metadata: authors: 0: author: Fuchs Tarlovsky,Alan
1: author: Tiwari,Sailesh
2: author: Shidiq,Akhmad Rizal
count: Caucasus,Armenia,Azerbaijan,Georgia
docna: 0: docna: Inequality of opportunity in South Caucasus
docty: Policy Research Working Paper
abstracts: cdata!: This paper discusses equality of
            opportunity in Armenia, Azerbaijan, and Georgia, with an
            emphasis on access to labor market opportunities. It
            develops an inequality of opportunity index on access to
            good jobs and decomposes the contributing factors in the
            prevailing inequality. Then, it discusses the extent to
            which inequality in accessing human capital inputs among
            individuals during the early formative years may affect
            access to good jobs. The main takeaways are as follows.
            First, connections play an important role in obtaining
            access to good jobs in the South Caucasus, highlighting the
            unfairness in processes in the sub-region's labor
            markets. Second, access to good jobs—defined as work for 20
            hours or more a week and work under contract or with
            tenure—is low in the South Caucasus in comparison with other
            parts of Eastern Europe and Central Asia. Third, even among
            people who have access to these jobs, the share of the total
            inequality of opportunity that may be characterized as
            unfair is relatively high. Armenia and Azerbaijan stand out
            for the significant share of inequality in access to good
            jobs associated with gender differences. Fourth, the
            analysis on access to education and basic human capital
            inputs in the earlier, formative stages of life shows that
            learning performance in the South Caucasus tends to be poor
            and unequal across the life circumstances of children.
            Nonetheless, the coverage rates of basic human capital
            inputs are generally high; the relatively narrow
            inequalities arise mostly from spatial disparities. These
            results indicate that addressing the deep structural
            inequalities shaping the landscape of opportunity in the
            South Caucasus must be a key consideration in any strategy
            to share prosperity sustainably.
geo_reg_key: 517208,517191,82689,517198
repnme: repnme: Inequality of opportunity in South Caucasus
display_title: Inequality of opportunity in South Caucasus
listing_relative_url: /research/2018/05/29871084/inequality-opportunity-south-caucasus
publishtoextweb_dt: 2018-05-07T00:00:00Z
no_of_pages: 49
author_keys: 0: author_key: 1107738
1: author_key: 687885
2: author_key: 796428
model_extractions: WPS8432 Policy Research Working Paper 8432 Inequality of Opportunity in South Caucasus _Alan Fuchs Sailesh Tiwari Akhmad Rizal Shidiq_ Poverty and Equity Global Practice May 2018
Policy Research Working Paper 8432

# **Abstract**

This paper discusses equality of opportunity in Armenia, Azerbaijan, and Georgia, with an emphasis on access to labor market opportunities. It develops an inequality of opportunity index on access to good jobs and decomposes the contributing factors in the prevailing inequality. Then, it discusses the extent to which inequality in accessing human capital inputs among individuals during the early formative years may affect access to good jobs. The main takeaways are as follows. First, connections play an important role in obtaining access to good jobs in the South Caucasus, highlighting the unfairness in processes in the sub-region’s labor markets. Second, access to good jobs—defined as work for 20 hours or more a week and work under contract or with tenure—is low in the South Caucasus in comparison with other parts of Eastern Europe and Central Asia. Third, even among people who have access to these jobs, the share of the total inequality of opportunity that may be characterized as unfair is relatively high. Armenia and Azerbaijan stand out for the significant share of inequality in access to good jobs associated with gender differences. Fourth, the analysis on access to education and basic human capital inputs in the earlier, formative stages of life shows that learning performance in the South Caucasus tends to be poor and unequal across the life circumstances of children. Nonetheless, the coverage rates of basic human capital inputs are generally high; the relatively narrow inequalities arise mostly from spatial disparities. These results indicate that addressing the deep structural inequalities shaping the landscape of opportunity in the South Caucasus must be a key consideration in any strategy to share prosperity sustainably.

This paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The authors may be contacted at afuchs@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Inequality of Opportunity in South Caucasus

Alan Fuchs, Sailesh Tiwari and Akhmad Rizal Shidiq<sup>1</sup>

**Keywords:** Equality of Opportunity, Intergenerational Mobility, Education, Employment **JEL Codes:** I240, I280, I310, J620, O15

> 1 Fuchs (afuchs@worldbank.org), Senior Economist in the Poverty and Equity Global Practice, World Bank. Tiwari (stiwari@worldbank.org), Senior Economist at the Poverty and Equity Global Practice, World Bank. Shidiq (a.r.shidiq@hum.leidenuniv.nl), Assistant Professor, Faculty of Humanities, Leiden Institute for Area Studies, Leiden University. The authors are grateful to Genevieve Boyreau, Cesar Cancho, Moritz Meyer and Ana Maria Munoz Boudet for providing comments and support and Gabriel Lara Ibarra and Victor Sulla for providing comments to an earlier version of this document. The work was carried out under the overall guidance of Mercy Miyang Tembon and LuisFelipe Lopez-Calva who provided substantive inputs at several stages of development of this work. The findings, interpretations, and conclusions in this research note are entirely those of the authors. They do not necessarily represent the views of the World Bank Group, its Executive Directors, or the countries they represent.
# 1. Introduction

For the countries of the South Caucasus sub-region, the issue of inequality is particularly important because of their trajectory as economies in transition from a planning system with a strong tendency to redistribution to a market-oriented economy. As in any country in transition, the expectation of economic improvement is high. Reform takes time, and adjustment may lead to adverse short-run distributional effects unknown in the past. In fact, a rise in inequality in outcomes may reflect increasing returns to assets, including human capital, indicating improvement in economic conditions and a functioning market mechanism. Nevertheless, perceptions of inequality in opportunities or outcomes may also become more salient during transition considering that populations in the South Caucasus regard their family life and the lives of their parents before the transition as the crucial benchmark in evaluating current life situations (Tiwari et al. 2018).

Inequality in outcomes such as income or consumption may influence other economic indicators of progress. For example, pressure for political redistribution that distorts the labor market or credit market imperfections that prevent the poor form investing in high return-human capital, can impact rates of investment and economic growth, thus lowering average productivity (Alesina and Rodrik 1994; Piketty 1997). However, the empirical findings are mixed. Barro (2000) finds that initial inequality has adverse effects on growth in developing countries, but not in developed countries. Forbes (2000) uses panel data to control for time-invariant characteristics and eliminate potential sources of omitted-variable bias to find that the relationship between inequality and growth is positive. Banerjee and Duflo (2003) note that it is not possible to interpret any of this evidence as causal because variations in inequality are likely to be correlated with a range of unobservable factors associated with growth.

Nonetheless, inequality in outcomes is probably not a pressing issue in South Caucasus. While countries in Eastern Europe and Central Asia show some degree of heterogeneity in terms of inequality, with Gini coefficients ranging from 0.25 to 0.45, the long-run trend of the Gini in Georgia has shown no discernible sign of deterioration over the last 15 years (figure 1). In Armenia, the Gini coefficient based on consumption has hovered between 0.30 and 0.35, which puts the country at a moderate level of inequality within the region in 2000–15. Armenia also saw a declining Gini in 2000–09. Data of the Commitment to Equity Institute show that, as of November 2017, inequalities of outcomes in incomes in Armenia and Georgia are well below the average among the 30 low- and middle-income countries the institute surveyed.<sup>2</sup> For example, the Gini coefficients of final income, treating contributory pensions as deferred income, in Armenia and Georgia are 0.36 and 0.38, respectively, in comparison with the 0.41 average Gini of the 30 countries.

> 2 See CEQ Standard Indicators (database), Commitment to Equity, Inter-American Dialogue, Washington, DC; Center for Inter-American Policy and Research and Department of Economics, Tulane University, New Orleans, http://www.commitmentoequity.org/data/.

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circumstances over which individuals have no control. Addressing inequality of opportunity— the bad inequality—therefore has universal appeal regardless of any differences in political spectrum. Early empirical findings also show that inequality in opportunity has negative effects on income (Molina, Narayan, and Saavedra-Chanduví 2013).

This paper focuses on inequality of opportunity, particularly in labor markets, based on the idea that the ability of individuals to access labor markets and obtain jobs based on their skills and work experience (human capital), irrespective of their circumstances, is critical to economic mobility and the reduction of inequality. In the context of transition economies, the effect of market reform depended on whether the countries were able to reorganize the labor market into more efficient and fair labor allocation processes. The discussion in this paper is structured around the main concept that fairness in processes is determined by the underlying equality or inequality of opportunity in society. Specifically, the paper examines, first, the extent to which fairness—the role of skills and effort versus connections in obtaining job—is perceived to exist in such processes by people in South Caucasus; second, whether access to good jobs is determined by effort and choice or by circumstances independent of the control of individuals; and, third, the extent to which inequality in the access to basic human capital inputs affects inequality in obtaining good jobs.

The study finds that inequality of opportunity in labor markets is a serious issue among the countries of South Caucasus. The access to good jobs in South Caucasus is not only limited relative to other countries in Eastern Europe and Central Asia, but also circumstances beyond the efforts individuals may undertake—the unfair element—have a substantial impact on inequality in the access to good jobs. The paper also highlights that some parts of the unobserved inequality in labor markets appear to be associated with inequalities in gaining access to education and basic services during the formative stages of life.

# 2. Methodology

The data used in this paper are taken from the 2015–16 round of the Life in Transition Survey (2015 LiTS) carried out by the European Bank for Reconstruction and Development in collaboration with the World Bank. This round of the survey was conducted in 34 countries, mainly in Eastern Europe and Central Asia, but also including Cyprus, Germany, Greece, Italy, and Turkey, and covered around 51,000 households. This paper utilizes the household survey not only because of the rich questions on the socioeconomic background and labor market status of respondents, but also because of the extensive information on attitudinal perspectives and perceptions of the social, political, and economic situation in the countries.

The first part of the analysis is devoted to identifying how people perceive fairness in processes. A simple gauge of fairness in processes is the perceived role of hard work, effort, and skill as a means to achieve one’s goals in life and to gain access to success in life. This concept of fairness is contrasted with the elements of processes or social arrangements that may unfairly help 5
individuals achieve better lives. The paper shows how the population of a country may perceive the balance between fair factors and unfair factors in accounting for the success of individuals.

A proxy for unfairness in processes is the perceived role of connections. Perceived fairness is therefore reflected in the extent to which people believe that hard work and effort are more important than connections in realizing success in life. In practice, connections are defined as, first, political connections, whereby people can use political power to influence decisions. The study involved observing whether people perceive such connections as generally helpful in gaining success in life. Second, another, more general sort of connection, not necessarily supported by political power, is associated with people who hold special functions or positions within a community and who may be asked by community members for help in influencing decision making. In particular, the paper examines the extent to which people believe this type of connections can help secure access to government or private sector jobs. Acemoglu et al. (2016) and Fisman (2001) have documented the role of political connections in providing people with valuable noncompetitive market advantages. While there is a possibility of an endogeneity problem associated with the reinforcing causality between belief in the role of connections and the efficacy of connections in providing access to jobs, this paper does not parametrically estimate the effect of connections on specific economic outcomes or apply a specific identification strategy to deal with the endogeneity and omitted variable bias problems. Instead, it simply offers a descriptive analysis of people’s perceptions of the role of connections in securing jobs to generate preliminary ideas on popular sentiments about fairness in processes in South Caucasus.

The more substantial analysis is in the second part of the paper where the fairness in processes is evaluated by measuring the inequality in opportunity in obtaining good jobs in the labor market. The main analytical tool is the human opportunity index (HOI) framework developed by Barros, Molinas Vega, and Saavedra-Chanduví (2010) and Barros et al. (2009), which has been adjusted so it is more applicable to labor markets (box 1). The HOI for children in the original framework is relabeled here as inequality-adjusted coverage in the labor market because, besides circumstances beyond the control of individuals, the analysis explicitly recognizes the role of effort and choice in obtaining good jobs.

Box 1. The HOI Methodology The HOI has been developed as part of the World Bank initiative to measure the equitable provision of opportunities among children. Since its introduction, the HOI methodology has been used widely in the literature to analyze the inequality of opportunity among children. (See, for example, Dabalen et al. [2015] for applications in Africa and Krishnan et al. [2016] for applications to the Middle East and North Africa.) The key premise of equality of opportunity among children is that basic services providing critical human capital development inputs, such as quality education, good health care, or water and sanitation, should be available to all children, irrespective of their birth circumstances, including gender, urban-rural residence, parental wealth, and so on. Thus, equality of opportunity means that the playing field should be level, and basic opportunities should be independent of initial circumstances. The HOI methodology is one tool to measure the extent to which the reality deviates from this ideal.

6
In general, the HOI for a given opportunity—for example, access to quality education—is a single index that captures both the opportunity’s universality (the share of children who enjoy the opportunity) and any inequality in access (variations according to circumstances in access among children to the opportunity). The penalty factor arises if the inequality in access is calculated based on an index of dissimilarity (D-index), which equals zero if the access to opportunity is independent of the circumstances of respondents. The underlying purpose of constructing the HOI is to generate a scaled measure that rises as opportunity increases but falls as inequality becomes wider in the coverage among groups characterized by differences in circumstances. Once an index score has been obtained, a Shapley decomposition procedure is applied to apportion the inequality across various circumstances.<sup>a</sup> Although causality cannot be ascribed through the Shapley decomposition; quantitative statements may be made, such as that a certain percent of the inequality in opportunity, for example, access to school, is associated with children’s circumstances, such as gender, birth location, and so on.

More formally, the inequality-adjusted coverage rate, �, is defined as follows: where �̅ represents the coverage rates of access to good jobs, and � is the dissimilarity index (D-index), calculated as follows: where � is a type of circumstances-group; �� is the coverage rate of group �; �� is the share of group � in the total labor force; and � is the number of circumstances-groups.

a. The Shapley decomposition in Shorrocks (2013) is a method to overcome the problem that a change in a dissimilarity scalar measure because of the addition of a circumstance depends on the initial set of circumstances that are changed. In this procedure, intuitively, the effect of a circumstance is calculated as the average value of all changes that occur if the circumstance is added to all possible subsets of initial circumstances.

This paper adopts the HOI methodology to measure the inequality of opportunity in obtaining a good job in the labor market and labels it as inequality-adjusted coverage. It adopts this terminology to accommodate two important considerations in interpreting inequality of opportunity measures. First, it is necessary to shed the normative baggage of the notion of opportunity in a labor market. In the original setting of the HOI among children, defining opportunity as children’s access to education is untainted by the effect of the effort and agency of individuals and thus has a universal appeal: every child should have access to quality education. But any labor market outcome is a function of accumulated opportunities, plus what individuals have done with the opportunities through effort and choices. The issue then becomes whether everyone is entitled to employment and jobs in the same manner. Perhaps some people with a certain desired, necessary, and appropriate level of education, skills, and temperament do deserve some set of jobs, but not everyone. For this reason, this paper adopts the HOI measurement tool sans the normative baggage. Second, the analysis maintains a sharp focus on 7
good jobs. Access to any kind of job is not always the most desirable state for everyone. People who are working and who are observed as participating in employment because they have no other choice are distinctly less well off than people who are not working and are thereby observed as not participating in employment precisely because of their high reservation wage or because they are seeking better outside options. To minimize this measurement error, the analysis focuses on good jobs.

However, defining selected types of employment as good jobs is not a straightforward exercise. Purely from the perspective of the development payoff, the definition of a good job varies by context. For example, the World Bank (2012) finds that, in agrarian societies, a job may be more productive if it is in smallholder farming or involves urban employment that is well connected with global markets. In countries with high youth unemployment, it may be a job that is not supported by rents or not allocated based on connections. In aging societies, it may be a job that keeps the skilled active at older ages. From the perspective of the individual, a good job may have desirable monetary and nonmonetary attributes such as good earnings, benefit stability, social prestige, and dignity. But a good job is also associated with positive spillovers in society. The World Bank (2012) addresses several potential mechanisms through which a good job may promote a better society. Thus, jobs that are filled by women may empower women’s position in society by rebalancing intrahousehold resource distribution and enhancing the role of women in decision making, both of which benefit children. Jobs integrated in world markets may also generate knowledge spillovers and help firms realize increasing returns to scale. Jobs that reflect a sense of fairness, especially in fragile and conflict-affected societies, may help maintain social cohesion. Meanwhile, the International Labour Organization (ILO 1999, 3) describes decent work as “opportunities for women and men to obtain decent and productive work in conditions of freedom, equity, security and human dignity.” In a slightly expanded version, the International Labour Organization defines decent work as “work that is productive and delivers a fair income, security in the workplace and social protection for families, better prospects for personal development and social integration, freedom for people to express their concerns, organize, and participate in decisions that affect their lives, and equality of opportunity and treatment for all women and men.”<sup>3</sup> Decent work is therefore instrumental in reducing poverty and achieving equitable, inclusive, and sustainable development.

This paper relies on three desirable characteristics to define a good job, as follows: (1) a job that allows the jobholder to work 20 or more hours per week, (2) salaried work through a contractual arrangement, and (3) salaried work that provides some measure of tenure. The assumption associated with the first criterion is that everyone would like to be employed full time if given the opportunity. This is a strong assumption because there may be specific instances in which people prefer to remain in part-time work or temporarily unemployed. However, the data on the types of jobs held by individuals do not indicate whether some people may not be working because they are waiting for better jobs or they may be staying at a job simply because there is no alternative. The study classifies such people as participants in the labor force who do not have appropriate jobs. The analysis also assumes that most people prefer jobs providing salaries under

> 3 See “Decent Work,” International Labour Organization, Geneva, http://www.ilo.org/global/topics/decentwork/lang--en/index.htm.

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no education to a postgraduate degree. For working experience, the ages of respondents are used as a proxy on the assumption that older workers generally have more work experience.

Parental educational attainment is defined as the educational attainment of the father or mother, whichever is greater, and this is also an aspect of the socioeconomic background of individuals. Parental political affiliation is identified according to the responses to questions about whether the parents of respondents were members of the Communist Party, which is particularly relevant because Armenia, Azerbaijan, and Georgia were part of the Soviet Union, and this is also used as an indicator of social status.<sup>4</sup> There is no direct measure of the ethnicity of individuals; so the language spoken by a respondent is taken as a cue, especially depending on the country of residence of the respondent.<sup>5</sup> Figure 4 illustrates the conceptual framework. An assumption supporting the framework is that educational attainment—an important marker of skills and experience—should be a major determinant of the ability to obtain a good job in the labor market. Therefore, a labor market that places a premium on education and experience can be regarded as a fair labor market. In contrast, a labor market that allocates opportunities based on the gender, ethnicity, paternal educational attainment, or parental political affiliation is deemed an unfair labor market, although, in many cases, this is not due to discrimination, but the unequal effect of an incomplete transition to equitable access to opportunities. The World Bank (2015) finds that, in Armenia and Georgia, education helps in gaining access to jobs, although the unemployment rate among the welleducated is relatively high in comparison with the average in the Organisation for Economic Cooperation and Development (OECD), and a significant share of workers (29 percent in Armenia and 33 percent in Georgia) consider themselves overeducated for their current jobs. The World Bank study also shows that, while skills matter more than educational attainment in explaining the variance in hourly wages among youth (ages 15–29), the role of education in explaining wage variance is higher among prime workers (ages 30–44).

> 4 Parental affiliation with the Communist Party can be considered an unfair advantage in the labor markets of former communist countries especially among people in older birth cohorts who entered the labor market during the communist era. Parental affiliation with the Communist Party might also affect labor market access negatively, an unfair disadvantage, among people who entered the labor market in the first years after the collapse of the Soviet Union. Yet, the analysis here is aligned with the view that social status is a durable institution that persists in the aftermath of a political crisis, especially if the crisis leads to more labor market imperfections because of the destruction of information networks. Another interpretation is that parental affiliation is a signal of motivation, especially in a situation in which the only opportunity for upward social movement is associated with Communist Party membership.

> 5 This paper reflects an acknowledgment that there is a possibility that ethnicity does not play a major role in accessing good jobs because of the effect of ethnic cleansing in the 1990s that effectively eliminated minorities.

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The scores achieved in the tests of the Program for International Student Assessment (PISA) of the OECD in Georgia and Azerbaijan in 2009 and 2015 are used to estimate the level of access to quality education. Gathered in 2015, data of the Integrated Living Conditions Survey in Armenia, the Monitoring Survey for Social Welfare in Azerbaijan, and the Monitoring of Households Survey in Georgia are used to estimate human capital inputs. The standard HOI among children is applied to examine the dimensions along which the inequality of opportunity in access to basic human capital inputs during the formative years may be most salient. Specifically, in this framework, opportunities are defined as access to running water and sanitation among children ages 0–16 and reflect the quality of health services in the early years of life.

The circumstances that may affect the access of children to running water and sanitation, are measured with the following variables: the number of 0- to 15-year-olds in the household, the educational attainment of the household head, the gender of the household head, the household consumption quintile, the gender of the child, and the location of the household (urban or rural area and province or region). Unlike the HOI framework for determining the access to a good job, all factors contributing to inequality, that is, the circumstances, are independent of the choice of children. Without a panel data structure, the HOI on human capital can only be generated for the current young generation, which is not directly relatable to the current labor force on which the HOI estimation of good jobs is focused.

# 3. Results

The empirical findings of the study are organized into three topics: the perceived fairness of the process, inequality of opportunity in the labor market, and inequality in human capital inputs (see the Methodology section). In this section, how people in South Caucasus generally perceive fairness in the processes involved in obtaining access to good jobs is described by way of perceptions on the role of connections. The next and more substantial part of the section highlights the level of access to good jobs in South Caucasus, measures the inequality of access to good jobs, and uses the HOI framework to decompose the sources of inequality and to determine the level of unfair inequality in accessing good jobs. The last part of the section presents the results produced by applying the HOI framework to determine the amount of the access of children to basic human capital inputs and provide some early indication on the extent to which inequality in access to good jobs is associated with inequality in access to human capital inputs.

# 3.1. Perceptions of the fairness of processes

The analysis generally finds that the populations of the countries of South Caucasus perceive that connections play a crucial role in gaining access to good jobs. Among Eastern Europe and Central Asia countries, the share of the population that believes connections are essential or important in obtaining good jobs in both the private sector and the public sector is the largest in 12
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Azerbaijan, where the inequality index is so high that it leads to a significant discount even on the low coverage rate (see figure 9). Similar to the situation in the coverage rate indicator, these countries belong to the group with low inequality-adjusted coverage rates as well.

# _Inequality index decomposition_

This paper finds that countries in South Caucasus have low coverage rates for good jobs and high inequality among population subgroups in the access to good jobs. The analysis now addresses the extent to which differences in individual circumstances beyond personal effort and choice (the unfair elements) contribute to the wide inequality in the access to good jobs. First, following the Shapley decomposition method outlined in Shorrocks (2013), between-group inequality in labor markets (D-index) is decomposed into two major contributing components: i) the behavioral characteristics of individuals related to their efforts and experience and, ii) the circumstances beyond the control of individuals, namely, gender, ethnicity, parental educational attainment, and parental political affiliation. The first component (broadly, effort and experience) is considered the fair element contributing to inequality in a labor market, while the second component (circumstances) is the unfair element. To assess the relative fairness of labor market inequality in the countries of South Caucasus, the shares of the two contributing factors in inequality in these countries are compared with the average shares in all countries surveyed in the 2015 LiTS, as well as with the averages in Belarus, Central Asia (Kazakhstan, the Kyrgyz Republic, Mongolia, Tajikistan, and Uzbekistan), Moldova, and Ukraine; Southeastern Europe (Albania, Bosnia-Herzegovina, Cyprus, Greece, Kosovo, FYR Macedonia, Montenegro, and Serbia); the European Union–11 (Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovak Republic, and Slovenia); the European Union (represented by only Germany and Italy), the Russian Federation, and Turkey.

An important finding of this paper is that a sizable share of the inequality in access to good jobs is unfair in Armenia and Azerbaijan, while the share is moderate in Georgia (figure 12). To illustrate, on the access to the first category of good jobs (those involving work of 20 hours or more a week), the share of the unfair element of inequality is small in Georgia, at 34 percent, but it is not small for Armenia and Azerbaijan. At 63 percent and 85 percent of total between-group inequality, respectively, the countries show the highest level of unfairness in the 34 countries of Eastern Europe and Central Asia, where the average share of the circumstances component in total inequality is 47 percent. The shares of circumstances in total inequality in Azerbaijan and Armenia are also higher than the averages in other sub-regions. Similar patterns in the share of the unfair element in inequality are observed in the access to good jobs involving work of 20 hours or more a week with contract and, especially, with tenure. In the category of good jobs involving work of 20 hours or more a week with contracts, Georgia registered the smallest share of the unfair element in between-group inequality.

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Figure 12: Decomposition of inequality in access to good job – working 20 hours or more per week 12a. Working 20 and more hours a 12b. Working 20 and more hours a week week and with contract 12c. Working 20 and more hours a week and with security of tenure Across different categories of good jobs, the unfair elements—the circumstances—matter less in accessing good jobs involving work of 20 hours or more a week with contracts. Yet, the notion of less unfairness in obtaining a better good job is difficult to establish because the share of unfair elements in the strictest category of good jobs—the ones with tenure or permanent status—is not substantially different from the share in the least strict category, jobs involving work of 20 hours or more a week (see figure 12, panels a and c; table 1). Neither labor market discrimination or market imperfection seems to diminish clearly with the quality of the job (such as jobs with better contracts or better tenure security) in South Caucasus; the diminishing role of the unfair element 22
in inequality among better secured good jobs is evident in Armenia, but not in Azerbaijan or Georgia.

Table 1: Contribution of effort and hard work and circumstances to total inequality in access to good jobs (%)

|||Effo<br>Age|rts and<br>|hard<br>Ed|work<br>ucati|on|G|end|er|F<br>ed|<br>athe<br>ucat|Circum<br>r's<br>ion|stance<br> <br>p<br>af|s<br>Parent<br>olitic<br>filiati|'s<br>al<br>on|Et|hnicity|Tot<br>e|al un<br>leme|fair<br>nt|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Type ofgoodjob*|1|2|3|1|2|3|1|2|3|1|2|3|1|2|3|1|2<br>3|1|2|3|
|Armenia|9|6|5|27|44|44|46|11|17|11|22|18|5|14|15|1|2<br>1|63|49|51|
|Azerbaijan|1|0|1|15|44|18|68|38|59|13|13|17|2|2|3|2|2<br>3|85|55|82|
|Georgia|21|1|5|45|74|55|9|0|5|20|17|29|1|2|1|4|5<br>5|34|24|40|
|.<br>BMU & Central|||||||||||||||||||||
|Asia|17|17|14|33|41|44|23|6|8|12|18|17|5|8|6|11|10<br>12|50|42|42|
|S.E. Europe|19|12|17|34|43|39|20|11|13|16|18|16|3|3|2|8|13<br>13|47|45|43|
|EU-11<br>GER, ITA, RUS,|21|16|22|38|40|40|7|8|5|18|21|18|4|4|4|11|11<br>10|41|44|38|
|TUR|24|24|28|27|28|21|22|14|22|18|19|16|1|3|1|9|14<br>13|50|49|51|

Note: *Type 1 is working 20 hours or more a week; type 2, working 20 hours or more a week with contract; type 3 working 20 hours or more a week with tenure Nonetheless, the share composition of the various factors contributing to the unfair element in the inequality in access to good jobs in South Caucasus varies across categories of good jobs and across countries. The gender factor plays a sizable role in Armenia and Azerbaijan, while Georgia is among the countries with the smallest share of the gender factor in the inequality in the labor market. Thus, 68 percent of the inequality in access to jobs involving work of 20 hours or more a week in Azerbaijan derives from differences in gender, while this is true of a smaller, but still considerable share of jobs of 20 hours or more a week with contracts or tenure (see table 1). Armenia shows a slightly different pattern: in jobs of 20 hours or more a week, the share of the gender factor in inequality is 46 percent, but this declines significantly, to 11 percent and 17 percent, respectively, in jobs of 20 hours or more a week with contracts and tenure.

Parental educational attainment, one of the proxies for family social status, plays a considerable role in inequality, especially in Georgia. The shares of the differences in parental educational attainment in inequality in Georgia are 20 percent for jobs of 20 or more hours a week, 17 percent for jobs of 20 or more hours a week with contracts, and 29 percent for jobs of 20 or more hours a week with tenure. The contribution of parental educational attainment to labor market inequality in Armenia and Azerbaijan is between 11 and 22 percentage points depending on the category of good jobs. Meanwhile, parental political affiliation is a relatively important 23
contributor to inequality in Armenia, especially in the access to good jobs with contracts (14 percent) or tenure (15 percent). Parental political affiliation and the ethnicity of an individual seem to have only a small role in inequality in the access to all categories of good jobs in the three countries in South Caucasus.

Among the fair components of inequality, education generally matters a great deal, especially in securing a good job with a contract or with permanent tenure (see table 1). In the case of the basic definition of a good job, 20 hours or more a week, the contribution of educational attainment to inequality in Armenia and Azerbaijan (27 percent and 15 percent, respectively) is limited relative to the gender differential factor (46 percent and 68 percent, respectively). In the stricter category of good jobs, the ones associated with contracts or tenure, the contribution of education generally increases. Yet, it appears that, in South Caucasus, differences in educational attainment contribute less to inequality in the access to good jobs with permanent tenure than to inequality in securing jobs with contracts. Another fair component of inequality, age (as a proxy for work experience), generally contributes less to inequality, except in Georgia in the access to jobs involving work of 20 hours or more a week (21 percent). The educational attainment of both respondents and parents appear to contribute substantially to inequality in the labor market according to the HOI approach. To check the robustness of this finding, the analysis included a probit regression run on access to good jobs with similar relevant variables (effort and circumstances), which found that the education variables of respondents and their parents are equally significant in driving the access to good jobs (see annex 2).

The research makes two assumptions about the fair component of inequality. First, work experience is important in obtaining access to good jobs. However, among transition economies such as those in South Caucasus, the massive disruption and exogenous economic restructuring in the 1990s may have rendered the role of work experience in gaining access to good jobs meaningless. For example, when Armenia became independent, the share of the manufacturing sector in total output shrank from 70 percent to 20 percent; so, skills and work experience in manufacturing suddenly became less relevant. To address this issue, the research also tests the assumption that work experience remains relevant in the region. In particular, this study observes the variations in the contributions of age as a proxy for the value of work experience in gaining access to good jobs in industries in which experience is still important after the massive restructuring (manufacturing) or in sectors characterized by human capital intensity, such as high-quality services (finance and public administration). The research also compares the contributions of age in accessing good jobs among younger cohorts among which work experience may matter more (see annex 3). The evidence shows that the age of respondents as a proxy for work experience does not contribute more to inequality in manufacturing and highquality services than in other industries. It also does not exhibit a greater share in inequality among younger cohorts.

Second, the research assumes that educational attainment is a valid measure of skills. However, many studies in the countries of South Caucasus point to a significant skills mismatch because of poor teaching quality and outdated curricula that often do not allow for a smooth school-work transition. To confront this problem, the research also tests if educational attainment among individuals is correlated with work skills by observing differences in the contributions of 24
education to access to good jobs across industries showing skills mismatches. If there were a skills-mismatch problem, industries in which the skills-mismatch is more severe, such as agriculture and low-quality services, would exhibit relatively greater contributions of educational attainment to labor market inequality, that is, workers would tend to be overeducated relative to the skills required by their jobs in these industries. The research finds that <mark>educational attainment among respondents, as a proxy for skills, does not have a greater effect on inequality in the access to good jobs in industries with more severe skills mismatches (see an</mark> nex 4, t <mark>able A4;).</mark>

# 3.3. Inequality in human capital inputs

The observed fair inequality component of the access to good jobs, that is, the component involving the effort, experience, and choice of individuals, may be affected by inequality in the access to human capital inputs among individuals during their formative years. The research extends the analysis by evaluating learning performance in Azerbaijan and Georgia based on the PISA test scores to describe access to education. The analysis also relies on the application of the HOI approach to the measurement of inequality in children’s access to basic utilities in South Caucasus. The study finds that, first, educational performance appears relatively poor and unequal depending on the life circumstances of children. Second, the coverage rates of basic human capital inputs such as access to gas and water and sanitation are generally high, although inequalities remain an issue in the countries, especially in higher-quality services. The inequalities are mostly associated with geographical disparities.

## _Learning performance_

While school attendance rates are high in the countries of South Caucasus, learning performance shows mixed results.<sup>8</sup> Only Azerbaijan and Georgia participate in the PISA test; the test was conducted in Azerbaijan in 2006 and 2009 and in Georgia in 2009 and 2015. The average PISA scores rose noticeably in Georgia between 2009 and 2015: by 38 points in science, 25 points in mathematics, and 27 points in reading (World Bank 2016) (figure 13). Because every 30-point difference in a PISA score corresponds to about one year of schooling in the 2015 round of the PISA, the improvement in Georgia is substantial. Meanwhile, in the two rounds of the PISA test in 2006 and 2009, the performance in Azerbaijan was less impressive. The country’s average score in reading rose by 9 points, but the mathematics score dropped rather significantly, by 45 points. Overall, these levels of educational achievement in the countries of South Caucasus are still far below the averages in the OECD and in Eastern Europe and Central Asia. For example, the science score in Georgia in the 2015 round of PISA was 411, while the regional average was 454, and the OECD average was 493. More than half of 15-year-olds in Georgia scored below basic proficiency in science, reading, and mathematics.

> 8 See, for example, UNESCAP (2017), which shows high attendance rates in secondary education.

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Figure 13: Learning performance: PISA scores

# 13a. PISA scores by subject

13b. Proficiency among 15-year-olds, Georgia Even more concerning, the educational disadvantages among the working-age population appear to emerge in Georgia early in life. While school attendance seems to be universal, the quality gaps are rather large, given that learning outcomes vary dramatically by the circumstances of children (figure 14). The 30-point difference in the PISA score equivalent in science between students of the same age and grade at the top and the bottom of the scale of economic, social, and cultural status is roughly equivalent to a difference of three years of schooling. The score differences by urban-rural location (36 points), gender (17 points), and the duration of exposure to preschool (23 points) are also substantial.

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Figure 14: Equity profile, PISA science score, Georgia, 2015

# _Children’s access to basic utilities_

The inequality in the access to basic human capital inputs among children ages 0–16 measured using a standard HOI on access to water and sanitation is generally low and mostly derives from spatial disparities.<sup>9</sup> In this analysis, the life circumstances of children are based on the number of children in the household; the educational attainment, age, and gender of the household head; the household consumption quintile; the gender of the children; and the urban-rural and provincial location of the household.

Among the three countries, the share of children who have access to water appears to be highest in Armenia (figure 15). In 2015, 96 percent of Armenian children had access to water, and the HOI for access to running water was approximately the same, at 94 percent, highlighting the narrow between-group inequality in access to the service. However, these large shares may

> 9 Because the data are generated though separate household surveys across the countries of South Caucasus, the definitions of access to water and sanitation are also slightly different. In Azerbaijan, the definition revolves around whether children have access to water in their dwellings, though the survey does not specify the source of the water. In Armenia, children are considered to have access if their households obtain water from a central supply. In Georgia, access refers to whether the households have water systems within the home or outside in the vicinity. Likewise, in Azerbaijan, children are considered to have access to sanitation if there are toilets in their dwellings. In Armenia, access refers to whether the households have local or centralized sanitation utilities. In Georgia, where all households claim to have toilets, children are considered not to have access to sanitation if the household toilets are latrines emptying into a river, channel, or ravine, and so on.

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derive from the broader definition of access to water in the case of Armenia. In Azerbaijan, using the definition of access to a central water supply, the coverage rate is 90 percent, while the HOI is 85 percent. Using the definition based on whether households have access to a water system, Georgia’s coverage rate is 79 percent, and the HOI is 68 percent. These relatively high rates of access are in line with the data of the United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP 2017) on household access to improved drinking water among 41 Asia-Pacific countries that show coverage rates in Armenia and Georgia at nearly 100 percent and in Azerbaijan at above 80 percent. All three countries also managed to meet the relevant Millennium Development Goal (WHO and UNICEF 2015).<sup>10</sup> Figure 15: Access to water and sanitation (0-16 years old) a. Armenian b. Azerbaijan

> 10 The notion of coverage rates of the United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP 2017) and the World Health Organization and the United Nations Children’s Fund (WHO and UNICEF 2015) is different from the notion here. The definition in the former two sources is the percentage of the population having access to water or sanitation, while the definition here is the percentage of children with access. The definitions of access to water and sanitation differ as well.

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# c. Georgia

Among lower-middle-income countries, indicators of service quality, such as whether running water is available for more than 12 hours a day, are more relevant. Based on these indicators, the coverage rates are lower, and the inequality gaps are wider than the results of indicators simply on access to running water. The coverage rate declines substantially, from 96 percent to 76 percent in Armenia, from 87 percent to 65 percent in Azerbaijan, and from 79 percent to 60 percent in Georgia (table 2). Inequality (D-index) also rises considerably, and, combined with the lower coverage rates, this leads to an increase in the penalty factors associated with greater inequality, that is, the gap between coverage rates and the inequality-adjusted HOI.

Table 2: Contribution of effort and hard work and circumstances to total inequality in access to good jobs (%)

|||Runnin|g water||Runnin|g water<br>more|- 12hrs m<br>/day|ore||Sanit|ation||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||||D-||||D-||||D-|
||Coverage|HOI|Penalty|index|Coverage|HOI|Penalty|index|Coverage|HOI|Penalty|index|
|Armenia|0.96|0.94|0.02|0.02|0.75|0.67|0.08|0.11|0.90|0.85|0.05|0.06|
|Azerbaijan|0.87|0.82|0.06|0.06|0.65|0.58|0.06|0.10|0.92|0.90|0.02|0.02|
|Georgia|0.79|0.68|0.11|0.14|0.60|0.47|0.13|0.22|0.93|0.89|0.04|0.04|

Despite the differing definitions of access to sanitation, sanitation coverage rates are high in South Caucasus: 90 percent in Armenia, 92 percent in Azerbaijan, and 93 percent in Georgia (see table 2). Between-group inequality in children’s access to sanitation also appears to be narrow as shown by the low D-index. Indeed, the United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP 2017) also assigns Armenia and Georgia among the countries with the highest household sanitation coverage rates in the Asia-Pacific region. Regarding 29
coverage rates between 1990 and 2015, only Azerbaijan managed to meet its Millennium Development Goal target, while Armenia and Georgia fell short (WHO and UNICEF 2015).

The striking feature of the composition of factors contributing to the penalty index is the substantial role of spatial differences—whether children reside in urban or rural areas or in a particular province—in opportunities in all three South Caucasus countries (figure 16). For example, in access to water for at least 12 hours a day, 33 percent and 53 percent of the total between-group inequality in Armenia arises from differences in urban-rural and provincial residence, respectively. In Azerbaijan, the shares are 11 percent and 67 percent, and, in Georgia, 28 percent and 55 percent. The relatively high contribution of location may suggest a spatial discrepancy in the supply of basic human capital inputs in the South Caucasus countries. In Azerbaijan, the discrepancy reflects a regional disparity between Baku and the Absheron region and the rest of the country. Moreover, while the contributions of other circumstances are relatively small, differences in per capita incomes appear to play a considerable role in Azerbaijan, where the differences in household income quintiles account for more than 10 percent of the inequality in access to water and sanitation among children.

Figure 16: Inequality decomposition (0- to 16-year-olds) 30
The research thus finds that educational performance still requires major improvement, and children’s access to education is unequal. Meanwhile, children’s access to basic utilities are generally high, although there is a spatial disparity in supply. Therefore, the fair component of inequality appears to derive from a learning gap associated with children’s circumstances.

# 4. Conclusion and Policy Discussion

The main takeaways from the document are as follows. First, connections play an important role in obtaining access to good jobs in South Caucasus, highlighting the unfairness in processes in the sub-region’s labor markets. Second, access to good jobs—defined as work for 20 hours or more a week and work under contract or with tenure—is low in South Caucasus relative to other parts of the Europe and Central Asia region. Third, even among the people who have access to good jobs, the share of the total inequality of opportunity that may be characterized as unfair is relatively large. Armenia and Azerbaijan stand out for the significant share of inequality in access to good jobs associated with gender differences. Fourth, the analysis on access to education and basic human capital inputs in the earlier, formative stages of life shows that learning performance in South Caucasus tends to be poor and unequal across the life circumstances of children. Nonetheless, the coverage rates of basic human capital inputs are generally high; the relatively narrow inequalities arise mostly from spatial disparities.

To some extent, these prevailing inequalities in access to good jobs suggest that there is a labor market failure in South Caucasus, that is, the inability of the labor market to allocate the labor force to the most efficient uses based on skills, efforts, and talents. The accompanying labor market policies or reform in South Caucasus needs therefore to be directed toward addressing this issue and ensuring that opportunities to participate in the labor market are not determined by circumstances such as gender or parental social status, but, rather, skill and effort. It is important that non-merit–based and discriminatory mechanisms do not distort the entry and exit associated with good jobs (promotion), and wage rate policies.

In practice, policy makers in the countries of the South Caucasus need to promote policies that enhance advancement based on the skills and effort of labor market participants, without overreliance on potentially distorting signals, to sort out who deserves the access to good jobs. One example of such policies is to ensure that school diplomas reflect the quality of an education system that provides the skills necessary for the labor market. Various smaller initiatives and campaigns to promote fairness in worker recruitment and promotion are also feasible and can be effective in reducing inequality of opportunity in the labor market, especially if such initiatives are based on credible evidence on the efficiency loss arising from unequal access associated with circumstances beyond effort and skills. Technology and scientific findings can also be used and promoted to help labor market actors design more efficient mechanisms to identify available skills and match them with demand.

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Labor codes and laws can also be enforced to eliminate discrimination in the labor market, thereby reducing inequality of opportunity in the labor market. A legal framework fostering equal opportunity and equal treatment in employment is available in South Caucasus, for example, Armenia’s 2004 Labor Code (amended in 2011) and Azerbaijan’s 1999 Labor Code, 2001 Employment Act, and 2006 Law on the Guarantee of Gender Equality (ILO 2011, 2012). These legal codes explicitly include legal equality in working relationships regardless of gender, social status, political affiliation, and so on. However, reports of the International Labour Organization (ILO 2011, 2012) suggest that the effective implementation of labor codes remains an issue. Thus, enforcing the already available legal codes is the logical next step in labor market reform to reduce the inequality in access to good jobs.

The empirical results described in this paper show that gender inequality is the main contributor to inequality in access in South Caucasus. The International Labour Organization (ILO 2011, 2012) finds that Armenia and Azerbaijan have low female employment rates and wide gender pay gaps. This highlights that, among the types of inequality hindering the access to good jobs, it is necessary to prioritize policies that address gender-based inequality. The empirical findings outlined in the paper also suggest that it is important to increase the quality of learning and to focus on eliminating spatial disparities in the supply of education and basic utilities. Similarly, policies should be oriented towards improving connections and matching of specific skills with employment where these are needed. Finally, constant updating and upgrading of human capital through ‘on the job training’ can help improve perceptions and actual quality of employment in the South Caucasus.

As in any reform effort, the challenges are numerous. However, the benefits of addressing the inequalities in the labor market are tangible in South Caucasus. First, reforms would be economically rewarding because they would remove labor market distortions and increase the incentives for investment in human capital and thus promote long-run growth. Second, reforms would also be politically rewarding because the perceived inequality in the labor market is positively associated with the public’s demand for redistribution. As the forces of globalization, technological change, and aging continue to shape the economic and social landscape of the broader Eastern Europe and Central Asia region, perceptions of reduced social mobility and inequality of opportunity are generating distributional tensions that will likely exert greater pressure on the existing social contract. Addressing the deep structural inequalities that are shaping the landscape of opportunity in South Caucasus must be a key consideration in any strategy to share prosperity sustainably.

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