STUDIES POVERTY, ETHNICITY, AND GENDER IN TRANSITIONAL SOCIETIES INTRODUCTION THEORETICAL ISSUES

Similar documents
III. World Population Growth

BILINGUALISM AND LANGUAGE ATTITUDES IN NORTHERN SAMI SPEECH COMMUNITIES IN FINLAND PhD thesis Summary

Housing and Communities Inequalities in Northern Ireland

Economic inequality and educational attainment across a generation

Executive summary. Global Wage Report 2014 / 15 Wages and income inequality

World Population Growth

Comparative Social Policy

UNINSURED ADULTS IN MAINE, 2013 AND 2014: RATE STAYS STEADY AND BARRIERS TO HEALTH CARE CONTINUE

The Social Dimensions of the Crisis: The Evidence and its Implications

Women, Wages and Work A report prepared by the UNC Charlotte Urban Institute for the Women s Summit April 11, 2011

Electoral Registration Analysis

Pan-European opinion poll on occupational safety and health

Summary. Accessibility and utilisation of health services in Ghana 245

Chapter 1. What is Poverty and Why Measure it?

THE DEMOGRAPHY OF POPULATION AGEING

Equality between women and men

Effects of CEO turnover on company performance

HOUSINGSPOTLIGHT FEDERALLY ASSISTED HOUSING? Characteristics of Households Assisted by HUD programs. Our findings affirm that

Poverty among ethnic groups

Striking it Richer: The Evolution of Top Incomes in the United States (Update using 2006 preliminary estimates)

Changes in the Demographic Characteristics of Texas High School Graduates. Key Findings

WINNERS OR LOSERS OF REFORM? GENDER AND UNEMPLOYMENT IN POLAND AND HUNGARY 1

Income and wealth inequality

What Is Poverty and Why Measure It?

Public Housing and Public Schools: How Do Students Living in NYC Public Housing Fare in School?

Long-term impact of childhood bereavement

2. Incidence, prevalence and duration of breastfeeding

Wealth and Demographics: Demographics by Wealth and Wealth by Demographics using the Survey of Consumer Finances. *** DRAFT March 11, 2013 ***

Levy Economics Institute of Bard College. Policy Note A DECADE OF FLAT WAGES?

Russia s Mortality Crisis WILL WE EVER LEARN?

It is important to understand child poverty as multidimensional. Income poverty in South Africa. Annie Leatt (Children s Institute)

Adult Education Survey 2006, European comparison

Statistical Data on Women Entrepreneurs in Europe

Unemployment: Causes and its Economics Outcomes during Recent Years in Afghanistan

The Development of Self-Employment in Russia

INTER-AMERICAN DEVELOPMENT BANK REGIONAL POLICY DIALOGUE

California Youth Crime Declines: The Untold Story

Conference on Population and Development, Cairo, 5-13 September 1994 (United Nations publication, Sales No. E.95.XIII.7).

Challenges of the World Population in the 21st Century.

2. THE ECONOMIC BENEFITS OF EDUCATION

CHAPTER ONE: DEMOGRAPHIC ELEMENT

architecture and race A study of black and minority ethnic students in the profession Research outcomes: 6

STATISTICAL ANALYSIS OF UBC FACULTY SALARIES: INVESTIGATION OF

Youth bulges and youth unemployment Youth bulges are not a major factor explaining current levels of youth unemployment

Ageing OECD Societies

Gandi (PhD) Cabinet Member, Minister of Social Welfare and Labor of Mongolia

Labour Market, Social Policy, Social Security System and Migration Policy - Current State and Problems Which Bulgaria Faces

Chapter 2. Education and Human Resource Development for Science and Technology

Economic Growth, Poverty and Inequality in South Africa: The First Decade of Democracy Haroon Bhorat & Carlene van der Westhuizen 1

BY Maeve Duggan NUMBERS, FACTS AND TRENDS SHAPING THE WORLD FOR RELEASE AUGUST 19, 2015 FOR FURTHER INFORMATION ON THIS REPORT:

Making Jobs Good. John Schmitt and Janelle Jones. April 2013

CONTENTS: bul BULGARIAN LABOUR MIGRATION, DESK RESEARCH, 2015

Comparison of Research Designs Template

Working and Still Poor. Sekia Dalton. Zane State College

Fédération des Experts Comptables Européens ACCRUAL ACCOUNTING IN THE PUBLIC SECTOR. January A Paper from the FEE Public Sector Committee

Black and Minority Ethnic Groups Author/Key Contact: Dr Lucy Jessop, Consultant in Public Health, Buckinghamshire County Council

Gender Sensitive Data Gathering Methods

SAMPLING INDIVIDUALS WITHIN HOUSEHOLDS IN TELEPHONE SURVEYS

Tool Name: Community Profile

In recent years, fiscal policy in China has been prudent. Fiscal deficits

Undergraduate Degree Completion by Age 25 to 29 for Those Who Enter College 1947 to 2002

The trend of Vietnamese household size in recent years

The Socio-Economic Impact of Urbanization

Political Parties and the Party System

Employment policy in Hungary with special regards to the problems of. unemployment

work Women looking for Discussions of the disadvantage faced by women

An update to the World Bank s estimates of consumption poverty in the developing world *

The U.S. labor force the number of

Women and Men in the Recovery: Where the Jobs Are Women s Recovery Strengthens in Year Four

Brazil. Country coverage and the methodology of the Statistical Annex of the 2015 HDR

Planning for the Schools of Tomorrow

A Static Version of The Macroeconomics of Child Labor Regulation

THE IMPACT OF MACROECONOMIC FACTORS ON NON-PERFORMING LOANS IN THE REPUBLIC OF MOLDOVA

Briefing note for countries on the 2015 Human Development Report. Palestine, State of

Survey of DC pension scheme members

WARSAW SCHOOL OF ECONOMICS

Nepal. Country coverage and the methodology of the Statistical Annex of the 2015 HDR

The ageing of the ethnic minority populations of England and Wales: findings from the 2011 census

State of Working Britain

Briefing note for countries on the 2015 Human Development Report. Philippines

Catching Up to Reality: Building the Case for a New Social Model

Financial capability and saving: Evidence from the British Household Panel Survey

Madagascar. Country coverage and the methodology of the Statistical Annex of the 2015 HDR

NCDs POLICY BRIEF - INDIA

Roma in Central East Europe: Ethnographic and historical overview of a people without a state. Syllabus Spring 2012

Forty years ago when the discovery of North Slope

Digital Heart of Europe: low pressure or hypertension? State of the Digital Economy in Central and Eastern Europe

MARK SCHEME for the October/November 2012 series 2251 SOCIOLOGY. 2251/13 Paper 1, maximum raw mark 90

A national poverty line for South Africa

RECOMMENDED CITATION: Pew Research Center, January, 2016, Republican Primary Voters: More Conservative than GOP General Election Voters

DIFFERENCES IN RETENTION AND PROMOTION FOR MINORITY AND FEMALE LINE OFFICERS

Malawi. Country coverage and the methodology of the Statistical Annex of the 2015 HDR

Global Food Security Programme A survey of public attitudes

Sierra Leone. Country coverage and the methodology of the Statistical Annex of the 2015 HDR

Women and Men in the Recovery: Where the Jobs Are Women Recover Jobs Lost in Recession in Year Five

Briefing on ethnicity and educational attainment, June 2012

CZECH REPUBLIC. Similarities of the good practice with the experience of the Czech Republic

Education and Employment Opportunities for the Roma

Social and Economic Factors Influencing Vulnerability to Floods in Southen Poland

Briefing note for countries on the 2015 Human Development Report. Niger

Transcription:

Review of Sociology Vol. 7 (2001) 2, 5 10 STUDIES POVERTY, ETHNICITY, AND GENDER IN TRANSITIONAL SOCIETIES INTRODUCTION Iván SZELÉNYI THEORETICAL ISSUES Both the extent and the character of poverty in Eastern Europe appear to have changed with the transition from socialism to a market economy. There has been not only a substantial increase in the proportion of the population living in extreme poverty, but according to some commentators, the actual character of poverty has changed as well. The conventional wisdom among social scientists is that during socialism poverty was mainly a life-cycle phenomenon. Thus, families with large numbers of young children, the temporarily or permanently disabled, and the elderly tended to be poor. Today, however, social class, ethnicity, and/or gender appear to play a more significant role than in the past in terms of predicting or explaining poverty. In addition, it is often asserted that with the emergence of the market economy some became locked into permanent poverty, and the spatial segregation of the extremely poor became more pronounced. Thus, post-communism may have produced new poverty. Stated differently, post-communism may be responsible for the formation of an underclass, especially in those instances when poverty is becoming racialized. Ladányi s key hypotheses are that many Roma in transitional societies are locked into extreme, long-term poverty, that Roma increasingly live in spatially segregated areas, and that among the Roma, the intergenerational transmission of poverty is high. Thus, a Roma underclass may be in formation. Arguably poverty is not only being racialized during the post-communist transition, but also feminized. The feminization of poverty implies that femaleheaded households are more likely to be in poverty compared to other households, and/or that within poor households, women disproportionately bear the burden of poverty compared to men. Finally, it appears that there are substantial cross-country differences in the nature, degree, and dynamics of poverty among the post-communist societies of Europe. While some countries more closely followed the neo-liberal reform agenda and entered onto an evolutionary trajectory towards liberal market capitalism, others moved more cautiously away from socialism and followed an involutionary path towards a neo-patrimonial version of capitalism. Neo-classical economists predict 1417-8648 2001 Akadémiai Kiadó, Budapest

6 IVÁN SZELÉNYI that liberal reforms will eventually generate trickle down effects. In other words, neo-liberal reform will generate economic growth and, though inequalities may increase, absolute poverty will decrease. Accordingly, in those countries that do not follow the path of neo-liberal reforms, we would expect to see slow, stunted growth and the reproduction of poverty. The papers included in this special issue of the Review of Sociology represent the first attempts to confront the data gathered in 1999 2000 with these theoretical issues. The authors explore whether new poverty emerged during post-communism and whether we can speak of the formation of an underclass during the last decade of the 20th century in Central and Eastern Europe. Some of the papers explore how Roma ethnicity is constructed and the extent to which poverty and ethnicity interact in the construction of Roma identity. Other papers address issues related to the feminization of poverty. Still others focus on cross-country variations in the degree and nature of poverty. DATA AND RESEARCH DESIGN We attempt to answer the preceding questions with statistical data generated by surveys conducted in the six post-communist countries of Bulgaria, Hungary, Poland, Romania, Russia, and Slovakia during the fall of 1999 and the winter spring of 2000. In addition to survey data, we rely on ethnographic studies conducted in all of these countries during the same time period. The Ford Foundation supported both the survey and fieldwork components of the research project. Iván Szelényi was the principal investigator; co-principal investigators were Rebecca Emigh, Éva Fodor, and János Ladányi. Our research team included a group of senior scholars and advanced Ph.D. students in each country. The surveys were based on random samples of the general population in each country. In Russia, we selected 2,500 households on a national random sample west of the Urals; in the other countries the sample size was 1,000. In Romania and Slovakia, the sample was selected using the random walk method, thus the primary sampling unit was the household. Individual respondents were selected from the household roster using a Kish table. In all other countries, various lists of individuals constituted the sampling frame. Overall, the samples are sufficiently representative, with the exception of Slovakia, where less educated, lower income groups, and Gypsies are under-represented. Our data also include over-samples of sub-populations, including the poor and the Roma. While both groups are of particular theoretical interest, both comprise too small a proportion of the overall population to conduct statistically reliable analyses using a general population sample. During the past few years, various survey research agencies have asked interviewers to identify the Roma. For example, Szonda Ipsos and TÁRKI in Hungary have used this technique a number of times. The paper in this issue by Ladányi and Szelényi elaborates the pros and cons of relying on an interviewer-based classification of Roma and reviews alternative methods. For instance, some scholars

POVERTY, ETHNICITY AND GENDER IN TRANSITIONAL SOCIETIES INTRODUCTION 7 and census designers have relied on self-identification and/or expert identification. In our analyses, we decided to use a combination of all three methods. Thus, we first relied on interviewer identification to generate an over-sample. Next, in the actual survey instrument, we asked respondents whether or not they self-identify as Roma. Finally, after the survey interview was completed, we asked experts in those locations where Gypsies were reported to live to identify Gypsies among our respondents. The comparative analysis of these three classification systems is our subject matter. However, because we have good reason to believe that those identified as Roma by interviewers also tend to self-identify and to be expert-identified, we conclude that interviewer-identification is an acceptable method for over-sampling. To create an ethnic over-sample in the three countries (Bulgaria, Hungary, and Romania) where there are sizeable populations of Roma, we worked closely with market research firms that carry out omnibus surveys on a regular basis. Over a period of a year, together with the market research firms, we screened between 10,000 19,000 households. To the omnibus questionnaire we added a short questionnaire that asked the interviewer to tell us whether any given household or any member within the household was Roma. We then asked the interviewer his/her degree of certainty in that assessment. (We also asked the interviewer to explain on what basis he/she classified any given respondent or household as Roma. The analysis of such data will be the subject of another book). Using this method, we accumulated an extensive list of Roma addresses, which comprise our Roma oversample. Relying on similar methods, we also generated an over-sample of the poor in four countries (Bulgaria, Hungary, Poland, and Romania). We did not create a poor oversample in Russia because our pretests indicated that the general population sample would include enough poor households to conduct statistically reliable analyses. In Slovakia due to the inability or unwillingness of the survey firm to sample the bottom of the social hierarchy we had to abandon our attempt to create an oversample of those in extreme poverty. As with the ethnicity over-sample, the poverty over-sample was determined using screening questions attached to the omnibus surveys of the market research firms. Interviewers were asked a series of questions designed to identify extremely poor households (e.g., Are there signs of undernourishment in the household?, Is the house dangerous and/or unhealthy?, etc.). If the interviewer answered positively to any question, the household was selected into the poverty over-sample. In the actual survey, respondents were asked detailed questions regarding living standards in order to measure the reliability of interviewer assessments. The poor over-sample ensures our ability to statistically compare the Roma and the non-roma poor. The Roma and poor over-samples are random samples, and we know the probability of being selected into each sub-sample. Furthermore, though we analyze interview-identified poor and Roma respondents with great interest, we believe poverty and ethnicity are social constructions. Therefore, we do not accept interviewer assessments as the true measure of who is poor and who is Roma (see the paper by Ladányi and Szelényi in this issue for a more detailed discussion of this issue). In our analyses of Roma ethnicity, we analyze both interviewer-identified

8 IVÁN SZELÉNYI Roma, as well as self-identified Roma. We rely on multiple indicators from the survey questionnaire to guide our analyses of the poverty over-sample in order to determine households in extreme poverty. Our survey data are complemented by ethnographic case studies. In each country we selected extremely poor communities. These communities were primarily rural villages, with the exception of one urban center. Most communities were Roma ghettos while others particularly those in Poland, Russia, and Georgia were simply poverty stricken or were predominated by a poor ethnic group other than Roma. Junior members of the research team received yearlong fellowships to conduct field projects in these communities. Ethnographic data collection methods were coordinated at a number of project meetings. Reports of these case studies can be found at: www.yale.edu/ccr/. (From the web site, select the link for Poverty Project, followed by the link for Final Reports. There you will find the complete set of ethnographic case studies.) The selection of the six countries was driven by our research questions. The countries differ both in terms of ethnic composition and in terms of which ideal-type of post-communist capitalism best describes their economic system. Overall, there are two sets of questions for which our research design can provide answers. First, we test hypotheses concerning underclass formation and ethnicity. More specifically, we test whether the presence of a sizeable ethnic minority namely, the Roma is a necessary and sufficient condition for the racialization of poverty and/or the formation of an underclass. To answer such questions, we compare Poland and Russia on one hand, and Bulgaria, Hungary, Romania, and Slovakia on the other hand. Second, we ask whether the divergent paths of post-communist capitalism discussed above are consequential for poverty outcomes. To answer this question, we compare the neo-liberal regimes of Hungary, Poland, and Slovakia to the neopatrimonial systems in Bulgaria, Romania, and Russia. Upon completing our survey and ethnographic data collection, we received funding from The Ford Foundation to bring teams of scholars from post-communist countries and the U.S. to Yale University to collectively analyze our results. From September 2000 through December 2001, each of three research teams composed of six eight scholars per team met consecutively at Yale University in the Center for Comparative Research. During the fall of 2000, we conducted preliminary cross-national comparisons of the poverty data; during the spring of 2001, we worked on the issues of ethnicity and poverty; and finally, during the fall of 2001, we focused on the feminization of poverty. INITIAL RESULTS The papers included in this issue offer the first results of our analyses. We intend to publish several monographs based on this study; therefore, this issue contains merely a glimpse of what is to come. Two articles, one by Gail Kligman and the other by Ladányi Szelényi, focus on questions regarding the social construction of Roma ethnicity. Relying on data from ethnographic case studies, Kligman attempts to answer the question, who is

POVERTY, ETHNICITY AND GENDER IN TRANSITIONAL SOCIETIES INTRODUCTION 9 Roma?. Ladányi and Szelényi offer a similar analysis using quantitative data. In particular, they analyze discrepancies between interviewer classifications and respondents self-identifications in three countries. This issue also contains two papers that focus on gender issues. Éva Fodor tests the feminization of poverty hypothesis and finds little evidence of feminized poverty in neo-liberal regimes, but strong evidence of feminized poverty in neopatrimonial systems. Christy Glass and Janette Kawachi focus on the gender gap in unemployment: are women more or less likely to be unemployed than men? They limit their analysis to a comparison of Hungary and Poland, and find strong evidence for discrimination against women in Poland, but not in Hungary. Finally, Henryk Domanski and Petar-Emil Mitev offer systematic comparisons of the extent and nature of poverty of all countries. Domanski claims that while there is no evidence of underclass formation in neo-liberal regimes, there is some evidence that such a process is underway in neo-patrimonial systems. Mitev s findings are consistent with those of Domanski; he finds deeper and more extensive poverty in neo-patrimonial systems than in neo-liberal regimes. In my view, the major findings of our investigation thus far are the following. First, while none of the papers in this issue report findings based on answers to retrospective questions in our survey, we attempted to reconstruct respondents memories of socialism. In particular, we try to assess respondents experience with poverty during the socialist era. We asked respondents whether they experienced poverty at three time points: when they were14 years old, in 1988, and/or in 2000. To the best of our knowledge, ours is the only cross-national study that systematically examines answers to retrospective questions about poverty during socialism. Comparisons of these answers are revealing. In all countries, respondents remember being better off in 1988 than in 2000. Furthermore, respondents of all age cohorts are less likely to report experiencing poverty in 1988 than they are to report experiencing poverty during earlier periods when they were 14. Respondents remember greater differences in poverty rates among countries at age 14 than in 1988. We interpret this finding to mean that people believe cross-country differences declined during socialism. Through cross-country comparisons, we also explored changes during the 1990s and, in particular, we contrasted how people experienced the transition in 1993 compared to 2000. Our findings show that in all countries in 1993, people experienced a similar deterioration of their living standards compared to 1988. By 2000, however, the trend is reversed in countries where more rigorous liberal reforms were implemented (Hungary and Poland) and in countries with a much slower progression towards the liberal model of capitalism (Bulgaria, Romania and Russia). In 2000 in neo-liberal regimes, the proportion of respondents who report deterioration in material conditions compared to 1988 is smaller than the proportion of respondents who report deterioration in 1993. The opposite is true in neo-patrimonial regimes, where the deterioration of living standards continues from 1993 to 2000. This crossnational gap, which was apparently narrowed during socialism, seems to have reopened during the second half of the 1990s. We also analyzed poverty rates by ethnicity in Bulgaria, Hungary, and Romania,

10 IVÁN SZELÉNYI by comparing poverty rates of Roma and non-roma. Cross-country differences are nearly as large as inter-ethnic differences. For example, the Roma in Hungary are only slightly poorer than non-roma Bulgarians in Bulgaria. In all countries, however, the very poor are significantly over-represented among the Roma, and most Roma tend to be extremely poor. If one looks at the ethnic composition of those in extreme poverty, the picture is more complex, however. In all three countries, while most Roma are extremely poor, most of the extremely poor are not Roma. Furthermore, we find a significant minority of Roma who are doing quite well. The evidence thus far suggests that those Roma who successfully maintained their traditions may have been better able to escape impoverishment compared to those who were assimilated into the bottom of society. Finally, we tested whether there are any indications that poverty is being feminized in market transition: are women more likely to be poor than men? To answer this question, we focused on female-headed households as our unit of analysis. Indeed, female-headed household are more likely to be poor than are maleheaded households in neo-patrimonial systems. However, we found weak evidence overall of a gender gap in poverty in neo-liberal regimes. Neo-liberal regimes seem to have a more developed social safety net than neo-patrimonial regimes. For example, neo-liberal regimes have been more able to maintain the pension system compared to neo-patrimonial regimes. Thus, it appears that weaknesses in the welfare state may be the major mechanism that leads to the feminization of poverty.