Report No. 18411

BulgariaPoverty during the Transition

June 7, 1999

Human Development Sector UnitEurope and Central Asia Region

Document of the World Bank

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CURRENCY EQUIVALENTS(as of April 30, 1999)

Currency Unit = Lev (plural Leva)1,841.05 Lev = US$ 1.00

US$ 0.000543 = lLev

WEIGHTS AND MEASURESMetric System

ABBREVIATIONS AND ACRONYMS

ALMP = Active Labor Market ProgramBIHS = Bulgaria Integrated Household SurveyBMI = Basic Minimum IncomeBNB = Bulgarian National BankCEE = Central and Eastern Europe

CMEA = Council for Mutual Economic AssistanceCPI = Consumer price index

EOP = End of periodFSU = Former Soviet UnionGDP = Gross Domestic ProductHBS = Household Budget Survey

IBRD = International Bank for Reconstruction and DevelopmentILO = International Labor OfficeIMF = International Monetary Fund

MOF = Ministry of FinanceMOLSP = Ministry of Labor and Social Policy

NES = National Employment ServiceNSI = National Statistics Institute

PAYG = Pay-as-you-go (pension system)SOE = State Owned EnterprisesUB = Unemployment BenefitUF = Unemployment Fund

UNDP = United Nations Development Program

FISCAL YEARJanuary 1 to December 31

Vice President Johannes F. Linn, ECAVPDirector Andrew N. Vorkink, ECCO5

Sector Director James Christopher Lovelace, ECSHDSector Leader, Economics Maureen A. Lewis, ECSHD

Staff Member Mamta Murthi, ECSHD

BULGARIA: POVERTY DURING THE TRANSITION

TABLE OF CONTENTS

EXECUTIVE SUMMARY .................. i - xii

1. POVERTY AND MACROECONOMIC DEVELOPMENTS ..A. Trends in output and inflation .2B. Fiscal challenges .3C. Trends in employment and unemployment. 4D. Trends in wages and pensions .5

2. POVERTY, INEQUALITY AND GROWTH . . 7A. Data and methodology. 7B. Poverty: level and trends .8C. The relative roles of declining consumption and rising inequality .11D. Looking ahead: what is the likely impact of growth on poverty

reduction .13

3. A PROFILE OF THE POOR .. 15A. Regional and rural-urban dimensions of poverty .15B. The ethnic dimension .17C. Poverty, household size and demographics .19D. Education and poverty .21E. The sources of income and the role of social transfers .23F. Patterns of consumption and poverty .24G. Housing conditions of the poor and non-poor .25H. Poverty persistence and household characteristics .27

4. LABOR MARKETS AND POVERTY . .30A. Changes in the labor force .30B. Profile of the unemployed and job search .32C. The skills gap .34D. Trends in real wages and earnings inequality .35E. Wage determination and relative wages .37F. Labor market characteristics of the poor .40G. Employment, earnings and poverty .41H. Unemployment and poverty .43

5. PUBLIC SPENDING AND POVERTY REDUCTION . .45A. Incidence analysis: who benefits from the social safety net? . 46B. Impact of the social safety net on poverty .50C. Scope for improved targeting .51D. Education .51E. Health Services .56

6. CONCLUSIONS AND RECOMMENDATIONS . .60A. Ensuring macroeconomic stability and undertaking structural reforms. 60B. Encouraging employment growth. 62C. Strengthening social assistance .65D. Investing in human capital .68E. Improving poverty monitoring .68

ANNEXES

Annex I Supplementary Tables for Poverty ProfileAnnex 2 Construction of PanelAnnex 3 Multivariate Estimation of Labor Market OutcomesAnnex 4 Trends in Social Expenditures in Bulgaria

BIBLIOGRAPHY

LIST OF TABLES:

1.1 Key macroeconomic indicators2.1 Recent trends in poverty and inequality in Bulgaria2.2 Alternative estimates of poverty and inequality in Bulgaria2.3 Decomposition of poverty into growth and inequality components2.4 A comparison of consumption inequality in selected transition economies2.5 Simulated poverty rates (head count) under alternative growth scenarios2.6 Simulated poverty rates (head count) under alternative growth and inequality scenarios3.1 Poverty measures and shares of individuals by region3.2 Poverty measures and shares by population group3.3 Poverty measures and shares of individuals 18 years or older and currently not in school3.4 Poverty measures and shares of individuals by major source of income and locality3.5 Expenditure budget share by poor/non-poor individuals3.6 Selected housing characteristics by poor/non-poor individuals3.7 Poverty dynamics, 1995-973.8 Characteristics of 'persistently' poor versus 'never' poor households4.1 Changes in the labor force, 1994-19974.2 Changes in labor force status, 1996-19974.3 Duration of unemployment in 1995 and 19974.4 Educational attainment of employed and unemployed, 19974.5 Trends in real wages, 1990-19974.6 Summary of earnings distribution, 1995 and 19974.7 Ratio of private to public sector wages by education level4.8 Contribution of selected factors to (log) earnings inequality4.9 Labor market characteristics of the poor4.10 Poverty incidence by number of earners in household4.11 The incidence of poverty by mean household earnings4.12 The relationship between household earnings and employment4.13 Poverty and unemployment5.1 Incidence of social benefit receipt among households5.2 Percent of poor (ex-ante) households moved out of poverty due to receipt of social benefits5.3 Ex-ante targeting of social transfers

LIST OF FIGURES

1.1 Index of real GDP, Bulgaria and Eastern Europe1.2 Inflation (CPI, annual average)1.3 Registered unemployment in Bulgaria1.4 Average monthly wages (public sector) and pensions2.1 CDF of per capita monthly consumption, 1995 and 19972.2 Share of consumption decile3.1 Poverty rates by regions3.2 Poverty rates by household size3.3 Poverty rates by gender of household head3.4 Poverty rates by age3.5 Education attainment by poor/non-poor3.6 Proportion of households by major income source5.1 Trends in social spending in Bulgaria5.2 Average benefit received in leva per month5.3 Benefit as a percentage of recipient household's expenditures5.4 Trends in enrollment rates in Bulgaria5.5 Net enrollment in basic and secondary education by quintile5.6 Distribution of education spending by quintile5.7 Distribution of health spending by quintile

LIST OF BOXES

1.1 Demographic trends in Bulgaria2.1 Perceptions of impoverishment2.2 Decomposition of poverty into growth and distribution components3.1 Ethnic dimensions of poverty in Bulgaria3.2 Examining poverty using panel data

ACKNOWLEDGEMENTSThis report was prepared by a team first led by Ms. Neeta Sirur, then Ms. Mamta

Murthi. The principal source of information is the Bulgaria Integrated Household Survey,conducted in two years 1995 and 1997, and accompanying qualitative surveys. Results basedon the 1995 round of the survey were presented and discussed with Government and otherstakeholders at a workshop held Sofia in 1996. The report has benefited greatly fromcomments provided by workshop participants and, more generally, from close collaborationwith the Ministry of Labor and Social Protection. The report is based on a number ofcontributions from: Zeljko Bogetic (macroeconomic developments, 1990-95); Anis Dani(Coordinator, additional qualitative inputs, 1997-98); Carlo del Nino (poverty profile, 1995);Lionel Demery (incidence of health and education spending, 1995); Stella Ilieva(macroeconomic developments, 1995-97); Kalpana Mehra (incidence of health and educationspending, 1995); Mamta Murthi (poverty profile, 1997, poverty dynamics 1995-97); DenaRingold (social sector spending, 1991-97); Menno Pradhan (incidence of health and educationspending, 1997); Lena Roussenova (macroeconomic developments, 1995-97); Jan Rutkowski(labor markets, 1995 and 1997); Emmanuel Skoufias (incidence of cash transfers, 1995 and1997); Ramya Sundaram (poverty profile, 1997, poverty dynamics 1995-97); and Wouter Zant(incidence of health and education spending, 1997).

EXECUTIVE SUMMARY

1. The transition from a planned to a market economy has not been easy in Bulgaria.Macroeconomic performance has been worse than the average for Central and EasternEurope (CEE). Output has dropped by more and inflation has been higher than othercountries in the region. As a result, households have seen a sharper contraction in theirstandard of living. It is only in 1998 when output has begun to recover and,simultaneously, inflation has been controlled that there are prospects for reversing thisdecline in living standards. Promoting a recovery in living standards through continuingthese positive macroeconomic trends, accompanied by structural reforms and programs toreduce poverty, is now one of the greatest challenges confronting the Government.

Figure 1

Index of Real G DP, Bulgaria and Eastern Europe

8 : 0 ---- ---- --- ----- -->--- --------- -- -- ---- ---- ---- --- --Ea- e

7 0 - -- - - - - - - --- - -- - - - - - -- - - - - - - u 0 - E a s te rn9 5

908 0 1--E asrn I

70-ia Bourga Vannaeh Mnaa Pviv Rse Sf e akv

19 90 1 9 91 1 9 92 1 9 93 1 9 94 189 95 1 9986 1 9 97 1 99 8

Figure 2

Poverty Rates by Region

60

50

40

30 adSvana 0 Ru~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~raI

20

10

0Sofia Bourgas Varna Lovech Montana Plovdiv Russe Sofia Reg Haskovo

Region

Source: Multiquery database, World BankNote: Eastern Europe is the average of Albania, Czech Republic, FYR Macedonia, Hungary, Poland, Romania, SlovakRepublic and Slovenia.

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Extent of poverty in Bulgaria

2. This report, which covers the period from 1995 to 1997 principally, estimates thatin early 1997, over 36percent of the population in Bulgaria was living in poverty.What is more, poverty increased sharply over the period 1995-97, when macroeconomicconditions took a sharp turn for the worse. The bulk of the rise in poverty can beexplained by the fall in consumption and incomes, however a significant share is due towidening inequality in earnings, and consequently, consumption. Since this time the,government has implemented a wide range of reforms stabilizing the economy leading to arecovery in growth, and an anticipated reduction in poverty.

3. The aim of this report is to examine the extent, nature, and characteristics ofpoverty in Bulgaria and to articulate short-term measures and a medium term strategythat would help to reduce poverty. In doing so, it relies on data from two speciallycommissioned multi-purpose household surveys conducted in 1995 and 1997,' as well asresearch undertaken by the Government, Bulgarian and foreign researchers, andinternational agencies. To measure poverty, the report uses a poverty line equal to two-

2thirds of average consumption in Bulgaria in 1997 (as measured by the BIHS). Whilethe precise level of poverty is a function of the chosen poverty line, there can be littledoubt that there was a substantial increase in poverty between 1995 and 1997 sincelevels of consumption declined substantially between the two years and people atlevels of consumption in 1995 suffered a clear deterioration in their standard of living.

Who is at risk of poverty?

4. According to the analysis presented in this report, about 36 percent of the populationor some 3 million people were living in poverty in 1997. A more detailed analysis ofpoverty rates among different sub-groups of the population reveals that poverty rates arehigher in rural areas. Over 41 percent of rural residents are found to be poor compared to33 percent in urban areas. Poverty also varies by region. The regions with the highestpoverty rates in 1997 were Sofia and Plovdiv, followed by Russe and Sofia city. Togetherthe poor from these four parts of the country account for 58 percent of all poor. The higher-than-average poverty rates in Plovdiv, Sofia region and Sofia city are in marked contrast to1995 when poverty rates in these areas were lower than average. Poverty rates are alsofound to be higher among ethnic minorities,3 and large households. Another vulnerablegroup is elderly, single women especially in urban areas outside Sofia city and in rural areas.

' The surveys were carried out by Gallup International, Sofia with technical support from the Ministryof Labor and Social Protection, the National Statistics Institute, and the World Bank. They shall bereferred throughout as the Bulgarian Integrated Household Survey (BIHS) with the relevant date -- 1995or 1997.

2 Since 1991, when poverty was first formally recognized in Bulgaria, the country has lacked anofficial poverty line. The absence of a meaningful official poverty line has complicated the task ofdetermining the level of and monitoring changes in poverty. A recently concluded joint project of theMinistry of Labor and Social Policy and ILO/UNDP has however made specific recommendationson the subject. The poverty line used in this report (BGL 45,466 in June 1997 prices) is close tothe lower poverty line (BGL 40,000) recommended by the joint team.

3 Over 40 percent of Bulgarian Turks and 84 percent of the Roma were found to be poor in 1997.

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Figure 3

Poverty Rates by Region

60

50

40

30 a

0RraI

IL 20

110

0Sofia Bourgas Varna Lovech Montana Plovdiv Russe Sofia Reg Haskovo

Region

Source: BIHS (World Bank Calculations)

Characteristics of the poor

5. The level of education and therefore earning opportunities appear remarkably lowerfor poor people than the population at large. As a result, labor force participation rates arelower and unemployment rates higher among the poor4. Due to their greater employmentopportunities and higher earnings, non-poor people rely more on wages as their main sourceof income, while poor people depend more on social transfers including pensions, or a mixof incomes.

Figure 4Education Attainmnent by PoorlNon Poor

100% - - - _ _ _ _ _ _ _ _- _ _ _ _

80%

Univ I Higher~

- D~~~~~~~~~~~~~~~MiddIleO40% j0 Primary

M No Education

20%

0% -_

O OPoor Non Poor Poor Non Poor

Source BIHS (World Bank estimates)

4 The unemployment rate among the poor (33 percent) is over twice as high as among the non-poor(15 percent). Only one-third of the working-age poor are employed, compared with almost one-halfof the non-poor.

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6. The poor have lower access to public services compared to the rich, especially inrural areas. Poor people have lower access to proper sanitation, and telephone services.They rely more heavily on coal (for both heating and cooking), wood, and kerosene assources of fuel. In rural areas, 76 percent of all poor use coal or kerosene stoves for cookingcompared to 62 percent of the non-poor. In urban areas, where access to district heating isgreater, 55 percent of the poor still rely on wood or coal, compared to 35 percent of the non-poor. Within the city of Sofia itself, 20 percent of the poor use wood or coal for heating,compared to 14 percent of the non-poor.

7. Not surprisingly, poor people allocate a larger amount of their budget to food(72.3 percent compared to 68.5 percent for the non-poor) and consume larger amounts ofcheaper staple grain commodities. In fact they spend nearly 29 percent of their budget oncereals compared to 14 percent for the non-poor. They also spend a larger proportion oftheir budget on energy and fuel (14.2 vs. 11.9 percent). Although out-of-pocket spending oneducation does not appear prohibitively high, enrollment rates in primary and secondaryeducation among children from poor households is below average.

Figure 5

Net enrollment in basic education Net enrollment in secondaryby quintile education by quintile

100 100

80 80 i- -- - -- - -- - -- - --

4 60 E 60 I m 197

o a,

1 2 3 4 5 1 2 3 4 5

Source * BIHS (World Bank Calculations)

8. The nature of the BIHS (which followed the same households over 1995 and 1997)allows us to examine the characteristics of those who remained poor over the period of thetwo surveys. Residents of rural areas, ethnic minorities, large households with heads whohad primary education or less, and households more reliant on social transfers or a mix ofincomes are over-represented among those who are found to be in poverty in both surveyyears. In general, households found to be 'persistently' poor between 1995 and 1997 aresimilar to those found to be poor in 1997. The only exception has to do with residence inSofia city. While residents of Sofia city show higher-than-average poverty rates and areconsequently over-represented among the poor in 1997, they are under-representedamong individuals who find themselves to be 'persistently' poor. This suggests thathigher poverty in Sofia city observed in 1997 may be an aspect of the 1996-97 crises, andmay well change in the future given that Sofia city residents are relatively well-placed tobenefit from economic growth (due to, for example, their significantly higher educationalachievements).

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Table 1: Characteristics of 'persistently' poor versus 'never' poor households

Household 'Persistently' poor 'Never' poorcharacteristics Bottom Bottom

20 percent 40 percentLocation

% Rural residence 48.2 43.5 31.0% Sofia 7.4 6.8 7.8% Other urban 44.4 49.7 61.2

Ethnicity% Bulgarian 46.2 65.3 92.9% Bulgarian Turks 19.2 16.0 6.1% Gypsy (Roma) 32.5 15.3 0.2%Other 2.1 3.3 0.8

DemographicsAverage household size 4.7 4.3 3.4

1995Average household size 4.8 4.3 3.4

1997%Femaleheaded 13.0 15.7 11.1

Education of householdhead

%No 10.3 7.7 3.9% Primary 26.9 21.7 18.5% Middle 15.7 23.9 27.5% Secondary 36.5 38.5 37.9% University and higher 10.6 8.2 12.2

Main source of incomeWages 32.8 42.7 46.2Pensions and other 12.8 11.0 5.5

transfersIn-kind 7.1 9.4 19.9Agriculture 5.7 8.6 5.7Mixed 41.5 28.3 19.0

Source: BIHS (World Bank Calculations)Note: A household is considered to be persistently poor if it finds itself in the bottom one or two quintiles in bothsurvey years. A household is 'never poor' if it did not fall in the bottom two quintiles in either survey year.

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Labor market developments and poverty

9. Looking more closely at the labor market we see that the labor market in Bulgariais fairly stagnant. Employment rates have risen by a fraction in the past four years (from43 percent to 45 percent of all people aged 15+) and unemployment has remained high.Although unemployment has declined recently, it may increase again (at least in the shortrun) as the restructuring process accelerates.

10. The turnover of the unemployment pool is low. An unemployed person has lowchances of finding a job.5 As a result, many unemployed become discouraged andwithdraw from the labor force. Average job search duration is long and thus theincidence of long-term unemployment is high. This is a worrisome feature of theBulgarian labor market as the long term unemployed face increasingly lower chances offinding a job due to erosion of their skills.

11. The problem of unemployment in Bulgaria is accentuated by a skills 'gap'. Manyunemployed will not be able to find a job even if there are enough vacancies becausetheir educational attainment fall short of those required by employers. Young, loweducated persons, especially those belonging to ethnic minorities, face the highest risksof unemployment. The link between low educational attainment and unemployment isparticularly strong.

12. Many of the unemployed in Bulgaria do not look intensively for a job and confinethemselves to visiting labor offices. At the same time, they have excessive wageexpectations; that is, the wages they are prepared to work for are much higher than whatthey can bargain for. These unrealistic expectations may contribute to the persistence ofhigh unemployment. The receipt of unemployment benefits does not appear to reduce theintensity of job search.

13. As mentioned above, one factor accentuating poverty in Bulgaria has been theincrease in earnings inequality. Between 1995 and 1997, there was a sharp increase inthe incidence of low pay. Low pay in Bulgaria is mainly associated with low educationalattainment, but also with working in a low paying industry, such as agriculture, trade, andthe social services. The incidence of low pay is higher in the private sector. Moregenerally, private sector jobs are less attractive than public sector jobs; although this maybe reflective of a greater degree of under-reporting of earnings in the private sector as aform of payroll tax evasion. In particular, the private sector offers substantially lowereducational premia, which is peculiar to Bulgaria, since in other transition economieswell educated workers are better off in the private than in the public sector.

5 According to the BIHS, the probability that an unemployed person will find a job within twelvemonths is around 6.2 percent. This is roughly one-sixth of the yearly exit rate from unemploymentobserved in CEE countries such as Poland, and less than one-eight of those prevailing in high-unemployment Western European countries such as Spain.

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Table 2: Summary of earnings distribution, 1995 and 1997

1995 1997National National Public sector Private sectoreconomy economy

Gini 28.1 40.0 39.3 41.5P1O 57.7 44.6 43.8 44.1P90 192.3 245.5 250.0 213.1Decile ratio 3.3 5.5 5.7 4.8Incidence of

Low pay 17.8 24.7 22.1 33.3High pay 14.0 15.1 16.9 9.2

Source: BIHS (World Bank Estimates)Notes:P10 denotes the earnings of the bottom decile relative to the median, expressed as a percentage.The decile ratio is the ratio of earnings at the top decile to earnings at the bottom decile, i.e. P90/PlO.Low pay is defined as earnings lower than 2/3 times the median.High pay is defined as earnings higher than 2 times the median.

14. Many of the poor do work, but their "earning power" is weaker than that of thenon-poor. Thus, the "working poor" account for a substantial proportion of all poor. Toa large extent this reflects the fact that the poor are employed in low productivityindustries, such as agriculture, or work in low paying jobs in the social services. Infamilies with workers, poverty is a consequence of low earning capacity and loweffective labor supply. Both factors tend to go hand in hand: households with lowerearning power tend to have a lower number of earners.

The incidence of public spending

15. Bulgaria's system of cash transfers (both social insurance and social assistance), ascurrently structured, is unable to satisfactorily fulfill either an income replacement or apoverty relief function, nor (given the large numbers of beneficiaries) is it able to raiseindividual benefits to meaningful levels without upsetting the fiscal balance. Despiterelatively high costs, the quality and impact of services within some unemploymentprograms and social assistance is open to question. Moreover, the present system isprobably acting as a hindrance to economic growth, inter alia by raising labor costs in theformal sector and encouraging increased informalization of the economy.

16. In practical terms, while the incidence of cash transfers is higher among the poor,and the average benefit received (with the exception of pensions) is higher for poor thannon-poor households, cash transfers are a relatively small share of total householdexpenditure. They have a relatively small impact on poverty: only about a third of (ex-ante) poor households are moved out of poverty as a result of social benefits. This can beexplained by a combination of factors: low incidence; low benefit levels; and, to anextent, poor targeting (over a third of households receiving various forms of socialassistance, and 58 percent of those receiving child allowances were not poor before thereceipt of the benefit).

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Figure 6

Average benefit received in leva per month

4000035000 ---- --30000 _ *-- --

° 25000 -_ --- |-- Poor20000 -- _- _- |Non-poor

> 15000 - - ------- --- A-- -

50000

Any or Pensions UB Child all. Socialall Ass.

Source: BIHS 1997

Figure 7

Benefit as a % of recepient household's exp.

40~

*t 3 0 --- - - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - - - P oeL 20 - :- Nonpoor

IL 10----111if AI

Any or Pens ions UB Child all. Socialall Ass.

Source: BIHS 1997Note: UB = unemployment benefit

17. Turning to in-kind transfers, we see that education spending is more or lessequally distributed across the population, with the poor benefiting the most from spendingon kindergartens and basic education. Health spending, however, favors the rich. This isbecause the bulk of public health spending occurs on hospitals, which tend to be used lessfrequently by the poor.

CONCLUSIONS AND RECOMMENDATIONS

A. Ensuring macroeconomic stability and undertaking structural reforms

18. Given the magnitude of output decline (over 30 percent since 1990), and thelimitations imposed on the Government by the need to maintain fiscal discipline, it shouldbe -clear that sustained growth, which raises wages and reduces unemployment, will becritical to reducing poverty in Bulgaria. It will be necessary to establish and maintain asound macroeconomic environment conducive to growth, reduce inherited price-distortions,and create conditions conducive to private sector development. The new Government, in

ix

place since April, 1997, has taken a number of steps to restore macroeconomic stability andhas initiated a program of structural reform, including privatization in the banking,agriculture and financial sectors. A first and key element of a poverty reduction strategy forBulgaria would thus consist of maintaining the current policy environment and carryingthrough much-needed reforms.

19. One fact highlighted earlier is the greater incidence of poverty in rural areas inBulgaria. The growth of the non-agricultural sector, coupled with agricultural reformsthat provide titles to land, develop land markets, increase the supply and timeliness ofagricultural inputs, and improve marketing arrangements, will all have an important rolein raising average incomes in rural areas, thereby reducing poverty. It will be importantto ensure that any initiatives to raise agricultural productivity (e.g., extension services) donot bypass the poor. An investigation into the factors that restrict access to the use ofcredit, or inputs, by poor agricultural households would also need to be undertaken toguide policy on how to (if possible) reduce these distortions.

20. Major sectoral reforms are also likely to be undertaken in the energy sector.Given the existing structure of household spending, if the adjustment of prices toeconomic levels is not to have an adverse impact on the poor, it will be important todesign suitable safety net schemes to protect the poor from unaffordable price increases.

21. Whatever combination of policies and measures is adopted by the Government, itwill be important to monitor poverty on a regular basis, as well as the effectiveness ofpoverty alleviation programs. Perhaps the first step would be to finalize a poverty line,drawing upon the recommendations of the joint MOLSP/ILO/UNDP study, or using thepoverty line used in this study (which is close to the lower poverty line of theMOLSP/ILO/UNDP study). Follow-up work on national and regional trends in poverty,and the incidence of public spending will be necessary. Closer analysis of a number ofsocial protection initiatives is also warranted. Capacity to undertake such analysis will needto be developed.

B. Encouraging growth in employment

22. Unemployment in Bulgaria is high and is one of the major causes of poverty.Economic growth is essential to assure an increase in the demand for labor and thecreation of new jobs. At the same time, sound labor market policies can encourageemployment growth.

23. Policies that would encourage the growth of employment, relative to thedevelopment of skills and qualifications of individuals, are:

* Long-term reform of the education system: In order to take full advantage of agrowing economy, individual skills, especially of the unemployed, will need to beupgraded. Bulgaria does have a well educated, skilled labor force. As in othereconomies, there is scope for improvement and over the long term, there are at leasttwo areas of reform in the education sector which would assist in expanding the labormarket opportunities of the population: (i) greater emphasis on increasing theeducational achievement of the population as a whole, through an increase in

x

secondary enrollments; and, (ii) within secondary education, greater emphasis ongeneral secondary education at the expense of obsolete or non-transferable vocationalskills.

* Raising enrollments among children from poor households: While educationreform is probably best considered a medium-term objective, the fall in enrollmentrates among children from poor households is of immediate concern. Reversing thesenegative trends will be important if children from poor households are not to be at adisadvantage in the future labor market.

* More and better labor market information: While the report finds no evidencethat the system of unemployment benefits has significant disincentives for job search,the unemployed do seem to have excessive wage expectations, which may get in theway of their accepting the jobs that are on offer. This suggests that there is a role forthe public employment services in providing more and better information on whatemployment prospects exist and at what rates of remuneration, thereby facilitating areduction in unemployment.

* Improvements in active labor market programs (ALMPs): In addition to runningthe employment services, the Government also conducts three ALMPs: (i) temporaryworks, (ii) wage subsidies, and (iii) training. Given the limitations on resources,6 itwould be important to evaluate existing programs from the viewpoint of outcomes,targeting, and cost-effectiveness. The findings could then be used to guide policydevelopment. International evidence suggests that ALMPs are often most effectivewhen they are used to assist groups who are the most disadvantaged in the labormarket. From this point of view, the emphasis in the new Act on Unemployment onALMPs that are aimed at the youth, the long-term unemployed, and ethnic minorities,is to be welcomed. The recently announced review of ALMPs by the Government isa very positive step.

24. Factors that would encourage employment generation are:

- Reduction in social insurance taxes: High payroll taxes associated with socialinsurance is likely to have a strong negative impact on employment creation inBulgaria, particularly in the formal sector.7 Significant reduction in these tax rateswill primarily depend on successful implementation of pension reform (pensions arethe largest source of tax), as well as a continued lowering of unemployment insurancecontributions. Likewise, the 6 percent payroll tax that will be imposed by the HealthInsurance Fund from mid-1999 will need to be offset by corresponding reductions inother payroll taxes.

* Encouraging greater flexibility in the market for labor: The Labor Code whichgoverns labor market institutions in Bulgaria has been through several revisions andis generally well-suited to the needs of a market economy -- avoiding some of themost restrictive provisions found in some neighboring transition economies (e.g.,

6 Total spending in 1996 on all ALMPs was less than 0.25 percent of GDP.

7 Social insurance taxes in Bulgaria currently average 47.5 percent of net wages.

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prohibition of fixed-term, part-time and additional work, restrictions on enterprise-level collective bargaining, unduly onerous standards for firings and lay-offs, etc.).Nonetheless, fuirther improvements can be made, including: reductions ofrequirements with respect to maternity and child leave; reform of sick payregulations; and easier termination for misconduct or economic reasons.

25. Given a return to economic growth and a rise in average incomes, poverty can beexpected to fall. The simulations presented below show the impact of uniform growththat benefits all sections of the population. With uniform growth of 3.0 percent perannum for 5 years, the proportion in poverty would fall from 36.0 percent to 27.6 percent,a reduction of over 23.0 percent. At a higher rate of growth, say 5 percent, the proportionin poverty would fall to 25.1 percent after 5 years, a reduction of over 30.0 percent.

Table 3: Simulated poverty rates (head-count)under alternative growth scenarios

No change in income distribution

Growth rate Head-count ratio after:% per annum 1 year 2 years 3 years 4 years 5 years

1 35.4 34.9 34.3 33.7 32.62 34.9 33.7 31.9 30.9 29.53 34.3 31.9 30.4 28.5 27.64 33.7 30.9 28.5 27.3 25.1

Source: World Bank Calculations

26. The above simulations ignore changes in inequality, or the fact that not allindividuals may benefit equally from growth. The table below presents illustrations ofthe likely impact of both growth and changes in distribution on poverty. With no changein inequality, poverty will fall from 36.0 percent to 33.7 percent; if there is one-timegrowth of 4 percent; 32.0 percent, if growth is 6 percent; 30.9 percent, if growth is8 percent; and 29.9 percent, if growth is 10 percent. With worsening inequality, thepoverty-reducing impact of growth is diminished. A widening of the distribution by asmuch as occurred between 1995 and 1997 would require rates of economic growth of 6 to8 percent to merely maintain current poverty levels.

Table 4: Simulated poverty rates (head-count)under alternative growth and inequality scenarios

Change in inequality Growth rate (one-off):n 0% 2 % 4 % 6 % 8 % 10 %

No change in inequality 36.0 34.9 33.7 32.0 30.9 29.9

Increase in inequality:Lorenz curve shifts out by 5 % 37.9 36.6 35.4 34.3 32.7 31.5Lorenz curve shifts out by 10 % 39.9 38.5 37.2 35.9 35.0 33.9Same outward shift as 1995-97 39.9 39.3 37.9 36.6 35.5 34.4Source: World Bank Calculations

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C. Strengthening the social safety net

27. These simulations draw attention to the fact that a strong social safety net, well-targeted at those who are the least likely to benefit from growth, will be essential toreducing poverty. The system of social assistance in Bulgaria prior to 1998 suffered fromsome key drawbacks:

(i) fragmentation;(ii) inadequate funding;(iii) poor targeting; and(iv) poorly defined financing responsibilities.

As a result, overall coverage of the system is very low. The overlap of programs withdifferent targeting mechanisms underrnines the ability to reach the poorest groups in thepopulation. Over a third of households receiving social assistance are not poor (ex-ante).The overall level of spending on social assistance, especially on income support, is low:spending on all social assistance was 0.7 percent of GDP; and on income support (theBasic Minimum Income (BMI) program) was 0.07 percent of GDP in 1996. This shouldbe raised to a level of 1.5 percent of GDP to provide a well-targeted basic minimumincome guarantee.

28. Reforms in four areas, some of which have been underway since 1998, wouldincrease the poverty reduction impact of the social assistance system:

R Reduced fragmentation: Following the passage of the Social Welfare Act early in1998, the Government has taken key steps to reduce fragmentation includingcombining eligibility criteria for the BMI program and the program of in-kind supportfor utilities. However, there is scope for further consolidation. In principle, this couldproceed to the point where the means-tested BMI program becomes the principalsource of social assistance.

- Increased funding: In addition to expanding the envelope for social assistance asindicated above, more resources could be made available for the poorest by lookingfor savings within programs. Increased fumding could also be sought by cutting backon untargeted programs. Perhaps the most significant program in this context ismaternity leave for uninsured mothers, which costs over twice as much as the BMIprogram (0.2 percent of GDP versus less than 0.1 percent for BMI), and whichbenefits rich and poor alike. Finally, increased NGO participation in the provision ofsocial assistance and social welfare is likely to expand funding further, as well asraise the standards of care for clients in social care institutions.

* Improved targeting: In general, social assistance in Bulgaria appears to be relativelywell-targeted. However, there is scope for improvement. Discretionary socialassistance payments, for example, often tend to be regressive (accruedisproportionately to the non-poor). The Government has already taken steps toreduce the scope for leakage from the system through altering the provisions for one-offdiscretionary payments to households. There is need for further analysis of the extent ofleakage from the BMI scheme, to allow the extent of leakages to be identified and

xiii

reduced.

* Clear responsibilities: The decentralization of social assistance in Bulgaria hasgenerally not worked well. However, the new Social Welfare Act is a step in theright direction. It clarifies institutional roles and provides for administrativestrengthening of the system. In order to improve the viability of the scheme, the BMIprogram will be funded on a cost-sharing basis between central and municipalbudgets, and incentives for municipal authorities to meet social welfare payments ontime will be introduced. The central government budget will provide earmarked fundstoward program costs, as well as an additional contribution to the general municipalbudget if social benefit payments are made on time. Implementation deserves carefulmonitoring to ensure that the program develops on the lines envisaged.

I

1. POVERTY AND MACROECONOMIC DEVELOPMENTS

1.1. Prior to 1991, Bulgaria was perhaps one of the most centralized of the EasternEuropean countries, as well as one of the most isolated from the West, as a result of bothits geographic position and historical ties to the Soviet Union. To a much more markeddegree than its Eastern European neighbors, the country was heavily dependent onCouncil for Mutual Economic Assistance (CMEA) markets for both imports and,especially, for the export of its otherwise largely uncompetitive goods. Thus, in the late1980s and early 1990s, two factors sent unusually large shocks through the Bulgarianeconomy: first, the unwinding of the CMEA system; and second, the introduction inFebruary 1991 of a radical reform program to shift the economy away from its (by then)demonstrably unsustainable growth path. Most sectors of the Bulgarian economy by thistime were characterized by internal inefficiency: the goods produced were largelyuncompetitive in international markets; and shortages of many products were widespreadin the last years of the 1980s, despite the government's attempts to maintain consumptionby means of heavy borrowing abroad during 1985-89.

1.2. For these and related reasons, discussed further below, the transition from aplanned to a market economy has not been easy in Bulgaria. Macroeconomicperformance has been worse than the average for Central and Eastern Europe (CEE).Output has dropped by more and inflation has been higher than other countries in theregion (see Figure 1.1). As a result, households have seen a sharper contraction in theirstandard of living.

Figure 1.1

Index of Real GDP, Bulgaria and Eastem Europe

100 1'

95 -

90

85

80 Eas te75 ~~~~~~~~~~~~~~~~~~~~Europe

70

65

60

1990 1991 1992 1993 1994 1995 1996 1997 1998*

Source: Multiquery database, World Bank

2

Figure 1.2

Inflation (CPI, Annual Average), Bulgaria and Eastern Europe

1200

600 - - Bulgaria

-a-EatenEop

200 :: -- - - - -

1990 1991 1992 1993 1994 1995 1996 1997 1998-

'estimate

f ~ ~Source: Multiquery database, World BankNote: Eastern Europe is the average of Albania, Czech Republic, FYR Macedonia, Hungary, Poland, Romania, SlovakRepublic and Slovenia.

A. Trends in output and inflation

1.3. From the vantage point of 1998, four distinct periods can be identified marked byalternating phases of contraction and expansion: 1989-93, 1994-95, 1996-mid 97, andmid-1997 onwards.

1.4. 1989-93: The first period saw the end of communism and the introduction ofeconomic reforms, including the liberalization of prices, trade and foreign exchange, therestitution of urban property, and initiation of privatization. Measured output declined byone-third and inflation averaged 96 percent annually.

1.5. 1994-95: Macroeconomic indicators improved during this period. Output grewby over 2 percent on average, while inflation declined further. The main reasons for theupturn was the improved performance of state enterprises and growth of the privatesector, related in part to improved access to Western markets. The recovery was,however, fragile.

1.6. 1996 through mid 1997: Accumulated structural problems in the banking andstate enterprise sectors and stalled privatization, reflected in a rising budget deficit andmounting payments arrears, caused the macroeconomic situation to deteriorate onceagain early in 1996. This marked the beginning of a second period of contraction. Thesituation reached crisis proportions by late 1996 when the country was caught in a viciouscircle of expanding public debt, mounting deficits, soaring inflation and rapid exchangerate depreciation. By the end of the year, GDP had declined by 10 percent, monthly

3

inflation had risen from 33 percent to 311 percent, and the lev had depreciated from 71 to487 per US dollar. The situation persisted into the first third of 1997.

1.7. The social impact of the crisis of 1996 and early 1997 was instrumental inbringing down the government, with the resignation of the Cabinet and the dissolution ofthe Parliament taking place in the wake of sustained and intensifying political protestsagainst the decline in the standard of living. A new government was elected in April1997 with a mandate to move quickly to restore economic stability.

Table 1.1: Key Macroeconomic Indicators

1993 1994 1995 1996 1997*Real EconomyGDP growth' -1.5 1.8 2.9 -10.1 -6.9Inflation (end-period) 63.9 121.9 32.9 310.8 578.6Nominal exchange rate, eop 32.7 66.0 70.7 487.4 1776.5(Leva/US$)

Balance of Payments (% of GDP)Current account balance -10.1 -0.3 -0.2 0.8 4.4

Public Finance2 (% of GDP)Total Revenue 39.4 41.8 37.3 33.2 34.2Total Expenditures 50.3 47.6 42.9 43.6 36.8

Social Protection 14.2 12.3 10.1 8.6 8.9Interest 9.4 13.5 14.1 19.7 8.4Other 26.7 21.8 18.7 15.3 19.5

Fiscal Balance -10.9 -5.7 -5.6 -10.4 -2.6Source: NSI, Ministry of Finance and BNB. *Preliminary data.

I Including holding gains in GDP estimate for 1993 and 1994.2 Consolidated General Government Budget including State Fund for Reconstruction and Development.

1.8. Mid-97 onwards: The new government introduced a currency-board arrangementin July 1997, as a part of a package of reforms designed to achieve and maintain asustainable stabilization. The IMF and international community has concluded that thisappears to be working, reform has been very successful to date, and the domestic thecurrency has stabilized. Month-on-month inflation fell rapidly to 1-2 percent per monthby year-end, and has been virtually zero thereafter. GDP grew modestly in the third andfourth quarters of 1997, and registered a substantial increase during the first quarter of1998.

B. Fiscal challenges

1.9. One factor contributing to problems with stabilization is the nature of theGovernment's budget which is highly inflexible on the expenditure side. Expendituresare dominated by very large interest payments and social protection expenditures,including pensions. High pension spending is related in part to the age structure of theBulgarian population (see Box 1.1). Central government domestic debt has expanded

4

substantially, to some extent due to attempts to resolve the bad debt problems in the statesector. Interest payments have ballooned, although the sharp drop in interest ratesfollowing the introduction of the currency board has brought much needed respite. On aless positive note, government revenues have declined as a share of GDP from a peak of41.8 percent in 1994 to 34.2 percent in 1997 aggravating the fiscal situation (see Table11.),

Box 1.1: Demographic Trends in Bulgaria

Demographic trends during the transition in Bulgaria have been dramatic andhave gained domestic and international attention. Along with Russia, Bulgaria was oneof the first transition economies to experience a negative natural growth rate.Beginning in 1990, deaths began to outnumber births. Although demographic trendsmay have been exaggerated by the transition, they are best seen as an acceleration ofpre-transition developments.

Declining births imply an aging population. In fact, Bulgaria's old-agedependency ratio (the share of population 60 years of age and older to the working agepopulation) is the highest of all transition economies. In 1996, this ratio was 27.4 inBulgaria compared to an (unweighted) average of 20.7 for the transition economies ofCEE and the Former Soviet Union. This has significant implications for the socialinsurance system. High dependency ratios mean that increasingly fewer individualscontribute to the social insurance system, while more and more receive benefits. Thisimplies either raising the burden on current workers or reducing the benefits of currentand future retirees to keep the system in balance. More immediately, a sharp reductionin the birth rate has implications for the size of the school system as it results in a rapidreduction in the number of new school entrants.

Bulgaria: Selected Demographic and Health Indicators (1989-96)

1989 1990 1991 1992 1993 1994 1995 1996Life expectancyMales 68.6 68.1 68.0 68.0 67.7 67.3 67.1 67.1Females 75.1 74.8 74.7 74.5 74.6 74.9 74.9 74.6

Total fertility rate 1.90 1.81 1.65 1.54 1.45 1.37 1.23 1.24Natural growth rate 0.7 -0.3 -1.6 -2.1 -2.9 -3.8 -5.0 -5.3Infant mortalityrate 4.4 14.8 16.9 15.9 15.5 16.3 14.8 15.6

1.10. Underlying growing debt has been the government's inability to impose andsustain hard budget constraints on largely unprivatized state banks and enterprises.Although some progress has been made with privatization since mid-1997, including thesale of certain large State-Owned Enterprises (SOEs) and the first wave of massprivatization, progress has been slower than originally anticipated. Nevertheless, thecombined effect of contraction in the public sector and limited privatization has been anincrease in the private share of the economy. Prior to 1991, virtually all economicactivity was in the hands of the state except for small family plots and private housing.

5

The share of the private sector has since grown, rising from 17.5 percent of gross valueadded in 1991 to 66 percent in 1997.

C. Trends in employment and unemployment

1.11. In line with the decline in output, employment has experienced a significantdecline. The decline in public sector employment, more than 50 percent since 1989, hasbeen especially severe in recent years with a reduction of over 12 percent in 1996 and14 percent in 1997. Many laid-off workers have not been re-employed in the privatesector. As a result, employment levels in Bulgaria are among the lowest in Central andEastern Europe. The decline in employment levels is reflected in the rise in openunemployment. Starting from virtual full employment at the start of the transition,registered unemployment grew to over 16 percent in 1993. It then declined to a littleover 10 percent towards the end of 1995, rising to 12-14 percent thereafter (see Figure1.2). The most recent estimates (October 1998) suggest that in response tomacroeconomic recovery unemployment has dropped to 11.2 percent. There are markedregional differences in unemployment. Montana and Rousse in the north, and Bourgas inthe east, have the highest unemployment rates in the country, while Sofia city has thelowest.

Figure 1.3

Re giste red unem ploym e nt in Bulga ria

1 81 6.1 4

1 4 _- -. _ -- - -- - - -- - - -- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - -- . _- - -- -

6 -M -- - - -*- M

4 -- - ---- - - - - - - - - - - - - - - -

. _ -1 . 0 0 _. _.

1991 1992 1993 1994 1995 1996 1997

Source: National Employment Service

D. Trends in wages and pensions

1.12. Trends in wages reflect the ups and downs of the transition. As in many othertransition economies, private sector wage data pose a problem due to the underreportingof wages. Public sector data point to a cumulative decline of over 70 percent since 1990,and a consequent decline in the real income of households (see Figure 1.3). Pensions, animportant source of income for a quarter of the population, have fallenl even more sharplythan wages. As a result, the ratio of average pensions to average (public sector) wagesfell from 44 percent in 1994 to 27 percent in 1997.

6

1.13. Even this simple review of macro indicators leads to the inevitable conclusion thatthe impact of macroeconomic shocks at the individual or household level is likely to havebeen serious. Among the factors that are the most important contributors to declininghousehold welfare and spreading poverty are: (i) the decrease in recorded public sectoremployment since 1989 which has been only partially compensated for by rises in privateemployment; (ii) a substantial decline in real wage levels since 1991; (iii) annual increasesin the numbers of individuals or households registering to receive unemployment and socialassistance benefits which are themselves falling in real terms owing to fiscal constraints; and(iv) an observed deterioration in some social indicators (e.g., some health status indicators).One factor not alluded to above, but which will emerge in subsequent discussion is growingincome inequality. All these factors point not just to a sharp contraction in the generalstandard of living in Bulgaria, but also to changes in the relative position of individuals,such as pensioners and wage-earners, residents of different regions. The precise impact ofthese factors at the individual or household level will be investigated further in this report.

Figure 1.4

Average monthly wages (public sector) and pensions

150 0

. -20 _Average w age in

-20 U

loo - ------------ ----------------------- l -------------------------- C um ulativ e de clinein wages since

-40 ~1990_ _ _ * + Cumulative decline

in pensions since

-60

0 .801991 1992 1993 1994 1995 1996 1997

Source: MOLSP

1.14. Chapter 2 looks at trends in poverty and the inter-relationship between growth,inequality and poverty. Chapter 3 examines the characteristics of the poor, while Chapter4 discusses labor markets and poverty. Chapter 5 examines the poverty-reductionpotential of the main public programs while Chapter 6 sunimarizes the main findings andconclusions.

7

2. POVERTY, INEQUALITY AND GROWTH

2.1. The macroeconomic developments surveyed in the last chapter have contributedto an increase in poverty in two ways: first, through the contraction in the general level ofincome or consumption; and second, through increased concentration of that income inthe hands of the rich. This chapter discusses the contribution of negative growth andrising inequality to poverty in Bulgaria.

Box 2.1: Perceptions of ImpoverishmentExcerpts from focus group discussions

Pre-transition:" In the 1980s , we were really living in the lap of luxury. Upon their marriage, young

people took their interest-free loan and, together with their wages, were able to build a two-storeyhouse, then furnish it and buy a car - all this within a period of one year ...Whatever money camefrom tobacco (family plots) we just put in the bank as a savings deposit...."

Post-transition:" A small number of people got much richer than before, while all others suddenly found

themselves in the opposite situation of becoming severely impoverished."

In 1995:" Our income is only sufficient only if all family members are in good health. Otherwise,

if someone in the family is very ill, this amount is not nearly enough."

In 1997:" The most important thing is to have employment. If you have a job, you have an income

too. In this case, we would be able to overcome all other problems. Even if healthcare wouldhave to be paid for and education was expensive and transport costs high, we would still managesomehow provided that jobs and employment were available."

" For some time now, we have been using our electric water heater as little as 1-2 times ina month. Since January 1997 we have also stopped using our electric cooker having switched towood instead."

Source: Balkan British Social Surveys (1996, 1998)

A. Data and methodology

2.2. The principal source of information for this report comes from two speciallycommissioned multi-purpose household surveys: the 1995 Bulgarian IntegratedHousehold Survey (BIHS 1995) and the 1997 Bulgarian Integrated Household Survey,(1997).8 The surveys are nationally representative and were conducted over the periods

8The BIHSs were carried out by Gallup Intermational, Sofia with technical support from the MOLSP,the NSI and the World Bank

8

March-May, 1995 and March-September, 1997.9 Poverty is measured using a monetaryindicator of household welfare, in particular per capita consumption. In focusing on percapita consumption, we do not mean to suggest that the non-monetary dimensions ofpoverty are unimportant. However, monetary inequities often reinforce non-monetaryaspects of poverty. Per capita consumption is therefore often a good proxy for householdwelfare in total. To take account of price variations in different parts of the country,household consumption was deflated by a regional price index to bring it to a comparablebasis."

2.3. To examine poverty, we use two poverty lines: the first (or lower) poverty lineequals 50 percent of average per capita consumption in 1997; and the second (or higher)poverty line equals 66.7 percent of average per capita consumption in 1997. To comparepoverty across the two surveys, the relevant poverty line was deflated by the ConsumerPrice Index (CPI) to bring it to 1995 prices.12

B. Poverty: level and trends

2.4. Using the higher poverty line, 36 percent of the population was found to be poorin 1997. If the lower poverty line is used, the poverty rate is found to be 20.2 percent(see Table 2.1).

2.5. These estimates represent a huge increase in poverty between the survey years. Interms of the higher poverty line, the proportion of the population in poverty rose from5.5 percent (approximately 450,000 people) in 1995 to 36.0 percent (approximately 3million people) in 1997. Using the lower poverty line, the poverty rates are 2.9 percent(approximately 250,000 people) in 1995 and 20.2 percent (approximately 1.7 millionpeople) in 1997. Not only was there an increase in poverty rates, but the poor becamemarginally poorer (as measured by the ratio of poverty depth to poverty rate).Underlying the increase in poverty is a sharp fall in average per capita consumption, from

To make allowances for seasonal bias in the data, the data were adjusted by seasonal factorscalculated from the 1994 Household Budget Survey which contains 12 month panel information onconsumption. For full details, see Skoufias (1996a).

10 Consumption was calculated by adding up all of the household's current expenditures and theestimated values of non-purchased commodities, including own production and commodities receivedfrom other sources. Expenses for rent (or its imputed value in case of owner-occupied housing) andthe services of durables were not included in the calculation. The data from every month weredeflated by the monthly national Consumer Price Index normalized at June = 100. For fiuther detailssee del Nino (1996) and Murthi (1998).

See del Nino (1996), ibid.

12 Since 1991, when poverty was first formally recognized in Bulgaria, the country has lacked anofficial poverty line. The absence of a meaningful official poverty line has complicated the task of

- determining the level of and monitoring changes in poverty, and, by implication, the task of designingappropriate policies and programs to assist the poor. A recently concluded joint project of theMinistry of Labor and Social Policy and ILO/UNDP has however made specific recommendationson the subject. The second (or higher) poverty line used in this report (BGL 45,466 in June 1997prices) is close to the lower poverty line (BGL 40,000) recommended by the joint team.

9

117,208 leva per month in 1995 to 62,604 leva per month in 1997. The Giri coefficient,the most commonly used index of inequality, rose from 27.1 to 31.4 during the sameperiod.

Table 2.1: Recent trends in poverty and inequality in Bulgaria13

1995 1997Higher Lower Higher Lower

_______________ poverty line poverty line poverty line poverty linePovertyRate 5.5 2.9 36.0 20.2Depth 1.7 0.9 11.4 5.9Severity 0.8 0.4 5.3 2.7

Average percapitaconsumption inJune 1997prices (leva) 117,208 62,604

Gini 27.1 31.4Source: BIHS 1995, 1997

2.6. While the precise increase in poverty is a function of the chosen poverty line, wecan expect to find a substantial increase in poverty for almost any poverty line. This isdemonstrated in Figure 2.1 which compares the distribution of consumption in the twosurvey years. The vertical axis shows the percent of people who have a level ofconsumption that is equal to or below the level shown (in log terms) on the horizontalaxis. Looking at the curves, it should be evident that levels of consumption declinedsubstantially between the two years. The curve for 1997 lies clearly above the one for1995 showing that people at all levels of consumption in 1995 suffered a cleardeterioration in their standard of living. 14

3 The poverty rate (head-count) is the proportion of individuals below the poverty line. The povertydepth index measures average consumption shortfall in the population (the non-poor have zeroshortfall) as a proportion of the poverty line. It is a measure of the intensity of poverty. Theseverity index measures the average squared consumption shortfall in the population (again withzero shortfall for the non-poor) as a proportion of the poverty line. It gives more weight to poorerhouseholds and is thus sensitive to inequality among the poor. For further details, see Ravallion(1994).

14 Using a different poverty line, e.g. two thirds of mean consumption in 1995, we find that over 70 percentof the population was poor in 1997 compared to around 20 percent in 1995. While not wanting tominimize the problem of poverty in 1995, we have adopted a poverty line that gives us relatively lowestimates of poverty in 1995 for two reasons: (i) first, it is close to the recommendations of theMOLSP/ILO/UNDP working group, and (ii) it allows us to focus on less well-off households (thebottom two quintiles) rather than the vast proportion of the population (the bottom 70 percent).

10

Figure 2.1

Cdf of per capita monthly consumption, 1995 and 1997

c) .8C

41~t

V(.)L-8o .0)

:;4.-

Eo .2

0

8 9 10 11 12 13 14Log Per Capita Monthly Consumption, June '97 prices

Source: BIHS 1995 and 1997Note: The vertical line on the left is the lower poverty line while the vertical line on the right is the upper poverty line.

2.7. The increase in inequality between the two survey years is apparent in Figure 2.2which plots the percentage of total consumption received by each decile in 1995 and1997. The top three deciles saw a large increase in their share of total consumption over1995-97 while the bottom six deciles saw a contraction.

2.8. Data limitations do not permit us to examine trends in poverty prior to 1995.However, the recent joint study of MOLSP and ILO/UNDP based on the HouseholdBudget Survey (HBS) of the National Statistical Institute provides some guidance on thematter. Although the poverty rates are not comparable (because the HBS and the BIHSare not comparable surveys and the poverty lines are different), the findings suggest asimilar pattern of rising poverty and inequality during 1992-96. The only exception is theperiod 1994-95 when poverty rates fell while inequality, as measured by the Gini, grew.Recall that 1994-95 was also a period during which GDP experienced a modest recovery.

I1

Figure 2.2

Share of consumption decile

25.0

2 0.0

150 ..019

C_ 19 95o0 10.0E

a~5.00

0.01 2 3 4 5 6 7 8 9 10

Deciles

Source: BIHS 1995, 1997

Table 2.2: Alternative estimates of poverty and inequality in Bulgaria(Poverty line = MOLSP's subsistence minimum)

1992 1993 1994 1995 1996PovertyRate 49.8 50.3 54.3 53.7 63.9Depth 12.9 13.5 15.9 16.6 21.0Severity 4.6 5.1 6.3 6.9 9.1

Gini 22.8 23.7 24.4 25.7 25.6

Source: ILO and UNDP (1998).

C. The relative roles of declining consumption and rising inequality

2.9. The most important factor contributing to the rise in poverty in Bulgaria was thecontraction in household consumption. Rising inequality played a significant, but smallerrole. Table 2.3 decomposes the rise in poverty during the period 1995-97 into thecontribution of negative growth and the rising inequality (see Box 2.1 for methodology).If we use the higher poverty line, we see that over 72 percent of the increase in poverty(22 percentage points out of 30.5 percentage points) between the two years can beexplained by the contraction in consumption. The rise in inequality contributed to theremaining 28 percent. In terms of the lower poverty line, over two-thirds of the increasein poverty (11.5 percentage points out of 17.3 percentage points) can be attributed tonegative growth, while one-third to rising inequality. Although we do not present anycalculations here, the share of inequality would be higher if we used the poverty severityindex or some other distributionally-sensitive measure of poverty to examine the relativeshares.

12

Table 2.3: Decomposition of poverty into growth and inequality components

Poverty Poverty Poverty Change in Growth Inequalityline rate in rate in poverty * component* component*

1995 1997 (b)-( a)(a) (b) (c)+(d) (c) (d)

Higher 5.5 36.0 30.5 22.0 8.5Lower 2.9 20.2 17.3 11.5 5.8

*: percentage pointsSource: BIHS 1995, 1997

Box 2.2: Decomposition of poverty into growth and distribution components

Information on growth or changes in the overall distribution of income can generally be quiteuninformative about how these changes affect the poor. Decomposition of poverty changes allow us to answerquestions such as : to what extent has income contraction contributed to an increase in poverty, or to what extenthave the poor been made worse off as a result of worsening of the income distribution?

Before we describe how this is done, we need to defme how we measure income inequality. In ouranalysis, we represent the distribution of income through a Lorenz curve which plots the cumulative fraction ofpopulation, starting from the poorest, on the horizontal axis against the cumulative share of total income on thevertical axis. If income was equally distributed, with everyone receiving the same, the Lorenz curve would be astraight line mapping identical points on the two axes: each group in the population would receive a share of totalincome (or expenditure) that was equal to its share in the population. In practice, Lorenz curves lie below the lineof perfect equality. They are upward sloping, with increasing steepness. The Gini coefficient is one way ofsummarizing the degree of inequality in the Lorenz curve. It is given by the ratio of two areas: the gap between theLorenz curve and the line of perfect equality, and the area under the line of perfect equality. It varies from zero (noinequality) to one (extreme inequality).

Lorsnz curve

100

_ c 60 --- -e---------- - -- _ Ler inequality0FiL < ghw equaityA40 - -

00

0 20 40 60 80 100Percent of popuation

Source: Datt and Ravallion (1992), Deaton (1994)

13

Box 2.2 Continued

The growth component of change in poverty is the change in poverty due to a change inaverage income holding income distribution (the Lorenz curve) constant. The inequalitycomponent is the change in poverty due to a change in the income distribution (the Lorenz curve)holding average income constant. These two components will, in general, not add up to the totalchange in poverty. The difference is a residual which exists because the effect on poverty of achange in average income (or a change in the Lorenz curve) usually depends on the level ofaverage income (or the precise Lorenz curve). In general, the residual does not vanish, nor can itbe apportioned between the growth and redistribution components. The empirical decompositionof changes in poverty into the share of growth, redistribution, and the 'residual' depends onwhether the initial or terminal year is chosen as the reference. In this context the residual has aconvenient interpretation. The residual is the difference between the growth (or redistribution)components evaluated using the initial and terminal years as base. If one takes the average of thedecompositions based on the initial and final years (as we have done in Table 2.3), the residualcan be made to vanish.Source: Datt and Ravallion (1992), Deaton (1994)

2.10. The increase in inequality in Bulgaria is not unusual compared to other transitioneconomies. All transition economies have seen a rise in income inequality, driven in partby growing wage inequality resulting from the spread of market-determined wages in theprivate sector (see, e.g., Milanovic, 1998). Bulgaria is no different in this respect.'5 Ifanything, inequality in consumption seems relatively low by the standards of some oftransition economies -- especially within the FSU -- see Table 2.4. Future increases ininequality in Bulgaria therefore cannot be ruled out. Growing inequality is likely toreduce the poverty reduction impact of income growth as discussed below.'

Table 2.4: A comparison of consumption inequality (Gini coefficients)in selected transition economies

Kyrgyz FYRRussia Rep. Kazakhstan Macedonia Poland Bulgaria1996 1993 1996 1996 1997 19970.48 0.54 0.35 0.29 0.31 0.31

Source: Kolev (1996), Okrasa (1998), World Bank (1995), World Bank (1998 b, c)

D. Looking ahead: what is the likely impact of growth on poverty reduction?

2.11. How would different rates of growth and changes in inequality affect povertyrates in Bulgaria? The effect of growth in consumption and changes in inequality aresimulated in Tables 2.5 and 2.6 below. These simulations are not intended to bepredictions of likely outcomes, but are intended as illustrations of the types of tradeoffs

15 Growing inequality in wage earnings is discussed in greater detail in Chapter 4.

16 Among the non-transition middle-income countries, Brazil saw periods during the 1980s whenworsening distribution played as big or a bigger role in increasing poverty e.g. 1981-83, 1987-88.See Datt and Ravallion (1992) for more details.

14

that are involved in a situation of growing income and rising inequality given theconsumption distribution in Bulgaria. Table 2.5 looks at the impact of 'pure' growthassuming no changes in distribution, while Table 2.6 looks at the impact of growthallowing for changes in inequality. In Table 2.6, changes in inequality are representedthrough outward shifts in the Lorenz curve.'7

2.12. Table 2.5 illustrates the poverty reduction potential of economic growth which isshared by everyone. We see that with uniform growth of 3 per annum for 5 years, theproportion in poverty would fall from 36 percent to 27.6 percent, a reduction of over23 percent. At a higher rate of growth, say 5 percent, after 5 years the proportion inpoverty would fall to 25.1 percent, a reduction of over 30 percent.

Table 2.5: Simulated poverty rates (head-count) under alternative growth scenariosNo change in inequality, higher poverty line

Growth rate Head-count ratio after:% per annum 1 year 2 years 3 years 4 years 5 years

1 35.4 34.9 34.3 33.7 32.62 34.9 33.7 31.9 30.9 29.53 34.3 31.9 30.4 28.5 27.64 33.7 30.9 28.5 27.3 25.15 32.7 29.8 27.6 25.2 22.4

Note: Simulations assume higher poverty lineSource: BIHS 1995 and 1997

2.13. Tables 2.6 illustrates the impact of increasing inequality. Clearly, the greatestimpact of growth would occur where there was no worsening in the distribution ofincome. A one-off increase in consumption by 10 percent with no increase in inequalitywould reduce the head-count ratio by over 16 percent from 36.0 percent to 29.9 percentIf growth were to be accompanied by further increases in income inequality, the povertyreduction impact would be lower. A rise in inequality which shifted the Lorenz curveoutwards by 5 percent, raising the Gini coefficient from 31.5 to 32.8, would reduce thepoverty-reduction impact of 10.0 percent growth by 1.5 percent points. Under theseassumptions, the head-count ratio would fall not to 29.9 percent but to 31.5 percent.Further increases in inequality would reduce the effects of growth still further. Anincrease in inequality by as much as the increase between 1995 and 1997 would negatethe effect of a 6 to 8 percent rise in consumption. Or, in other words, consumption wouldhave to grow by more than 8.0 percent for growth to have any impact on poverty ifinequality went up by as much as between 1995 and 1997.

17 The end-points of the Lorenz curve are, obviously, fixed. In the literature, an outward shift inthe Lorenz curve refers to the stretching of the Lorenz curve further away from the 45-degree lineof equality. For example, an x percent shift in the Lorenz curve is a fall in the share of eachpercentile (except the 100th percentile) by x percent.

15

Table 2.6: Simulated poverty rates (head-count)underalternative growth and inequality scenarios

Higher poverty line

Change in inequality Growth rates0% 2% 4% 6% 8% 10%

No change in inequality 36.0 34.9 33.7 32.0 30.9 29.9Increase in inequality:Lorenz curve shifts out by 37.95%Lorenz curve shifts out by 39.9 36.6 35.4 34.3 32.7 31.510%

39.3 37.9 36.6 35.5 34.4

Note: Simulations assume higher poverty lineSource: BIHS 1995 and 1997

16

3. A PROFILE OF THE POOR IN BULGARIA

3.1. The previous chapter examined poverty in the aggregate and its evolution overtime. This chapter provides an in-depth view of poverty in 1997, using the higherpoverty line.'8 It tries to answer the questions: which groups are at a higher risk ofpoverty, and what are the main characteristics of poor households? While the discussionwill be based largely on an analysis of the 1997 data, relevant differences with 1995 willbe highlighted. The chapter concludes with a discussion of the distinguishing features ofthe 'chronically' poor -- households which have remained in poverty since 1995.

A. Regional and rural-urban dimensions of poverty

3.2. Poverty varies considerably between different regions and between rural and urbanareas of different regions.19 We begin by reporting poverty rates based on the BIHS for1997. Looking at Figure 3. 1, it is evident that the highest poverty rates are found in Plovdivand Sofia regions, and that individuals residing in rural areas are poorer than people in urbanareas, even after adjusting for differences in price structure. In fact, poverty rates in almostall rural areas are higher than those in the urban areas in the same regions. Detailed data onpoverty (rate, depth, and severity) and poverty shares for each region are reported inTable 3.1.

Figure 3.1

Poverty Rates by Region

80

50

40.

30 U Urban0 Rural

CL 20 *AIl

10

0 Sofia Bourgas Varna Lovech Montana Plovdiv Russe Sofia Reg Haskovo

Region

Source: BIHS 1997

18 The higher poverty line is two-thirds of average per capita consumption in 1997. It is preferredbecause it close to the recommendations of the joint MOLSP/ILO/UNDP task force.

19 While the sample is nationally representative, it is not representative at the regional level. Theregional decompositions should therefore be treated as indicative.

17

3.3.Looking at Table 3.1 we see that in addition to Plovdiv and Sofia region, Russe andSofia city also show poverty rates which are higher than the national average20 . Together,these four regions account for over 58 percent of all poor individuals in Bulgaria. Thehigher-than-average poverty rates in Plovdiv, Sofia region and Sofia city are in markedcontrast to 1995 when poverty rates in these areas was lower than average.

Table 3.1: Poverty Measures and shares of Individuals by Region

URBANIRURAL Total PopulationRegion Poverty Measures

Urban Rural % of Rural Rural Poverty Total % of PovertyPopulation Share Population Shara

Poverty Rate^Sofia 37.64 0.00 0.00 0.00 37.64 13.18 13.77Bourgas 18.50 38.74 31.09 48.59 24.79 10.57 7.27Varna 30.62 41.33 29.84 36.47 33.82 11.16 10.47Lovech 30.47 31.95 40.18 41.32 31.07 11.53 9.94Montana 22.38 34.38 40.94 51.58 27.29 6.94 5.26Plovdiv 42.38 52.31 34.28 39.17 45.78 14.04 17.83Russe 37.25 38.55 46.13 46.98 37.85 8.41 8.83Sofia Reg 50.20 48.97 44.42 43.80 49.66 13.00 17.91

Haskovo 22.25 37.00 39.79 52.36 28.12 11.16 8.71

Bulgaria 33.50 41.18 33.00 37.71 36.04 99.99 99.99

Poverty Gap'Sofia 11.35 0.00 0.00 0.00 11.35 13.18 13.08Bourgas 6.40 23.06 31.09 61.91 11.58 10.57 10.70Varna 7.60 15.95 29.84 47.17 10.09 11.16 9.84Lovech 7.30 11.92 40.18 52.29 9.16 11.53 9.23Montana 5.73 10.10 40.94 54.99 7.52 6.94 4.56Plovdiv 15.33 15.12 34.28 33.97 15.26 14.04 18.73

Russe 8.11 13.94 46.13 59.54 10.80 8.41 7.94SofiaReg 17.05 16.67 44.42 43.84 16.89 13.00 19.19Haskovo 4.83 9.93 39.79 57.60 6.86 11.16 6.69

Bulgaria 9.90 14.55 33.00 41.97 11.44 99.99 99.97

Poverty DepthSofia 5.24 0.00 0.00 0.00 5.24 13.18 12.98Bourgas 2.96 15.96 31.09 70.89 7.00 10.57 13.91Varna 3.01 6.97 29.84 49.64 4.19 11.16 8.79Lovech 2.48 5.52 40.18 59.94 3.70 11.53 8.02Montana 2.33 4.11 40.94 54.99 3.06 6.94 3.99Plovdiv 7.68 6.60 34.28 30.95 7.31 14.04 19.29Russe 2.67 7.21 46.13 69.87 4.76 8.41 7.52Sofia Reg 8.47 7.97 44.42 42.91 8.25 13.00 20.16Haskovo 1.71 3.77 39.79 59.29 2.53 11.16 5.31

Bulgaria 4.42 7.13 33.00 44.23 5.32 99.99 99.97

Survey Class 4525 2229 6754

Source: BIHS 1997*see footnote 6, Executive Summary, page ix

Note: Poverty line is defined as two thirds of mean consumption 1997

3.4. The data from Table 3.1 also confirm the picture of higher poverty in rural areas.The poverty rate in rural areas is 41.2 percent compared to 33.5 percent in urban areas.As a result the share of rural areas in total number of poor (37.7 percent) is greater thanits share in the population as a whole (33 percent). The greater poverty of rural areas is

20 According to the 1995 poverty profile the regions with higher than average poverty rates wereVarna (30.4 percent), Lovech (28.8 percent), Russe (25.5 percent) and Bourgas (21.9 percent).

18

reinforced by the depth and severity indices which are higher in rural areas (povertydepth is 14.5 percent in rural areas vs. 9.9 percent in urban areas and poverty se-verity is7.1 percent in rural areas vs. 4.4 percent in urban areas). The highest poverty rates arefound in the rural areas of Plovdiv (52.3 percent), Sofia (48.9 percent), and Varna(41.3 percent).

B. The ethnic dimension

3.5. The disparity in poverty among individuals of different ethnic backgrounds isevident in Table 3.2 . The poverty rate among Bulgarian Turks is 40 percent and amongGypsies (or Roma) 84.3 percent. Despite the relative small number of Turks and Gypsies,nearly 25 percent of all poor are from these minority populations. Not only does the Gypsypopulation suffer higher poverty rates, but since the poverty depth and severity areproportionally larger (e.g. they account for 26.5 percent of the poverty depth index and 37.4of the severity index), they are also the poorest of the poor.

Table 3.2: Poverty measures and shares by population group

Population % of Poverty rate Poverty depth Poverty severitygroup population

Percent Share Percent Share Percent Share

Bulgarian 83.6 31.7 73.5 8.5 62.1 3.4 52.6Bulgarian 8.5 40.0 9.5 12.8 9.5 5.2 8.2TurksGypsies 6.5 84.3 15.2 46.6 26.5 30.6 37.4(Roma)Other 1.4 46.9 1.8 15.0 1.9 6.2 1.6

Bulgaria 100.0 36.0 100.0 11.4 100.0 5.3 100.0Note: Poverty line is defined as two-thirds mean per capita consumption in 1997.Source: BIHS 1997

Box 3.1: Ethnic dimensions of poverty in Bulgaria

The Roma (or Gypsies) have been settled in Bulgaria for many centuries. In contrast to WesternEuropean gypsies who in many cases may be of nomadic character, the Roma of Bulgaria were alreadysettled in Ottoman times. However, they have fared less well than other communities. The Roma are aheterogeneous community. In fact, they are a "community" only in so far as others are concerned, sincethe internal diversity of the group is as big or bigger than the differences with the rest of the population.The Roma themselves do not seem to have any awareness of a uniform Roma "community". They are ofvarying religions (Muslims, Eastern Orthodox Christians, Protestants, Jews), mother-tongues (Romanidialects, Turkish, Bulgarian, Wallachian dialects), traditional crafts and occupations.

The Roma are dispersed all over Bulgaria. Their proportion tends to be lower in the mountainous regions.In some towns (e.g., Lom, Sliven), the Roma constitute up to one-third of the population. There arevillages -- mainly in north-west Bulgaria - which are predominantly Roma. There are clearly definedRoma neighborhoods in almost every town, although the Roma may live among the rest of the

19

Box 3.1 Continued

population in other residential districts. Many of these neighborhoods can be ghetto-like with houses thatdo not meet sanitary standards. Poverty, poor nutrition, and poor living conditions give the Roma poorhealth status. In a recent survey, 44 percent of Roma households reported having a chronically ill member,and 20 percent reported having two or more ill members in the household. In response to rising out-of-pocket expenses in medical care, many Roma are reported not to visit doctors or vaccinate their children.

The Bulgarian Roma have distinct demographic behavior. Early universal marriage is common --according to a recent survey, 40 percent were married before the age of 16, and 80 percent before the age of18. Their birth rates are among the highest in the country. Once married, the Roma do not tend to continuetheir education. This factor, combined with the generally lower enrollment rates and higher drop-out rates,makes the Roma the most poorly educated group in Bulgarian society. As a result, unemployment ratesamong the Roma are extremely high. According to a survey conducted in the summer of 1997, only23 percent of Roma declared that they work full-time (some of them in publicly-funded temporaryemployment programs), and another 11 percent said that could get seasonal employment from time to timein agriculture or construction. According to other estimates only 8.5 percent of Roma own agricultural land(usually a small area around the house), reducing the role of self-production as a fall-back option for thiscommunity, although the government is seeking to increase access to land and improved housing for theRoma, in some cases with the active support of NGOs. The Roma are often not able to draw uponunemployment insurance because they often do not have enough contributions (6 months without a break)to qualify. However, MOLSP analysis of social assistance expenditures shows that two thirds of these arechanneled to the persons of Roma origin. Medical examinations for the prevention of illness are regular andobligatory regardless of ethnic group. There is a compulsory medical immunization calendar approved inthe country and all vaccines are supplied free of charge.

Bulgarian Turks and Bulgarian Muslims (or Pomaks) have also been living in the territory ofBulgaria for many centuries. In more recent times, the communities have been subject to campaigns tochange their traditional way of life, clothing, and names. A flash-point in the 1980s was the policy,initiated in 1984, of forbidding the speaking of Turkish in public and forcibly changing the names ofBulgarian Turks. This was rescinded after the downfall of the communist regime. The end of thecommunism also saw a surge in emigration among members of the Bulgarian Turk community, althoughmany of them subsequently returned.

The regions inhabited by the Bulgarian Turks and Pomaks are among the most backward in thecountry. More than 90 percent of Bulgarian Turks may be found in 4 regions: Haskovo, Russe, Varna andBourgas. Most of the Pomaks can be found in the south, in the Rhodope mountain area. The greater part ofBulgarian Turks and Pomaks live in rural areas. Although Bulgarian Turks and Pomaks have higher birthrates, recent surveys show that the demographic behavior among the young in these groups is convergingtowards that of the rest of the country.

Tobacco cultivation which was the mainstay for a considerable part of the Turk and Pomakcommunities has undergone a severe crises since 1991. Output has fallen two to five fold with negativeconsequences for employment and income. Although many small farmers have tried to reorient themselvesto other crops, these have not proved as lucrative. The Bulgarian Turk community has also suffered fromthe loss of the most qualified and skilled personnel who emigrated after the end of communism.Unemployment levels among the remainder remain higher than the national average.

Source: Tomova (1998)

C. Poverty, household size and demographics

3.6. Average household size in Bulgaria is 2.9 persons per household. Poverty ratesincrease as household size increases. Nearly 40 percent of all poor individuals live in

20

households of 5 or more people. These households also represent a larger share of povertygap and depth (48.7 percent and 56.8 percent respectively -- see Table A. 1 in the Annex).

Figure 3.2

Poverty Rates by Household Size

60

50

Housd SeSofia

* Other Urban

307. Individuals living in female-headed households have higher poveRural0 g~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~3All

20

1 0

01 2 3 4 5 or more

Household Size

Source: BIHS 1997

3.7. Individuals living in female-headed households have higher poverty rates thanindividuals living in male-headed households (40.4 vs. 35.4 percent). Female-headedhouseholds are composed mostly of single older women and are particularly worse offoutside Sofia city and in rural areas -- see Figure 3.3 In terms of their share of the poor,female-headed households comprise a relatively small group (16 percent of the poor live infemale-headed households compared to 84 percent in male-headed households) becausethey are small proportion of the population as a whole.

Figure 3.3

Poverty Rates by Gender of House hold Head

454035

E 30is 25 iFm*lerising20 fo thF er ma le0e

1 050

S of ia Other Urban Rural AlIf

Source: BIHS 1997

3.8. Looking at poverty rates by age, we see that, in general, they fall with age beforerising for the 55+ age group. Children appear to be at a greater risk of poverty than theelderly in Bulgaria (see also Table A.2 in the Annex).

21

Figure 3.4

Poverty by age

50.00

40.00

30.00--- - * Rate

20.00 --. .-- - -- * * a a * Depth.3 Severity

10.00 - ----

0.00 _ _ _ _

0-5 6-10 11-17 18-25 26-45 46-55 55<

Age groups

Source: BIHS 1997

3.9. Demographic profiles are generally quite sensitive to the use of equivalence scalesand to economies of scale in consumption.z In the analysis presented in this report, wehave used per capita consumption to rank households. However, if we were to rankhouseholds using equivalized consumption instead of per capita consumption (using, forexample, OECD equivalence scales) the results might well be different. In fact, Lanjouw,Milanovic and Patemostro (1998) show that higher poverty rates arnong children vis-a-visthe elderly in Bulgaria may be overturned once we allow for fairly small economies of scale

22in consumption. In other words, with scale economies the elderly may have higher povertyrates than children. In the same vein, allowing for economies of scale would weaken thecorrelation between poverty and household size by making large households appear lesspoor. We therefore need to be cautious about interpreting demographic profiles based onper-capita measures too strictly.

21 Equivalence scales refer to the idea that people of different ages have different needs (e.g., achild needs fewer calories and, thus, less food than an adult), while economies of scale refer to theidea that two can often live as cheaply as one (because the cost of goods shared within thehousehold, such as housing, does not rise proportionately with household size). In using per capitaexpenditure to rank households we are making the assumption that all household members haveidentical needs and there are no economies of scale in consumption.

22 Their analysis is based on the 1995 BIHS. The authors consider seven transition economies inall: Bulgaria, Estonia, Hungary, Kazakhstan, the Kyrgyz Republic, Poland and Russia. Bulgariastands out for being the country where the demographic profile is very sensitive to economies ofscale: with low scale economies (T =0.9 in the economies of scale parlance), children do not appearto have higher poverty rates than the elderly.

22

D. Education and poverty

3.10. Individuals with lower education levels are, in general, poorer than people withhigher education levels. Table 3.3 looks at individuals over the age of 18 years who arenot attending school. Poverty rates for individuals with no education are 46.3 percent;and with primary education, they are 42.9 percent compared to the population average of34.6 percent. Higher poverty among those with less education is particularly true foryounger generations, which are in general poorer than older, more experiencedgenerations. The share of poverty due to lower education levels (primary or none)however, represents only 17 percent of all poverty. This is due to the relatively smallnumber of people with low education levels in Bulgaria. Interestingly, though, the shareof poverty depth and severity increase to 22 and 26 percent, which means that thoseindividuals are further from the poverty line than the average.

3.11. Higher poverty among the less educated is reflected in differences in the educationattainment for poor and non-poor individuals over 5 years of age. The poor have muchlower educational attainment (see Figure 3.5). The difference is more evident in Sofia andother urban areas, where most of the non-poor individuals have secondary and universitydegrees. There are no marked differences by gender. However, one interesting finding isthat a greater proportion of women than men have university or higher education.

Figure 3.5

Education Attainment by Poor/Non Poor

100% -- _ _ _ _ - - _ _ _ _

80%

*Unrv & Higher60% o PSecondary

40% *Prima

:No Eduscation20%

0 ~~~~ 0 a~~~ Q R

i 0i U-

Poor Non Poor Poor Non Poor

Source: BINS 1997

3.12. Educational attaimnment has obvious imnplications for labor market outcomes andthrough labor market outcomes for poverty. The nexus between education, labor marketstatus and poverty will be examined in greater detail in Chapter 4.

Table 3.3: Poverty Measures and Shares of Individuals 18 Years or Older and Currently Not in SchoolBy Education Level and Age Group

ALLEducational Poverty Measures by Age Groups Total % of PovertyAttainment 18-21 yr 22-25 yr 26-45 yr 46-55 yr Above 55 yr Population Share

Poverty Rateno education 50.00 100.00 90.91 100.00 56.67 63.64 1.47 2.71primary 85.71 100.00 94.29 68.29 40.44 47.34 10.43 14.28middle 64.81 62.71 58.08 43.02 34.49 42.91 28.24 35.04secondary 21.29 37.21 29.38 26.95 30.73 29.31 43.63 36.98univ & higher 0.00 28.57 22.85 17.00 29.15 23.38 16.22 10.96

ALL 33.94 41.99 34.61 31.16 35.10 34.58 100.00 99.99

Poverty Gapno education 13.19 83.96 49.10 85.64 24.64 30.98 1.47 4.28primary 49.24 61.00 53.52 30.91 13.18 18.19 10.43 17.77middle 29.82 26.26 23.13 12.8 9.04 13.94 28.24 36.86secondary 7.33 10.79 7.59 7.45 7.75 7.88 43.63 32.19univ & higher 0 9.82 5.52 4.30 7.09 5.87 16.22 8.91

ALL 14.11 14.69 11.02 9.94 9.96 10.68 100.00 100.02

Poverty Depthno education 3.48 70.49 29.87 75.15 14.21 19.27 1.47 5.87primary 30.46 41.08 34.75 17.20 6.18 9.60 10.43 20.70middle 18.00 15.13 12.48 5.59 3.53 6.66 28.24 38.86secondary 3.18 4.42 2.85 3.00 2.88 3.06 43.63 27.59univ & higher 0.00 4.32 1.88 1.47 2.50 2.08 16.22 6.97

ALL 7.63 7.29 5.12 4.19 4.21 4.84 100.00 99.98

N 221 331 1696 995 1980 5223

Source: BIHS (World Bank Estimates)Note: Poverty Line is defined as two-thirds of mean per capita consumption in 1997.Note: Secondary education includes general, technical and vocational levels.

23

E. The sources of income and the role of social transfers23

3.13. Bulgarians derive their income from a variety of sources. If we look at the majorsource of income (defined as the source which provides more than 50 percent of totalincome), we can see that while a larger proportion of the non-poor rely on wages, poorpeople rely more on pensions and other social transfers (28 percent versus 20 percent of nonpoor). It is also interesting to note that while agricultural and in-kind earning account for alarge percentage of total income on average (nearly 14 percent), only a few households relyon them as a major source of income.2 4

Figure 3.6: Proportion of households by major income source

Poor Non Poor

M ixed 'e30% Wages 28_

36%

Wages41%

>, Agricultur

Pension 2% 20%28% Inkind In kind Agriciltur

4 % 7% 04 %*

Source: BIHS 1997Note: Mixed means that no individual source is more than 50 percent of household income.

3.14. The data in Table 3.4 confirms that people living in households where the majorsource of income is social transfers are more likely to be poor than families whose majorsource of income is earned income. In fact, 44 percent of people whose major source ofincome is social transfers are poor and they account for over 27 percent of all poverty. Thisproportion, however, does not go up for the poverty depth and severity measures (see TableA.4 in the Annex), which means that while this group has a higher percentage of poorpeople, but they are not relatively poorer. If we look at the data by location, we see thatpoverty rates are slightly lower for people relying on social transfers in Sofia, while they arehigher for people relying on earned income in the rural areas. It is also interesting to notethat while poverty rates are generally lower for single people (see Figure 3.2), they remainrelatively high for single people relying on social transfers (30.0 percent - Table A.5 in theAnnex).

23 Self reported income data are generally less reliable than consumption data for a variety of reasons,see e.g. Deaton, 1994. These results should therefore be viewed with a certain element of caution.

24 For the shares of different sources of income, see Table A.3 in the Annex.

24

Table 3.4: Poverty Measures and Shares of Individualsby Major Source of Income and Locality

Major Source Region Bulgaria % of Poverty

Sofia Other Rural Population Share

Urban

Poverty Rate

Earned Inc 36.42 28.38 46.73 32.82 39.40 35.24

Agriculture 0.00 30.77 28.33 26.83 3.28 2.40

In kind 30.00 23.24 28.99 26.83 5.91 4.32

Soc. ben 41.21 45.42 44.11 44.42 22.83 27.64

Mixed 39.88 32.69 46.79 39.04 28.57 30.40

Total 38.03 32.95 42.54 36,69 100.00 100.01No of cases 881 3,390 1,970 6,241

Source: BIHS 1997

F. Patterns of consumption and poverty

3.15. The analysis of budget shares by poverty groups is presented in Table 3.5.Bulgarians spend a large amount of their budget on food. This is partly due to the fallingliving standards of the Bulgarian population and in part to the fact that expenditures for rentand durables have not been included in our estimate of cons;umption. Poor people allocate alarger amount of their budget to food (72.3 percent compared to 68.5 percent for the nonpoor) and consume larger amounts of cheaper staple grain commodities. In fact they spend28.6 percent on cereals, versus 14 percent for the non-poor.

3.16. The bigger difference in expenditure pattern between poor and non poor is reflectedin expenditure shares for the non-food items. The expendiiture shares of the poor are largerthan the non-poor for housing-related expenses (14.2 versus 11.9 percent). This resultreflects the burden of energy and electricity expenditure on1 the poor. The non-poor spendmore on alcohol, transportation (they own cars), clothing, and entertainment. Although thepoor spend a larger proportion of their expenditure on education, expenditures for health andeducation are generally low (less than the expenditure on tobacco, 2.1 versus 12.9 percentfor Bulgaria as a whole).

3.17. The different food expenditure pattern mentioned above results in different patternsof calorie consumption. The poor derive over 50 percent of their caloric intake form cereals,compared to 40 percent by the non-poor (Table A.6 in Annex). Non-poor people derive alarger proportion of their calories from meats and dairy products (8.1 and 20.7 percent fornon poor versus 5.2 and 17.2 percent for the poor).

3.18. Bulgarians rely substantially on own production or transfers from other sources forfood consumption. Over 40 percent of vegetable consumption, over two-thirds of fruitconsumption and approximately one quarter of meat and dairy consumption comes from

25

own production. Nearly one-tenth of mean consumption comes from other sources. It isinteresting to note that while poor people produce or receive a larger share of cheapercommodities (fiuits), the non poor receive a larger share of meats and dairy products.

Table 3.5: Expenditure Budget Sharesby Poor/Nonpoor Individuals

Poor Non-poor Bulgaria

Food 72.32 68.54 69.90

Cereals 28.58 14.03 19.25

Fruits 16.97 19.43 18.55

Meats 20.34 28.14 25.35

Fats 4.43 3.53 3.85

Other foods 2.00 3.41 2.90

Nonfood Items 12.34 18.46 16.27

Alcohol 1.58 2.75 2.33

Tobacco 2.88 2.93 2.91

Personal 1.90 2.31 2.16

Cleaning 1.76 1.61 1.67

Gasoline 0.56 2.33 1.70

Other transport 1.13 2.01 1.69

Clothing 1.05 1.98 1.65

Health 0.86 0.91 0.89

Entertainment 0.40 1.06 0.82

Other nonfood 0.22 0.58 0.45

Housing 14.13 11.89 12.70

Central Heating 2.09 1.94 2.00

Electricity 6.43 4.95 5.48

Gas 0.31 0.53 0.45

Other Energy 2.36 2.07 2.18

Water 1.48 1.00 1.17

Fees 0.31 0.23 0.26

Telephone 1.15 1.17 1.16

Education 1.33 1.17 1.23

Total 100 100 100

Number of Cases 2321 4158 6479

Source: BIHS 1997

Note: Poverty Line is defined as two-thirds of per capita mean consumption in 1997.

26

G. Housing conditions of the poor and non-poor

3.19. In Table 3.6, we look at a number of housing characteristics. The pattern thatemerges is one in which people living in the rural areas do not have the same access toservices as the people living in Sofia and other urban areas.

Table 3.6: Selected Housing Characteristics by Poor)Nonpoor Individuals(Percentage)

Sofia Other Urban Rural AllPoor Nonpoor Poor Nonpoor Poor Nonpor Poor Nonpoor

Type of ToiletFlush Toilet 87.61 94.94 80.55 88.43 20.48 22.02 58.74 69.07Pit Latrines 10.57 5.06 19.20 11.36 73.53 75.44 38.62 30.05Other 1.81 0.00 0.26 0.21 5.99 2.54 2.64 0.88ALL 100 100 100 100 100 100 100 100

Electricityless than 23 hrs/day 2.13 10.67 5.80 6.01 4.79 5.16 4.92 6.46>=23 hrs/day 97.87 89.33 94.20 93.99 95.21 94.84 95.08 93.54ALL 100 100 100 100 100 100 100 100

Waterless than 23 hrs/day 4.88 10.85 10.58 9.88 6.21 5.62 8.15 8.81-=23 hrs/day 95.12 89.15 89.42 90.12 93.79 94.38 91.85 91.19ALL 100 100 100 100 100 100 100 100

CookingElectricity 92.07 84.99 69.45 76.08 21.68 35.10 54.38 64.88Gas Cylinder 1.83 10.85 5.03 12.47 0.98 2.77 3.06 9.30Coal/Kerosene 6.10 4.16 25.43 11.36 76.14 61.66 42.06 25.64Other 0.00 0.00 0.09 0.08 1.20 0.46 0.50 0.19ALL 100 100 100 100 100 100 100 100

HeatingDistrict Heating 68.29 71.07 10.75 18.53 0.00 0.00 14.47 19.65Elect. Heat 11.59 12.30 33.02 44.96 2.61 5.23 18.57 28.73Wood/Coal 20.12 13.74 55.03 34.91 97.39 94.00 66.38 50.10Oil 0.00 0.72 0.68 0.99 0.00 0.08 0.33 0.68Other 0.00 2.17 0.51 0.62 0.00 0.69 0.25 0.84ALL 100 100 100 100 100 100 100 100

DisposalPublic Sewage 95.12 96.20 83.36 91.97 22.44 29.19 61.83 73.45SepticTank 3.05 2.17 16.64 7.95 71.24 68.96 35.53 25.73Other 1.83 1.63 0.00 0.08 6.32 1.85 2.65 0.82ALL 100 100 100 100 100 100 100 100

PhoneAvailable 63.61 71.58 69.23 84.35 43.79 66.90 58.80 77.35Not Available 36.39 28.42 30.77 15.65 56.21 33.10 41.20 22.65ALL 100 100 100 100 100 100 100 100

No of Cases 328 553 1172 2429 918 1299 2418 4291

Source: BIHS 1997

3.20. Within regions, the poor rely more on coal or kerosene for cooking than the non-poor. In the rural areas, 76 percent of all poor use coal or kerosene stoves for cooking(compared to 62 percent of the non-poor). District heating is used mostly in Sofia (71percent of the non-poor have access to it, compared to 68 percent of the poor), a little in the

27

other urban areas and not at all in the rural areas. Wood and coal are a more importantsource of heating for the poor. Over 97 percent of the rural poor, 55 percent of the -poor inurban areas outside Sofia, and 20 percent of the poor in Sofia use wood or coal. Among thenon-poor, the figures are 94 percent, 35 percent and 14 percent respectively. Access topublic sewer system is also lower for the poor population. Lastly, access to a phone is muchhigher for non-poor individuals (77 percent versus 59 percent for the poor).

H. Poverty persistence and household characteristics

3.21. To what extent is poverty persistent, affecting the same groups of individuals, andto what extent is it transitory, affecting different individuals or groups over time? Thenature of the BIHS, which has a set of repeated households (or a panel) allows us toexamine this question for the group of individuals who were sampled both in 1995 and in1997.25

3.22. In Table 3.7, we analyze movements into and out of poverty using consumptionquintiles. We begin with a narrow notion of poverty -- whether a particular householdfalls in the bottom quintile (or bottom fifth) of the population in any one year. We findthat over the two survey years over two-thirds of the individuals (67.8 percent) never fellinto poverty, nearly a third (32.2 percent) found themselves to be poor at least once,while 7.8 percent remained poor. This last group is a candidate for the title of'persistently' poor. Using a more generous notion of poverty (whether individuals fallinto the bottom two quintiles of the distribution in any one year), we find that 41.5percent of individuals never found themselves to be poor, 58.5 percent found themselvesto be poor at least once, while 21.5 percent remained 'persistently' poor. More detailedinformation on movements across quintiles are presented in Table A.7 of the Annex.

Table 3.7: Poverty dynamics in 1995-97

Proportion of the sample Proportion of the sampleTime in poverty which falls in the bottom which falls in the bottom

20 percent 40 percent

Never 67.8 41.5At least once 32.2 58.5Twice 7.8 21.5

Source: BIHS 1995, 1997

25 The 1997 survey covered over 80 percent of dwellings (2,048 households) surveyed in 1995.Dropping households who appear to have no members in common between 1995 and 1997, we areleft with a working panel of 1,662 households. For further details, see Annex 2.

28

Box 3.2: Examining poverty using panel data

The standard cross-sectional household survey is a one-time affair and is designedto obtain a snapshot of a representative group of households at a given moment in time.Although such surveys take time to collect (frequently, a few months to a year), so thatthe 'moment in time' may vary from household to household, and although householdsare sometimes visited more than once, the aim of the survey is to gather informationabout the a given year's income, or about consumption in the month prior to the survey.Panel data in contrast, track households over time and gather multiple observations onthe same household. For example, instead of gathering income for one year, a panelwould collect data on income for a number of years, so that using such data, it is possibleto see how survey magnitudes change at the level of the individual household. This is thegreat attraction of panel data, that they can be used to study dynamics for individualhouseholds, including the dynamics of living standards. They can be used to addressquestions such as: are the same households or individuals repeatedly poor, or is poverty atemporary phenomenon affecting different households at different points in time. Untilrecently panel data were rare. The survey that attracted the most attention and researcheffort in the United States is the Michigan Panel Study of Income Dynamics (PSID),which has been following members of about 4,800 original households since 1968. Thetransition economies have a long tradition of collecting panel data, but samplingmethods had numerous deficiencies and panel attrition was high. More recently, therehave been attempts to collect panel data correcting for these problems. Examples are theRussian Longitudinal Monitoring Survey, which started in July 1992, and the modifiedHousehold Budget Survey in Poland, which followed about 8,000 households for fiveyears between 1992-96.

As well as their advantages, panel data have a number of problems that arepeculiar to themselves. Perhaps the most significant is attrition, whereby for one reasonor another, households are lost from the survey so that the actual survey and its designbecome increasingly divergent over time. One reason for attrition is simple refusal;households which have participated once may refuse to do so again. This is typicallymore of a problem in rich than in poor countries. Even when households are willing tocooperate, there may be difficulties in finding them at subsequent visits. Individuals maymove house, or migrate out of the area, households may cease to exist if the head dies, orif the household splits up as children move away. Depending on whether the surveyattempts to follow these migrants and 'splits' as well as whether new births andimmigrants are added to the sample, the process of household dissolution and formationcan result in changes to the representativeness of the household over time. There istherefore likely to be a tradeoff between, on the one hand, obtaining a representativesample, which is best done by drawing a new sample each year, and tracking individualdynamics, which requires households to be held from year to year. Comparing thecharacteristics of the panel with a representative cross-section is a good way ofexaminng potential bias.

Source: Deaton (1994), Glewwe and Jacoby (1998)

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3.23. Table 3.8 looks at the characteristics of 'persistently' poor households relative tohouseholds who are 'never' poor. Following the discussion in sections A-E, we focuson location, region, ethnicity, demographics, education, and sources of income. Themain findings are the following:

* Households who are persistently poor are more likely to live in rural areas. Residentsof urban areas, including Sofia, make up a smaller proportion of the chronically poor.

* Ethnic minorities are over-represented among the consistently poor. Over ninetypercent of those who are 'never' poor are ethnic Bulgarian. In contrast over 30percent of those who were repeatedly found in the bottom quintile are of Roma originand over 19 percent ethnic Turks.

* The chronically poor consist of a greater proportion of large households, with onaverage four or more members. In contrast, households who are 'never' poor have3.4 members on average, which is over one household member less per householdthan those who are consistently found in the bottom 20 percent.

* The education of the household head varies significantly between the chronic andnever poor. Over 38 percent of households who are 'persistently' in the bottomquintile have heads with no education or primary education only compared to lessthan 23 percent of 'never' poor households.

* Households whose main source of income is pensions, unemployment benefit, andother social transfers are more common among the chronically poor than among the'never' poor.

Table 3.8: Characteristics of 'persistently' poor versus 'never' poor households

Household 'Persistently' poor 'Never' poorcharacteristics Bottom Bottom

20 percent 40 percent

Location% Rural residence 48.2 43.5 31.0% Sofia 7.4 6.8 7.8% Otherurban 44.4 49.7 61.2

Ethnicity% Bulgarian 46.2 65.3 92.9%Bulgarian Turks 19.2 16.0 6.1% Gypsy (Roma) 32.5 15.3 0.2% Other 2.1 3.3 0.8

DemographicsAverage household size 4.7 4.3 3.41995Average household size 4.8 4.3 3.4

30

Household 'Persistently' poor 'Never' poorcharacteristics Bottom Bottom -

20 percent 40 percent1997% Female headed 13.0 15.7 11.1

Education of householdhead

%No 10.3 7.7 3.9% Primary 26.9 21.7 18.5% Middle 15.7 23.9 27.5% Secondary 36.5 38.5 37.9% University and higher 10.6 8.2 12.2

Main source of incomeWages 32.8 42.7 46.2Pensions and other 12.8 11.0 5.5transfersIn-kind 7.1 9.4 19.9Agriculture 5.7 8.6 5.7Mixed 41.5 28.3 19.0

Source: BIHS 1995, 1997Note: 'Never poor' are defined as those who did not fall into the bottom two quintiles in either year (48.5 percent of thesample).

3.24. Thus, overall, it would appear that the characteristics discussed in this section ofthose found to be 'persistently' poor between 1995 and 1997 are similar to thecharacteristics of those found to be poor in 1997 discussed previously. The onlyexception is residence in Sofia city. While residents of Sofia city show higher-than-average poverty rates in 1997 and are consequently over-represented among the poor,they are under-represented among individuals who find themselves to be 'persistently'poor. This suggests that higher poverty in Sofia city observed in 1997 may be an aspectof the 1996-97 crises, and may well change in the future given that Sofia city residentsare relatively well-placed to benefit from economic growth (see Eigure 3.5, for example,on educational attainment in Sofia city versus the rest of Bulgaria).

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4. LABOR MARKETS AND POVERTY IN BULGARIA

4.1. The last chapter emphasized the correlation between low education levels andpoverty. This chapter explores the nexus between education, labor markets, and povertyin greater detail drawing on the two household surveys, BIHS 1995 and 1997, theNational Statistics Institute's (NSI) Labor Force Survey, as well as other published data.Labor markets can affect poverty in two ways: (i) through unemployment; and (ii) throughearnings. The unemployment of a family member can significantly increase the chancesthat the family slides into poverty. This is especially the case, if unemployment affects thehead of the household and the unemployment spell is prolonged. As regards earnings,poverty depends on both on changes in real earnings and on changes in the earningsdistribution. Poverty increases if real earnings fall or if, other things being equal, thedistribution of earnings becomes more unequal.

4.2. Since the introduction of economic reforms in the early 1990s, all the transitioneconomies of CEE have experienced simultaneous sharp increases in unemployment, fallsin the real earnings of those who retained jobs, and a widening of eamings differentials. Inthis respect, Bulgaria is no exception although the market-oriented reforms have progressedhere at slower pace than in, for example, the Czech Republic, Hungary, or Poland. Thediscussion that follows is divided into three sections. The first section examinesdevelopments in the labor force and unemployment over time. The second sectiondiscusses trends and differential in wages, while the third takes a closer look at therelationship between unemployment, low pay and poverty.

Labor Force Developments and Unemployment

A. Changes in the labor force

4.3. As discussed in Chapter 1, unemployment has seen a marked increase since theearly 1 990s (see Figure 1.2). Although it has fallen from its peak in 1994, unemploymentremains relatively high (see Table 4. 1).27 Moreover, the overall picture is one of astagnant labor market with limited employment opportunities. The labor forceparticipation rate has remained at a low level of 52 percent and the employment rate hasrisen marginally: in 1997 only 45 of working age population in Bulgaria had jobscompared to 43 percent in 1994. The picture is thus one of significant under-utilizationof labor resources.

26 For an overview of the inheritance of communist labor relations and key issues of labor markettransition see Jackman and Rutkowski (1994), Jackman (1994) and Blanchard et. al. (1995). Beleva et. al.(1995) provides an analysis of labor market transition in Bulgaria.

27 It is often argued that actual unemployment is lower than reported because of informal sectoremployment. This should not be the case, however, if one uses the Labor Force Survey (LFS) datawhich, in principle, should allow for informal sector employment. LFS data are generally considered asproviding a relatively reliable indicator of actual employment and unemployment and we rely on themthroughout the text (unless indicated otherwise).

32

Table 4.1: Changes in the labor force, 1994-1997

1994 1995 1996 1997Labor force participation 53.4 52.2 52.5 51.9rateUnemployment rate 20.0 15.7 13.5 13.7Employment rate 42.7 44.0 45.4 44.8Source: NSINotes:1. June data2. Labor force participation rate = (Employment + Unemployment)/Population aged 15+3. Employment rate = Employment/Population aged 15+4. Unemployment rate = Unemployment/Labor force

4.4. Data from the BIHS suggest that transitions across employment, unemploymentand inactivity are low, confirming the picture of stagnant labor market in Bulgaria. Anunemployed person in Bulgaria has an extremely low chance of finding a job. Inparticular, the probability that an unemployed person will find a job within twelvemonths is around 6.2 percent (see Table 4.2). This is roughly one-sixth of the yearly exitrate from unemployment observed in CEE countries such as Poland, and less than one-eight of those prevailing in high-unemployment Western European countries such asSpain (Boeri, 1998). Many of the unemployed (11 percent) became discouraged by thefutility of their job search and withdrew from the labor force. At the same time, theyearly inflow into unemployment is moderate (3.5 percent), similar to that observed inPoland. Given the substantial labor market slack, the flow from inactivity to employmentor unemployment is also very low (about 1 percent). Few people decide to enter thelabor market, and even fewer succeed.

Table 4.2: Changes in labor force status, 1996-97

Labor market Present labor market statusstatus

12 months ago Employed Unemployed InactiveEmployed 94.5 3.5 2.0Unemployed 6.2 82.5 11.3Inactive 1.0 0.7 98.3Source: BIHS 1997

4.5. As suggested by these figures, unemployment in Bulgaria is a large stagnant pool.This is reflected in a high incidence of long term unemployment and a long duration ofjob search. Six out of ten unemployed are jobless for more than one year. Four out often are jobless for more than two years (Table 4.3). The pool of the long-termunemployed (those unemployed for a year or more) - over 300,000 people - is aparticularly worrisome feature of the Bulgarian labor market. Looking at theireducational attainments, we find that the long term unemployed are persons withdisproportionately low skills: 45 percent of them have only primary or lower education.The skills they possess and their motivation may erode as joblessness persists. Thus,

33

there is the danger that a relatively large group of persons with limited employability willdevelop.

Table 4.3: Duration of unemployment in 1995 and 1997

Duration in months 1995 1997In percent

Less than 1 3.1 2.91 - 5 17.3 19.96- 11 12.0 15.012 - 23 19.0 18.524 + 48.5 43.7

Source: NSINote: Figures are for February 1995 and February 1997

B. Profile of the unemployed and job search

4.6. What personal characteristics increase the probability of becoming unemployed?Persons running the highest risk of unemployment in Bulgaria are young, with loweducational attainment, and of Gypsy ethnicity.28 The role of educational attainment isparticularly pronounced: a worker with primary education faces odds of beingunemployed 4 times higher than a worker with university diploma, 2.3 times higher thana worker with secondary vocational education, and 1.9 times higher than a worker withsecondary general education. Secondary earners (especially children) are more likely tobe unemployed than primary earners (household heads). Single persons are more likelyto be unemployed than married ones. Other things being the same, women are not at asignificantly higher risk of unemployment than men. This profile of unemployment issimilar to that observed in other transition economies. Two features, however, deserve tobe highlighted: (a) the strong link between unemployment and educational attainment;and (b) a higher risk of unemployment among secondary earners compared with primaryearners.

4.7. On the supply side, the probability of finding a job depends on two factors: (a) jobsearch intensity; and (b) the reservation wage, which is the lowest wage that anunemployed person is willing to accept. Data from the BIHS 1997 suggest that the timespent on job search amounts on average to 18 hours per week.29 However, this averageconceals large differences. The median job seeker devotes only 4 hours to job search.Many of the unemployed (15 percent) do not actively look for ajob at all. A suspiciouslylarge fraction (28 percent) of job-seekers say they spend 56 hours per week or more onjob search. Insofar as this is indeed the case, their job search is a full-time job: 8 hoursper day, 6 days per week.

28 Annex 3 reports the multivariate analysis on which these conclusions are based.

29 For this analysis we consider all persons who report that they are unemployed. This is a somewhatlarger pool than the sample of persons who are defined as unemployed by standard criteria (ILO):they do not work for remuneration, are available for a job, and are looking for a job.

34

4.8. Job search intensity of women is considerably lower than that of men. Onaverage, women devote 5 hours less per week to job search than men do. Older workersspend more time looking for a job than younger ones. There is no distinct pattern of jobsearch intensity depending on education. For example, the unemployed with primaryeducation spend the same amount of time on job search as university educated workers.Surprisingly, unemployed household heads do not search for a job more intensively thansecondary earners: spouses (usually wives), or children.

4.9. Job search effort does not appear to depend on the duration of unemployment.The long-term unemployed neither increase their job search intensity, nor decrease it.The latter is a positive phenomenon, as it may indicate that the long-term unemployed donot become increasingly discouraged by the futility of their job search.

4.10. The receipt of unemployment benefit does not seem to reduce the search effort.Contrary to what is usually assumed, in Bulgaria the recipients of unemployment benefitstend to look for jobs as intensively as those who are not eligible. This means that thedisincentive effect usually created by the unemployment benefit system is not very strongin Bulgaria.3 0 The registration at the labor office is not associated with strongermotivation to find a job: unemployed who are not registered at labor offices look for a jobas intensively as those who are.

4.11. Job search effort is also related to the search method. Those who look for a jobthe most actively - visit firms - spend the most time on job search (on average 24 hoursper week). Those who confine themselves to visiting labor offices spend, on average, 8hours less. In between are those who look for a job through friends (20 hours).Unfortunately, we do not know whether a more active and time intensive job search ismore effective than a more passive approach.

4.12. The reservation wages, data from the BIHS 1997 suggest that the unemployed inBulgaria have excessive wage expectations. Their reservation wages - the lowest wagesthey are willing to accept - far exceed the wages that employers actually offer for peopleof given qualifications. Insofar as this is the case, unemployment in Bulgaria is not onlya problem of insufficient labor demand and few vacancies, but also a problem of theunemployed not willing to work at the going wage rates. The average differentialbetween the reservation wage, and a wage that is predicted based on individual's humancapital characteristics, is almost 100 percent.31 In other words, the unemployed tend toclaim wages almost twice as high as those they can actually receive. This large disparitybetween reality and expectations remains even if one allows for possible underreporting

30 The disincentive effect of the unemployment benefit system in Bulgaria is also diminished byrelatively stringent eligibility conditions and low level of benefit. As to the former, only about 20percent of all unemployed and 29 percent of the registered unemployed receive unemploymentbenefits.

31 For fuller discussion of the estimated eamings functions on which this analysis is based, see Annex3 and Rutkowski (1998a).

35

of actual wages. This means that wage expectations of the unemployed may beunrealistic and may effectively prevent them from getting a job.3 2

4.13. Excessive wage expectations are characteristic of all worker groups. However,some groups are more unrealistic in their expectations than other. These are women,younger workers, and workers with college or university education.

4.14. The longer duration of unemployment does not appear to moderate wageexpectations. Only the unemployed for more than two years significantly scale downtheir reservation wages, but still they bargain for wages substantially (60 percent) higherthan those prevailing on the market. It is usually assumed that job search is adaptive;that is, that reservation wages fall in the course of search. There is little evidence of thisin Bulgaria, which is worrisome, as this lack of adjustment by itself prolongs job search.

4.15. Higher intensity of job search tends to moderate wage expectations, but therelationship is weak. The unemployed, who spend less than an hour per week on jobsearch, tend to expect wages more than twice as high as those prevailing on the market.Those who look for 8 hours or more are ready to accept wages 'only' 75 percent higherthan the actual ones.

4.16. The unemployed who use less active methods of job search, such as reading adsin newspapers or through friends, tend to have higher wage expectations than those whouse more active methods and are exposed to the reality of the labor market. For example,those who confine themselves with reading ads in newspapers expect wages 120 percenthigher than they can actually count on. Those who visit firns want wages 80 percenthigher; whereas the clients of labor offices are the most modest in their wage claims andwant wages that are 70 percent higher than those actually offered. Unemployedregistered with labor offices have lower reservation wages than those who are not,although they still want wages that are higher than what may be on offer. One possibleexplanation is that persons who are exposed to actual job offers tend to abate their wageclaims. It is also possible that this result reflects a self-selection process, whereby it isless active and energetic persons who register with labor offices and who a priori havelower wage expectations.

4.17. Job search theory suggests that the recipients of unemployment benefits are likelyto have higher reservation wages than non-recipients. The data for Bulgaria do notsupport this hypothesis. The unemployed registered at labor offices have the samereservation wages whether or not they receive unemployment benefits. This is yetanother piece of evidence suggesting that the unemployment benefit system in Bulgariadoes not seem to have a distortionary impact on the effectiveness of the job search of theunemployed.

32 Interestingly, the unemployed appear to have good knowledge on premia to different labor marketskills, however they err when it comes to the "baseline wage", i.e. the intercept of the eamingsfunction. See Annex 3 for fiurther details.

36

C. The skills gap

4.18. The high share of poorly educated people in unemployment in Bulgaria points tothe problem of the skills gap. The comparison of the skill and educational composition ofthe employed with that of the unemployed reveals that workers with low skills andeducational attainment account for a disproportionate share of unemployment (Table 4.4).For example, workers with only primary education account for over 40 percent theunemployed and for only 25 percent of the employed. This suggests a large excesssupply of low skilled, poorly educated labor.

4.19. One way of measuring the contribution of low education to unemployment inBulgaria is to examine how unemployment would change if there is growth whichreplicates the existing employment structure, and if we allow skill mismatches (proxiedby educational attainment) to exist only between skill categories. Results indicate that,under these conditions, about 17 percent of the unemployed would not be able to findjobs due to inadequate skills. In other words, one of every six unemployed may not beable to find employment even if there are enough vacancies because the skills/educationthat he or she possesses fall short of skills demanded by employers. Put still differently,the unemployment rate due to the skills gap is 2.6 percent. These figures provide alower-bound estimate of the extent of the magnitude of the skills gap because of severalsimplifying but optimistic assumptions (e.g. growth replicates the existing job structureand there is no mismatch within skill categories). Thus, the skills gap turns out to be animportant - although not a predominant - cause of unemployment in Bulgaria.

Table 4.4: Educational attainment of employed and unemployed, 1997

Education level Employment Unemployment 'Excess supply'University 15.6 5.7 -9.8College 5.9 2.6 -3.3Secondary vocational 22.3 18.2 -4.1Secondary general 31.7 32.5 0.8Primary or less 24.5 40.9 16.4Source: NSI, World BankNotes: Employment and Unemployment, 2/97. See paragraph 4.18 on interpretation of 'excess supply'.

D. Trends in real wages and earnings inequality

4.20. As discussed in Chapter 1, a consistent time series is available only for the publicsector where real wages have fallen dramatically since the outset of the transition (Table4.5). As a result, the average public sector wage in 1997 was only one-half that in 1991,and one-fourth of its pre-transition value.33

33 The fall in wages is probably overstated largely as a result of problems with correct pricemeasurement under conditions of widespread shortages in consumer goods markets common tocommand economies.

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Table 4.5: Trends in real wages, 1990-1997

1990 1991 1992 1993 1994 1995 1996 1997Real wage index1990=100 100.0 48.4 54.1 49.4 38.7 36.4 30.0 25.01991=100 206.4 100.0 111.6 102.0 79.9 75.2 62.0 51.7Source: NSI

4.21. The BIHS provides information on both the public and private sectors. Data fromthe BIHS shows that earnings inequality increased significantly between 1995 and 1997.The Gini coefficient increased by 12 percentage points between the two survey years,reaching the level of 40. By West European standards, this indicates a very high level ofinequality in earnings. Similar values of the Gini coefficient are observed in developingcountries and in some of the FSU countries. By contrast, the Gini for earnings in thetransition economies of CEE is around 30, and ranges from 25 to 30 in West EuropeanOECD countries (Rutkowski, 1996b).

Table 4.6: Summary of earnings distribution, 1995 and 1997

1995 1997National National Public Private sectoreconomy economy sector

Gini 28.1 40.0 39.3 41.5PIO 57.7 44.6 43.8 44.1P90 192.3 245.5 250.0 213.1Decile ratio 3.3 5.5 5.7 4.8Incidence of

Low pay 17.8 24.7 22.1 33.3High pay 14.0 15.1 16.9 9.2

Source: BIHS 1995, 1997Notes: P1O denotes the earnings of the bottom decile relative to the median, expressed as a percentage.The decile ratio is the ratio of earnings at the top decile to earnings at the bottom decile, i.e. P90/P 10.Low pay is defined as earnings lower than 2/3 times the median.

High pay is defined as earnings higher than 2 times the median.

4.22. Table 4.6 shows that the wage distribution has widened at both ends. Low-paidworkers have seen their relative wage status substantially deteriorate. In 1995, a workerat the bottom decile earned 58 percent of the median wage; in 1997, this figure was 45percent of the median (the P10 ratio). The wage gap between the bottom decile workersand the median worker in Bulgaria is much larger than in most transition economies. Forexample, in Poland (which is a medium-to-high wage inequality country) the wage of thebottom decile worker accounts for 57 percent of the median. Simultaneously, the relativeearnings position of top-paid workers has considerably improved. In 1997, a worker inthe top decile earned a salary that was 2.5 times higher than that of the median worker(the P90 ratio). The relative earnings position of top-paid workers in Bulgaria is betterthan in most transition economies. For example, in Poland a top-paid worker earns twiceas much as the median worker.

38

4.23. The ranks of low-paid workers have grown. The incidence of low pay (earningsless than 2/3 of the median wage) increased by 7 percentage points from 1995 to 1997,and at present, one in four workers is low paid. This is a significant increase. In OECDcountries, the percentage of low-paid workers does not exceed 20 percent even in high-wage inequality countries. In contrast, the proportion of top-paid workers has increasedonly slightly, by one percentage point, reaching 15 percent.

4.24. The incidence of low pay is substantially higher in the private sector than in thepublic sector. In the private sector one-third of all jobs are low paid, compared with justover one-fifth in the public sector. Quite surprisingly, it is the public sector that is theprimary source of good jobs. In the public sector, 17 percent of workers earn more thantwice the median earnings while in the private sector the figure is 9 percent. Thus, inBulgaria, unlike most transition economies, the public sector appears to offer more well-remunerated jobs than the private sector.

4.25. The large increase in inequality observed during 1995-97 is quite unusual, evenby standards of transition economies. A possible cause is the runaway inflation of 1997.It is possible that in some firms, workers were able to maintain the real value of theirearnings, while in others they were not. Moreover, under high inflation, monthly realearnings tend to be extremely volatile: they go down in the wake of the price shock, thengo up as workers strive to recoup the purchasing power of their wages. If the increase inwage dispersion was an outgrowth of inflation, then it may be the case the high level ofearning inequality was a transitory phenomenon characteristic of 1997. Further researchis needed to establish whether this was the case.

4.26. Is high wage dispersion good or bad? It depends. If a more flexible wagestructure leads to the creation of more jobs, then the net effect on poverty may well bepositive. If, however, the widening of the wage distribution does not bring aboutemployment growth, then the impact on poverty is unambiguously negative. Given thatthe employment rate has remained roughly stable during 1995-1997, widening of thewage distribution has not been accompanied by a growth in employment. One cannotrule out the possibility that unemployment would have increased if the wage distributionhad not widened, but this hypothesis holds less force in the face of prevailing highunemployment. This suggests that the increase in earning dispersion, associated with thesharp increase in the incidence of low pay, has most likely contributed to growingpoverty.

E. Wage determination and relative wages

4.27. What factors determine earnings in Bulgaria?34 First, high skills appear to payoff. For example, holding all other things constant, a worker with secondary generaleducation earns on average 25 percent more than a worker with primary education.Moreover, returns to education appear to be increasing over time. In fact, returns to

34 The analysis that follows is based on the estimation of an earnings function the details of which aregiven in Annex 3.

39

education were higher in 1997 than in 1995 for all categories of education (Rutkowski,1996a and 1998a).

4.28. One aspect in which Bulgaria appears different from other countries is thateducational premia are substantially higher in the public than in the private sector. Theprivate sector offers virtually no premia to secondary education and even to a collegeeducation. It does value university education, but to a lower degree than the public sector(55 percent premium over primary education, compared with 110 percent in the publicsector). This is unusual, as in the transition economies of CEE, as a rule, it is the privatesector which drives the changes in relative wages, and in particular offers significantlyhigher retums to education.35

4.29. Second, the sector of employment is an important factor determiningremuneration. All else equal, private sector wages are lower than public sector wages.The private/public wage differential varies by educational attainment (Table 2.4). Allworker groups lose on private sector employment, regardless of their educationalattainment; but those who lose the most are workers with secondary education (eithergeneral, or vocational). Earnings of workers with primary education and universityeducation in the private sector are only slightly lower than in the public sector. Thispattern of no gains on private sector employment suggests that no group of workers has aclear (short-term) interest in the privatization of the economy. This pattern differsconsiderably from that occurring in other transition economies in CEE where, in general,only workers with low or narrow skills lose on private sector employment, whereasworkers with secondary and tertiary education gain. Moreover, the gain is greater thehigher the educational attainment.

4.30. Third, tenure with one's employer does not matter much. The returns to tenurewith the current firm are low in Bulgaria. Thus, wages of younger workers, with shorttenure, are not much higher than those of oider workers. The fall in returns to experienceis characteristic of most transition economies and reflects the fact that experience gainedunder the old regime is now of lesser value.

Table 4.7: Ratio of private to public sector wages by education level

Education Ratio of private to public wage in %Primary 96.0Secondary general 83.5Secondary vocational 74.8College 92.2University 97.8All levels 84.8

Source: BIHS 1997.

35 One factor may be that private sector in Bulgaria is less skill intensive than the public sector (evenafter controlling for industry composition), and thus demand less highly qualified labor. This impliesthat a truly modem, skill and capital intensive private sector, which can be an engine of growth, is yetto develop in Bulgaria.

40

4.31. Fourth, the presence of trade unions raise wages. Wages of workers employed infirms where trade unions are present are significantly higher than in non-union firms (by

369 percent). Trade unions in Bulgaria operate mainly in public firms; their presence inprivate firms is negligible. Correspondingly, the union wage effect is visible only in thepublic sector. This partly accounts for wages in the public sector being higher on averagethan in the private sector.

4.32. Fifth, gender and ethnicity are important factors in determining wages. Womenearned on average 28 percent less than men with similar human capital characteristics in1997. This gap has fallen somewhat since 1995 when it was estimated to be 30 percent.The relative wage position of women in the private sector also appears to have improvedduring the period 1995-97. In 1997, the gender wage gap in the private sector wassimilar to that in the public sector. In 1995, the gap was much more pronounced in theprivate sector. Gypsies earn over 20 percent less than Bulgarians with similar observablecharacteristics.

4.33. Sixth, regional unemployment does not have a significant moderating impact onwages. This is an important result which implies that in Bulgaria an equilibratingmechanism of higher joblessness causing lower wages is not in place. In other words,local wages do not seem to adjust to local unemployment. This rigidity can lead to thepersistence of unemployment.

4.34. Seventh, the industry of employment has a significant role to play in determiningremuneration. Agriculture is, by far, the lowest paying industry, even after controllingfor workers' human capital characteristics. All else equal, wages in agriculture are90 percent lower than in manufacturing. Low-paying industries also include socialservices (education, health care, social welfare), where wages are on average 70 percentlower than in manufacturing. Low salaries in social services are characteristic ofhistorically planned economies in general, but in Bulgaria, the gap seems particularlypronounced. Given that social services are publicly financed, low salaries probablyreflect the fiscal crisis of the government. Altogether, the low paying industries accountfor 38 percent of total employment. However, as many as 46 percent of the working poorhave jobs in these industries, which suggests that industry affiliation can be a separaterisk factor leading to poverty

4.35. To what extent do these factors help to explain wage dispersion in the economy?An answer to this question is provided in Table 4.8. The factors listed above explainslightly over one-fourth of the total variance in earnings in Bulgaria.37 Inter-industrywage differentials (industry rents) prove to be the most important factor accounting forwage inequality. They explain almost 10 percent of total variance in earnings and36 percent of the explained variance. An important part is played by differences in

36 In addition, members of trade unions receive wages significantly higher than non-members withcomparable qualifications.

37 This is standard; the remaining variance is explained by unobservable, individual and firm specificfactors.

41

educational attainment. They explain 8.2 percent of total variance in earnings and31.4 percent of the explained variance. Interestingly, the effect of education- comesentirely from university education. The gender wage gap contributes almost 5 percent tototal earnings inequality and close to one-fifth to the explained inequality. Other factors- experience, sectoral and regional affiliation - are of secondary importance.

4.36. The predominant role played by industry rents in generating wage dispersion ispeculiar to Bulgaria. As a rule, it is differences in educational attainment whichcontribute most to wage dispersion. Large inter-industry wage differentials in Bulgariaare a likely outgrowth of loss making and subsidized public firms paying their workerswages above the competitive level. For example, public firms in manufacturing paywages on average 25 percent higher than private firms. The existence of substantialindustry rents probably reduces the incentives created by educational premia, as one'searnings depend to a greater degree on industry of employment rather than on educationalattainment. In particular, many workers are low paid not because of their failure toacquire skills, but because they are attached to a 'wrong' industry.

Labor markets and Poverty

F. Labor market characteristics of the poor

4.37. We now take a closer look at labor markets and poverty. For the purposes of thissection the poor are identified as the bottom quintile of the population.38 The BIHS 1997suggests that the poor are less frequently employed than the non-poor and morefrequently unemployed, or out of the labor force (Table 4.9). Only one-third of theworking-age poor are employed, compared with almost one-half of the non-poor. Theunemployed account for 16 percent of the poor but only 8 percent of the non-poor. Putdifferently, the unemployment rate among the poor is over twice as high as among thenon-poor: 33 percent and 15 percent, respectively. Thus, the poor are less economicallyactive and less successful in finding ajob than the non-poor.

38 This assumption means that, in effect, we are using the lower poverty line. The reason for doingthis is that it brings out the results more starkly. For the purposes of this analysis, the sample islimited to persons aged 15 or more; that is, to persons who can participate in the labor force.

42

Table 4.8: Contribution of selected factors to (log) earnings inequality3 9

Share (in percent) of:Variable Total variance Explained

varianceEducation 8.2 31.4

of which Tertiary 8.1 31.1Job experience 0.7 2.7Gender 4.6 17.5Private/public sector 1.3 5.0Industry 9.5 36.3Region 2.0 7.7

Total explained (le) 26.2Unexplained 73.8Total 100.0

Source: BIHS, 1997

4.38. Work does not keep families out of poverty: the 'working poor'4 0 account for34 percent of all poor. Not surprisingly, the earning capacity of the poor is considerablyweaker than that of the non-poor. As much as 35 percent of the poor are low-paid,compared with 23 percent of the non-poor. However, many of the poor (55 percent) havejobs that pay moderately well, and some even have well paying jobs (10 percent). Thepoor are disproportionately employed in agriculture and in social services (e.g. healthcare and education). One out of ten poor persons has a job in agriculture, in contrast withone out of twenty of the non-poor. Many of the poor work in manufacturing (21 percent),but their share of manufacturing jobs is lower than that of the non-poor (27 percent). Thepoor are, more often than the non-poor, employed in the private sector; however, thislargely reflects the fact that agriculture, which is an industry of employment for manypoor, is predominantly private.

Table 4.9: Labor market characteristics of the poor

Poor Non-poor AllIn percent

TOTAL 100.0 100.0 100.0Labor force status

Employed 32.4 44.7 42.4Unemployed 15.9 7.9 9.4Outofthelaborforce 51.8 47.4 48.3

39 The contribution of a variable, x, to the variance of log-earnings, w, was calculated as b*r(w, x),where b is the standardized regression coefficient in the earnings function, and r is the correlationcoefficient. The contribution of a categorical variable (e.g. education) is measured as a sum ofcontributions by binary regressors representing each category (e.g. primary education, secondaryeducation).

40 Working poor are poor families where at least one person has a job.

43

Poor Non-poor AllIn percent

Earnings categoryLow 35.0 23.2 24.7Middle 55.0 47.6 48.5High 10.1 29.3 26.8

Sector of employmentPublic 71.0 76.6 75.9Private 29.0 23.4 24.1

Industry of employmentManufacturing 20.8 26.6 25.8Construction 11.9 11.4 11.5Agriculture 10.2 4.9 5.6Transport & 7.6 9.9 9.6

communicationTrade 14.4 13.1 13.3Social services 21.6 18.5 18.9Public administration 13.6 15.7 15.4

Source: BIHS 1997Note: The sample is restricted to individuals working age (15 years or more). Poverty means being in the bottomquintile of the distribution of per-capita consumption. For definitions of earnings capacity see Table 4.11.

G. Employment, earnings and poverty

4.39. Shifting the focus from individuals to households, a household's labor marketperformance is determined by two variables: the number of family (household) memberswho are employed, and their earnings. Two questions arise. First, what is the impact ofboth variables on the poverty status? Second, what is the relationship between thevariables: do households with low earnings capacity tend to increase labor supply; or, onthe contrary, do low earnings go hand in hand with low labor supply?

4.40. How strong is the impact of an increase in the number of earners on the incidenceof poverty? Poverty incidence among persons from households with two earners is12.6 percent, which is 28 percent lower than poverty among persons from householdswith only one eamer (Table 4.10). This is a significant reduction; however it isconsiderably smaller than in most countries. In other words, poverty incidence amongfamilies with two earners is still quite high. In fact, it is much larger than in othercountries. For example, in FYR Macedonia the differences in the incidence of povertybetween one-earner families and two-earners families is 15.3 points, or 82 percent; andthe poverty incidence among two-eamer families is very low (3.3 percent).41 Thus,Bulgaria does not conform to the pattern observed in many countries whereby "doubleearnership - both partners earming a wage - appears to be an almost watertight guaranteeagainst poverty," (Marx and Verbist, 1997).

41 See Rutkowski (1998b) for details.

44

Table 4.10: Poverty incidence by the number of earners in a household

Household employment rate % of persons* Poverty incidenceZero 53.7 24.4One-third or less 20.3 17.4More than one-third 26.0 12.6All households 100.0 19.9

Source: BIHS 1997Notes: (1) Household employment rate is the number of earners in the household per one household member. Forpractical purposes, the employment rate of one-third implies one earner in the household, and the employment rate ofmore than one-third implies two earners. (2) Poverty means being in the bottom quintile of the per-capita consumptiondistribution.*Persons in households with given employment rate.

4.41. How sensitive is poverty to the changes in household wages? The incidence ofpoverty among households having middle earnings is 16.5 percent, which is 28 percentlower than among households having low earnings (Table 4.11). Clearly, higher earningsreduce the risk of poverty, but the reduction is moderate. The risk of poverty is, however,significantly lower for high earner households.

Table 4.11: The incidence of poverty by mean household earnings

Mean household earnings % of persons* Poverty incidenceLow 23.5 23.0Middle 50.7 16.5High 25.7 3.6All households** 100.0 14.7

Source: BIHS 1997Notes:1. Mean household earnings ("earning capacity") are total household earnings divided by the number of earners.(a) Low earning capacity = mean household earnings lower or equal to 2/3 of the median.(b) Middle earning capacity = mean household earnings higher than to 2/3 of the median but lower of equal to 1.5 ofthe median.(c) High earning capacity = mean household earnings higher than 1.5 of the median.2. Poverty means being in the bottom quintile of the per capita consumption distribution.*Persons in households which are in a given earnings category.**With at least one eamer.

4.42. How do number of earners and household earnings capacity interact? In Bulgaria,low earnings and low labor supply tend to go hand in hand. Table 4.12 illustrates thepattern whereby households with low earning capacity tend to have fewer earners thanhouseholds with high earning capacity. As many as 66 percent of high wage householdshave two earners in contrast to 54 percent of low wage households. As a result, povertyin Bulgaria is often a result of both low earning capacity and low household employmentrate.42

42 Further evidence of this: if a family head is in the top wage quintile, other family memberscontribute on average four times more than in families where the head is unemployed and three times

45

Table 4.12: The relationship between household earnings and employment

Household employment rate

Mean household Less or equal to Higher than All householdsearnings 1/3 1/3

Low 46.6 53.4 100.0Middle 37.2 62.8 100.0

High 34.0 66.0 100.0

All households 38.5 61.5 100.0

Source: BIHS 1997

H. Unemployment and poverty

4.43. The relationship between unemployment of household members and poverty issummarized in Table 4.13. The risk of poverty critically hinges on the labor force statusof the family's head. Among families where the head is unemployed, the incidence ofpoverty is 1.7 times higher than among those where the head is employed. Turning to thelabor force status of all potential eamers, we see that while unemployment of one familymember raises the risk of poverty moderately, the 'unemployment syndrome' (when twoor more family members are unemployed) multiplies it. The incidence of poverty amongfamilies hit by the 'unemployment syndrome' is 2.7 times higher than among familieswhere there is no unemployment. In comparison, the incidence of poverty amongfamilies where one person is unemployed is 1.3 times higher. As a result, 45 percent ofpeople from families suffering from the 'unemployment syndrome' are in the bottomquintile of expenditure distribution.43

more than in families where the head is in the bottom wage quintile. Thus, poverty tends to be aresult of the inability of the whole family to find productive, well paying jobs. For further details seeRutkowski (1998a).

43 If one focuses on households where only one person is unemployed, we see that the incidence ofpoverty is higher in households where the unemployed person is a secondary earner (spouse or child),than if he or she is the household head. This unexpected result may reflect the fact thatunemployment is often the effect as well as the cause of poverty. Specifically, secondary earners inpoor households have a stronger incentive to look for a job, and thus become unemployed if jobs arenot available. In well-to-do families secondary earners can afford to be out of the labor force (e.g. tostudy).

46

Table 4.13 Poverty and unemployment

Household characteristics Poverty Sample Povertyincidence share share

Labor force status of household headEmployed 17.0 50.1 42.6Unemployed 29.0 7.1 10.3Out of the labor force 22.0 42.8 47.1Unemployed household memberYes 30.0 22.8 34.3No 17.0 77.2 65.7Number of unemployed householdmembers

obne 17.0 ~ 77.2 65.7One 22.5 15.4 17.4

:Head 13.9 3.5 g :2.4Spouse 21.3 3.0 3.2Son/Daughter 26.S 8.6 11.6

Two or more 45.4 7.4 19.9

Source: BIHS 1997Notes: Poverty means being in the bottom quintile of the per-capita expenditure distribution.

47

5. PUBLIC SPENDING AND POVERTY REDUCTION

5.1. This chapter examines government spending in Bulgaria from a povertyreduction perspective. The discussion focuses on two main types of programs whichhelp to reduce poverty: namely, those which provide income transfers (usually in cash);and those which contribute to earning capacity in the long run. The first part of thechapter discusses the main public transfer programs, including: (i) the pay-as-you-gopension system; (ii) family benefits; (iii) social assistance, in both cash and kind; and(iv) unemployment benefit. The second part discusses the public health and educationsystems. Three different sources of information are used: (i) information from theMinistry of Finance (MOF) on government recurrent spending on education and health;(ii) data on school enrollments for the school year 1994/95 and 1996/97 furnished by theNSI; and (iii) the data from the 1997 BIHS. Given the integrated nature of the survey, itis possible to relate enrollment and usage behavior of households, and benefit receipt, tokey household characteristics, such as, expenditure, region of residence, and so on.Where relevant, comparisons with BIHS 1995 are made.

5.2. Government spending on income transfers, education and healthcare in Bulgariais relatively high for a middle-income country (though not for a transition economy).In 1997, the government spent 8.9 percent of GDP on public transfers and additional7.4 percent on the education and healthcare systems (see Annex 4). Spending on bothtypes of programs (income transfers and human capital development) constituted over45 percent of total public spending. The largest share of government spending onpublic transfers went on pensions (75 percent), followed by family benefits(12 percent), social assistance (7 percent), and labor market programs (6 percent).Figure 5.1 reports the main trends.

Figure 5.1

Trends in social spending in Bulgaria

12.00

0 1200 ------------------------ L----- - - Pe nsions

C 8.00 - _ FlealthA, Education

C o Social Assistance4.00 Labor Markets

2.00 -=- -- . | Farnily Benefits

0.001991 1992 1993 1994 1995 1996

Sources: MOF, MOLSP

48

5.3. In discussing income transfers, we will examine: (i) who benefits from- publictransfers, and whether and to what extent income transfers are directed at the poor; (ii) therole of public transfers in reducing poverty; and (iii) the extent to which benefits areprovided to the non-poor at the expense of the poor. In this context, the terms 'socialtransfers', 'social benefits', and 'public transfers' will be used interchangeably. In thefollowing section, public expenditures on the various levels of health-care and educationservices will be combined with information on the use of such services by households (asreported in the 1997 BIHS), to trace the incidence of such spending among differentgroups in the population.

Public transfer programs: the social safety net

A. Incidence analysis: who benefits from the social safety net?

5.4. With the exception of guaranteed employment, Bulgaria's pre-transition socialprotection system -- consisting of pensions, short-term benefits for illness andmaternity, family allowances, and in-kind social assistance programs/institutions --remains essentially intact today. Moreover, it has been overlaid with new categories ofassistance; principally, unemployment insurance and benefits, and a variety of socialassistance or welfare benefits aimed at helping households cope with transition-relatedshocks. Since the start of the transition, economic shocks, government policiesinvolving generous early retirement options for laid-off workers, and the take-up by thepopulation of benefits made available under new programs have meant that the numbersof people eligible for, and receiving, income support from the state through its socialprotection programs have increased significantly.

5.5. Financing of social insurance programs is derived from earmarked payroll taxesamounting to an average of 47.5 percent of net wages. The highest tax rate is tofinance pensions and short term benefits for illness/maternity.4 Cumulative socialinsurance payroll tax rates are considerably higher today than at the start of thetransition, the rates increased by policy-makers in an effort to cover rising expendituresand compensate for a shrinking contributions base -- in turn, the result of risingunemployment, payment arrears by state enterprises, and general non-compliance bythe growing private sector.45 At the same time, average benefits have fallensignificantly vis-a-vis average wages (cf. Figure 1.3). Ironically, the high payroll taxesare themselves a major disincentive for both work and job creation in the formal sector,contributing to rapid informalization of the economy (with consequences going well

4 This rate is set at 37 percent for workers eligible to retire at the normal retirement ages of 55, and60 years for women and men, respectively. The rate is considerably higher (47 and 52 percent,respectively) for those in special categories of labor who are entitled to retire from 5 to 8 yearsearlier. The rate for the unemployment fund (UF), which pays cash benefits and finances activelabor market programs, is presently set at 4.5 percent.

45 The rate for the UF has fallen from 7 percent at the start of the decade to 4.5 percent, but remainshigh by international standards.

49

beyond the social protection system itself). Financial constraints have also affected thesocial assistance program which is financed from general revenues.

5.6. To analyze the different elements of the social safety net in Bulgaria, we groupthem into four major categories:

(i) Pensions, including old-age, disability, and survivor pensions;(ii) Unemployment benefits;(iii) Child allowances; 46 and,(iv) Social assistance, including maternity benefits, regular monthly and

occasional cash, food, clothing and other benefits; other cash and in-kindbenefits.47

5.7. According to the BIHS, approximately 81 percent of all households receive someform of social benefit, although the percentage of households receiving a given transfervaries by socio-economic category (see Table 5.1). For example, the incidence of socialbenefit receipt is higher in female-headed households (87 percent) than in male-headedhouseholds (80 percent), mainly due to the high incidence of pensions and, in particular,survivor benefits in female-headed households.

5.8. In general, the incidence of social benefit receipt increases with the age of the head,irrespective of whether the head is malc or female, to the point where more than 98 percentof households with heads aged 70 or older receive beinefits (for further details, see Skoufias,1998). The incidence of social transfers is also relatively higher in poor households(86 percent),4 8 in households where the head is out of the labor force (95 percent), and in therural regions of the country (89 percent).

46 Child allowances are the most important family benefit created by the 1968 Birth Promotion Act

and amount to over 0.6 percent of GDP - see Annex 4. Eligibility is universal and benefits are typicallypaid at the parent's workplace. Maternity benefits are the second most important family benefit. Forinsured mothers they are paid out of payroll contributions, and for the uninsured, out of the socialassistance budget. In terms of funding source, the bulk of maternity benefits get paid out of the socialassistance budget -- see Annex 4 -- they are therefore considered under that heading.

47 Social assistance consists of a large number of small programs. Maternity grants are the mostimportant cash benefit (0.2 percent of GDP), followed by the regular monthly and occasional benefit (0.1percent) -- see Annex 4. In the winters of 1996/97 and 1997/98, there was an energy voucher schemefor low-income households funded by the EU's Emergency Social Aid Program (0.2 percent of GDP).For a discussion of eligibility criteria for these and other programs, see ILO and UNDP (1998). Thefragmentary nature of social assistance programs means that that only a small proportion of samplehouseholds benefit from individual programs and targeting efficiency of these programns is best analyzedas a group.

48 The higher poverty line is assumed throughout this chapter for comparisons between the poor andnon-poor. Thirty-six percent of the population falls below this poverty line.

50

5.9. By far, the most commonly received social transfer is the pension, which isreceived by 58 percent of all households. Approximately 79 percent of female-headedhouseholds receive a pension whereas only 53 percent of male-headed householdsreceive one. The inclusion of survivor benefits under pensions, together with the longerlife expectancy of females, are primarily responsible for this large difference. Theincidence of pension benefits is also relatively higher in poor households (66 percent), inhouseholds where the head is out of the labor force (92 percent), and in the rural regions of thecountry (74 percent).

5.10. The second most commonly received social transfer (by 28 percent of households) isthe child allowance. Approximately 32 percent of male-headed households receive a childallowance whereas only 14 percent of female-headed household receive it. In contrast to thepattern of pension receipt, child allowance benefits are most frequently received byhouseholds where the head is employed. The incidence of child benefit receipt is slightlyhigher in poor households than non-poor households. The incidence of these benefits is alsosignificantly lower in rural areas compared to urban areas (including Sofia city).

Table 5.1: Incidence of social benefit receipt among households

Percent of households receiving

Any or all Pensions Unemployment Child Socialbenefits Benefit allowance Assistance

All households 81.29 58.44 4.75 28.12 13.48

Gender of Head

Male 79.65 53.92 5.22 32.18 10.06

Female 87.01 74.22 3.1 13.95 25.39

Employment Statusof Head

Employed 64.27 20.49 4.51 48.07 7.51

Unemployed 74.42 26.74 24.42 42.44 17.44

Out of the labor force 95.44 92.38 2.07 10.52 17.56

Poverty Status ofHousehold

Non-Poor 78.87 54.76 4.38 27.28 11.74

Poor 86.47 66.31 5.55 29.90 17.18

Location ofHousehold

Sofia City 72.05 48.76 0.31 25.78 13.97

Other Urban areas 78.81 51.57 5.00 31.35 14.75

Rural Areas 89.36 73.94 6.25 23.80 11.17

Source: BIHS 1997

51

5.1 1. The third most common social transfer (received by over 13 percent of households)is social assistance. The incidence of these benefits is higher among female-headedhouseholds, the unemployed and non-participants, and among the poor. The incidence byregion is fairly equal.

5.12. The least common social transfer (received by less than 5 percent of households) isunemployment benefit. Turning from households to individuals, we see that approximately34 percent of all unemployed persons were receiving unemployment benefits in 1997, anumber which is rather low compared to the incidence of unemployment benefit receipt inother transitional economies (see Skoufias, 1998, for further details).

5.13. The incidence of social transfers, in general, and pension, unemployment benefit andother benefits, in particular, is higher among poor households than among non-poorhouseholds. This suggests that the social safety net system in Bulgaria is rather well-targeted to the poor. In addition, with the exception of pensions the average benefit receivedby poor households is greater than non-poor households (see Figure 5.2).

Figure 5.2

Average benefit received in leva per month

4000035000 . .30000 -

o 25000 ---- .- _- -or -£^ 20000 - -- Non-poor

sooo ----1 -- -----U0 - --- 1- . .I10000 5000 ----

Any or all Pensions UB Child all. Social Ass.

Source: BIHS

5.14. The social safety net in Bulgaria represents 22.6 percent of the expenditure of anaverage household (the average being calculated based on both recipient and non-recipienthouseholds). Pensions are the major share (90.1 percent), and by themselves contribute19.8 percent to average household expenditure. Unemployment benefits represent0.4 percent of household expenditure, child allowances 0.9 percent, and social assistance afurther 1.4 percent.

5.15. Social benefits constitute 28 percent of household expenditure among householdsreceiving any or all types of benefits. For households that receive a pension, pensionsconstitute 34 percent of household expenditure, whereas among households receiving childallowances, child allowances constitute only 3.4 percent of expenditure (see Figure 5.3).

52

Figure 5.3

Benefit as a % of recepient household's exp.

50

40 - -- -- - -- --- - - - - - - - - - --- - ------------ --------- - - - - - - - - - - - -30 - -- - -- ---- ^ r-- -Poor .

Y _U1 * Non-poor: 20 - ------ - -- All--

0----------L---.~ ~ ~~~~~~~~~~~~I ---- -------L---i------- L-0 - I 4

Any or all Pensions UB Child all. Social Ass.

Source: BIHS

5.16. According to the calculations in Figure 5.3, the social safety net system in Bulgariaappears to be quite progressive. In general, the aggregate of the social benefits constitutes42 percent of the average expenditure of those poor households that receive benefits,whereas social benefits constitute only 20 percent of the average expenditure of non-poorhouseholds (a ratio of 2:1). This large difference remains essentially the same for pensions,unemployment benefits, child allowances, and social assistance. The benefit most focusedon the poor is the unemployment benefit (a ratio of 3:1).

B. Impact of the social safety net on poverty

5.17. What is the poverty alleviation impact of the social transfers? Pensions contributethe most to raising households out of poverty; 39 percent of the households that were poorbefore the receipt of social transfers rely on the pension as a means for getting out of poverty(see Table 5.2). The second largest contributor to poverty alleviation is social assistance,followed by unemployment benefit and child allowance. The contribution of the latterbenefits to alleviating poverty seems to vary depending on the labor force status of the headof the household, his/her gender, and across regions. Note that unemployment benefits havea rather significant role in moving households with unemployed heads out of poverty. Childallowances and social assistance seem to have a considerable impact on alleviating povertyamong households where the head is employed rather than unemployed.

53

Table 5.2: Percent of poor (ex ante) householdsmoved out of poverty due to the receipt of social benefits

Any or all Pension Unemp. Child 1 SocialBenefits benefit allowance Assistance

All 36.77 39.23 7.41 7.25 11.82

Gender of Head

Male 35.09 38.32 8.70 7.38 14.63

Female 41.33 41.36 n.a. 6.25 | 7.50

Employment Status of Head l

Employed 23.81 31.39 0.00 9.37 22.22

Unemployed 15.71 13.33 16.67 5.71 14.29

Out of the labor force 42.58 41.32 0.00 3.75 8.90

Location of Household

Sofia 30.83 34.95 2.56 20.69

Other Urban areas 36.23 37.79 10.45 11.67

Other Rural Areas 39.36 42.07 4.85 7.41

Source: BIHS 1997Note: A household is classified as poor ex-ante if average household expenditure per capita net of all socialAhousehold is classified as poor ex-ante if average household expenditure per capita net of all social transfers is less thanthe poverty line.

C. Scope for improved targeting

5.18. The success of a social transfer system is also measured by the extent to whichtransfers go to poor households rather than non-poor households prior to the receipt of thetransfer. Thus, it is necessary to assess the extent to which there are leakages in the socialtransfer system and, in effect, the extent to which there is room in the system for reallocationin favor of the poor. This is the subject of Table 5.3.

5.19. In general, there do not seem to be substantial leakages in the Bulgarian socialbenefit programs. Over 40 percent of households receiving child allowances and nearlytwo-thirds of households receiving social assistance were poor before the receipt of socialtransfers. This being said, there does appear to be some scope for further improvements intargeting. Two possible ways to increase the share of the benefits going to poor householdswould be to institute means-testing for these benefits or to tax them as ordinary income.More broadly speaking, there would appear to be room in the system for reallocation infavor of the poor, as 46 percent of all households receiving benefits are non-poor before thereceipt of social transfers.

54

Table 5.3 Ex-ante targeting of social transfers

Are social benefits going to poor (ex ante) households or not?

Households Receiving: Percent of ex Percent of exante non-poor ante poor

households householdsreceiving receiving

Any or all benefits 46.39 53.61

Pension 38.58 61.42

Unemployment benefit 50.91 49.09

Child allowance 57.60 42.40

Social assistance 34.94 65.06

Source: BIHS 1997Note: A household is classified as poor ex-ante if average household expenditure per capita net of all socialtransfers is less than the poverty line.

Public Services: Healthcare and Education

D. Education

5.20. As in other socialist countries, the government in Bulgaria has historically givenhigh priority to providing for the health needs and educational qualifications of thepopulation, resulting in relatively good health status and school enrollment indicators.However, recent adverse macroeconomic trends have had a direct bearing on the level ofgovernment expenditures as well as an effect on the behavior of households in the face ofdeclining living standards. This may have influenced schooling and health care decisions at

the household level, which may have modified the use of publicly provided services. This

section seeks to establish how spending on publicly-provided health and education is

distributed to the population at large in Bulgaria.

5.21. We recall from paragraph 5.2 that expenditures on health and education as a share of

GDP have fallen during the transition. As a result, Bulgaria (with Romania) now ranks

among the low spending countries among the transition economies of CEE. 4 9 In 1997,

spending per capita in education was US $49, and in healthcare US $43 (at market rates of

exchange). These expenditures represent a significant fall from former levels: in 1997,

49 In 1997, for example, spending on education as a share of GDP was 2.9 percent in Romania and 3.4percent in Bulgaria, but 4.9 percent in Poland, 4.6 percent in Hungary and 6.4 percent in the CzechRepublic. In health, the figures (for 1996) are Romania 3.4 percent, Bulgaria 3.2 percent, Poland 5.4percent, Hungary 5.0 percent and Czech Republic 5.8 percent (Sources: UNICEF-ICDC, WorldBank).

55

education spending was 69 percent and healthcare spending 80 percent of 1991 levels in realper-capita terms.50

5.22. The Bulgarian education system begins with an optional pre-school program forchildren above three years of age. This is followed by an eight-year period ofcompulsory education (known as 'basic education'), which consists of elementaryschooling (ages 6 to 10 years) and junior high or pre-secondary schooling (ages 11 to14). Secondary schooling has three main streams. Secondary general education involvesa four-year course which is a preparation for entry into higher education. Four-yearcourses in secondary technical and specialized schools also prepare students for highereducation. The three-year secondary vocational course is not designed as a conduit forhigher education. There is very little private provision of education services in Bulgaria,though recently there has been some limited expansion at the elementary level in someurban areas.

5.23. Higher education is characterized by a great deal of fragmentation for a countrythe size of Bulgaria. There are about 30 public institutions-universities and more-narrowly specialized (mostly engineering) institutes, and some 40 'semi-higher' facilities,which have a mainly occupational-oriented mandate, such as primary-school teacher-training and nurses training. Some consolidation is being considered.

5.24. The Ministry of Education, Science and Technology (MEST) has overallresponsibility for the education system. It provides the budget for universities,specialized schools and semi-higher institutions under central responsibility, butotherwise its direct financing and administrative role at the lower levels is limited. Thehigher education budget which is administered by the MEST is a matter of negotiationbetween the Ministry and the higher education institutions.

5.25. Both the municipalities and especially in the schools themselves have preventedschools from exercising their full management authority as set out in the 1991 Law onSchool Education. In March 1998, Parliament passed Bulgaria's first Law on MunicipalBudgets. While the Law increases the transparency and clarity of the relationshipbetween central and local governments, it does not introduce major changes into thebudgeting process, and ambiguities on intergovernmental fiscal responsibilities remain.

5.26. Within-sector allocations in education have not changed much during thetransition.5 1 Expenditure on pre-primary education amounts to approximately 23 percentof total education expenditures, while spending on basic and secondary educationamounts to approximately 60 percent. Spending on tertiary education has grown

so The use of GDP deflators may give a misleading impression of trends in real education spending,simply because the main cost item in the sector is teachers' salaries. If these have also declined inreal terms, estimates of real resources to education based on the commonly-used deflators willoverstate the true decline.

51 The discussion in paragraphs 5.26 through 5.30 is based on Ringold (1998) which should be consultedfor full details.

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marginally from 16 percent of total spending to 17 percent during the same time period.Combined with the picture on enrollment (see Figure 5.4 below) this suggests thesharpest declines in spending per student eprolled have occurred in the area of tertiaryeducation where enrollment grew by nearly 45 percent between 1991 and 1996.

5.27. Turning to the share of different costs within the education system we see that theshare devoted to personnel grew by nearly 10 percentage points from 52 percent to62 percent of all spending between 1991 and 1996, largely due to an increase in thenumber of teachers. The total number of teachers increased from 115,416 to 119,251during the period, despite attempts to scale back civil service employment. There was ashift away from capital spending (which fell from 4.3 percent in 1991 to 2.6 percent in1996) and an increase in the share of utilities. Declines in expenditures on textbooks andother educational materials has been severe (falling in real terms to 15 percent of 1991levels), threatening educational quality.

5.28. The data show diverse trends in enrollments.5 2 Enrollments in kindergarten appearto be relatively unaffected by transition (see Figure 5.4), although the total rate masksdeclining trends particularly for younger children. In particular, enrollment rates for 4and 5 year olds fell 10 and 7 percent, respectively, between 1989 and 1996. Some of thisdecline may be related to declining female labor force participation, and the erosion ofaccess to pre-primary schools and nurseries attached to state-owned enterprises.

5.29. Enrollment rates point to a decline of approximately 5 percent for basic educationduring the same period. Disaggregated data show that the decline has primarily been forlater years of education, lower secondary (grades 5-8), rather than primary (grades 1-4)(UNICEF, 1998). Recent studies suggest that the decline may be due to the increase incosts to families of sending children to school (e.g. Noncheva, 1997). School serviceswhich were previously free -- including books, meals and transportation -- are now oftencharged to families.

5.30. At the secondary level, enrollments in general programs have increased slightly,while vocational school enrollments have fallen approximately 5 percent. The mostnoticeable development has come at the tertiary level, where enrollment rates -- for bothpart and full-time students -- have nearly doubled between 1989 and 1996.

52 Available data refer to gross enrollment, except for kindergartens where the figures are net -- seeRingold (1998) for details.

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Figure 5.4Trends in Enrollment Rates in Bulgaria

100908070 - Kindergarten60 - Basic education

50 . -General secondary40 M--x Vocational secondary

30 X *. Tertiary education

20

1001989 1990 1991 1992 1993 1994 1995 1996

Source: TransMONEE Database, UNICEF-ICDC

5.31. The BIHS provides the opportunity to examine enrollment by expenditure quintile(see Figure 5.5). The total enrollment rates derived from the BIHS are close to thoseobtained from the NIS, which are the basis for the UNICEF-ICDC data in Figure 5.4.53 Thedata point to a drop in enrollment among children from the poorest households. Comparedto 1995, where enrollment in basic education did not vary much by expenditure quintile, in1997 we observe a drop in enrollment among children in the lowest quintile. Enrollment insecondary education among children from the lowest quintile also experienced a similar fall.This decline in enrollment in primary and secondary education among the poor raisessignificant concerns about the long-term prospects for children from these households.

Figure 5.5

Net enrollment in basic education Net enrollment in secondarybyquintile education by quintile

120 100 -100 - .- 80 - l80- 1995 60 -*----- -- 1995I

40 - 101997 E 40 -199720hIfl*201 I-0

1 2 3 4 5 1 2 3 4 5

Sources: BIHS1995; BIHS 1997

53 The enrollment rates (gross and net) derived from the 1995 and 1997 BIHS correspond closely to theadministrative (NIS) data with two exceptions. Kindergarten and tertiary enrollment derived from1997 BIHS 1997 are significantly lower than the administrative data. We do not understand the reasonfor the discrepancy. However, as there is no reason to believe that the lower enrollment estimated bythe BIHS 1997 at these two levels is due to under-enrollment in poor households, this should notaffect the results of the incidence analysis in paragraphs 5.32-5.36.

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5.32. To calculate the benefit incidence of education expenditures, we started byestimating the unit costs of education using the NIS data on enrollments by region.54 Wefound some variability in the unit costs (of per capita spending per pupil) among regions,which are partly due to underlying differences in schooling characteristics, notably numberof students per school and number of students per teacher. Sofia City and, to a lesser extent,Plovdiv region come out with large schools and many students per teacher, while regionsHaskovo, Montana and Rousse figure at the other end. The benefit incidence estimates thatfollow are based on the region-specific unit costs.

5.33. These unit costs are allocated to all households which reported having childrencurrently enrolled at the appropriate level, depending on the regional location of thehousehold. For the education sector as a whole, per student spending is distributed evenlyacross the expenditure quintiles. The poorest 20 percent of the population gained 20 percentof the total spending, compared with a share of 19.1 percent to the richest quintile. Thesecond, third, and fourth quintiles gained 20.4 percent, 21.0 percent and 19.4 percentrespectively.

Figure 5.6

Disribution of education spending by quintile120

IIe X80 - -

[ - .° 60 .w.-- 4 +Kindergarten

~~Basicc4 X/ ' Sec, Tech

20 - - - - - - -- - -- - - - - - - - - -- - - - - - - - - Tertiary

0 45 degree0

0 20 40 60 80 100Percent of population

Source: BIHS, 1995,1997

54 The benefit incidence analysis is drawn from Pradhan and Zant (1998) which should be consulted focfull details.

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5.34. These shares, however, mask quite significant variations across the different levelsof education. The poorest quintile gained proportionately most from kindergartens(23 percent) and primary schooling (21 percent), and least from secondary vocational andtechnical education (16 percent), and university and other post secondary education(I Ipercent). Figure 5.6 illustrates this point. While overall education spending isdistributed neutrally, spending on basic education is mildly progressive.55 Kindergartensubsidies are distributionally neutral, while spending on secondary, vocational, and technicaltraining mildly favor the non-poor. The poor benefit the least from spending on tertiaryeducation which largely goes to the upper quintiles.

5.35. In determining benefit incidence there are at least two factors at play. One is thedifference in needs by quintile. In general, we would expect the poorest quintile/s to havemore children of school going age (cf. paragraph 3.2 on the relationship between povertyand household size). Thus, some of the relatively high share of per capita spending going tothe lowest quintile arises because it has greater needs i.e. more children of (basic) schoolage. A second factor is differences in household behavior as reflected in enrollmentdecisions by quintile. We noted in paragraph 5.31 the lower enrollment among poorhouseholds in Bulgaria. It is possible to calculate how much spending on the lowest quintileshould be if we allow for variations in demographic structure, but control for householdbehavior. If the poorest quintile's enrollment behavior were the same as that for the countryas a whole, and given its greater need for basic schooling, it would obtain 25 percent of thebasic education subsidy (compared with an actual share of 21 percent). In other words, eventhough the basic schooling subsidy is well targeted to the poorest quintile, its share is stillinadequate to address fully its schooling needs. Although its share of the educationspending is higher that its share in population, it is simply not high enough to meet its needsdue to its greater share of school-aged children. The same result applies to spending at allthe other education levels.

5.36. Overall males and females gained the same spending per capita in 1997, with malesgaining more from basic schooling and secondary vocational/technical education, andfemales having an advantage in kindergarten and university education. In no case was thedifference very marked.

E. Health Services

5.37. The publicly-funded health system in Bulgaria is organized along the lines of districtand municipal administration, consisting of: first, rural health posts, district health centersand urban polyclinics for primary clinical care; second, municipal (300-bed) and district(1000-bed) hospitals for secondary care; and third, medical academies and a variety ofspecialist hospitals and institutes for tertiary care. The most fundamental reform in thesystem in recent years has been the decentralization of its management and financing to themunicipalities in which the health facilities are located. District and municipal healthservices are financed almost entirely from the municipal budget, which is distinct from the

55 A benefit is progressive (pro-poor) if the share received by the poor is greater than their share in thepopulation.

60

central or 'republican' budget. However, the municipal budget is dominated by transfersfrom the center (out of general tax revenues). These transfers are based mainly on historiclevels, and are not sufficiently sensitive to changes in service needs and utilization, leadingto problems of mismatch between resources and needs in some municipalities.

5.38. Health services are generally understood to have deteriorated in the country, in partas a result of the problems surrounding the transition from a centrally planned to market-based economy. As with most countries in former socialist eastern Europe, Bulgaria's healthsystem is characterized by the following limitations: resource constraints; centralizedplanning and management; extensive infrastructure and staffing; and limited incentives forefficiency improvements. Current policies are concerned with addressing each of theseweaknesses. They include measures to expand available resources (including through theintroduction of contributory health insurance); strengthen primary health care and otherbasic clinical services (emergency services and the blood transfusion service); greateremphasis on disease prevention; and improvements in the allocation and efficiency ofresource use within the sector.

5.39. As in education, within-sector allocations by level have not changed much duringthe transition. About two-thirds if the health budget goes on hospitals, the remainder onprimary care. The shares of different costs have however hanged over time. Personnelcosts, which are the largest share of spending, have been contained at around 40 percent oftotal spending, largely through squeezing wages. The total number of personnel in somecategories has in fact risen over the transition (from 27,039 physicians and 50,230 nurses in1992 to 29,592 physicians and 51,109 nurses in 1996). In contrast, the share of medicinesand pharmaceuticals has grown from 15 percent in 1991 to 24 percent in 1997, with totalspending having been maintained in real terms. The share of administrative costs, includingutilities, has grown from 16 percent to over 19 percent as energy prices have risen. Capitalspending however plummeted from 5.4 percent in 1991 to 2.3 percent in 1996.

5.40. The economic decline of recent years, combined with a deterioration in the health-care system has led to emerging health problems in the country. Life expectancy at birth formales was just 67.1 in 1996, which compares with 68.8 in 1965 (cf. Box 1.1 specifically forpost 1991 trends). This decline is due to excess mortality among males between the ages of15 and 49, which is a major challenge for the health system. These deaths are mainly aresult of a high incidence of cardiac and cerebro-vascular diseases, which tend to be relatedto environmental and life-style factors. Infant mortality, which decreased from 45.1 (per1000 live births) in 1960 to just 13.6 in 1988, has increased in recent years (to 16.9 in 1991and 15.6 in 1996). Matemal mortality rates, though decreasing, remain among the highestin CEE.

5.41. Many of the serious health problems in Bulgaria are probably best addressedthrough preventive public health measures aimed at improving the quality of the physicalenvironment, and changing eating and other life-style habits (reducing smoking). Publicinformation campaigns and taxation policy may be better suited to addressing theseproblems. Such programs would be population-based and designed to benefit both rich andpoor alike. The incidence of spending on such preventive measures is almost impossible todetermine, since the benefits are usually population-based. Exceptions include certain types

61

of preventive service, such as vaccinations and pre-natal care. However, the incidence ofspending on clinical facilities (such as polyclinics, primary health centers, and hospitals) canbe estimated, since we know through the BIHS which individuals benefited from suchservices.

5.42. Information on the incidence of illness and injury is self-reported in the BIHS, in thesense that the respondent is asked to identify cases of illness and injury during the referenceperiod. Although self-reported data are widely used, they are unlikely to be a reliable basisfor estimating illness incidence as people's perceptions of their health status is likely to becorrelated with income. However, the BIHS also recorded health consultations (bothcurative and preventive) during the reference period, and these formed the basis of ourincidence analysis. Of the medical consultations that were reported, the great majority werein the public sector, and especially in polyclinics and PHCs. There were some importantdifferences across quintiles. The richer groups were more inclined to have a medicalconsultation than the poor. Although the better off made greater use of private services --according to the 1995 BIHS, less than 5 percent of all consultations in the poorest quintilewere with private practitioners compared to 13 percent of all consultations in the richestquintile56 -- the better-off still make significantly greater use of publicly provided health carethan other groups. This pattern implies that spending on publicly provided health care isunlikely to benefit the poor as much as the rich.

5,43 As with education, it is possible to estimate the benefit incidence of health spending inBulgaria by combining information on health spending with data from the BIHS. Unitcosts were estimated for the provision of health care, and were then allocated to householdsthat reported (in the 1997 BIHS) that their members used publicly funded health facilities.Public expenditure estimates are made on an annual basis. To obtain unit costs, therefore,we needed estimates on the number of visits to publicly funded health facilities over theyear. The BIHS recorded health visits over a four-week period prior to the householdinterview. These were annualized by simply multiplying reported visits by the factor 13.

5.44. The level of disaggregation permitted in the analysis that follows was constrainedby the available data. Public expenditure information could only be obtained for healthspending on hospitals and other facilities (notably primary health centers andpolyclinics).58 No distinction could be made between secondary- and tertiary-level care.

56 See Demery and Mehra (1996) for further details.

57 This procedure may well introduce a bias in the estimate, since the incidence of ill health andinjury, and the consequent treatment may well be unevenly distributed through the year (the bulk ofthe 1997 BIHS was conducted during the months of April-June 1997). It would only affect thepattern of illness and treatment across household/income groups if some groups (such asagricultural workers) are more prone to seasonal effects than others.

58 As with education expenditures, we allocated a number of expenditure items (for example unspecifieditems in the Republican budget, and some 'other' categories of expenditure in the regional budgets)on a pro rata basis.

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Combining this information with reported health visits from the BIHS, estimates of unitcosts per visit were obtained for these two categories of health care in each of the nineregions. Combining these unit costs with information on the use of the services yieldsestimates of the benefit incidence of government health spending in Bulgaria. These aregiven in Figure 5.7.

5.45. For the health sector as a whole, the spending accruing to the poorest quintile was13 percent of total health spending while that accruing to the richest quintile was nearly28 percent. The share rises with per capita expenditures-the second quintile obtained15.1 percent, the third quintile 23.2 percent, while the fourth quintile obtained 27.9 percent.The inequality is most apparent for hospital-based care-the poorest 20 percent of thepopulation gaining less than 10 percent of spending. Their share of spending on primaryhealth facilities was significantly greater, at 17 percent of total spending on these facilities.However, given that about two thirds of the total health budget is devoted to hospital-basedservices, the poorest groups in Bulgarian society gained relatively little from health spendingas a whole. One clear message emerges from these estimates of benefit incidence of healthspending in Bulgaria -- to target the poor more effectively, allocations to PHCs andpolyclinics needs to be increased.

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6. CONCLUSIONS AND RECOMMENDATIONS

6.1. Chapter 1 surveyed the main macroeconomic developments since 1991, drawingout their implications for poverty. Chapter 2 discussed concrete estimates of levels andtrends in poverty, while Chapter 3 constructed a more detailed profile of poverty,including the characteristics of poor and non-poor households. Chapter 4 discussed linksbetween labor markets and poverty while Chapter 5 examined public spending on incometransfers and social services -- a major direct tool for poverty reduction -- asking thequestion: does this spending reach the poor? This chapter draws conclusions andimplications from the earlier discussion.

A. Ensuring macroeconomic stability and undertaking structural reform

6.2. It is clear from the analysis presented in this report that the standard of living, interms of current consumption, has decreased significantly for all the people in Bulgaria inthe last few years. As a result, there has been a sharp increase in poverty. There has alsobeen a widening of the income distribution during the transition. Both the contraction ineconomic activity (and as a result, the fall in household income and consumption) and therise in inequality have contributed to growing poverty, with the first playing a greater role inexplaining the rise in poverty than the second.

6.3. Given the magnitude of output decline (over 30 percent since 1990), and thelimitations imposed on the government by the need to maintain fiscal discipline, it should beclear that sustained growth that both raises wages and reduces unemployment will be criticalto reducing poverty in Bulgaria. To this end, it will be necessary to establish and maintain asound macroeconomic environment conducive to growth, reduce inherited price-distortions,and create conditions conducive to private sector development. The new government, inplace since April, 1997, has taken strong actions to restore macroeconomic stability and hasinitiated a program of structural reform, including privatization in the banking, agricultureand financial sectors. A first and key element of a poverty reduction strategy for Bulgariawould thus consist of maintaining the current policy environment and carrying throughmuch-needed reforms.

6.4. So far, the government's fiscal performance has exceeded expectations. Sincetaking office, the government has substantially reduced the budget deficit due to lower-than-projected interest payments on domestic debt, stronger revenues, and strict expenditurecontrol. For 1997 as a whole, the overall budget deficit was lower than targeted, allowingthe building up of fiscal reserves, and helping restore confidence in the government's abilityto meet its obligations. Further progress on this front is expected during 1998. Over themedium term, with the restoration of fiscal normalcy, it will be important to restoreoperations and maintenance expenditures (e.g. infrastructure), and to increase the leveland quality of public investment, both of which have been unsustainably compressed.

6.5. In parallel with the restoration of macroeconomic stability, the government hasinitiated structural reforms in key sectors. To date, progress in these areas has been slowerthan anticipated in the spring of 1997, reflecting, inter alia: (i) weak implementationcapacity to prepare firms and financial institutions for privatization; (ii) hesitation withproceeding with full privatization in some areas (e.g. agriculture) out of concern that the

64

underlying legal and structural conditions may be inadequate for the proper functioningof markets; and (iii) stronger than expected political constraints which have forced amore cautious approach. In the medium term, therefore, a key challenge would besustain and accelerate the process of enterprise restructuring and privatization in aconcerted effort to encourage private sector development. Reforming the stateadministration, the judiciary and the civil service will also need to receive priority as partof the effort to establish a fair and predictable legal and administrative climate forbusiness.59

6.6. Poverty and agricultural reform: One fact highlighted in Chapter 3 is the greaterincidence of poverty in rural areas in Bulgaria, and the lower access of rural residents,especially the rural poor, to public services. The growth of the non-agricultural sector,coupled with agricultural reforms that provide titles to land, develop land markets,increase the supply and timeliness of agricultural inputs, and improve marketingarrangements, will all have an important role in raising average incomes in rural areas,thereby reducing poverty. It will be important to ensure that any initiatives to raiseagricultural productivity (e.g., extension services) do not bypass the poor.6 0 Aninvestigation into the factors that restrict access to the use of credit, or inputs, by pooragricultural households would also need to be undertaken to guide policy on how to (ifpossible) reduce these distortions.

6.7. Poverty and energy-sector reform: Major sectoral reforms are also likely to beundertaken in the energy sector and they will need to address issues such as: (i)restructuring, commercialization, and privatization of energy enterprises; and (ii) theadjustment of prices to economic levels. The aspect of structural reforms that will affectthe poor the most is the second of these two. In chapter 3, we drew attention to the factthat the poor devote a large proportion of household spending to utilities. There are threegeneral options for protecting the poor from unaffordable price increases: (i) cashpayments to those most in need; (ii) energy vouchers which can be used to pay forutilities; and (iii) differentiated tariffs. A combination of these measures is possible.

6.8. There is no single system which is clearly advantageous under any circumstances.However, the main principles to be taken into account in designing an appropriate systemcan be set out. First, in theory there are 'consumer sovereignty' advantages in havingcompensation to poor households paid in cash rather than in kind (vouchers) or ties to theutilization of utility services. In practice, it should be recognized that any financialsupport could be used for 'inappropriate' purchases, and so govermments may often wantto tie the assistance in some way in order to ensure that any increased utility charges are

59 For a more detailed discussion of government priorities and medium term prospects, seeBulgaria: Country Assistance Strategy, Washington DC: The World Bank. April, 1998

60 Although land restitution cannot, strictly speaking, be described as a measure designed to raiseproductivity, it can be viewed as deriving from both economic and political motivations. In thiscontext it should be noted that one group that lost out from the 1991 Law for the return of agriculturalland to its former owners are the Roma. Enforced collectivization in the 1950s had previously giventhe Roma an opportunity to work on state and cooperative farms. With restitution, a large proportionof the Roma living in the countryside were left without land (Tomova, 1998)

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in fact met by the provided assistance. The relative advantages of using cash paymentswould also depend on the extent of regional differences in prices: if they were large, thenthe suitability of using standard cash assistance payment would be reduced. Thepossibility and advisability of using cash payments or vouchers would also depend on theavailability of suitable targeting mechanisms. In Bulgaria, this may be less of an issuebecause of the existence of a means-tested social assistance program which guarantees aBasic Minimum Income (BMI). Our analysis indicates however that the BMI program isfairly small.6 ' Thus while it could serve as a basis for a safety net aimed to protect thepoor from the effects of energy price increases, it would have to wider in coverage tomake a significant impact. Expanding coverage among the poor would raise fiscal costs,but there may be savings to be had from consolidation of different programs andimproved targeting of social assistance at the most needy, discussed further in paragraphs6.27-6.29 below.

B. Encouraging employment growth

6.9. Unemployment in Bulgaria is still high and is one of the major causes of poverty.Economic growth is essential to assure an increase in the demand for labor and thecreation of new jobs. At the same time, sound labor market policies can encourageemployment growth. We have already mentioned the role of appropriate administrativeand legal policies (see paragraph 6.5 above). These are especially important in the smalland medium enterprise sector, and for self-employment, where misguided bureaucraticinterference can act as a brake on employment growth.

6.10. Further changes to the Labor Code: The government can enhance job creation byreducing labor market rigidities. Regulation of the labor market in Bulgaria is governedprincipally by the Labor Code, which has undergone considerable revision over the yearssince the start of the transition. At this stage, the Labor Code is a relatively modemdocument, generally well-suited to the needs of a market economy -- avoiding some ofthe most restrictive provisions (e.g., prohibition of fixed-term, part-time and additionalwork, restrictions on enterprise-level collective bargaining, unduly onerous standards forfirings and lay-offs, etc.) found in some neighboring transition economies. Nonetheless,further improvements can be made, including: reductions of requirements with respect topaid education leave and maternity and child leave; reform of sick pay regulations,transferring initial responsibilities to employees and employers to prevent abuse; andeasier termination for misconduct or economic reasons.

6.11. Reduction in social insurance taxes: While the Labor Code may not poseinsurmountable hurdles to formal sector job creation, the high payroll taxes associatedwith social insurance (see paragraph 5.5) probably have a severely negative impact.Significant reduction in these tax rates is primarily dependent on successfulimplementation of pension reform (pensions are the largest source of tax), but there is aneed, too, to continue to lower unemployment insurance contributions which currently

61 According to the 1997 BIHS, where the BMI is identified as 'regular monthly cash', 12 percentof households below the lower poverty line and 10 percent of households above the poverty linereceive assistance from this program.

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stand at 4.5 percent (from a peak of 7 percent). The government's plans to further reduceunemployment insurance contributions to 3 percent of gross payroll, via annual half-percent reductions, is definitely a step in the right direction.

6.12. In the area of pensions, the basic strategy would be to:

(i) move away from the present over-reliance on a pay-as-you-go (PAYG)public pension system and move towards a fiscally sustainable, diversifiedthree-tier system involving the public and private sectors;

(ii) achieve a significant reduction in the long-term payroll taxes used to financemandatory pension programs; and

(iii) increase the 'fairness' of the public system to increase equity acrossoccupations and gender.62

The government has already taken some actions towards systemic reforms with a keyinitial focus on the improvement of fiscal balance within the existing PAYG scheme.63

6.13. Improvements in active and passive labor market programs: In parallel withefforts to increase flexibility in the market for labor and reduce labor costs, thegovernment can consider improving its set of passive and active labor programs. Themain passive labor market program is unemployment insurance which provides cashassistance (for a limited duration of time) in the event of unemployment. We found noevidence that unemployment benefits reduce incentives to find work (see 4.10).Although, they are not a well-targeted benefit (they are not meant to be), they play animportant role in reducing poverty among households whose heads are unemployed (see5.16). The scheme has been recently strengthened by the passage of the new Act onUnemployment in November 1997 which strengthens the insurance basis forunemployment benefit by eliminating coverage for non-contributors, tightens eligibility,and reduces the lower bound of benefits from 90 to 80 percent of the minimum wage. Inthis section we therefore confine our attention to active labor market programs.

62 These efforts are being supported by the World Bank under the Social Protection Adjustment Loan(SPAL).

63 Steps taken so far include: (i) a major effort to clear up past arrears to the social security fund andlimit future ones through the passage of laws which require employers to pay social insurance debtsbefore any other obligation and limit wage increases in, and access to loans for, enterprises withpayroll tax arrears; (ii) strengthened compliance through changes in contribution reporting to includeinformation on an individualized as well as enterprise basis -- coupled with regulatory changes tosubstantially strengthen the link between contributions and eventual pension benefit levels; (iii)elimination of duplicative, non-insurance related programs, such as provision of special dietary foodsupplements; (iv) amendment of the Labor Code to allow individuals to voluntarily retire up to threeyears later with higher benefits; (v) steps to reduce the medium- and longer-run costs of the PAYGsystem by reducing or eliminating early retirement privileges for about 75 percent of thosepreviously entitled to these privileges; (vi) substantial progress with legislation to regulate andestablish the legal foundations for a third pillar of voluntary pensions.

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6.14. It is worth stressing that active labor market programs (ALMPs) can play at best amarginal role in permanently reducing unemployment. Sustained reductions inunemployment will have to rely on improving macroeconomic conditions, reducing labormarket rigidities, and lowering labor costs. ALMPs themselves are more likely to beeffective in a situation of buoyant demand than one of stagnation or contraction. Thegovernment has three ALMPs of significance: (i) temporary works; (ii) wage subsidies;and (iii) training. Given the limitations on resources, the government should evaluateexisting programs. As a first step, it should undertake an assessment of the effectivenessof past and current programs, examining their outcomes, targeting and cost-effectiveness.The findings should be used to guide policy development. International evidencesuggests that ALMPs are often most effective when they are used to assist groups that aredisadvantaged in the labor market.f4 From this point of view, the emphasis in the newAct on Unemployment on ALMPs that are aimed at the youth, the long-termunemployed, and ethnic minorities, is to be welcomed.

6.15. More and better labor market information: One finding brought out in theanalysis in Chapter 4 was the high wage expectations held by the unemployed. Thedisparity between reality and expectations may effectively prevent the unemployed fromfinding jobs. This suggests that there is a role for the public employment services inproviding more and better information on what employment prospects exist and at whatrates of remuneration. Improving the access to and quality of employment-relatedinformation is also likely to make the National Employment Services more effective, aswould improvements in the job search assistance and counseling services provided bythem.

6.16. Long-term reform of the education system: In order to take full advantage of agrowing economy, individuals, and especially the unemployed, need to upgrade theirskills. It is generally assumed that Bulgaria has well educated, skilled labor force. This istrue, although upon closer inspection one can notice that the labor force in Bulgaria is tosome extent polarized with regard to educational achievements (see Table 3.3). On the onehand, there is a large proportion of people with tertiary education (16.2 percent overall), onthe other there is a substantial fraction - almost one third - of the labor force having onlybasic education. There is also a problem of no education and, by association, illiteracy,confined almost exclusively to the Roma minority.

6.17. In Chapter 4, we drew attention to a certain element of skill mismatch between thestructure of existing jobs and the skills and education possessed by the unemployed (see4.18). More than 15 percent of all jobs go to persons with tertiary education while only 6percent of all unemployed has college degree. At the other extreme, there is 25 percent ofjobs requiring primary or less education and as many as 40 percent of the unemployed fallinto this category. Apparently, there is a substantial oversupply of unskilled workers.6 5 The

64 See World Bank (1995), Workers in an Integrating World.

65 Further evidence of skll mnismatches comes from a survey of private businesses conducted by NSI,during a period of demand expansion (See, Bulgarian Economic Review No. 3, December 8-12, 1995which reported the results). A considerable fraction of firms (23 percent) pointed to personnel recruitingas one of the major problems in going into business.

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point to note is that the problem of skill mismatch is independent of overall demandconditions and therefore will not be remedied by the upsurge in the aggregate demand.

6.18. There may also be skill mismatches within education categories. Over fortypercent of the labor force has secondary education (43.6 percent). Out of this, however,some fraction received secondary level education which is either general or technical, butwhich prepares students for higher learning, while some part received only vocationaltraining which is not a conduit for higher education.66 Experience from other transitionaleconomies (for example, from Poland) shows that the latter category has considerabledifficulties in adapting and developing their skills so as to meet changing job requirements.Those people were often trained only to meet a particular skill demands of a local employer.Once the labor market becomes subject to changes, they tend to get 'stuck' with theirnarrow skills which are no longer in demand. Retraining, although necessary in such a case,is not a panacea since effectiveness of training tends to be correlated with the level of initialeducation and people with narrow basic vocational skills often face substantialpsychological costs of acquiring additional education.

6.19. This suggests that over the long-term, there are at least two areas of reforrn in theeducation sector which would assist in expanding the labor market opportunities of thepopulation: (i) first, greater emphasis on increasing the educational achievement of thepopulation as a whole through an increase in secondary enrollments, and an eradicationof pockets of no education and associated illiteracy; and (ii) within secondary education,greater emphasis on general secondary education at the expense of obsolete or non-transferable vocational skills.

6.20. In the short-run, stem the fall in enrollments among children from poorhouseholds: While education reforrn is probably best considered a long-run objective, thefall in enrollment rates among children from poor households (see 5.31) is of immediateconcern. Closer investigation of this matter is warranted. Existing studies point to thehigh out-of-pocket fees (for clothes, stationary, etc.). Other factors could be the distanceto the school, lack of adequate facilities, and lower quality of education in poorer areas,all of which may create significant disincentives for enrollment. A contributory factormay be the opportunity costs of work foregone, although this may be more of an issue inthe context of secondary rather than primary enrollment. Reversing these negative trendswill be important if children from poor households are not be at a disadvantage in thefuture labor market.6 7 The responsibility for monitoring enrollments and taking the lead

f6 This sort of training, lasting 3 years and focusing heavily on providing narrowly defined technicalskills rather than general secondary education, is provided by so called SPTUs (Secondary VocationalTechnical Schools).

67 A number of regulatory measures are in place to encourage school attendance, but none areparticularly effective. Municipalities can impose fines for non-attendance, but inflation has erodedthis fee to less than 10 percent of the minimum wage discouraging collection. School attendance hasbeen an eligibility criteria for the receipt of child allowances for children at the secondary level, butnot for children of compulsory (basic) school age. Like the fines, the real value of child allowances isso low that the rule is unlikely to significantly improve attendance, particularly if the child can eanmore than the child allowance if they are pulled out or drop out of school.

69

with respect to policy development in this area should lie with the national Ministry ofEducation, Science and Technology (MEST) with the municipal governments beingresponsible for implementation.

C. Strengthening the social safety net

6.21. Given the return to economic growth and a rise in average incomes, poverty canbe expected to fall. The simulations presented in Chapter 2 show that, if the economygrows by 3 percent per annum and there is no change in the distribution of income,poverty will fall from 36 percent to 27.6 percent after 5 years. It the rage of growth ahigher 5 percent per annum, poverty will fall to 22.4 percent. With widening of theincome distribution -- not an unlikely event -- some of the poverty-reducing impact ofgrowth will be diminished. A widening of the distribution by as much as occurredbetween 1995 and 1997 will wipe out the impact on poverty of 6-8 percentage pointsworth of growth. These simulations suggest that it is important to be realistic about theimpact of growth on poverty-reduction, and recognize that a strong social safety net,well-targeted at those who are the least likely to benefit from growth, will be essential toreducing poverty.

6.22. Before discussing what might be done to strengthen the social safety net, a fewwords are in order about rising inequality. In Chapter 4, we discussed one of the factorsunderlying the growing consumption inequality; namely, growing inequality in earnings.This growth in inequality has its source in the decentralization of wage setting in the wakeof economic liberalization as well as in demand shifts induced by transition. Wagedifferentials under centrally planned economy were narrow and rewards to 'human capital'were small compared to market economies. Economic freedom given to enterprises(although to some extent restrained by the prevailing incomes policy) and the growth of theprivate sector means that wage setting now resembles market conditions more closely. As aresult of these changes, there is greater inequality in earnings, with more people on low paythan earlier, and with the highest paid workers getting paid a substantially greater proportionof median wage than before (see paragraph 4.21).

6.23. If one attaches a high value to equity and social cohesion, then rising inequalitymeans lower social welfare. However, if an economy mis-allocates its resources, thensacrificing some equity in order to efficiency is beneficial. Evidence from other transitionaleconomies shows that to a large extent the widening of earnings distribution is driven by anincrease in the returns to education and labor market skills. Evidence from the BIHSsuggest that, like elsewhere, returns to education have increased in Bulgaria during thetransition (see 4.26). If this increase in retums to education is the major driving force behindthe rising earnings inequality then - providing that inequality is kept within reasonablelimits - this process is probably conducive to economic growth. Thus, it seems that at themoment there is limited economic justification for policies to counter the trend towardgreater earnings inequality (e.g., through more progressive taxation of personal income). Itis important, however, that inequalities do not rise beyond the point when they endangersocial cohesion and imperil political viability of economic growth and development. At themoment, Bulgaria seems far from such a point.

70

6.24. We now turn to ways in which the system of social assistance can be made to betterprotect the poor. The system, prior to 1998, suffered from some key drawbacks:

(i) fragmentation;(ii) inadequate funding;(iii) poor targeting; and(iv) poorly defined financing responsibilities.

The first of these is excessive fragmentation. In addition to the main income supportprograms, Bulgaria has a wide range of cash transfer and in-kind benefit programs,administered through different agencies. The present multiplicity of programs increasesthe administrative costs of the system without substantially increasing the number ofbeneficiaries. Indeed, overall coverage is low: less than a fifth of poor householdsreceive any form of social assistance (see Table 5.1). And, the overlap of programs withdifferent targeting mechanisms undermines the ability to reach the poorest groups in thepopulation. As a result, over a third of households receiving social assistance are notpoor (ex-ante). The overall level of spending on social assistance, especially on incomesupport, is low: spending on all social assistance was 0.7 percent of GDP, and on incomesupport (BMI) 0.07 percent of GDP in 1996. This should be raised in order to providean adequate basis for a minimum income guarantee. Given the scale of poverty, twicethe level of expenditure (1.4-1.5 percent of GDP) would not be unwarranted.68

6.25. Financing for social assistance programs is derived from general revenuesallocated through the state budget or by means of block grants to local governments who,in turn, allocate the block grant funds and own revenues to programs for which they areresponsible. In the social assistance area, responsibility for social care institutions, themonthly BMI program, occasional income support, family benefits for the uninsured, andmany smaller in-kind programs was devolved to the local level in 1993. A program forin-kind support to meet utility needs was introduced in 1995 and is financed through acentrally-managed fund. By and large, decentralization of the basic poverty relieffunction has not worked well. Although a minimum poverty benefit, based on a survivalbasket of food requirements, is mandated by law and, in principle, forms the basis for themeans-tested BMI -- in practice, very few poor households receives assistance regularlydue to severely constrained budgets (see paragraph 6.8). Similarly, budget allocations forsocial care institutions which cater to the mentally and physically disabled, orphans andother disadvantaged groups have declined to less than a quarter of their 1991 levels --with a concomitant decline in the quality of services.

6.26. Reforms in four areas would increase the poverty reduction impact of socialassistance: (i) reduce fragmentation; (ii) explore ways to increase funding; (iii) improvetargeting; and (iv) establish clearer financing responsibilities between the centralgovernment and local municipalities.

68 These figures represent the estimated resources needed to provide all eligible households withsocial assistance and energy benefits given current benefit levels. Projections were made using BIHS1997 data.

71

6.27. Reduce fragmentation: Following the passage of the Social Welfare Act early in1998, the Government has taken key steps to reduce fragmentation including combiningeligibility criteria for the BMI program and the program of in-kind support for utilities.A second step would be to complete this consolidation by replacing in-kind utilitysupport with an equivalent cash benefit.7 0 Similarly, a duplicative program for provisionof free medicines to the needy has been transferred to the Ministry of Health, whichmanages a similar program. However, there is scope for further consolidation. Inprinciple, this could proceed to the point where the means-tested BMI programn becomeson principal source of social assistance.

6.28. Explore ways in which to increase funding: In addition to raising the overallenvelope for social assistance, it will be important to look for savings within programs.So, for example, the elimination of utility-component of income support during the non-heating season and reduction of the unrealistically high norms for the heating seasonunder the new Social Welfare Act, are steps in the right direction. More funding couldbe made available by cutting back on untargeted programs. Perhaps the most significantprogram in this context is maternity leave for uninsured mothers which costs over twiceas much as BMI (0.2 percent of GDP versus less than 0.1 percent for BMI), and whichbenefits rich and poor alike. Finally, increased NGO participation in the provision ofsocial assistance and social welfare is likely to expand both funding, as well as raise thestandards of care for clients in social care institutions.

6.29. Improve targeting: Overall, social assistance in Bulgaria appears to be relativelywell-targeted. However, there is scope for improvements in targeting. Discretionarysocial assistance payments often tend to be regressive (accrue disproportionately to thenon-poor). The Govermnent has already taken steps to reduce the scope for leakage fromthe system through altering the provisions for one-off discretionary payments to households.These payments, intended to help households cope with emergencies, were previouslypayable up to 7 times per year per household. The new regulations reduce these payments toa maximum of 3 times a year per household, and a further reduction to a single payment peryear will shortly be introduced. There is also the need for further analysis of the extent ofleakage from the BMI scheme. This would allow the source of leakages to identified andreduced. Any reduction in leakage would have to be weighed against the administrativecosts of tighter means-testing.

6.30. Establish clear responsibilities: The new Social Welfare Act establishes animproved basis for the decentralization of social assistance. From 1999, the entireprogram will be funded on a cost-sharing basis between central and municipal budgetswhile introducing incentives for municipal authorities to meet social welfare payments ontime. In order to eliminate financing gaps at the municipal level, the central government

69 The new Act also increase protection for the poorest households, by raising the benefitcoefficients for pensioners over 70 living alone, children aged 0-16 years, and the disabled. Thenew regulations also improve work incentives by re-introducing a 30 percent disregard for earnedincome when determining eligibility.

70 This step is to be implemented by calendar year 1999 under one of the conditions of the SPAL.

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budget will provide earmarked funds toward program costs, as well as an additionalcontribution to the general municipal budget if social benefit payments are made on time.The supplement would serve as an incentive for municipalities to allocate the necessaryresources to the social assistance system.

D. Investing in human capital

6.31. We have already touched upon a number of policy initiatives that could be takento encourage investment in human capital especially by the poor, including measures toraise primary and secondary enrollment among poor households, raising secondary andgeneral secondary enrollments among the population at large, training initiatives focusedon the most- disadvantaged groups in the labor market etc.

6.32. In addition to these initiatives in the area of education, it would be important forpoverty reduction to guarantee access to health services, especially among the poor, andraise their quality. One finding that emerged from the incidence analysis in the healthsector is the much lower use by the poor of publicly-funded hospitals. This is a findingthat deserves closer investigation. At least some of the lower use can be ascribed tocharges that households would have to incur in order to take full advantage of hospitals.71The financing reforms under consideration in the health sector should take account of thisaspect of things. The reforms should ensure that the poor are not left under-insured, withreduced access to healthcare.

E. Improve poverty monitoring

6.33. Whatever combination of policies and measures is adopted by the Government, itwill be important to monitor poverty on a regular basis. Perhaps the first step would be tofinalize a poverty line by drawing upon either the recommendations of the jointMOLSP/ILO/UNDP study, or the poverty line used in this study which is close to the lowerpoverty line recommended by the expert group. Follow-up work on national and regionaltrends in poverty, and the incidence of public spending will be necessary. Closer analysis ofa number of social protection initiatives is also warranted. Capacity to undertake suchanalysis will need to be developed.72

71 We can think of two types of charges. The first are transaction costs, which confer noadditional benefit to the household (in addition to the in-kind transfer gained by using the publiclyfunded service). Examples of these are transport costs. The second are (informal and formal)service charges that confer a benefit that can be added to the in-kind subsidy. Examples includemedicines but also doctor's fees, etc.

72 Some of this capacity building could be undertaken under the existing IDF grant.

Annex 1: Supplementary Tables for Poverty Profile

Table A.1: Poverty Measures and Shares by Household Size

Household Poverty Measures Poverty % of PovertySize Sofia Other Rural Measure Population Share

Urban

Poverty Rates1 27.14 24.62 25.60 25.40 6.47 4.562 35.71 24.93 26.10 26.50 19.78 14.543 38.27 23.41 36.89 29.36 19.37 15.784 35.29 31.67 41.84 34.45 26.47 25.30

5 or more 46.67 49.53 54.18 51.41 27.91 39.81Bulgaria 37.64 32.49 41.18 36.04 100.00 100.00

Poverty Gap1 8.97 5.61 7.56 6.90 6.47 3.902 9.71 6.27 6.25 6.62 19.78 11.453 9.77 6.86 11.19 8.42 19.37 14.264 9.88 8.11 12.66 9.38 26.47 21.70

5 or more 18.52 17.38 22.77 19.95 27.91 48.67Bulgaria 11.35 9.55 14.55 11.44 100.00 99.98

Poverty Depth1 3.93 2.17 3.04 2.78 6.47 3.382 4.39 2.29 2.18 2.47 19.78 9.183 3.69 3.06 4.82 3.59 19.37 13.074 3.65 2.81 5.43 3.51 26.47 17.46

5 or more 11.42 9.16 12.40 10.84 27.91 56.87Bulgaria 5.24 4.23 7.13 5.32 100.00 99.97

Note: Poverty Line is defined as two-thirds of mean per capita consumption in 1997.

Table A.2: Poverty Measures and Shares of Individuals by Age Group and Locality

Age-groups of Poverty Measures ALLIndividuals Other % of Poverty

(years) Sofia Urban Rural Total Population Share

Poverty Rates0-5 36.36 41.28 57.65 47.22 3.20 4.20

6-10 52.38 38.68 59.31 47.23 6.69 8.7911-17 41.54 32.78 48.63 38.34 9.06 9.6618-25 30.15 32.23 44.50 34.98 11.11 10.8126-45 32.44 29.91 45.19 34.60 25.47 24.5146-55 37.68 27.92 35.19 31.23 14.82 12.87

above 55 42.02 35.64 33.14 35.32 29.65 29.13Bulgaria 37.66 32.49 40.93 35.95 100.00 99.98

Poverty Gap0-5 14.47 13.46 23.98 17.70 3.20 4.97

6-10 18.62 11.39 23.92 16.43 6.69 9.6411-17 11.89 10.28 18.91 13.04 9.06 10.3618-25 9.13 10.75 18.00 12.30 11.11 11.9926-45 9.51 8.82 16.11 10.99 25.47 24.5546-55 11.23 7.70 12.78 9.56 14.82 12.43

above 55 12.06 9.72 9.79 10.03 29.65 26.09Bulgaria 11.35 9.54 14.46 11.40 100.00 100.03

Poverty Depth0-5 9.17 6.79 13.13 9.53 3.20 5.75

6-10 10.30 5.39 12.06 8.22 6.69 10.3811-17 4.38 4.74 10.40 6.40 9.06 10.9418-25 3.98 5.13 9.86 6.12 11.11 12.8326-45 4.41 3.86 7.94 5.09 25.47 24.4646-55 5.36 3.10 6.34 4.29 14.82 12.00

above 55 5.20 4.10 4.10 4.23 29.65 23.66Bulgaria 5.24 4.22 7.09 5.30 100.00 100.02

N 887 3,629 2,226 6,742

Note:Poverty Line is defined as two-thirds of mean per capita consumption in 1997.N = Number of cases

Table A.3: Sources of Income forPoor/Non-poor Individual

Source Poor Non-poor All

Agriculture Sales 2.83 5.26 4.37Agriculture in kind 7.32 10.87 9.57Wages 34.69 42.97 39.94Self-employment 1.13 2.61 2.07Social Assistance 16.72 6.96 10.52Pensions 32.87 23.28 26.78Unemployment 1.81 1.38 1.54Remittances Sent 35.60 28.14 30.86Remittances Received 38.70 23.97 29.35Revenue from Assets 0.37 0.40 0.39Other Revenue 5.35 2.11 3.30

Total 100.00 100.00 100.00N 2,253 3,918 6,171

Total Household Average MonthlyIncome 97,532.71 16,9749.20 143,325.10

Average Household Size 4.33 3.43 3.76Per Capita Average Monthly Income 22,524.88 49,489.56 38,118.38

N 2,262 3,920 6,182

Note:Poverty Line is defined as two-thirds of mean per capita consumption in 1997.N = Number of cases

Table A.4: Poverty Measures and Shares of Individualsby Major Source of Income and Locality

% of PovertyMajor Source Region Bulgaria Population Share

Other.Sofia Urban Rural

Poverty RateEarned Income 36.42 28.38 46.73 32.82 39.40 35.24Agriculture 0.00 30.77 28.33 26.83 3.28 2.40In kind 30.00 23.24 28.99 26.83 5.91 4.32Social Benefits 41.21 45.42 44.11 44.42 22.83 27.64Mixed 39.88 32.69 46.79 39.04 28.57 30.40

Total 38.03 32.95 42.54 36.69 100.00 100.01

Poverty GapEarned Income 8.56 7.40 19.42 9.73 39.40 32.99Agriculture 0.00 2.83 9.47 8.49 3.28 2.40In kind 9.75 3.71 7.64 6.24 5.91 3.18Social Benefits 11.31 14.39 13.65 13.74 22.83 27.00Mixed 15.22 10.88 17.44 14.01 28.57 34.45

Total 11.47 9.60 15.16 11.62 100.00 100.01

Poverty DepthEarned Income 2.97 2.77 10.46 4.18 39.40 30.67Agriculture 0.00 0.26 4.76 4.20 3.28 2.57In kind 4.72 1.38 3.18 2.57 5.91 2.83Social Benefits 4.78 6.67 5.69 6.09 22.83 25.89Mixed 8.32 5.34 8.93 7.16 28.57 38.09

Total 5.29 4.18 7.47 5.37 100.00 100.05

N 881 3,390 1,970 6,241

Note:N = Number of cases

Table A.5: Poverty Measures and Shares of Individualsby Major Source of Income and Household Size

Major Source Household Size All % of Poverty1 2 3 4 5 Population Share

Poverty RateEamed Income 5.71 15.57 22.68 31.28 50.87 32.82 39.40 35.24Agriculture 0.00 10.00 14.29 26.67 34.00 26.83 3.28 2.40In kind 10.53 16.28 18.18 33.33 38.24 26.83 5.91 4.32Social Benefits 30.04 35.48 50.00 61.11 69.74 44.42 22.83 27.64Mixed 23.66 24.44 36.52 35.65 51.71 39.04 28.57 30.40Total 25.25 27.42 30.40 35.01 51.93 36.69 99.99 100.00

Poverty GapEamed Income 0.78 3.86 5.28 8.09 18.16 9.73 39.40 32.99Agriculture 0.00 3.42 1.54 9.34 10.80 8.49 3.28 2.40In kind 3.41 3.00 2.36 9.49 8.97 6.24 5.91 3.17Social Benefits 8.23 9.26 15.57 17.22 28.38 13.74 22.83 27.00Mixed 6.92 5.59 12.06 10.14 22.76 14.01 28.57 34.45Total 6.97 6.87 8.56 9.57 10.17 11.62 99.99 100.00

Poverty DepthEarned Income 0.14 1.21 1.87 2.97 8.98 4.18 39.40 30.67Agriculture 0.00 1.17 0.16 6.05 4.70 4.20 3.28 2.57In kind 1.16 1.13 0.44 4.02 4.07 2.57 5.91 2.83Social Benefits 3.38 3.61 6.13 6.21 15.72 6.09 22.83 25.89Mixed 2.98 1.86 5.93 3.66 13.43 7.16 28.57 38.09

Total 2.87 2.54 3.58 3.61 10.91 5.37 99.99 100.05

N 404 1,240 1,194 1,668 1,735 6,241

Note:N = Number of cases

Table A.6: Caloric Consumption and Share ofFood Consumption Received from Other Sources

by Quintiles (QUI)

QUI I QUI 2 QUI 3 QUI 4 QUI 5 Bulgaria

Share of Calories from Food GroupsCereals 57.21 46.14 43.31 39.99 36.01 44.54Vegetables 8.03 7.80 7.51 7.95 7.42 7.74Fruit 4.73 4.91 5.44 5.49 6.10 5.41Meat Family 4.64 5.64 6.56 8.51 9.84 7.24Dairy 15.30 19.40 19.92 20.22 22.11 19.50Fats 14.19 14.18 14.29 14.59 13.89 14.23Sugar 3.78 4.02 3.91 3.98 4.00 3.94Other Food 0.29 0.61 0.69 0.99 1.43 0.81

Share of food from home consumptionCereals 2.61 2.79 4.45 6.86 6.81 4.70Vegetables 33.93 44.26 47.17 49.17 44.97 44.02Fruit 70.98 70.50 70.63 70.53 61.87 68.59Meat Family 23.83 27.95 33.03 33.63 32.25 30.62Dairy 26.61 29.80 31.48 32.22 29.27 29.96Fats 5.57 9.43 13.34 12.22 15.23 11.26Sugar 1.38 0.00 0.32 0.00 1.01 0.53Other Food 5.87 7.11 9.39 12.95 11.56 9.43

Share of food received from other sourcesCereals 1.13 1.81 2.58 2.94 3.81 2.46Vegetables 9.84 6.49 8.19 5.78 7.97 7.63Fruit 7.36 7.37 6.98 6.44 8.75 7.40Meat Family 11.34 8.27 9.06 7.72 11.41 9.47Dairy 4.96 5.05 7.89 9.66 11.33 7.86Fats 4.03 5.35 5.44 6.81 6.86 5.73Sugar 1.21 0.64 0.56 1.01 0.99 0.87Other Food 2.29 2.11 3.51 3.04 5.92 3.40

Note: Poverty Line is defined as two-thirds of mean expenditure in 1997.

Annex 2: Construction of Panel

HouseholdsSample size, 1995 2,500Sample size, 1997 2,432

Dwellings with repeated interviews 2,048

On comparing households, we found that:No. of households with no 1995 member present in 1997 383No. of households with same head in 95 and 97 1,512Case 2* 65Case 3 ** 86Case 4 *** 2

Number of households in working panel (2048-383-2) 1,663

Note:Households where no 95 member was present in 97 and Case 4 households weredropped.

* Case 2 households are those where the head had changed between 95 and 97 but the 95head was part of the 97 household. The 95 head was chosen as the head in both years.

** Case 3 households are those where the 95 head was absent in 97, but the 97 head was amember of the 95 household. The 97 head was chosen as the head in both years.

*** Case 4 households are those where the 97 head was absent in 95 and the 95 head wasabsent in 97. These households were dropped.

Annex 3: Multivariate Estimation of Labor Market Outcomes

Table A3.1: Logit estimate of the odds of being unemployed

Dependent variable: whether individual is unemployedOdds Ratio

Female 0.90IC'25-34 0.534a'35-44 0.237a'45-54 0.288a/55-64 0.160a'65 + 0.044a/Secondary general 0 .527a'Secondary vocational 0 *439a1College 0.267a'University 0.247a/Turkish 1.278 C'Gypsy 3.124a/Other 1.762 c'Single 1.629a'Spouse 1.269 c/Child 1.422b'Others 2.581 b/

Urban 0.757 Cl

Region dummies Yes

N 2,877Log likelilhood -1,121.78Chi2 478.34Pseudo R2 0.1757

a Significant at 1 percent levelbi Significant at 5 percent levelCl Not significant estimateN = Number of cases

Source: BIHS, 1997

TableA3.2: Determination of reservation wages and actual wages (OLS estimates)

Dependent variableIndependent Log actual Log reservation Difference SignificanceVariables wage wage (*100) *

Education, years 0.062 0.059 0.388 noAge 0.019 0.049 -3.061 yesAge2/100 -0.022 -0.054 3.236 noFemale -0.273 -0.335 6.185 noTurkish 0.081 0.007 7.361 noGypsy -0.344 -0.320 -2.443 noOther ethnicity -0.167 -0.175 0.821 noReg. Unemployment -0.011 -0.001 -1.029 yesReg. Wage 0.003 0.004 -0.043 noConstant 10.755 9.493 126.227 yes* Significance of the difference between coefficients at the 5 percent significance level.

Source: BIHS 1997

It is interesting to note that the unrealistic wage expectations discussed in Chapter 4 are notthe result of a misperception of returns to different human capital characteristics. To the contrary,the unemployed seem to be well aware of their relative strengths and weaknesses. In technicalterms, the earnings function they implicitly use to 'estimate' their reservation wage quite closelymatches the actual earnings function as far as the returns to different labor market characteristicsare concerned. The problem is that the expected baseline earnings (the constant term) are far toohigh -- see Table A3.2. According to our estimates, the unemployed virtually perfectly 'guess'the returns to education. Furthermore, younger workers expect lower earnings than moreexperienced workers. Women expect lower earnings than men, and Gypsies expect lower earningthan Bulgarians with* comparable labor market skills. They do take into account localunemployment and relative wage conditions. That is, they have almost perfect recognition ofrelative wages. The only thing that they do not recognize is the actual wage level, which theytend to overestimate by a substantial margin.

Table A3.3: OLS estimates of earnings functions

Dependent variable: log monthly earningsNational Public Private sectoreconomy sector

Education (Primary)Secondary general 0.227 a! 0.267 a/ 0.064Secondary vocational 0.304 a' 0.344 a' 0.083 dv

College 0.397 a' 0.474a' 0.145 d/

University 0.691 a' 0.741 a' 0.444 a'Job experience 0.014 b 0.013 cl 0.028 d/

Job experience2 -0.028 d/ -0.022 d/ -0.081 d/Female -0.253 a' -0.261 a' -0.222 a'Ethnicity (Bulgarian)Turkish 0.Ol4d/ -0.0 66d/ 0.281 clGypsy -0.2321d 0.199 dl -0.114 d/Other ethnicity 0.067d' 0.1o0 d/ (dropped)Trade union 0.087 C/ 0 .1 0 9 b/ 0.016d/

Private sector -0.085 Cl -

Occupational Sector Yes YesConstruction -0.166 a/Agriculture -0.637 a'Transport -0.159 aTrade -0.385 aSocial services -0.524a'Public services -0.197a'Region dummies Yes Yes Yes

N 1,102 839 263F 15.29 14.22 3.09R 2 0.270 0.304 0.237Root MSE .5805 .5644 .6112

a/ Significant at I percent levelb/ Significant at 5 percent levelc/ Significant at 10 percent leveld/ No significant estimateN = Number of cases

Source: BIHS, 1997

Annex 4: Trends in Social Expenditures in Bulgaria

Social Protection Expenditures(% of GDP)

1991 1992 1993 1994 1995 1996Social Assistance

Monthly and occasional benefits 0.13 0.28 0.39 0.23 0.09 0.07Child allowances 0.01 0.01 0.01 0.02 0.07 0.06

Maternity leave 0.17 0.21 0.30 0.27 0.23 0.17Birth grants 0.00 0.00 0.00 0.01 0.01 0.01

Cash and in-kind benefits for the disabled 0.06 0.07 0.07 0.06 0.04 0.03Energy subsidy na na na na 0.07 0.16

Social care services and institutions 0.41 0.38 0.38 0.36 0.30 0.25Administrative costs na na na na 0.07 0.05

Total 0.78 0.96 1.16 0.93 1.04 0.74

Labor MarketsUnemployment benefits 0.53 0.58 0.69 0.51 0.33 0.25

Unemployment assistance for school leavers na na 0.07 0.05 0.04 0.03Unemployment assistance (for LTU) na na na na 0.05 0.04

Vocational Training 0.00 0.01 0.01 0.01 0.01 0.01Public employment programs na na 0.04 0.03 0.06 0,07

Agricultural credit scheme na na na na na 0.004Other employment promotion measures na na 0.001 0.002 0.001 0.000

Operational expenses (NES) na 0.03 0.11 0.09 0.10 0.08Severance Pay na na 0.03 0.01 0.02 0,04

Other na na na na na 0.02Total 0.53 0.62 0.95 0.71 0.61 0.53

PensionsOldAgePensions 7.91 8.47 9.34 8.35 6.88 6.15

Craftsmen, private trademen and professionals 0.02 0.07 0.08 0.07 0.06 0.05Farmers pensions 0.37 0.91 0.88 0.69 0.52 0.38

Social pensions 0.06 0.17 0.19 0,17 0.15 0.12Special pensions 0.01 0.01 0.01 0.01 0.01 0.01

Disability pensions 0.80 0.82 0.89 0.79 0.66 0.53Total 9.18 10.45 11.38 10.09 8.28 7.24

Family Benefits (financed through NSSI)Child allowances 2,16 1.58 1.27 0.98 0.76 0.55

Birth grants 0.01 0.01 0.00 0.02 0.02 0.01Sickness benefits 0.53 0.63 0.61 0.54 0.48 0.38

Care for sick child 0.05 0.06 0.06 0.05 0.05 0.04Maternity benefits 0.16 0.15 0.14 0.10 0.08 0.06

Administrative expenses (total NSSI) 0.04 0.06 0.07 0.04 0.06 0.06Total 2.94 2.48 2.14 1.73 1.45 1.10

Health 4.36 5.48 4.93 4.20 3.83 3.19

Total Social Protection (% ofGDP) 14.85 17.50 18.42 15.93 13.76 11.71(1991=1) 1.00 1.09 1.13 1.00 0.88 0.68

Other Social ExpendituresEducation 5.14 6.06 5.74 4.80 4.10 3.29

Memorandum ItemsGDP 131.1 203 298.9 522.2 867.7 1660.2GDP deflator (1991=1) 1 1.59763314 2.41715976 4.14497041 6.73964497 14.4430592

BIBLIOGRAPHY

Balkan British Social Surveys. (1998). Poverty Assessment in Bulgaria, 1997, Focus GroupResearch.

. (1996). Main Findings: A Background Paperfor the Poverty Assessment.

_ Club Economica 2000 and UNDP. (1997). Problems Related to Heating in Winter,September-October 1997.

Beleva, Iskra, Jackman Richard, and Nenova-Amar, Mariela. (1995). Bulgaria, in SimonCommander and Fabrizio Coricelli (eds.), Unemployment, Restructuring, and the Labor Marketin Eastern Europe and Russia,

Blanchard, Oliver, Commander, Simon and Coricelli,Fabrizio (1995). Unemployment andRestructring in Eastern Europe, in Simon Commander and Fabrizio Coricelli (eds.),Unemployment, Restructuring, and the Labor Market in Eastern Europe and Russia,Washington D.C.: Economic Development Institute, World Bank.

Boeri, Tito. (1998). Labor Market Flows in the Midst of Structural Change in SimonCommander (ed.), Enterprise Restructuring and Unemployment in Models of Transition.Washington, D.C.: World Bank.

Bogetic, Zeljko. (1996). Political, Macroeconomic, Fiscal and Social Developments. A.Background Paper for the Poverty Assessment, Draft.

Datt, Gaurav and Ravallion, Martin (1992). Growth and Redistribution Components of Changesin Poverty Measures. A Decomposition with Applications to Brazil and India in the 1980s.Journal of Development Economics, 38, 275-295.

Deaton, Angus. (1994). The Analysis of Household Surveys. Microeconometric Analysis forDevelopment Policy. Draft, April 1994.

Demery, Lionel and Mehra, Kalpana. (1996). Incidence of Social Spending in Bulgaria.Background paper prepared for the Bulgaria Poverty Assessment.

Glewwe, Paul and Jacoby, Hanan. (1998). Recommendations for collecting panel data as a partof LSMS Surveys. Mimeo. Development Research Group. Washington D.C: World Bank.

Jackman, Andrew. (1994). Economic Policy and Employment in the Transition Economies ofCentral and Eastern Europe: What have we Learned?, International Labour Review, 133(3),327-346.

Jackman, Andrew and Rutkowski, Michal. (1994). Labor Markets: Wages and Employment inNicholas Barr (ed.), Labor Markets and Social Policy in Central and Eastern Europe: TheTransition and Beyond. Oxford: Oxford University Press.

International Labor Office and United Nations Development Programme. (1998). Republic ofBulgaria. Poverty in Transition. Geneva: International Labour Office.

Ilieva, Stella and Roussenova, Lena. (1998). Macroeconomic Developments in Bulgaria, 1995-97. Background paper prepared for the Bulgaria Poverty Assessment.

Kolev, Alexandre. (1996). Poverty Analysis in Russia: What can we learn from RLMS, Round6?

Lanjouw, Peter, Milanovic, Branko and Paternostro, Stefano (1998). Poverty in TransitionEconomies: A Case of Children Pitted Against the Elderly? Draft. Washington D.C.: TheWorld Bank.

Marx, Ive and Verbist, Gerre. (1997). Low-paid work, the household income package andpoverty. A cross-country analysis. Paper presented at the European Low-Wage EmploymentResearch Network conference on the Analysis of Low-wage Employment, London, December12-13, 1997.

Milanovic, Branko. (1988). Explaining the Increase in Inequality during the Transition. PolicyResearch Working Paper 1935. Development Research Group. Washington D.C.: The WorldBank.

Murthi, Mamta (1998). Evidence on levels and trends in poverty in Bulgaria. Backgroundpaper prepared for the Bulgaria Poverty Assessment.

Noncheva, Theodora. (1997). Education in Transition: Bulgaria 1997. Mimeo. Florence:UNICEF International Child Development Centre.

Pradhan, Menno and Zant, Wouter. (1998). Incidence of Public Education and HealthcareExpenditures in Bulgaria. Background paper prepared for the Bulgaria Poverty Assessment.

Ravallion, Martin. (1994). Poverty Comparisons. Switzerland: Harwood.

Ringold, Dena. (1998). Trends in Health and Education Spending in Bulgaria during theTransition. Background paper prepared for the World Bank Poverty Assessment.

Rutkowski, Jan. (1998a). Labor Market and Poverty in Bulgaria.An Update for 1996-97.Background paper prepared for the Bulgaria Poverty Assessment.

- (1998b). Labor Market Developments and Poverty. The Case of Macedonia. Backgroundpaper prepared for the Macedonia Poverty Assessment Study of the World Bank.

_ (1996a). Labor Market and Poverty in Bulgaria.An Update for 1996-97. Background paperprepared for the Bulgaria Poverty Assessment.

_ (1996b). Changes in the Wage Structure during Economic Transition in Central and EasternEurope. World Bank Technical Paper No. 340. Washington D.C.: World Bank.

Skoufias, Emmanuel. (1998). A Re-Examination of Social Transfers and the Social Safety Net inBulgaria using the 1997 BIHS. Background paper prepared for the Bulgaria PovertyAssessment.

_ (1996a). Seasonality in Household Consumption in Bulgaria. Background paper prepared forthe Bulgaria Poverty Assessment.

- (1996b). An Examination of Social Transfers and the Social Safety Net in Bulgaria using the1995 BIHS. Background paper prepared for the Bulgaria Poverty Assessment.

Tomova, Ilona. (1998). The Ethnic Dimensions of Poverty in Bulgaria.Background paper prepared for the Bulgaria Poverty Assessment.

UNDP (1997). Human Development Report

UNICEF. (1998). Education for All?. The MONEE project Regional Monitoring Report, No.5. Florence: UNICEF International Child Development Centre.

USAID, Open Society Foundation and UNDP. 1998. Early Warning Report.

World Bank. (1998a). Bulgaria : Monthly Economic Report, Number 3. Sofia: World BankResident Mission.

World Bank (1998b). Kazakhstan. Living Standards During the Transition. Report No. 17520-KZ. Washington D.C.: World Bank.

World Bank (1998c). FYR Macedonia: Poverty Assessment. Report No.. Washington D.C.:World Bank.

World Bank. (1997). Romania: Poverty and Social Policy, Report No. 16462-RO. WashingtonDC: World Bank.

World Bank. (1995). The Kyrgyz Republic: Poverty Assessment and Strategy. ReportNo. 14380-KG. Washington DC: World Bank.