526 157.12 13.68 5.16 1.32 1.48 0.47 0.64 0.24 Karlovo PDV13 29,091 40,415 69,506 122.69 10.19 6.82 1.57 1.82 0.44 0.76 0.21 Laki PDV15 1,069 2,858 3,927 132.65 17.82 2.90 1.44 0.62 0.35 0.22 0.15 Maritsa PDV17 32,119 32,119 154.31 10.48 6.39 1.37 1.82 0.49 0.78 0.25 Plovdiv PDV22 334,005 334,005 150.78 12.50 3.51 1.41 0.74 0.41 0.24 0.17 Parvomay PDV23 15,697 15,340 31,037 139.09 13.43 5.31 1.37 1.36 0.41 0.55 0.20 Rakovski PDV25 12,084 16,239 28,323 166.42 24.37 5.47 1.73 1.61 0.65 0.71 0.35 Rodopi PDV26 40,660 40,660 170.27 12.13 3.31 1.37 0.83 0.46 0.33 0.22 Sadovo PDV28 13,994 2,582 16,576 131.76 10.70 8.48 2.23 2.38 0.76 1.02 0.38 Saedinenie PDV33 5,732 6,386 12,118 151.12 15.85 3.30 1.11 0.80 0.31 0.31 0.14 Hisarya PDV37 7,286 8,153 15,439 185.74 23.41 2.18 1.05 0.52 0.31 0.20 0.14 Krichim PDV39 8,522 8,522 102.43 19.46 9.39 6.53 1.74 1.46 0.50 0.47 Perushtitsa PDV40 5,378 5,378 137.30 28.50 4.31 3.28 0.83 0.72 0.25 0.24 Stamboliyski PDV41 9,613 12,397 22,010 154.68 19.37 4.84 1.67 1.27 0.52 0.52 0.26 Pernik Total 35,757 113,296 149,053 134.34 18.46 3.31 1.95 0.65 0.41 0.21 0.13 Breznik PER08 4,179 4,312 8,491 120.93 11.61 4.17 1.74 0.83 0.40 0.27 0.15 Zemen PER19 1,882 2,213 4,095 118.17 12.56 4.93 1.93 1.05 0.45 0.38 0.19 Kovachevtsi PER22 2,128 2,128 130.15 12.27 3.57 2.42 0.79 0.81 0.29 0.40 Pernik PER32 15,959 88,378 104,337 138.96 25.67 2.63 2.57 0.49 0.52 0.15 0.17 Radomir PER36 8,844 15,642 24,486 127.12 15.65 4.52 3.10 0.93 0.71 0.31 0.25 Tran PER51 2,765 2,751 5,516 113.40 8.76 8.23 3.25 1.79 0.89 0.61 0.35 Pleven Total 111,904 194,930 306,834 152.34 12.41 4.23 0.51 1.14 0.15 0.48 0.08 Belene PVN03 2,563 9,308 11,871 178.05 24.68 1.12 0.67 0.23 0.16 0.08 0.06 Gulyantsi PVN08 12,821 3,825 16,646 151.74 11.17 2.78 1.13 0.63 0.34 0.23 0.16 Dolna Mitropolia PVN10 16,487 8,655 25,142 139.53 10.91 5.77 1.28 1.59 0.45 0.67 0.24 Dolni Dabnik PVN11 10,414 4,966 15,380 143.37 13.44 9.30 2.13 2.80 0.82 1.25 0.45 Levski PVN16 13,747 12,094 25,841 146.42 16.03 4.96 1.37 1.28 0.42 0.51 0.20 Nikopol PVN21 8,795 4,490 13,285 141.61 11.25 4.98 1.74 1.24 0.48 0.49 0.21 Iskar PVN23 4,976 4,104 9,080 137.18 16.38 5.32 2.45 1.32 0.76 0.52 0.38 Pleven PVN24 22,213 124,162 146,375 160.69 27.08 3.12 0.86 0.87 0.22 0.38 0.10 Pordim PVN27 5,531 2,329 7,860 140.89 12.31 5.39 1.82 1.37 0.59 0.55 0.29 Cherven Bryag PVN37 14,357 20,997 35,354 137.20 14.26 5.88 1.52 1.52 0.45 0.62 0.21

57

Table D2. Poverty and inequality in districts and municipalities (poverty line = 46.1 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. Razgrad Total 83,112 67,074 150,186 117.36 7.84 9.55 1.15 2.48 0.36 1.01 0.18 Zavet RAZ11 8,712 3,493 12,205 92.79 9.31 14.94 4.75 3.93 1.60 1.60 0.79 Isperih RAZ14 15,234 9,762 24,996 104.30 11.54 13.18 2.50 3.53 0.83 1.46 0.41 Kubrat RAZ16 14,991 8,896 23,887 116.68 9.39 9.07 2.49 2.33 0.79 0.94 0.38 Loznitsa RAZ17 12,207 2,596 14,803 113.17 7.95 11.59 2.30 3.13 0.81 1.28 0.41 Razgrad RAZ26 19,644 38,131 57,775 134.06 18.53 6.01 1.63 1.49 0.46 0.58 0.21 Samuil RAZ29 7,971 7,971 87.70 7.82 17.35 4.09 4.86 1.40 2.08 0.71 Tsar Kaloyan RAZ36 4,353 4,196 8,549 114.73 13.67 5.62 3.23 1.18 0.86 0.41 0.37 Ruse Total 79,629 182,313 261,942 148.79 17.59 3.77 0.81 0.92 0.19 0.36 0.08 Borovo RSE03 5,131 2,607 7,738 128.55 12.44 8.58 3.12 2.28 1.03 0.93 0.51 Byala RSE04 6,812 9,910 16,722 145.73 19.36 7.12 1.72 2.03 0.61 0.89 0.33 Vetovo RSE05 11,787 6,834 18,621 114.71 9.49 8.45 3.06 1.99 1.01 0.74 0.50 Dve Mogili RSE08 7,215 4,678 11,893 119.47 11.42 8.52 2.29 2.19 0.74 0.87 0.38 Ivanovo RSE13 11,018 11,018 157.15 14.11 5.19 2.31 1.49 0.84 0.66 0.43 Ruse RSE27 16,880 158,284 175,164 157.04 26.27 1.81 1.10 0.36 0.22 0.12 0.07 Slivo Pole RSE33 12,838 12,838 126.94 9.66 9.90 3.02 2.70 1.04 1.14 0.52 Tsenovo RSE37 7,948 7,948 140.50 12.33 5.35 2.00 1.42 0.68 0.58 0.34

58 Table D2. Poverty and inequality in districts and municipalities (poverty line = 46.1 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. Sofia district Total 111,627 158,127 269,754 138.16 5.33 4.17 0.64 0.97 0.17 0.37 0.07 Bozhurishte SFO06 2,771 5,149 7,920 154.85 17.10 1.43 0.89 0.27 0.20 0.09 0.08 Botevgrad SFO07 14,004 21,426 35,430 142.68 18.55 4.56 1.58 1.15 0.44 0.46 0.20 Godech SFO09 1,571 5,012 6,583 137.54 20.75 2.67 1.61 0.53 0.35 0.17 0.12 Gorna Malina SFO10 6,958 6,958 139.81 11.82 3.80 1.48 0.94 0.45 0.36 0.20 Dragoman SFO16 2,810 3,732 6,542 136.94 17.32 3.17 1.36 0.68 0.31 0.24 0.13 Elin Pelin SFO17 17,222 6,643 23,865 156.43 13.47 2.99 1.12 0.71 0.32 0.27 0.14 Etropole SFO18 2,223 11,360 13,583 134.12 23.33 4.17 2.39 0.95 0.55 0.35 0.20 Ihtiman SFO20 5,643 13,466 19,109 129.85 17.60 6.50 3.16 1.44 0.75 0.51 0.27 Koprivshtitsa SFO24 2,650 2,650 139.61 24.97 2.65 1.96 0.46 0.38 0.14 0.12 Kostenets SFO25 5,158 9,926 15,084 123.05 15.38 4.83 2.46 1.08 0.60 0.39 0.25 Kostinbrod SFO26 5,730 12,098 17,828 131.80 17.81 3.17 1.96 0.64 0.41 0.21 0.15 Pravets SFO34 4,027 4,226 8,253 116.85 15.18 11.88 2.21 3.91 0.98 1.88 0.61 Samokov SFO39 14,638 27,230 41,868 133.59 16.51 4.63 2.15 1.00 0.50 0.35 0.18 Svoge SFO43 16,607 8,523 25,130 141.60 14.23 3.00 1.07 0.66 0.25 0.24 0.10 Slivnitsa SFO45 2,440 7,902 10,342 139.99 22.93 2.52 1.68 0.51 0.39 0.17 0.16 Zlatitsa SFO47 885 5,729 6,614 136.27 25.55 3.45 2.13 0.68 0.46 0.22 0.16 Anton SFO54 1,803 1,803 148.54 30.82 3.23 3.53 0.74 1.11 0.27 0.51 Pirdop SFO55 921 8,324 9,245 158.64 29.89 1.90 1.74 0.34 0.36 0.10 0.12 Mirkovo SFO56 3,095 3,095 130.41 19.95 5.99 3.62 1.48 1.17 0.58 0.56 Chavdar SFO57 1,420 1,420 128.06 29.41 5.72 4.52 1.54 1.36 0.67 0.66 Chelopech SFO58 1,701 1,701 139.42 27.96 3.39 3.85 0.74 1.12 0.26 0.49 Dolna Banya SFO59 4,731 4,731 122.62 22.78 5.86 4.05 1.13 0.92 0.35 0.32 Shumen Total 76,958 123,986 200,944 128.15 13.85 7.96 1.12 2.04 0.30 0.81 0.13 Venets SHU07 8,012 8,012 85.12 7.78 16.96 4.66 4.37 1.51 1.73 0.74 Varbitsa SHU10 7,565 3,635 11,200 86.01 6.50 19.37 4.47 4.79 1.39 1.81 0.62 Hitrino SHU11 7,017 7,017 103.39 7.39 11.74 2.96 3.05 1.00 1.24 0.50 Kaolinovo SHU18 10,929 1,552 12,481 90.81 6.51 16.25 3.77 4.53 1.33 1.92 0.69 Kaspichan SHU19 4,892 4,805 9,697 124.12 11.54 11.12 2.83 3.11 1.10 1.30 0.59 Nikola Kozlevo SHU21 7,083 7,083 80.14 7.02 25.49 4.57 7.75 1.83 3.43 1.04 Novi Pazar SHU22 5,987 13,339 19,326 129.77 18.42 6.33 2.61 1.56 0.69 0.61 0.29 Veliki Preslav SHU23 6,904 8,908 15,812 125.80 14.38 7.48 2.10 1.87 0.62 0.73 0.28 Smyadovo SHU25 3,666 4,398 8,064 114.66 14.17 8.14 3.33 1.88 0.87 0.69 0.37 Shumen SHU30 14,903 87,349 102,252 147.23 25.99 3.58 1.55 0.82 0.34 0.30 0.12

59 Table D2. Poverty and inequality in districts and municipalities (poverty line = 46.1 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. Silistra Total 77,757 62,595 140,352 121.79 8.68 9.06 1.17 2.44 0.37 1.01 0.18 Alfatar SLS01 1,787 2,119 3,906 115.65 13.53 8.07 2.59 2.15 0.86 0.87 0.44 Glavinitsa SLS07 11,710 2,061 13,771 103.32 5.91 11.79 2.44 2.94 0.78 1.13 0.36 Dulovo SLS10 23,476 6,950 30,426 97.93 7.24 14.91 2.67 4.18 0.91 1.78 0.46 Kaynardzha SLS15 5,377 5,377 82.90 7.53 28.35 5.48 8.90 2.57 4.03 1.51 Silistra SLS31 19,795 41,144 60,939 140.22 18.30 4.41 1.61 1.06 0.43 0.40 0.19 Sitovo SLS32 6,786 6,786 106.65 9.42 11.76 3.69 3.62 1.42 1.68 0.78 Tutrakan SLS34 8,826 10,321 19,147 131.90 18.04 6.42 2.26 1.55 0.62 0.59 0.28 Sliven Total 71,316 141,777 213,093 130.04 12.46 8.81 1.92 2.50 0.54 1.09 0.24 Kotel SLV11 14,483 6,679 21,162 89.45 7.25 22.83 3.85 7.66 1.98 3.73 1.30 Nova Zagora SLV16 19,991 24,307 44,298 148.70 14.71 6.80 1.60 1.86 0.43 0.78 0.19 Sliven SLV20 31,916 101,413 133,329 131.24 18.57 7.06 2.74 1.86 0.71 0.76 0.28 Tvarditsa SLV24 4,926 9,378 14,304 121.06 12.72 10.62 3.02 2.87 0.90 1.19 0.42 Smolyan Total 65,779 71,347 137,126 117.31 6.75 5.07 1.01 1.03 0.23 0.34 0.09 Banite SML02 6,661 6,661 120.62 9.11 4.51 2.17 0.97 0.57 0.34 0.24 Borino SML05 4,098 4,098 102.77 13.80 7.58 5.07 1.68 1.19 0.60 0.46 Devin SML09 7,444 7,476 14,920 107.97 11.93 7.52 3.39 1.59 0.78 0.55 0.29 Dospat SML10 7,504 2,618 10,122 109.56 9.66 7.15 3.25 1.50 0.84 0.51 0.34 Zlatograd SML11 6,091 7,835 13,926 113.68 15.31 5.02 2.89 0.99 0.66 0.32 0.25 Madan SML16 7,210 6,516 13,726 105.92 10.32 6.69 3.92 1.31 1.00 0.42 0.38 Nedelino SML18 3,567 5,073 8,640 108.75 10.80 5.19 2.50 0.98 0.50 0.31 0.18 Rudozem SML27 6,613 4,228 10,841 109.24 10.87 5.97 2.52 1.18 0.59 0.38 0.22 Smolyan SML31 13,115 32,224 45,339 127.50 16.50 3.40 1.44 0.68 0.30 0.23 0.10 Chepelare SML38 3,476 5,377 8,853 135.68 17.17 2.75 1.35 0.53 0.29 0.17 0.11 Sofia city Total 54,038 1,103,900 1,157,938 157.19 5.82 0.80 0.26 0.14 0.05 0.05 0.02

60 Table D2. Poverty and inequality in districts and municipalities (poverty line = 46.1 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. Stara Zagora Total 115,792 249,426 365,218 136.83 10.75 5.60 0.99 1.47 0.24 0.60 0.09 Bratya Daskalovi SZR04 10,773 10,773 110.43 5.88 14.21 2.17 4.60 1.06 2.14 0.63 Galabovo SZR07 6,953 9,150 16,103 148.73 19.14 3.89 1.53 0.96 0.41 0.38 0.18 Kazanlak SZR12 26,074 54,596 80,670 135.40 16.71 4.75 2.46 1.09 0.58 0.40 0.21 Maglizh SZR22 9,157 3,480 12,637 121.80 11.14 11.93 2.67 3.34 0.92 1.39 0.47 Opan SZR23 4,103 4,103 175.81 34.24 3.69 2.10 0.98 0.65 0.40 0.30 Pavel Banya SZR24 12,694 3,055 15,749 117.04 8.36 12.40 2.52 3.45 0.94 1.47 0.52 Radnevo SZR27 9,669 13,943 23,612 144.69 17.44 4.09 1.05 1.06 0.29 0.43 0.14 Stara Zagora SZR31 23,723 141,102 164,825 139.84 23.00 4.07 1.81 1.00 0.39 0.40 0.14 Chirpan SZR36 8,035 18,116 26,151 135.17 20.21 6.69 2.32 1.77 0.58 0.73 0.25 Gurkovo SZR37 2,639 3,027 5,666 150.03 23.68 9.45 3.49 3.05 1.49 1.47 0.90 Nikolaevo SZR38 1,972 2,957 4,929 103.45 15.66 18.09 4.61 5.73 1.64 2.64 0.88 Targovishte Total 64,719 71,380 136,099 121.10 10.00 9.10 1.14 2.33 0.32 0.93 0.15 Antonovo TGV02 5,809 1,732 7,541 92.71 6.71 17.32 2.83 4.70 0.99 1.94 0.51 Omurtag TGV22 16,387 8,578 24,965 96.16 7.62 15.01 2.45 3.88 0.77 1.55 0.38 Opaka TGV23 4,553 3,177 7,730 105.87 12.16 9.15 3.66 2.14 1.02 0.81 0.46 Popovo TGV24 18,008 17,703 35,711 130.78 12.06 6.60 1.37 1.70 0.42 0.68 0.21 Targovishte TGV35 19,962 40,190 60,152 131.23 20.79 7.10 1.96 1.79 0.47 0.71 0.19 Varna Total 93,970 361,256 455,226 150.16 11.59 4.04 0.59 1.00 0.15 0.39 0.07 Avren VAR01 8,651 8,651 117.56 7.61 12.71 2.87 3.63 1.14 1.58 0.64 Aksakovo VAR02 18,840 18,840 126.25 16.62 9.52 2.96 2.58 0.98 1.06 0.48 Beloslav VAR04 3,042 8,021 11,063 167.70 25.80 1.73 1.25 0.34 0.28 0.11 0.10 Byala VAR05 1,292 2,062 3,354 119.27 16.15 10.49 2.80 2.79 1.04 1.13 0.55 Varna VAR06 7,538 307,841 315,379 161.92 16.46 1.71 0.71 0.36 0.15 0.13 0.05 Vetrino VAR08 6,920 6,920 118.07 10.49 7.43 3.01 1.94 0.85 0.80 0.37 Valchi Dol VAR09 9,036 3,685 12,721 117.50 9.21 11.19 1.99 3.08 0.68 1.29 0.35 Dolni Chiflik VAR13 13,087 6,825 19,912 125.35 11.57 9.52 2.83 2.46 0.90 1.00 0.44 Devnya VAR14 947 8,704 9,651 108.78 16.73 8.50 5.59 1.72 1.38 0.54 0.50 Dalgopol VAR16 10,434 5,369 15,803 110.51 10.07 11.34 2.96 2.99 0.99 1.22 0.50 Provadia VAR24 11,311 14,024 25,335 123.53 12.67 9.68 1.89 2.67 0.65 1.11 0.33 Suvorovo VAR26 2,872 4,725 7,597 119.25 16.31 8.82 3.63 2.16 1.08 0.83 0.50

61 Table D2. Poverty and inequality in districts and municipalities (poverty line =46.1 BGL per month in 2001 prices), continued Population Per capita consumption Poverty headcount, % Poverty depth, % Poverty severity, % Municipality District Municipality code rural urban total mean std. err. mean std. err. mean std. err. mean std. err. Vidin Total 52,207 76,298 128,505 144.51 13.29 4.38 1.33 1.09 0.31 0.44 0.12 Belogradchik VID01 2,311 5,725 8,036 140.70 24.18 5.47 2.77 1.27 0.72 0.47 0.28 Boynitsa VID03 2,190 2,190 110.03 13.61 7.09 3.94 1.69 1.22 0.63 0.57 Bregovo VID06 4,144 3,091 7,235 152.93 15.51 3.28 1.33 0.79 0.36 0.31 0.16 Vidin VID09 16,807 59,998 76,805 151.28 22.31 2.85 2.12 0.60 0.48 0.21 0.17 Gramada VID15 1,078 2,099 3,177 155.50 24.99 4.21 2.44 1.03 0.67 0.40 0.29 Dimovo VID16 7,236 1,500 8,736 113.19 9.46 10.62 3.06 3.03 1.14 1.32 0.60 Kula VID22 2,761 3,885 6,646 146.76 19.06 3.30 1.35 0.75 0.37 0.28 0.17 Makresh VID25 2,513 2,513 124.30 13.69 5.68 3.16 1.42 0.97 0.56 0.46 Novo Selo VID30 4,150 4,150 162.17 19.40 3.37 1.85 0.88 0.58 0.37 0.27 Ruzhintsi VID33 6,039 6,039 113.67 10.15 12.02 3.21 3.57 1.27 1.59 0.70 Chuprene VID37 2,978 2,978 115.26 10.63 10.68 2.37 3.64 1.00 1.75 0.61 Vratsa Total 101,619 138,346 239,965 135.36 9.28 5.66 0.80 1.45 0.21 0.58 0.09 Borovan VRC05 7,080 7,080 93.91 10.08 16.09 5.58 4.64 2.05 2.01 1.09 Byala Slatina VRC08 17,258 13,660 30,918 128.54 14.40 7.92 1.98 2.04 0.60 0.83 0.29 Vratsa VRC10 16,128 67,533 83,661 141.58 23.35 3.60 1.68 0.85 0.36 0.33 0.13 Knezha VRC19 4,250 12,776 17,026 148.05 22.00 3.86 1.84 0.85 0.46 0.30 0.19 Kozloduy VRC20 9,388 14,761 24,149 159.71 22.87 4.57 1.73 1.16 0.51 0.46 0.24 Krivodol VRC21 8,369 3,805 12,174 113.08 9.32 10.18 2.17 2.94 0.77 1.29 0.41 Mezdra VRC27 13,297 12,312 25,609 129.86 12.82 4.66 1.18 1.15 0.31 0.45 0.14 Mizia VRC28 5,527 4,053 9,580 133.28 14.74 5.67 2.51 1.42 0.78 0.57 0.37 Oryahovo VRC31 8,910 6,073 14,983 129.00 15.14 6.49 2.50 1.60 0.76 0.62 0.36 Roman VRC32 4,529 3,373 7,902 117.54 10.29 8.94 2.40 2.42 0.78 1.00 0.40 Hayredin VRC35 6,883 6,883 113.39 11.78 8.15 3.17 2.15 1.04 0.88 0.52 Veliko Tarnovo Total 100,792 188,116 288,908 147.18 10.41 4.51 0.56 1.16 0.15 0.47 0.07 Veliko Tarnovo VTR04 15,748 72,759 88,507 156.35 26.27 2.29 0.95 0.51 0.19 0.19 0.07 Gorna Oryahovitsa VTR06 14,097 38,545 52,642 152.50 20.61 3.45 1.22 0.83 0.30 0.32 0.13 Elena VTR13 4,787 6,335 11,122 117.93 17.55 11.29 2.54 3.20 0.94 1.37 0.52 Zlataritsa VTR14 2,229 2,651 4,880 102.32 12.04 12.04 5.13 2.81 1.41 1.01 0.58 Lyaskovets VTR20 6,285 9,196 15,481 141.58 17.70 3.70 1.56 0.96 0.45 0.40 0.22 Pavlikeni VTR22 15,299 15,645 30,944 159.84 15.74 5.01 1.20 1.35 0.39 0.56 0.20 Polski Trambesh VTR26 13,378 5,156 18,534 136.18 10.60 8.33 1.78 2.41 0.73 1.05 0.41 Svishtov VTR28 16,972 30,172 47,144 146.99 17.53 3.03 1.15 0.73 0.27 0.29 0.11 Strazhitsa VTR31 10,996 5,159 16,155 107.19 9.38 12.98 3.00 3.51 0.98 1.44 0.48 Suhindol VTR32 1,001 2,498 3,499 149.50 19.02 4.01 1.60 0.93 0.48 0.34 0.24

62 Appendix E. Poverty and inequality maps E. Poverty and inequality maps Figure E1. Mean Per Capita Consumption by Municipality, BGL

Mean per capita consumption 80.1 - 113.1 113.2 - 125 125.1 - 134.8 134.9 - 146.4 146.5 - 185.7

Note: The categories are based on the consumption quintiles; the numbers are in 2001 prices

63 Figure E2. Poverty Headcount Index by Municipality, % (poverty line = 61.5 BGL)

Poverty headcount index 3.2 - 9.0 9.1 - 11.8 11.9 - 16.1 16.2 - 20.4 20.5 - 43.8

Note: The categories are based on the poverty headcount index quintiles

64 Figure E3. Poverty Depth Index by Municipality, % (poverty line = 61.5 BGL)

Poverty depth index 0.6 - 2.1 2.2 - 3.0 3.1 - 4.3 4.4 - 5.9 6.0 - 15.8

Note: The categories are based on the poverty depth index quintiles

65 Figure E4. Poverty Headcount Index by Municipality, % (poverty line = 46.1 BGL)

Poverty headcount index 0.8 - 3.5 3.6 - 5.2 5.3 - 7.4 7.5 - 10.4 10.5 - 28.3

Note: The categories are based on the poverty headcount index quintiles

66 Figure E5. Poverty Depth Index by Municipality, % (poverty line = 46.1 BGL)

Poverty depth index 0.1 - 0.8 0.9 - 1.2 1.3 - 1.8 1.9 - 2.8 2.9 - 8.9

Note: The categories are based on the poverty depth index quintiles

67 Figure E6. Theil mean log deviation index, GE(0), by Municipality, %

GE(0) 9.9 - 11.9 12.0 - 13.2 13.3 - 14.5 14.6 - 15.9 16.0 - 20.5

Note: The categories are based on the Theil mean log deviation index quintiles

68 Figure E7. Theil entropy index, GE(1), by Municipality, %

GE(1) 10.2 - 12.1 12.2 - 13.5 13.6 - 14.7 14.8 - 16.2 16.3 - 20.1

Note: The categories are based on the Theil entropy index quintiles

69