Corresponding author: Ben Slay (
This paper focuses on how questions of inequalities in middle-income countries in Europe and Central Asia are dealt with in three recent studies: the EBRD’s “Transition Report 2016–17”; the World Bank’s 2018 study “Toward a new social contract: Taking on distributional tensions in Europe and Central Asia”; and UNDP’s “Regional human development report 2016. Progress at risk: Inequalities and human development in Eastern Europe, Turkey, and Central Asia.” While the three studies differ in terms of objectives, conceptual frameworks, country coverage, data and indicators, and policy recommendations, they also share important commonalities — particularly in terms of creating “regional” inequality narratives for transition economies, reconciling official data with common perceptions of inequalities in the region; improving data quality, quantity and availability, and changes in tax and social policies.
Concerns about inequalities are growing globally, as observers in many developed and developing economies increasingly believe they undermine prospects for sustainable development through a multitude of channels. In developed economies, these concerns are apparent
These narratives and experiences are not irrelevant for the transition economies of Europe and Central Asia. However, they miss some important elements of the challenges posed by inequalities for these countries. For one thing, despite their “developing”/middle-income country status, during socialism (prior to the 1990s) these economies reported relatively low socio-economic inequalities. While official data indicate that income inequalities rose during the “transition recessions” of the 1990s, these increases were interpreted by at least some observers as desirable (or at least inevitable) “corrections” of/responses to often violent pre-transition social leveling.
However, a closer look at official income inequality data may suggest less optimistic conclusions. For one thing, the official data may significantly understate actual levels of income inequalities in the region: household budget survey data are well known to suffer from errors of exclusion regarding the incomes of the very rich and the very poor. Moreover, the absence of credible, internationally comparable data on personal wealth often precludes evidence-based discussions about inequalities in the distribution of wealth — which, for a region whose political economy has often been described as dominated by “oligarchs” (
The three studies considered here — the EBRD’s “Transition Report 2016–17” (
In its focus on linkages between inequalities and the SDGs, the UNDP report highlights the opportunities (and limitations) of using the SDGs (particularly when combined with official household survey data) to support analyses and narratives inequality concerning inequalities in the region. This reflects the UNDP report’s objective of operationalizing the “leave no one behind” principle that underpins the global Agenda 2030 for sustainable development
Such common measures of inequalities as Gini coefficients and Palma ratios are not included in the global SDG indicator set (so that many SDG10 indicators cannot be monitored on basis of publicly available national statistical data);
Official income distribution data in many of these countries do not show particularly high or rising levels of inequality;
Different national and international data sets for income distribution in these countries often show different trends that complicate international comparisons and confuse narratives;
There are virtually no official data on the distribution of wealth in these countries; and
Subjective (unofficial) data indicate that survey respondents in the region often perceive of inequalities to be significant, growing, and problematic.
In line with its narratives linking inclusion (and sustainability) to economic transition, the EBRD report combines a general overview of inequality issues in transition economies with an analysis of subjective inequality data collected in the EBRD’s life in transition (LITS) survey data set. These data, which are based on information collected from some thousands of survey respondents across the region,
By contrast, the EBRD and World Bank reports draw extensively on international data sets (e.g., POVCALNET) that present internationally standardized/harmonized measures. While these metrics may aspire to greater methodological quality and consistency, they are less likely to meet with national approbation. Moreover (as mentioned above), the EBRD report is strengthened by analysis drawn from the LITS data, which provide a critical contribution to understanding popular perceptions of inequalities that seem to inform popular and policy discourses in the region.
In terms of social policy responses, the World Bank report takes the closest look at universal basic income schemes, but concludes that such policies are less important than investments in education and labor market flexibility. While the EBRD report likewise emphasizes investments in education, it also calls for more extensive use of conditional cash transfers and better targeting of social benefits in general. The UNDP report by contrast focuses on integrated, whole-of-government approaches to social insurance, assistance, services, education, employment, and migration. This report’s proposed expansion of care services to address gender-based labor market (and related forms of social exclusion) is a reflection of this integrated approach.
Differences aside, the reports share a number of analytical and policy commonalities and recommendations, which generally fall into two areas.
Better data could be combined with more appropriate use of inequality indicators — particularly as concerns the shares of national income devoted to labor and capital. For example, because income from capital/property provides such a small share of total (reported) household income in the region, increases in the share of wages and salaries in household incomes can increase inequalities — particularly if this growth occurs towards the top of the wage scale. And because large shares of capital in the region remain under (or have been returned to) state ownership, increases in the share of national income distributed to capital can increase state revenues and help to fund social protection systems — thereby reducing inequality. Expanded use of multi-dimensional inequality indicators like UNDP’s inequality-adjusted human development index, or its gender and development and gender inequality indexes, could also be helpful. (This would also better support monitoring of SDGs 5 and 10.)
Conspicuously lacking in these reports are the sorts of flat-tax narratives that were fixtures of tax reform debates in the region during the first decade of the new millennium (at least up until the onset of the global financial crisis in 2008–2009; see, for example,
Other policy reforms to address inequalities, and which find support in these three reports, include:
Increased investment in national capacities for the collection and analysis of official data that are disaggregated by gender and other vulnerability criteria;
Increased investment in access to education;
Efforts to strengthen the implementation/enforcement of anti-discrimination legislation (e.g., to provide for “equal pay for equal work,” or to reduce discrimination against ethnic minorities); and
The more aggressive implementation of market and governance reforms to improve commercial environments for small and medium-sized businesses (particularly in depressed areas).
This paper does not constitute an official statement of the views of UNDP, the United Nations, or its Member States.
For example, the World Bank’s study of the first decade of transition in the region argued that “positive developments largely explain the rise in inequality [such as] rising returns to education, decompressing wages, and emerging returns to risktaking and entrepreneurship. These forces are welcome despite the increase in inequality, because they signal that the market is now rewarding skills and effort, as in more mature market economies” (World Bank, 2002, p. 14).
This can be seen, for example, in the data from the World Bank’s ASPIRE database, which show relatively high (compared to other middle-income countries) shares of GDP devoted to social protection, as well as the shares of poorer households receiving pensions and social transfers.
UNDP’s gender and development and gender inequality indexes show that middle-income countries in Europe and Central Asia generally report less gender inequality than do middle-income countries in other regions (see http://hdr.undp.org/en/data) — when measured, for example, in terms of labor force participation and education attainment).
This can be seen in the numbers of people working (or shares of total employment) in subsistence agriculture (i.e., sole proprietorships working on small holdings) or in sectors where average wages are close to the poverty line. For more on Roma labor market and social exclusion, see Robayo and Millan (2019).
In addition to the data to this effect presented in the UNDP (2016) and EBRD (2017) reports, other sources with the same results include the World Values Survey and Transparency International corruption perceptions index.
World Bank data show women’s labor force participation rates falling in the last decade for Kyrgyzstan and Tajikistan. Gender parity rates (showing the ratio of women to men) in tertiary education enrollments during the past decade dropped for Georgia, Ukraine, and Uzbekistan.
See https://sustainabledevelopment.un.org/sdgs
See https://sustainabledevelopment.un.org/sdgs
The third phase of the EBRD (2016) survey is based on data collected from 51,000 respondents.
The work by Dávalos et al. (2016) also makes an important contribution in this direction.
In order to compensate for possible reductions in government budget revenues, the UNDP report calls for increases in carbon taxes or other levies to internalize negative environmental externalities. Because such taxes are generally regarded as regressive, this proposal can be seen reducing tax systems’ overall de facto progressivity.