Regional Human Development Report draft

UNDP REGIONAL HUMAN DEVELOPMENT REPORT Progress at Risk: Inequalities and Human Development in Europe and Central Asia1 Draft FOR COMMENTS (2 February 2016) Abstract: Many of the developing and transition economies of Europe, Turkey, and Central Asia have enjoyed relatively high levels of socio-economic equalities. Since 2000 income inequalities have generally been low or falling, which has helped to reduce poverty and allowed the middle class to stage a comeback. Relatively comprehensive pre-1990 social protection systems and high levels of gender equality have ensured that the benefits of economic growth have been fairly evenly spread. However, the expansion of informal, vulnerable, and precarious employment is combining with growing gaps in social protection systems and (in the region’s less wealthy countries) new pressures on household food and energy security to put these accomplishments at risk. This is particularly the case for those countries in the Commonwealth of Independent States that have made some of the best progress in reducing inequalities—and which now face growing socio-economic pressures. This report examines the human development aspects of these challenges, within the context of the Sustainable Development Goals and the promise of the global sustainable development agenda 2030 to “leave no one behind”.

Table of contents Subject Executive summary -----------------------------------------------------------------------------------------------------Chapter 1—Measuring income and non-income inequalities -------------------------------------------------Chapter 2—Inequalities, employment, and social protection ------------------------------------------------Chapter 3—The economic dimensions of gender inequalities -------------------------------------------------Chapter 4—Inequalities, health, and HIV/AIDS -------------------------------------------------------------------Chapter 5—Natural Capital, Inequalities, and Sustainable Human Development -----------------------Chapter 6—Inequalities and inclusive governance --------------------------------------------------------------References ------------------------------------------------------------------------------------------------------------------

Page 2 5 26 57 77 86 97 134

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This paper does not necessarily reflect the views of the United Nations Development Programme, the United Nations, or its Member States.

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Executive summary 

Significant reductions in income inequalities have been reported in much of the region 2 since the turn of the millennium—particularly Belarus, Kazakhstan, Moldova, and Ukraine, and possibly also Albania, Kosovo,3 and the Kyrgyz Republic. By contrast, income inequalities seem to have increased in Georgia, Turkey, and possibly the former Yugoslav Republic of Macedonia (fYRoM).



Low or falling income inequalities have helped economic growth reduce poverty—particularly in this first group of countries. In Georgia and fYRoM, by contrast, high or rising levels of income inequality have slowed or frustrated progress in poverty reduction. This underscores how—in addition to being desirable in and of themselves—low or falling inequalities are central to prospects for poverty reduction, inclusive growth, and sustainable development in the region.



The numbers of people in the region living in poverty fell from at least 46 million in 2001 to about 5 million in 2013. The numbers of people living in extreme poverty dropped below 1 million during this time. Likewise, the numbers of people vulnerable to poverty dropped from about 115 million in 2003 to some 70 million in 2013. By contrast, the size of the middle class grew from about 33 million in 2001 to 90 million in 2013. The numbers of relatively “wealthy” individuals (living on more than PPP$50/day) had risen to some 32 million in 2013—most of whom were living in Turkey and Kazakhstan.



The region’s middle classes have made a comeback since the turn of the millennium, following both absolute and relative declines during the 1990s. In much of the region, middle classes have grown as the shares of national income claimed by wealthy households have declined. As of 2013, at least 80 million people in the region had achieved living standards that are broadly consistent with the bounds of the “global middle class”.



Progress in reducing income inequalities is now being put to the test in much of the region. The combination of low commodity prices, falling remittances, and slow or negative growth on key European and Russian export markets is putting pressures on vulnerable household incomes that have not been seen since the turn of the millennium. This poses new challenges as the implementation of the global sustainable development agenda 2030 begins in the region—particularly for labour markets and social protection systems, but also in light of the growing pressures on natural capital and ecosystems in some of the region’s less wealthy countries.



Labour market inequalities and exclusion lie at the heart of the region’s inequality challenges. This is the case both in terms of labour markets per se, and because access to social protection is often linked to formal labour market participation. People without decent jobs face much higher risks of poverty, vulnerability, and exclusion from social services and social protection. The share of workers in vulnerable in Albania, Azerbaijan, Georgia, the Kyrgyz Republic, and Tajikistan is estimated at around 50%.



Employment does not necessarily offer much protection against poverty and vulnerability, because informal, precarious, migratory, and vulnerable employment is widespread throughout the region.

Women, young workers, migrants, the long-term unemployed, people with disabilities, and others with unequal labour market positions are particularly vulnerable. While trends are improving in some countries and for some groups, in others, labour market inequalities are increasing.



The region faces important challenges in better measuring progress in reducing inequalities and promoting sustainable development. This is apparent in the data on income inequalities, which tend to

2

Unless otherwise noted, reference in this publication is to Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Georgia, Kazakhstan, Kosovo (as per UNSCR 1244 (1999)), the Kyrgyz Republic, the Former Yugoslav Republic of Macedonia, Moldova, Montenegro, Serbia, Tajikistan, Turkey, Turkmenistan, Ukraine, and Uzbekistan.

3 All references to Kosovo in this publication are within the framework of UNSCR 1244 (1999).

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report on disparities in consumption spending rather than income. It is apparent in the “employment”/”unemployment” statistical dichotomy, and in the infrequency with which publicly available labour-market data are disaggregated by age, gender, ethnicity, and other criteria. And it is apparent in the paucity of indicators to measure the depletion of the region’s natural capital and environmental sustainability. 

Long-term efforts to formalize employment are crucial. Three directions are particularly important: (i) efforts to boost the institutional capacity of the institutions charged with labour market regulation, in order to better enforce legal protections for workers’ rights in the formal sector; (ii) the abolition of those labour market regulations that cannot be credibly enforced by state agencies and drive employment into the informal sector; and (iii) increased investment in active labour market policies, vocational education, and other measures to boost worker productivity.



Policy linkages between labour markets and social protection need to be strengthened. While poorly aligned social policies can reduce incentives for labour market participation and hiring, this is not a reason for reducing social protection spending and coverage. Instead, wherever possible, the taxation of labour to fund social benefits needs to be reduced in favour of other funding sources. These may include: (i) higher taxes on environmentally unsustainable activities; (ii) reductions in budget subsidies that accrue to the wealthy; (iii) more aggressive measures to reduce the diversion of budget revenues to tax havens; and (iv) more robust direction of budgetary procurement and contracting resources to companies (e.g., social enterprises) that explicitly promote social inclusion.



Social protection is also about social services and the care economy. Increased investments in social service provision—particularly terms of care for children, the elderly, and persons with disabilities—can boost participation in labour markets and vocational training programmes, particularly for women. In Turkey, for example, a decision to bring state budget spending on social care services up to OECD levels would generate an estimated 719,000 social care jobs—more than 2.5 times the total number of jobs that would be created by devoting the same amount of budget funds to construction/infrastructure projects. An estimated 84% of the workers hired into these social care jobs would have permanent contracts of unlimited duration (versus 25% in construction); 85% would have social security coverage (compared to 30% in construction).



While the region compares favourably to many other developing countries in terms of gender equality, it also lags behind global best practices in many areas. Moreover, pre-1990s progress in gender equality that had been attained in many countries—many of which featured relative equality between men and women—has come under growing threat.



Gender-based inequalities tend to intersect with, and magnify the impact of, other forms and dimensions of inequalities, based on class, race, age, ethnicity, disability, occupation and income.

Unequal labour market outcomes in particular can have major implications for broader gender inequalities and the exclusion of women. Women’s unequal access to social capital or their inferior position in the networks that constitute social capital (which are more marked in some countries in the region than in others) is both a cause and a manifestation of inequality.



Adjustable net savings, the ecological footprint, and the sustainable human development index suggest that the depletion of natural capital, and environmental sustainability concerns more broadly, are relatively pronounced in the region’s lower-middle income countries—which are concentrated in the Caspian Basin. In addition to being the site of one of the world’s largest man-made ecological disasters (the Aral Sea tragedy), development models in many of these countries are based on the extraction and processing of non-renewable fossil fuels, minerals, and non-ferrous metals. In some of these countries, this is accompanied by significant household food and energy insecurities. This points

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to a certain geographic inequity—environmental risks to sustainable development tend to be concentrated in the eastern parts of the region. 

Governance reforms must be at the heart of policy and programmatic responses to these challenges.

Efforts to improve labour market performance, strengthen social protection systems, and better address the region’s HIV/AIDS challenges require investments in the institutional capacity of labour inspectorates, public employment and public health services, the local authorities, and NGOs. Reductions in gender-based and other forms of discrimination require investments in institutions that protect human rights, as well as judicial reforms and access to justice. Better quality and more extensive and timely data on social exclusion and environmental sustainability require investments in the institutional capacity of national statistical institutions—particularly in light of the reporting obligations associated with Agenda 2030 and the SDGs. Improvements in all of these areas require investments in public administrations and civil services, at both the central and local government levels.

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Chapter 1—Measuring income and non-income inequalities4 Key messages 

Significant reductions in income inequalities have been reported in much of the region since the turn of the millennium—particularly Belarus, Kazakhstan, Moldova, and Ukraine, and possibly also Albania, Kosovo,5 and the Kyrgyz Republic. By contrast, income inequalities seem to have increased in Georgia, Turkey, and possibly the former Yugoslav Republic of Macedonia (fYRoM).



Low or falling income inequalities have helped economic growth reduce poverty—particularly in this first group of countries. In Georgia and fYRoM, by contrast, high or rising levels of income inequality have slowed or frustrated progress in poverty reduction. This underscores how—in addition to being desirable in and of themselves—low or falling inequalities are central to prospects for poverty reduction, inclusive growth, and sustainable development in the region.



The numbers of people in the region living in poverty fell from at least 46 million in 2001 to about 5 million in 2013. The numbers of people living in extreme poverty dropped below 1 million during this time. Likewise, the numbers of people vulnerable to poverty dropped from about 115 million in 2003 to some 70 million in 2013. By contrast, the size of the middle class grew from about 33 million in 2001 to 90 million in 2013. The numbers of relatively “wealthy” individuals (living on more than PPP$50/day) had risen to some 32 million in 2013—most of whom were living in Turkey and Kazakhstan.



The region’s middle classes have made a comeback since the turn of the millennium, following both absolute and relative declines during the 1990s. In much of the region, middle classes have grown as the shares of national income claimed by wealthy households have declined. As of 2013, at least 80 million people in the region had achieved living standards that are broadly consistent with the bounds of the “global middle class”.



Progress in reducing income inequalities is now being put to the test in much of the region. The combination of low commodity prices, falling remittances, and slow or negative growth on key European and Russian export markets is putting pressures on vulnerable household incomes that have not been seen since the turn of the millennium. This poses new challenges as the implementation of the global sustainable development agenda 2030 begins in the region.

Introduction Quantitative data concerning inequalities can be divided into three classes: (1) income inequalities; (2) non-income inequalities; and (3) subjective perceptions of inequalities (in the form of survey data gathered via representative samples). This chapter focuses on (1) and elements of (2)—particularly as concerns inequalities in the distribution of wealth, but also in terms of inequalities in access to basic services. (Many other aspects of non-income inequalities are taken up in the subsequent chapters—particularly as concerns labour markets, gender, health, and social protection). By contrast, subjective perceptions of inequalities are not a major focus of this chapter, or report—although, for reasons explained below, they almost certainly merit additional research and analysis.

Analyses concerning inequalities and programming to respond to them are often hindered by the paucity of quantitative data—particularly once these discussions go beyond income inequalities, and particularly in the context the transition and developing economies of Europe and Central Asia. Despite this, even in the region’s

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Please send comments on this chapter to Elena Danilova-Cross (elena.danilova-cross@undp.org) and Ben Slay (ben.slay@undp.org).

All references to Kosovo in this publication are within the framework of UNSCR 1244 (1999).

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less wealthy countries, policy makers are increasingly focusing on inequalities, exclusion, and vulnerability, rather than on extreme income poverty.

This growing interest is accompanied by an emphasis within the Sustainable Development Goals (SDGs), which underpin the global Agenda 2030 for sustainable development on inequalities, both in terms of SDGs 10 (“reduce inequality within and among countries”) and 5 (“achieve gender equality and empower all women and girls”), and in terms of numerous other SDG targets and (prospective) indicators. It is also matched by a renewed commitment on the part of the UN system to support national efforts to improve the quality, quantity, and availability of sustainable development data—including data pertaining to inequalities. The 2014 publication of A World That Counts report by the UN Secretary General’s Independent Expert Advisory Group on a Data Revolution for Sustainable Development called for a “data revolution” in order to support the SDG indicators that will be used to measure and monitor to sustainable development.

Income inequality Any assessment of the data on income inequality in the developing and transition economies of Europe, Turkey, and Central Asia must begin by calling attention to tensions between multiple and sometimes confusing data presented for the same country(s) on the one hand, versus the absence of publicly available, comparable data for other countries in the region on the other. Further complications result from the fact that the most common international data bases that show income distribution data for the countries of the region—such as POVCALNET or SWIID—often present data that differ from what can be found on the public websites of the national statistical offices in the region.

Table 1—Gini coefficients for income distribution available on national statistical office web sites Year Country Albania Armenia Azerbaijan Belarus BiH Georgia Kazakhstan Kosovo Kyrgyz Republic fYRoM Moldova Montenegro Serbia Tajikistan Turkey Turkmenistan Ukraine Uzbekistan

I I I C I I C C I I C I C I C I I C

2002

2005

2007

2008

2009 2010 No data

2011

2012

2013

2014

0.53

0.40

0.37

0.37

0.34 No data

0.36

0.36

0.37

0.37

0.37

-

0.26 -

0.33 -

0.30 -

0.27 0.33 0.41 0.46 0.31 0.32

0.27 0.41 0.45 0.29 0.27

0.27 0.42 0.46 0.27 0.30 0.25

0.27 0.43 0.46 0.28 0.29 0.25

0.29 0.41 0.43 0.28 0.23

0.28 0.4 0.42 0.28 0.22

0.28 0.4 0.41 0.28 0.22

0.36 0.32 0.37 0.25 0.41

0.37 0.30 0.37 0.26 0.42 No data

0.37 0.41 0.30 0.35 0.24 0.40

0.28 0.42 0.46 0.29 0.28 0.25 0.38 0.39 0.29 0.34 0.26 0.40

0.42 0.39 0.27 0.34 0.27 0.38 0.40

0.46 0.37 0.27 0.33 0.26 0.38 0.40

0.43 0.25 0.32 0.29 -

0.26

0.26

0.25 0.3

0.23

0.24

0.23 0.29

0.23

-

-

-

-

0.42 0.33 0.37 0.26 0.41

0.30

0.25

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I—income-based data; C—consumption-based data.

Gini coefficients. Although it is not listed as prospective SDG indicator, the Gini coefficient remains the most commonly used (and most available) indicator to measure income inequality in the region—as reported by national statistical offices (based on household budget survey data). However, as the data in Table 1 show, while Armenia, Belarus, Bosnia and Herzegovina (BiH), Kazakhstan, the former Yugoslav Republic of Macedonia (fYRoM), Serbia, Turkey, and Ukraine report Ginis measured in terms of income per se, Kosovo, Montenegro, Tajikistan, and Uzbekistan report Ginis measured in terms of consumption spending—while Georgia, the Kyrgyz Republic, and Moldova report both income- and consumption-based Ginis for income distribution. As the data for the Kyrgyz Republic show, differences in these series can be quite dramatic—suggesting very different conclusions about the extent of income inequality in a given country. An even greater concern is the fact that these data seem to be publicly available to very limited degrees (or not at all) in Albania, Azerbaijan, Bosnia and Herzegovina, Tajikistan, Turkmenistan, and Uzbekistan. That is: judging from publicly available national sources, only Armenia, Belarus, Georgia, Kazakhstan, the Kyrgyz Republic, Moldova, Montenegro, Turkey, and Ukraine report significant time series data on income inequalities.

A second perspective is offered by the Gini coefficients for income distribution available in the World Bank’s POVCALNET data base, which are shown in Table 2 below. These data, which are all consumption-based, indicate that reasonably complete and current time series are only available for Armenia, Belarus, Georgia, Kazakhstan, the Kyrgyz Republic, Moldova, Montenegro, Turkey, Ukraine, and possibly Kosovo.

A comparison of the data in Tables 1 and 2 suggest that, in terms of income inequalities as measured by the Gini coefficient, the countries of the region can be placed in four groups: 1) Countries in which the available data on balance point to low or falling income inequality. This group includes Belarus, Kazakhstan, Moldova, and Ukraine. Although the data are shakier, Kosovo and possibly Albania could be placed in this group as well.

2) Countries in which the available data on balance point to high or rising income inequality. This group includes Georgia and Turkey, and possibly the former Yugoslav Republic of Macedonia (although the data are shakier).

3) Countries for which data are available, but do not lend themselves to a clear judgement in this respect. This group includes Armenia, the Kyrgyz Republic, and Montenegro.

4) Countries for which the availability of national and international data (combined) is not sufficient for such an assessment. This group includes Azerbaijan, Bosnia and Herzegovina, Serbia, Tajikistan, Turkmenistan, and Uzbekistan.

Table 2—Gini coefficients for income distribution from the POVCALNET database Albania Armenia Azerbaijan Belarus BiH Georgia Kazakhstan Kosovo

2002 0.32 0.35 0.17 0.30 0.40 0.34 -

2003 0.33 0.19 0.30 0.40 0.33 0.29

2004 0.38 0.16 0.27 0.34 0.40 0.31 -

2005 0.31 0.36 0.17 0.28 0.40 0.30 0.31

2006 0.32 0.28 0.40 0.30 0.30

2007 0.30 0.29 0.33 0.41 0.29 -

2008 0.30 0.31 0.27 0.41 0.29 -

2009 0.30 0.28 0.42 0.29 0.32

2010 0.31 0.28 0.42 0.29 0.33

2011 0.31 0.26 0.42 0.27 0.28

2012 0.29 0.30 0.26 0.41 0.27 0.29

2013 0.32 0.40 0.26 0.27

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Kyrgyz Rep. fYRoM Moldova Montenegro Serbia Tajikistan Turkey Turkmenistan Ukraine Uzbekistan**

0.30 0.39 0.36 0.33 0.41 0.29 0.33

0.29 0.39 0.35 0.33 0.33 0.42 0.29 0.35

0.35 0.39 0.35 0.33 0.33* 0.41 0.29 -

0.38 0.39 0.36 0.30 0.33 0.42 0.29 -

0.38 0.43 0.35 0.29 0.30 0.40 0.30 -

0.33 0.34 0.31 0.29 0.32 0.38 0.29 -

0.32 0.44 0.35 0.30 0.28 0.38 0.27 -

0.30 0.33 0.30 0.29 0.39 0.25 -

0.30 0.32 0.29 0.30 0.39 0.25 -

0.28 0.31 0.31 0.40 0.25 -

0.27 0.29 0.32 0.40 0.25 -

0.29 0.33 0.00 0.25 -

* Average of two different values. **Based on econometric analysis.

These differences notwithstanding, a common pattern across the region can be seen when the income distribution data are considered over a longer period of time—particularly for those transition economies (not counting Turkey) for which longer time series are available. That is, income inequalities jumped sharply during the 1990s with the “transition recession”, as real incomes fell for the vast majorities of households, labour markets loosened, and social protection systems began to encounter increasing strains. The onset of “recovery growth” in the new millennium then saw reductions in income inequalities, as the income growth that was recorded for middle-class and low-income families apparently exceeded that reported for wealthy households.

Moreover, despite the impact of the global financial crisis of 2008-2009 and the Eurozone crisis of 2010-2012— both of which slowed growth in the region substantially—income inequality does not appear to have deteriorated (Figure 1).

Thus, for those countries for which longer time series are available, the data indicate that income inequalities have generally returned to “pre-transition levels”. A similar pattern is apparent (over a shorter time span) is apparent for Albania and Kosovo as well. Obvious exceptions to this pattern include Turkey (which is not a transition economy, and whose development since 1990 has followed a different logic) and Georgia—which reports similarly (to Turkey) high levels of income inequality.

Figure 1—Trends in Gini coefficients for income inequality in select countries of the region 0.50 Belarus

Kazakhstan

Moldova

Ukraine

Kyrgyz Rep.

0.40

0.30

0.20 1988

1998

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

POVCALNET data.

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Figure 2—Albania: Ratio of income of poorest two quintiles to national income (1996 = 100)

Figure 3—Armenia: Ratio of income of poorest two quintiles to national income (1996 = 100)

100

150

98

140

96

130

120

94

110

92

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2012

2003

2008

2002

2005

2001

2002

1999

1996

1996

100 90

UNDP calculations, based on POVCALNET data.

Other measures of income inequality. SDG target 10.1 calls for “income growth of the bottom 40% of the population at a rate higher than the national average”. As the below figures show, most countries in the region perform well against this “bottom 40” indicator. A number (Armenia, Kazakhstan, the Kyrgyz Republic, Moldova, Ukraine) score quite well; others (Albania, Georgia, Montenegro) less so.

Figure 5—Georgia: Ratio of income of poorest two quintiles to national income (1998 = 100)

110

110

105

105

100

100

95

95

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

1995 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Figure 4—Belarus: Ratio of income of poorest two quintiles to national income (1995 = 100)

UNDP calculations, based on POVCALNET data.

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Figure 6—Kazakhstan: Ratio of income of poorest two quintiles to national income (1996 = 100)

Figure 7—Kosovo: Ratio of income of poorest two quintiles to national income (2003 = 100) 110

130 125

105 120 115

100

110 95

105 100

90 2003 2005 2006 2009 2010 2011 2012 2013

UNDP calculations, based on POVCALNET data.

Other indicators (e.g., Palma ratios, or other ratios of the richest deciles to the poorest) of income inequality may be calculated on the basis of the quintile/decile income distribution data available on some national statistical office websites or POVCALNET. However, they do not show dramatically different pictures from what has been presented above.

Figure 8—Kyrgyz Rep.: Ratio of income of poorest two quintiles to national income (1993 = 100)

Figure 9—Moldova: Ratio of income of poorest two quintiles to national income (1999 = 100)

250

140

130 200 120 150 110

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

100

1999

1993 1998 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

100

UNDP calculations, based on POVCALNET data.

10

Figure 10—Montenegro: Ratio of income of poorest two quintiles to national income (2005 = 100)

Figure 11—Turkey: Ratio of income of poorest two quintiles to national income (1987 = 100)

105 110

100 105

95

100

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

1987

2005 2006 2007 2008 2009 2010 2011 2012 2013

1994

95

90

UNDP calculations, based on POVCALNET data.

Poverty, inequality, and inclusive growth Most of the countries of the region enjoyed strong economic growth during the first decade of the new millennium. While the global financial crisis pushed many of these economies into recession, as a rule they experienced a recovery during 2010-2013. This economic growth clearly helped reduce income poverty in the region: the most recent World Bank internationally comparable data (based on 2011 global purchasing-powerparity exchange rates) indicate that poverty rates (measured at the PPP$3.10/day threshold) have fallen in most countries. In this sense, growth in the region has been “pro-poor”. Moreover, in a number of economies—such as Albania, Belarus, Kazakhstan, Kosovo, the Kyrgyz Republic, Moldova, and Ukraine (Figures 13-19)—declining poverty rates have been accompanied by low falling Gini coefficients for income inequality. In countries such as Belarus and Ukraine, these continuing declines in poverty and inequality occurred in spite of slow economic growth, currency crises, and other macroeconomic challenges.

Figure 12—Ukraine: Ratio of income of poorest two quintiles to national income (1995 = 100) 150

140

Figure 13—Income poverty and inequality (Gini coefficient) trends in Albania (1996-2012) 0.35 0.30 0.25

130

Income poverty

0.20 120

110

Income inequality

0.15 0.10 0.05

1995 1996 1999 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

100 0.00 1996

2002

2005

2008

2012

11

UNDP calculations, based on POVCALNET data.

Figure 14—Income poverty and inequality (Gini coefficient) trends in Belarus (1998-2012)

POVCALNET data. Note—poverty rate percentages are:  Relative to the PPP$3.10/day threshold; and  As a rule greater than 1 (i.e., a .50 value implies a poverty rate of 50%, not 0.5%).

Figure 15—Income poverty and inequality (Gini coefficient) trends in Kazakhstan (1996-2013)

0.35

0.40

0.30

0.35 0.30

0.25

0.25 0.20 Income poverty 0.15

Income inequality

0.10

0.20 0.15

Income poverty Income inequality

0.10

0.05

0.05

0.00

0.00

POVCALNET data. Note—poverty rate percentages are:  Relative to the PPP$3.10/day threshold; and  As a rule greater than 1 (i.e., a .50 value implies a poverty rate of 50%, not 0.5%).

Figure 16—Income poverty and inequality (Gini coefficient) trends in Kosovo 2003-2013)

Figure 17—Income poverty and inequality (Gini coefficient) trends in the Kyrgyz Rep. (1993-2012)

0.35

0.80

0.30

0.70 0.60

0.25 0.20 0.15

0.50

Income poverty Income inequality

Income poverty

0.40 Income inequality 0.30

0.10

0.20

0.05

0.10

0.00 2003 2005 2006 2009 2010 2011 2012 2013

POVCALNET data. Note—poverty rate percentages are:  Relative to the PPP$3.10/day threshold; and  As a rule greater than 1 (i.e., a .50 value implies a poverty rate of 50%, not 0.5%).

12

Figure 18—Income poverty and inequality (Gini coefficient) trends in Moldova 1997-2013) 0.70

Figure 19—Income poverty and inequality (Gini coefficient) trends in Ukraine (1995-2013) 0.40

0.60 0.50

Income poverty

0.35

Income inequality

0.30 0.25

0.40

0.20

0.30

Income poverty

0.15

Income inequality

0.20 0.10 0.10 0.05 2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

0.00

0.00

POVCALNET data. Note—poverty rate percentages are:  Relative to the PPP$3.10/day threshold; and  As a rule greater than 1 (i.e., a .50 value implies a poverty rate of 50%, not 0.5%).

Figure 20—Income poverty and inequality (Gini coefficient) trends in fYRoM 1998-2008) 0.45

Figure 21—Income poverty and inequality (Gini coefficient) trends in Montenegro (2005-2013) 0.35

0.40 0.30 0.35 0.25

0.30 Income poverty 0.25

Income inequality

0.20

Income poverty

0.20

Income inequality 0.15

0.15 0.10 0.10 0.05

0.05 0.00

0.00 1998 2000 2002 2003 2004 2005 2006 2008

2005 2006 2007 2008 2009 2010 2011 2012 2013

POVCALNET data. Note—poverty rate percentages are:  Relative to the PPP$3.10/day threshold; and  As a rule greater than 1 (i.e., a .50 value implies a poverty rate of 50%, not 0.5%).

By contrast, in countries like the former Yugoslav Republic of Macedonia and Montenegro (Figures 2021), prospects for further poverty reduction seem to have been frustrated by relatively high or rising levels of income inequality. These trends confirm that, in addition to being “pro-poor”, economic growth in the region has also been “inclusive”—in the sense of reducing income inequalities as well as poverty. The experience of countries like Belarus and Ukraine also suggest that slow economic growth need not mean more poverty and inequality.

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Non-income inequality measures The Multiple Indicator Cluster Surveys (MICS) tool designed by UNICEF, to assess the well-being of women and children, has been used in more than 100 countries over the past twenty years, in five rounds. Most of the countries of the region have been covered. The MICS database contains data for a large number of indicators that have been disaggregated by gender, age, education level, ethnicity, and other vulnerability criteria.

For purposes of this report, the MICS database was examined for the countries of the region in terms of data corresponding to 12 proposed SDG indicators (Table 3).

Table 3—MICS data and proposed SDG indicators Proposed SDG indicator 3.1.1 Maternal deaths per 100,000 live births 5.b.1 Proportion of individuals who own a mobile telephone, by sex 7.1.1 Percentage of population with access to electricity 1.3.1 Percentage of population covered by social protection floors/systems, disaggregated by sex, and distinguishing children, the unemployed, the elderly, people with disabilities, pregnant women/newborns, work injury victims, the poor and vulnerable 3.2.1 Under-five mortality rate (deaths per 1,000 live births) 3.2.2 Neonatal mortality rate (deaths per 1,000 live births) 3.7.2 Adolescent birth rate (10-14; 15-19) per 1,000 women in that age group 4.2.1 Percentage of children under 5 years of age who are developmentally on track in health, learning and psychosocial well-being (disaggregated by sex, location, wealth, and other criteria, where possible).

6.1.1 Percentage of population using safely managed drinking water services

6.2.1 Percentage of population using safely managed sanitation services

MICS database Data for these indicators were only collected from one round of MICS survey Data for these indicators were collected from 2-3 rounds of MICS survey Data for these indicators were collected from 4 rounds of MICS survey

In terms of proposed SDG indicator 3.7.2 (adolescent birth rates per 1,000 women in the 10-14, 15-19 age groups, disaggregated by rural/urban residence—Figure 22): In general, fertility rates among women 15-19 years in Southeast Europe is lower than in CIS countries. In addition, these figures are almost twice as high in rural areas of the CIS countries as they are in other countries. These high birth rates mean that young women have early child bearing and rearing responsibilities, while they may in fact still be children themselves. Such circumstances can turn limit their ability to fully participate in social, economic, and professional life.

Early childbearing may also increase the risks of infant and child mortality, which corresponds to proposed SDG indicators 3.2.1 (under-five mortality rate, deaths per 1,000 live births) and 3.2.2 (neonatal mortality rate, deaths per 1,000 live births). An important role is often played by maternal education levels: infant mortality rates are often higher among less well educated women. As the data from the available countries, the average infant mortality rate of mothers with primary or incomplete secondary education is 50 (per 1,000 live births), versus 28 for women having secondary, vocational or higher education. Moreover, in almost all countries studied, infant and child mortality rates among the poorest 60% of the population were above those for the wealthiest 40% (Figures 23-24).

14

Figure 22—Fertility rates among young women 15-19 years (number of births per 1,000 women of the same age) in urban and rural areas 60 Rural

50

Urban

48 44

40 31.5

29

30 21 18

20

22

20

24

22

19

17.1 9

10 2

2

0 Bosnia and Herzegovina 2012

Kosovo 2014

Macedonia 2011

Serbia 2014

Kazakhstan 2012

Moldova 2012

Ukraine 2012

Montenegro 2013

Indicators measuring access to education and indirect indicators covering the SDG indicator Percentage of youth (15-24) not in education, employment or training (NEET), SDG target 8.6.1, it is an indicator of the proportion of eligible children attending secondary school. The data show that coverage is not universal. A significant role in the expansion of enrolment in secondary school is the level of household income. So, for both boys and girls, with an increase in the level of income is an increase in the proportion of eligible children attending secondary school (Figures 25-26). Children in poor families are forced to abandon their education and go to work to help support the household.

Figure 23—Child mortality rates (for children under 5 years of age) per 1,000 live births 54

Tajikistan 2005 Turkmenistan 2006 Uzbekistan 2006 Georgia 2005 Serbia 2006 Kazakhstan 2011 Albania 2005 Macedonia 2005 Moldova 2012 Ukraine 2012

100 64

46 22

62

44

26 24 6

73

33 35

26 25 11

5

0

19

10

20

40 Rischest 40%

60

80

100

120

Poorest 60%

15

Figure 24—Infant mortality rates per 1,000 live births 46

Tajikistan 2005 Turkmenistan 2006

79 61

54 39.5

Uzbekistan 2006 20

Georgia 2005

38 23

Serbia 2006

30

21

Kazakhstan 2011 6

Albania 2005

52

30

23

Macedonia 2005

22 11

Moldova 2012 Ukraine 2012

5

0

18

10

10

20

30 Rischest 40%

40

50

60

70

80

90

Poorest 60%

Figure 25—Percentage of children of secondary school age attending secondary school or higher (adjusted net attendance ratio) by wealth index quintiles, male 120.0 100.0

%

80.0 60.0 40.0 20.0 0.0 1

2

3

4

5

wealth index quintile

Figure 26—Percentage of children of secondary school age attending secondary school or higher (adjusted net attendance ratio) by wealth index quintiles, female

16

120.0 100.0

%

80.0 60.0 40.0 20.0 0.0 1

2

3

4

5

wealth index quintile

MICS indicators concerning access to safe drinking water and sanitation services correspond to SDG targets 6.1.1 and 6.2.1. MICS data also show that access to improved sanitation and drinking rises with income levels (Figures 27-28).

Figure 27—Users of improved sanitation facilities (4th, 5th round data) and users of sanitary means of excreta disposal (third-round data), % of population by wealth index quintiles 110.0 100.0 90.0

%

80.0 70.0 60.0 50.0 40.0 1

2

3

4

5

wealth index quintile

Figure 28—Users of improved water source, % population by wealth index quintiles

17

110.0 100.0 90.0

%

80.0 70.0 60.0 50.0 40.0 1

2

3

4

5

wealth index quintile

Middle classes in the region Many studies of inequalities naturally focus on the “most unequal”—the richest and the poorest, how many of them there are, what makes them this way, and how different they really are from the rest of us. But analyses of the “tails” of the income distribution are implicitly also concerned with the “middle” of the distribution, since a smaller middle makes for bigger tails (and vice versa). Studies of inequalities can therefore also be studies of the middle class—particularly since concerns about greater inequalities are often accompanied by concerns about middle classes.

Such issues are particularly relevant among the developing and transition economies of Europe, Turkey, and Central Asia. Prior to the 1990s virtually all of the region’s transition economies had “socialist” middle classes, consisting of well educated blue- and white-collar workers, engineers, and other members of the technical, creative, and administrative intelligentsia. While not necessarily commanding incomes or possessing wealth that corresponded to middle-class societies in OECD countries, these middle classes were forces of stability, and progress prior to the advent of transition. They certainly thought of themselves as possessing middle-class status.

Moreover, since the 1990s, many of these countries—as well as Turkey—have experienced significant increases in per-capita income. Their relatively low income inequality levels imply that millions of people in the region’s upper middle-income countries (Albania, Azerbaijan, Belarus, BiH, Kazakhstan, Kosovo, fYRoM, Montenegro, Serbia, Turkey, and Turkmenistan) could today be considered members of the “global middle class”—possibly with aspirations and world views to match.

How large are the region’s middle classes? How are they best defined and measured? Three approaches to answering these questions may be identified:   

Material well-being, as reflected in such criteria as per-capita income and wealth/property ownership (e.g., car(s), housing) and the corresponding ability to access certain services (e.g., education, health, travel); Subjective perceptions, concerning such issues as education, family background, and the associated social implications—based on individual self-identification; and “Neither rich nor poor”. To be a useful category of social analysis, the middle class (those in the middle of the socio-economic distribution) must be qualitatively and quantitively different from those in the tails.

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Many different approaches to defining and measuring the middle class can be found in the literature (for a subset of these, see Box 1). A key question that must be faced is whether the middle class is to be defined in terms of absolute criteria (e.g., “members of the middle class earn between ‘X’ and ‘Y’ per day/month/year”); or relative criteria (e.g., “if the rich are the top 10% and the poor are the bottom 20%, then the middle class is the middle 70%”).

Box 1—Methodologies for defining and measuring the middle class    

ILO: Members of the middle class have average daily per capita incomes in the PPP$4-13 range in developing countries, and above PPP$13/day in developed countries.

African Development Bank: Members of the middle class have average daily per capita incomes in the PPP$10-20 range.

OECD: Members of the middle class have average daily per capita incomes in the PPP$10-100 range.

Atkinson/Brandolini: Members of the middle class have average daily per capita incomes in the range of 75-125% of the median income.

In this report, we present the results of the application of two such approaches, both of which embody two key elements: (i) they are based on quantitative indicators that are methodologically compatible with the income equality data presented above; and (ii) they reflect both the “material well being” and “neither rich, nor poor” logic described above. These are: 

A relative approach, which defines the: o o o



Bottom two deciles of national household income distribution data as “lower-income” (i.e., relatively poorer than the middle class); Middle six income deciles as “middle class”; and Top two income deciles as “upper-income” (i.e., relatively richer than the middle class); and

An absolute approach, which defines the: o o o o

Poor as those living below the World Bank’s new global poverty threshold of PPP$3.10/day (with the extreme poor living below the PPP$1.90/day threshold); Vulnerable as those living below the PPP$10/day threshold, but on more than PPP$3.10/day; Middle class as those living below the PPP$50/day, but on more than PPP$10/day; and Upper class as those living on more than PPP$50/day.

Results of the “relative” approach. Trends in the evolution of the middle classes in the region’s transition economies generally show similar pattern: their share of the national income fell in the 1900s (during transition recessions) and then recovered after the new millennium. In most of these countries, the middle classes’ shares of national income are now at, or above, pre-transition levels.

Virtually all of the variation in middle classes’ shares of national income can be explained by offsetting changes in upper-income classes’ shares of national income. The shares of national income received by the bottom two deciles have remained surprisingly constant over time (at around 8-10% of national income) in most of the region.

In all but two countries in the region (Georgia and Turkey—Figures 29-30), the middle classes’ shares of national income have generally been significantly larger than the upper-income classes’ share. In Georgia and Turkey, by contrast these two shares are roughly constant (at 45-50%). The shares of national income received by the bottom two deciles in these countries have been the smallest in the region (fluctuating around 5%).

19

Figure 29—Shares of national income received by middle, other classes—Georgia (1996-2013)

Lower income

Figure 30—Shares of national income received by middle, other classes—Turkey (1987-2012)

60%

60%

50%

50%

40%

40% Lower income

30%

Middle class Upper income

30%

Middle class 20%

Upper income

20%

10%

10%

0%

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

0%

UNDP calculations, based on POVCALNET data. The “middle class” is defined as the middle six deciles (“middle 60%”) of the national income distribution. The other classes are defined in terms of the top and bottom two deciles (upper and lower 20%), respectively.

Figure 31—Shares of national income received by middle, other classes—Belarus (1988-2012)

60%

50%

50%

40%

40%

30%

Middle class

20%

Upper income

20%

Upper income

2013

2012

2011

2010

2009

2008

2005

2004

2003

2002

0% 2001

0%

1996

10%

1993

10%

1988

1988 1993 1995 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

30%

Lower income

2007

Middle class

60%

2006

Lower income

Figure 32—Shares of national income received by middle, other classes—Kazakhstan (1988-2013)

UNDP calculations, based on POVCALNET data. The “middle class” is defined as the middle six deciles (“middle 60%”) of the national income distribution. The other classes are defined in terms of the top and bottom two deciles (upper and lower 20%), respectively.

20

Figure 33—Shares of national income received by middle, other classes—Kosovo (2003-2013)

Figure 34—Shares of national income received by middle, other classes—Ukraine (1988-2013)

60%

60%

50%

50%

40%

40%

30%

Lower income

30%

Lower income

Middle class

Middle class

20%

20%

Upper income

Upper income

10% 10% 2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

1999

1996

1995

2003 2005 2006 2009 2010 2011 2012 2013

1992

1988

0% 0%

Economies with the largest middle classes (e.g., Belarus, Kazakhstan, Kosovo, Ukraine—Figures 31-34) also tend to have the largest shares of national income received by the bottom two deciles, and the smallest shares of national income received by the richest 20%.

Figure 35—Changes in absolute numbers of middle, other classes in the region (2000-2013) 10 7 28

103

8 7 26

100

9

9

34

35

114

115

12

2 14

2 16

1 20

43

52

56

60

111

103

102

98

25 14

31

15

21 9

20 9

16 5

13 6

11 4

10 3

2000

2001

2002

2003

2004

2005

2006

2007

Extreme poverty

Poverty

Vulnerable

6 20

65

92

8 2 2008

Middle class--lower tier

8 18 61

96

8 2 2009

16 21

24

25

32

22

25

25

64

65

66

86

78

75

70

6 2 2010

6

5

5

64

2011

2012

Middle class--upper tier

2013 Wealthy

UNDP calculations, based on POVCALNET data. Figures are in millions. Turkmenistan and Uzbekistan are not included.

On the whole, the income distribution data do not describe a region whose middle classes have been decimated by transition or development. They instead broadly suggest a return to pre-transition income shares.

In light of the region’s generally low Gini coefficients, this conclusion should not come as a surprise. Still, it stands in contrast with many of the narratives. It may be that the truly relevant changes are occurring within the deciles (especially the bottom two) rather than across them—or that quantitative data are unable to accurately capture

21

the truly wrenching social changes that these countries have experienced in the past 25 years. Still, these results provide food for thought.

Results of the “absolute approach”. Compared to the above analysis, this approach has a number of advantages. These include inter alia: (i) explicit links to global poverty thresholds—thereby linking absolute and relative poverty (i.e., inequality) measures; (ii) an extension of the previous approach’s three-tiered social stratification, to include also those vulnerable to poverty (i.e., living above the poverty line but not necessarily in the middle class)—and also (if we so chose) those living in extreme poverty (i.e., below the World Bank’s new PPP$1.90/day threshold), as well as different tiers within the middle class (i.e., those living between PPP$10/day and PPP$20/day, versus those living between PPP$20/day and PPP$50/day); and (iii) answers to such questions as “how many people in country X have incomes above $20/day?”

This analysis suggests that, during 2000-2013, the numbers of people in the region living in poverty fell from 46 million in 2001 to about 5 million in 2013 (Figure 35).6 (The numbers of people living in extreme poverty, as per the World Bank’s PPP$1.90/day criterion, dropped below 1 million.) Likewise, the numbers of people vulnerable to poverty (i.e., in the PPP$3.10/day – PPP$10/day range) dropped from about 115 million in 2003 to some 70 million in 2013. By contrast, the size of the middle class grew from about 33 million in 2001 to 90 million in 2013. Interesting, after nearly disappearing 2002-2004, the numbers of “wealthy” individuals (living on more than PPP$50/day) had risen to some 32 million in 2013—most of whom were living in Turkey and Kazakhstan.

Adding the 25 million individuals estimated to be living on between PPP$20/day and PPP$50/day to this figure suggests that nearly 80 million people in the region have achieved living standards that are broadly consistent with the bounds of the “global middle class”.

Figure 36—Changes in shares of middle, other classes in the region (2000-2013) 6% 4% 15%

55%

4% 4% 14%

54%

14%

17%

7% 2000

5%

5%

18%

19%

61%

61%

1% 6% 23%

59%

1% 7% 28%

54%

1% 8% 29%

54%

1% 10% 31%

51%

3% 10%

4% 10% 32%

34%

49%

48%

8%

12%

13%

11%

13%

33%

33%

44%

40%

38%

35%

11%

33%

16% 12%

33%

8%

11% 5%

11% 5%

9% 3%

7% 3%

6% 2%

5% 2%

4% 1%

4% 1%

3% 1%

3% 1%

2% 1%

2% 1%

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

Extreme poverty

Poverty

Vulnerable

Middle class--lower tier

Middle class--upper tier

Wealthy

UNDP calculations, based on POVCALNET data. Turkmenistan and Uzbekistan are not included.

Consideration of these trends in terms of changes in the relative size of the various classes shows that, whereas more than three quarters of the region was living in poverty or vulnerable to it during 2000-2003, by 2013 this share had dropped to under 40%. While the middle classes were the chief beneficiaries of these improvements in living standards, it is interesting to note that the share of those living on more than PPP$50/day had risen to 16% in 2013 (from close to zero in 2002-2003).

6

These data do not include Turkmenistan and Uzbekistan.

22

In broad brush strokes, these results are quite consistent with those suggested by the “relative” approach to defining the region’s middle classes described above. They also do not describe a region whose middle classes have been decimated by transition or development. An important difference lies in the two approaches’ treatment of the wealthy, however. Whereas the relative approach shows the upper classes’ shares of national income remaining roughly constant or shrinking in most of the region, the absolute approach points to the rapid growth in this group’s share of total income from virtually nothing in 2003 to 16% a decade later.

This may be able to explain the widespread concerns about growing inequalities in the region—even if the distribution of total household incomes (as measured in deciles) has not changed so dramatically.

How rich are the region’s rich?

Global household wealth is unequally distributed: there are an estimated 31 million millionaires and more than a thousand billionaires (in US dollar terms) in the world. As one authoritative source notes: “The bottom half of the global population together possess less than 1% of global wealth. In sharp contrast, the richest 10% own 86% of the world’s wealth, with the top 1% alone accounting for 46% of global assets” (Credit Suisse Global Wealth Databook, 2013).

Chart 1--The region's billionaires (in billion US$) 3.9

top ranking second to the top bottom ranking

5.3

2.3

1

2.2 1.9 1.4

5.2 1.4 1

Turkey 3.9

Kazakhstan 2.2

Ukraine 5.3

2.3

1.9

1.4

1

1.4

1

top ranking

second to the top

Georgia 5.2

bottom ranking

UNDP calculations based on Forbes’s list of real-time billionaires.

A quick browse through Forbes’ most recent billionaires list7 shows that only 33 (2%) come from the developing and transition economies of Europe, Turkey, and Central Asia.8 Turkey is responsible for 22 of these, followed by Ukraine and Kazakhstan (five each) and Georgia (with one). Five of these are women (four from Turkey, one from Kazakhstan). Interestingly, large differences in wealth are apparent between these billionaires: the richest billionaire in Turkey is some four times richer than the “poorest” billionaire; in Ukraine the gap is fivefold. Wealth is predominantly and accumulated via the natural resources and banking sectors of economy; construction and pharmaceuticals are specific to Turkey. Interestingly, one billionaire in Ukraine makes money in the agricultural sector.

7http://www.forbes.com/billionaires/list/#version:realtime

(last consulted on 16 January 2016) Of course, rich lists are just estimates.

They are popular precisely because they’re willing to put a hard dollar number on the personal wealth of the super-rich. Yet in truth, no one really knows what many of the super-rich are worth at any given moment (including the super-rich themselves). Many of them own private companies, which are hard to value until they’re sold. And they often have debts, other accounts, financial obligations and investments that don’t show up to the public.

8 Reference is to the programme countries/territories whose development aspirations are supported by UNDP’s Regional Bureau for Europe and CIS. These are: Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Georgia, Kazakhstan, Kosovo (as per UNSCR 1244 (1999)), Kyrgyzstan, the Former Yugoslav Republic of Macedonia, Moldova, Montenegro, Serbia, Tajikistan, Turkey, Turkmenistan, Ukraine, and Uzbekistan

23

According to the Global Wealth Report, the numbers of millionaires in the region dropped by some 95% during 2010-2015 (Figure 37). Perhaps more usefully, the Global Wealth Report also estimates Ginis coefficients for the distribution of wealth, in the region as well as globally (Table 3). A number of conclusions are suggested by these estimates. First: with the exceptions of Kazakhstan, Turkey, and Ukraine, inequalities in the distribution of wealth generally remained the same or declined during this time. Second, inequalities in wealth in most of the region are generally below world averages. This also can be seen as a legacy from the region’s socialist past, when significant private holdings of wealth as such did not exist. (In light of the large share of state property that remains in state hands in much of the region, the role of the state may not be a legacy.)

Figure 37--The region's millionaires 2259 1903

2010

2011

114

116

113

59

2012

2013

2014

2015

Table 3—Gini coefficients for the distribution of wealth in the region (2010-2015) 2010 2011 2012 2013 2014 Albania 0.68 0.654 0.657 0.656 0.668 Armenia 0.668 0.644 0.639 0.639 0.668 Azerbaijan 0.612 0.595 0.652 0.651 0.646 Belarus 0.648 0.637 0.624 0.622 0.646 BiH 0.678 0.665 0.659 0.658 0.663 Georgia 0.703 0.684 0.79 0.68 0.68 Kazakhstan 0.658 0.863 0.838 0.867 0.873 Kyrgyz Republic 0.673 0.659 0.66 0.659 0.646 fYRoM 0.727 0.694 0.689 0.688 0.69 Moldova 0.688 0.671 0.648 0.647 0.68 Montenegro 0.652 0.669 0.635 0.634 0.657 Serbia 0.645 0.635 0.626 0.625 0.654 Tajikistan 0.669 0.657 0.638 0.638 0.629 Turkey 0.704 0.844 0.842 0.837 0.843 Turkmenistan 0.68 0.667 Ukraine 0.64 0.889 0.892 0.9 0.919

2015 0.658 0.628 0.591 0.65 0.67 0.666 0.874 0.633 0.693 0.674 0.658 0.661 0.624 0.821 0.673 0.916

Africa Asia-Pacific China Europe

0.856 0.892 0.733 0.834

0.849 0.869 0.69 0.799

0.872 0.881 0.697 0.829

0.865 0.889 0.689 0.831

0.846 0.887 0.695 0.83

0.856 0.895 0.719 0.827

24

India Latin America North America World

0.778 0.785 0.799 0.881

0.804 0.793 0.816 0.893

0.813 0.797 0.842 0.902

0.813 0.806 0.841 0.905

0.814 0.809 0.837 0.911

0.831 0.809 0.842 0.915

Conclusions For those who are concerned about the global effects of increasing inequalities, the above analysis of the quantitative data on the distribution of income and wealth in the region suggests a reassuring picture. Many of the developing and transition economies of Europe, Turkey, and Central Asia (with a few exceptions) report low, or declining, levels of income inequality; estimates of the distribution of wealth that are based on internationally comparable methodologies propose the same results. However, such a picture is at odds with many commonly accepted narratives about the region—which tend to reference large and growing inequalities in income, wealth, access to basic services, and other important aspects of human development.

This raises the question: what’s wrong—the data, or the perceptions? To be sure, the quality of the data on income and wealth inequalities in the region is not beyond reproach. For example, that the household budget survey data from which the income inequality indicators that populate both national and international data bases are drawn are widely recognized as missing both the very poor (who typically slip between the cracks of national surveying activities) and at least a portion of the incomes of the very rich. It is telling, for example, that the POVCALNET database reports that virtually no one in the region earns more than PPP$100/day—millionaires and billionaires (as reported by Forbes) notwithstanding. Part of this may be due to the reliance on consumptionbased surveys that underpin internationally comparable databases like POVCALNET. Such surveys do not reflect incomes earned but not spent on consumption—which, in the case of wealthy households (with high average propensities to save)—may further understate the shares of national incomes distributed to wealthy households.

All this underscores the need for more investment in national statistical offices’ capacity to conduct regular household budget surveys that accurately capture (according to internationally comparable methodologies) the entirety of household incomes—including those shares that are not consumed.

Still, these data should not be dismissed out of hand. Declines in income inequalities in many Latin American countries during the past decade have been well documented; there’s no reason that other developing regions can not report similar tendencies. Perhaps more serious questions concern whether those economies in the region that seem to have made the most progress in reducing income inequalities—Albania, Belarus, Kazakhstan, Kosovo, Moldova, Ukraine—will be able to maintain these accomplishments in the face of the socioeconomic tensions that are now present in the region.

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Chapter 2—Inequalities, employment, and social protection9 Key messages 

Labour market inequalities and exclusion lie at the heart of the region’s10 inequality challenges. This is the case both in terms of labour markets per se, and because access to social protection is often linked to formal labour market participation. People without decent jobs face much higher risks of poverty, vulnerability, and exclusion from social services and social protection.



While labour market inequalities exist in many dimensions, they are particularly important when it comes to access to formal employment. Because informal, precarious, migratory, and vulnerable employment is widespread throughout the region, employment does not necessarily offer much protection against poverty and vulnerability. Women, young workers, migrants, the long-term unemployed, people with disabilities, and others with unequal labour market positions are particularly vulnerable to broader risks of poverty and exclusion. While trends are improving in some countries and for some groups, in others, labour market inequalities are increasing.



Many commonly used labour market indicators offer only limited insights into labour market performance and equalities. This is apparent in the “employment”/”unemployment” statistical dichotomy, and in the infrequency with which publicly available labour-market data are disaggregated by gender, ethnicity, and other vulnerability criteria. Different labour market statuses—inactivity, unemployment, underemployment, informal employment, formal employment, migrant work, etc.— should be understood as representing points along multi-dimensional continua of labour market positions, with much overlap and fluidity between the categories. Inequalities among the employed can be as great, or greater, than those between the employed and unemployed.



Long-term efforts to formalize employment are crucial. Three directions are particularly important: (i) efforts to boost the institutional capacity of the institutions charged with labour market regulation, in order to better enforce legal protections for workers’ rights in the formal sector; (ii) the abolition of those labour market regulations that can not be credibly enforced by state agencies and drive employment into the informal sector; and (iii) increased investment in active labour market policies, vocational education, and other measures to boost worker productivity.



Policy linkages between labour markets and social protection need to be strengthened. While poorly aligned social policies can reduce incentives for labour market participation and hiring, this is not a reason for reducing social protection spending and coverage. Instead, wherever possible, the taxation of labour to fund social benefits needs to be reduced in favour of other funding sources. These may include: (i) higher taxes on environmentally unsustainable activities; (ii) reductions in budget subsidies that accrue to the wealthy; (iii) more aggressive measures to reduce the diversion of budget revenues to tax havens; and (iv) more robust direction of budgetary procurement and contracting resources to companies (e.g., social enterprises) that explicitly promote social inclusion. The region’s prevailing demographic trends indicate that needs to find non-labour sources of budget revenues will sharpen in the future.



Social protection is also about social services and the care economy. Increased investments in social service provision—particularly terms of care for children, the elderly, and persons with disabilities—can boost participation in labour markets and vocational training programmes, particularly for women. In Turkey, for example, a decision to bring state budget spending on social care services up to OECD levels

9

Please send comments on this chapter to Sheila Marnie (sheila.marnie@undp.org) and Ben Slay (ben.slay@undp.org).

Unless otherwise noted, reference in this publication is to Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Georgia, Kazakhstan, Kosovo (as per UNSCR 1244 (1999)), the Kyrgyz Republic, the Former Yugoslav Republic of Macedonia, Moldova, Montenegro, Serbia, Tajikistan, Turkey, Turkmenistan, Ukraine, and Uzbekistan.

10

26

would generate an estimated 719,000 social care jobs—more than 2.5 times the total number of jobs that would be created by devoting the same amount of budget funds to construction/infrastructure projects. An estimated 84% of the workers hired into these social care jobs would have permanent contracts of unlimited duration (versus 25% in construction); 85% would have social security coverage (compared to 30% in construction). 

In many countries, gaps between de jure social protection guarantees and de facto access to social benefits and services are significant and growing. Addressing these gaps balancing centralized social protection and employment schemes with more scope for locally provided, more flexible and individualfocused modalities of inclusion.



Many of those excluded from the labour market are not reached by traditional active-labour market programmes. This is due in part to weaknesses in outreach to vulnerable communities (e.g., ethnic minorities, low-skilled workers in rural communities), but also to chronic under-funding.

Overview Labour market inequalities concern not only differences between those who are employed and those who are not, but also among those who are employed. In most countries of the region, those who are in precarious, informal, low wage, low productivity jobs can easily suffer the same (or worse) risks of poverty and exclusion as those who are without jobs. Inequalities among the employed can be as great, or greater, than those between the employed and unemployed.

However, these disparities are not easy to unravel using standard labour market indicators and data.

While these may help ensure international comparability, they often fail to capture critical dimensions of labour market and broader social inequalities. As such, they may provide a poor basis for policy design and implementation. Low labour force participation rates and (in some countries) high unemployment figures underscore problems of labour market exclusion for significant sections of the working age population. But even within the employed population there are clearly inequalities affecting individual and household welfare, as evidenced by the data on the “working poor”, and on informal and vulnerable employment. Many of those at the bottom of the income scale cannot afford to be “idle”; they may have little choice but to engage in low quality or vulnerable employment. Given the restrictive criteria for defining the unemployed, and the low level and limited duration of support for registered unemployed, many workers without jobs do not register. They either withdraw from the labour force, accept low-quality jobs, or join the army of labour migrants.

It is difficult to characterize or generalize about these inequalities within the employed population. The ILO’s “decent work” paradigm—as opposed to precarious, vulnerable, or informal sector work—can certainly help. But quantifying the share of the workforce enjoying decent work is extremely complex. Some authors refer to dual labour markets, between those in formal and those in informal employment; or between those in decent jobs and those in non-decent jobs. But even here, reality is often more complex than dichotomous, black-andwhite characterizations. For example, public sector employees may have more job security and better access to social protection—but their wages may be so low as to make them part of the “working poor”. Informal sector workers may not enjoy labour rights or social protection, but they may be able generate incomes that are sufficient to keep themselves, and their families, out of poverty. Moreover, even workers who are formally employed may receive significant shares of their wages in the form of unregistered (and therefore untaxed) cash under the table.

Unequal employment opportunities have also led to large internal and external migration flows—many of which exhibit high degrees of irregularity/informality. While these movements can raise income and development opportunities for migrants and their families, they are also associated with many risks and insecurities. They may also contribute to new forms of inequalities, most notably between those households with migrant members and access to remittances, and those without.

27

UNDP’s 2011 Regional Human Development Report showed that, while joblessness heightens the risk of economic exclusion, but it also tends to be associated with other forms of deprivation which together heighten individual risks of exclusion. Exclusion from employment opportunities were found to be a major driver of exclusion from economic life, which in turn contributed to exclusion from social and political processes.11 Drivers of labour market exclusion include the capital- and resource- (as opposed to labour- ) intensive economic growth patterns which have taken root. These often result in the paucity of decent, formal, private sector jobs. This can be attributed to a lack of structural reforms to strengthen institutional capacity in both the private and state sectors. But it also reflects the low priorities often ascribed to employment goals, reflecting the (often mistaken) belief that economic growth would automatically lead to more and better jobs. But while it is now widely understood that this link is not automatic, governments have been slow to put in place the institutional frameworks needed to design and implement comprehensive national employment policies. The success of efforts to address the considerable skills mismatches that stand behind many cases of labour market exclusion (particularly for young workers) has not been especially noteworthy.

Helping economic growth to boost decent job opportunities requires holistic, whole-of-government approaches—particularly in terms of the links between employment and social protection policies. Most countries in the region inherited social protection systems that were designed to complement full or near-to-full employment situations. In circumstances of entrenched joblessness, however, proposals to compensate for the lack of formal employment opportunities by providing minimum income floors have often encountered opposition, in the form of concerns about excessive fiscal burdens and disincentives for labour market participation. Many workers have therefore had to seek informal employment—thereby losing access to social insurance (e.g., health and pension insurance) as well as other benefits (e.g., maternity leave) and protections nominally guaranteed by law.

Efforts to promote decent jobs and strengthen social protection in the region must therefore focus on addressing drivers of informality. Three directions seem particularly important in this respect: 

Efforts to boost the institutional capacity of the institutions charged with labour market regulation, in order to better enforce legal protections for workers’ rights in the formal sector. In too many cases, inspections that identify violations of commercial, labour, migration, or social protection legislation are dealt with through payment of bribes—which are seen as necessary to provide a living wage for the (not always fully trained) civil servants working in these inspectorates. Civil service and public administration reforms to raise public-sector salaries and reduce other drivers of corruption and malfeasance that distort labour market regulation.



The reconsideration of taxes and regulations that can not be credibly collected or enforced by state agencies and drive employment into the informal sector. Regulations and taxes that place inordinate burdens on SMEs, or migrants and other vulnerable workers, need to be reconsidered or abolished.



Increased investment in active labour market policies, vocational education, and other measures to boost worker productivity.

Labour market inequalities Inequalities in employment outcomes and opportunities are in practice difficult to separate. Both are reflected in low employment rates, as well as in high rates of long term unemployment, as well as informal, vulnerable, and migratory employment.

11

See for example RHDR 2011, pp18-19.

28

Labour force participation rates in the region vary from relatively high (70-80% of the working age population) to below 50% in others ( Figure ), while the average regional unemployment rates of those who are participating in the labour force was 9.6 percent in 2014.12 Employment and participation rates tend to be particularly low in the Western Balkans, and much higher in Central Asia. And whereas employment rates declined in much of the region after the early 1990s, they have generally returned to “pre-transition� levels in Central Asia and the Caucasus.

Figure 1. Labour Market Status of Working Age Population in 2014 90

Unemployment as % of population 80

Employment rate Regional employment rate (weighted average)**

70 60 50 40 30 20 10 0

KAZ AZE KGZ TJK GEO TKM UZB UKR ARM BLR ALB TUR SRB MNE MKD MDA BIH KOS*

Source: ILO, 2015, KILM 9th ed. * 2012 figure; ** not including Kosovo under UNSCR 1244.

Figure 2. Labour force participation (left) and employment rate (right), working age 70

65 Central Asia Central Asia

65

60

55

50

45

12

60

South Caucasus and Western CIS

ECIS* South Eastern Europe*

55

50

45

South Caucasus and Western CIS

ECIS*

South Eastern Europe*

40

ILO, 2015, World Employment and Social Outlook. Figure for 2014.

29

Source: Calculations based on ILO, 2015, KILM 9th ed. * except for 2012 and 2013, averages do not include Kosovo under UNSCR 1244.

Figure 1. Unemployment by sub-region for working-age population, over time (left) and in 2014 (right)

14

100% South Eastern Europe*

80%

Active

16

60%

12

ECIS* Central Asia

Jobless

10

40% 20% 0% Central Asia

8 South Caucasus and Western CIS 6

South Caucasus and Western CIS

South Eastern Europe*

ECIS*

Employment rate Unemployment as % of population Inactive

Left: Regional and sub-regional unemployment rates (weighted averages). Right: Sub-regional breakdown of labour market for working age population, 2014. Source: Calculations based on ILO, 2015, KILM 9th ed. * except for 2012 and 2013, averages do not include Kosovo under UNSCR 1244.

In some countries, and in all the Southeast European economies, employment rates are below 50% of the working age population. The economic crisis of 2008-2009 resulted in the loss of many jobs, which is clearly reflected in the unemployment trends (Figure 3). Although in most countries, economic growth recovered relatively quickly, in some countries employment rates have been slower to recover. The impact on youth participation and employment rates has been particularly stark (discussed further below).

Long-term unemployment (LTU) is usually defined as unemployment lasting for over 12 months.

Available data indicate high LTU incidence in the Western Balkans, where 70-90% of the unemployed have been searching for employment for longer than 12 months (Figure 4). Considering the overall high unemployment rates in these countries, this makes for a substantial section of the working age population. A study using different data13 shows a high incidence of LTU in Azerbaijan, wherever 50% of the unemployed were found to have been searching for jobs for over 12 months, and 75% were not officially registered. (Of those registered, less than 5% were receiving social benefits.) Long-term unemployment manifests itself more strongly among certain social groups, such as Roma (discussed further below).

Figure 2. Unemployment and LTU for working-age population, latest available data

13

UNDP / Martina Lubyova, 2013, Towards Decent Employment through Accelerated Structural Reform in Azerbaijan.

30

35 30 25 20 15 10 5 0

Unemployment rate in 2014

LTU

Source: ILO, 2015, KILM 9th . Unemployment data for 2014 * unemployment data for 2012; ** average does not include Kosovo under UNSCR 1244. Latest available LTU data for various years 2009-2014 (see Statistical Annex).

Labour market gender differences are significant throughout the region. These differences are particularly visible in the Caucasus and Central Asia, but also in some Southeast European countries such as Bosnia and Herzegovina and Turkey. Worryingly, in most countries, gender inequalities on the labour market, as measured by the inactivity rate are increasing. Long-term unemployment has particularly strong gender dimensions in Central Asia: in all the countries of this sub-region except for Kazakhstan, gender gaps in labourforce participation rates have been increasing.

Figure 3. Adult labour force participation rate gender gap, male minus female 50

40

30

20

10

0

-10

TUR KOS* TKM UZB MKD BIH KGZ ALB GEO TJK ARM SRB MNE UKR BLR KAZ AZE MDA 2014-2005

2014

Gender gap in labour force participation for 2014, and change in the gender gap over 2014-2005 period.

Source: Calculations based on ILO, 2015, KILM 9th ed.

31

Overall, standard labour market indicators point to worrying disparities in employment outcomes, which in turn suggest considerable inequalities in employment opportunities. They also point to significant differences in employment outcomes by sub-region, with Southeast European countries having more troubling indicators than Central Asia, the South Caucasus and Western CIS countries. However, as discussed below, the standard indicators may be unable to fully capture labour market disparities in the region, largely because they do not capture the quality of employment. Central Asia may have higher participation rates and lower unemployment rates than the Southeast European countries, but few would argue that the quality of employment is better, or that there is less vulnerability.

Limitations of standard employment indicators Such standard labour market indicators as labour force participation, employment, and unemployment rates cannot in themselves capture the full extent of inequalities in the labour market in the region, for several reasons.

First: the employment rate shows the share of the working-age population that is engaged in a productive activity—irrespective of whether this activity corresponds to full time, regular, formal and decent employment. This indicator does not distinguish between those who work “normal” or regular work hours on regular contracts, versus those on shorter and unstable work schedules. Nor does it indicate whether the activity is in the formal or informal sector, and therefore whether the individuals in question have rights to protection, a safe working environment, and to social insurance coverage. This indicator thus gives no indication of the quality of the employment enjoyed by different sections of the workforce, and the extent of under-employment and low quality, low wage employment.14 A person working a 40-hour week as an employee of a formal sector enterprise will be counted as employed, in the same way as somebody working in a temporary job for 1-2 hours a day, or as a self-employed farmer, working informally on a small plot. To give some examples: 

Kazakhstan has the highest participation rate in the region (at just under 80% of the working age population), but some 30% of the employed workforce is self-employed, with the majority engaged in small scale low-productivity agricultural activities.15



In Azerbaijan (the country with the second highest participation rate in the region), 37% of the workforce (and 44% of the female workforce) is employed in agriculture, which accounts for just over 5% of GDP.16 This disparity results in low rates of labour productivity, and therefore low agricultural incomes.



Kyrgyzstan and Tajikistan have high participation rates, but also some of the largest shares of working poor and vulnerable employment (see below), as well as labour migrants in the region—suggesting that the number and quality of employment opportunities are insufficient.

Second: the unemployment rate is usually seen as a measure of the lack of employment opportunities: the proportion of people who do not have a job but are “actively” looking for one. This definition is also problematic, particularly in those countries with low labour force participation rates. As one analyst puts it: “most ‘potentially’ unemployed persons either do not ‘actively’ search for employment, falling in the category of ‘discouraged workers’, or seek out a living in the overcrowded informal economy, in a state often described as ‘disguised unemployment’”.17 Variations in the eligibility criteria used for registering the nature and duration of unemployed status may also affect incentives for job-seekers to register as unemployed or engage in job search activities (i.e., stay in the labour force)—thereby influencing reported labour-market trends. In some countries 14

see ILO’s standard definition, used to derive employment indicators from Labour Force Surveys. Экономическая активность населения Казахстана 2010-2014, Kazakhstan State Statistical Committee 2015 16 http://www.worldbank.org/en/news/feature/2015/01/06/jobs-challenge-in-the-south-caucasus-azerbaijan; Lyubova/UNDP 17 Ghai, D., 2003, Decent Work: Concepts and Indicators. International Labour Review, 142(2), 113-145.

15

32

these criteria are more restrictive, in order to limit entitlements to unemployment and other benefits; whereas in other countries they are more generous. (In some countries of the region, less than one per cent of the unemployed receive benefits.18) Seen in this light, the quality of the unemployment rate as an indicator for capturing those affected by lack of employment opportunities is problematic.

Third: assessments of labour market performance in the region are sometimes confused by data quality questions for those indicators that are reported. Differences in reported unemployment rates sometimes reflecting differing methodologies used to collect the underlying data (e.g., labour force surveys versus registration data reported by employment offices). The region’s large circular and irregular migration flows tend to depress reported labour force participation rates, as migrants working abroad may be included in domestic populations (as per national census data) but not counted by labour force surveys as labour force participants or among the employed. While not unique to the transition and developing economies of Europe, Turkey, and Central Asia, these lacunae may further complicate the interpretation of labour market data in the region.

Measures to improve labour market statistics are crucial for more effective policy making. So are efforts to ensure the regularity of published data on employment and/or migration flows, which allow disaggregation by socio-economic (gender, age, rural/urban location, conflict impact) vulnerability criteria. Innovative ways of combining quantitative and qualitative data collection and analytical methods are also required in order to understand the inequalities within the employed, and the barriers facing those not participating in the labour market.

Employment quality and the disadvantaged within the labour force While the ILO manual on Decent Work Concepts and Indicators sets out 10 different types of work, these can be generally be treated in terms of: (i) productive work delivering a fair income; (2) safety in the workplace; and (3) access to social protection for workers and their families. Low quality employment can be “precarious” if it entails unfavourable or short-term contracts. Informal employment (much of which is precarious) falls into two main categories: work in informal (unregistered) enterprises, and paid work in the formal sector (registered enterprise) but under informal conditions (without core benefits, workers’ rights, or a written contract). While the former is more common in rural areas (where agricultural work is prominent), the latter is more commonly found in urban areas.

Figure 4. Share of informal employment, 2013

18

ILO, 2014, World Social Protection Report 2014/15.

33

70 60 Total

Outside agriculture

In agriculture

50 40 30 20 10 0 ALB

ARM

TUR

MDA

KAZ

MKD

SRB

Source: ILOSTAT, 2015, countries with available data.

Precarious and informal employment in the region is particularly prominent in agriculture: in many countries agriculture accounts for more than a third of the employed population (Figure 7). In Ukraine, for example, two-thirds of informal employment take place in agriculture;19 in Armenia, this share has been reported as close to 100%.20 Such employment often consists of low-productivity agricultural self-employment on small plots. Incomes from such work are highly unstable, due to poor harvests or fluctuating farm gate prices. For these reasons, agriculture is often considered to be a buffer between employment and unemployment or inactivity, or as “hidden unemployment”. For example, following the 2008-20099 financial crisis in Armenia, agriculture was the only sector to report employment growth.21 Employment in agriculture therefore often meets the criteria for non-decent work: low and unstable income, and no or insufficient social protection coverage.

On the other hand, formal sector employment is not always “decent”, and can also be associated with low wages and poverty risk. For example, while public sector workers in Kazakhstan may enjoy regular contracts and access to social protection, 2009 household budget survey data indicated that up to 50% of the poor in some regions of the country lived in households that were headed by a public sector employee.22 Figure 7. Employment by sector

19

ILO, 2013, Decent Work Country Profile: Ukraine.

ILO, 2011, Decent Work Country Profile: Armenia.

21 ILO, 2011, Decent Work Country Profile: Armenia.

22 ADB/UNDP Poverty Assessment, Astana 2012, p19 (based on household budget survey data for 2009) 20

34

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% GEO TJK ALB AZE ARM KGZ MDA KAZ SRB BIH TUR MKD UKR BLR MNE KOS ECIS 2007 2009 2009 2014 2013 2013 2013 2013 2013 2012 2014 2014 2014 2013 2014 2012 2012 Agriculture

Industry

Service

Source: ILO, 2015, KILM 9th ed; HDRO, 2015.

The ILO defines “vulnerable employment” as the share of contributing (non-paid) family workers and own-account (self-employed) workers. The share of the working poor, defined as those who are employed with per-capita incomes below international poverty lines can be another indicator of vulnerable and low quality employment. As shown in Figure 8 (left), over half of the employed in the Southern Caucasus and Central Asia live on incomes below the ILO upper threshold used to measure the share of working poor (i.e., those with per capita incomes below PPP$4/day). Figure 8 (right) shows the share of the workforce who are self-employed (own-account workers) and contributing family workers.

Figure 8. Working Poor and Vulnerable Employment

Working poor 80 70

Vulnerable employment (20082013)

70 At PPP $2 a day (2003–2012)

60

At PPP $4 a day (2008–2012)

50

60 50 40 40 30 30 20 20 10

10

TJK KGZ GEO ARM ALB AZE MDA MKD KAZ TUR BLR MNE SRB UKR BIH ECIS

GEO ALB AZE KGZ TJK TUR MDA ARM KAZ SRB BIH MKD UKR BLR ECIS

0

0

35

Left: Share of working poor at a PPP US$ 2 and PPP US$ 4 thresholds, for countries where data is available, latest available year. Sources: HDRO, 2015; ILO, 2015, KILM 9th Ed. Right: Share of vulnerable employment (sum of contributing family workers and own-account workers). Source: HDRO, 2015.

The ILO working poor and vulnerable employment data may imply a reconsideration of the conclusions suggested by the above-mentioned employment and labour force participation data. Whereas workers in Southeast Europe may face greater difficulties in finding a job than workers in the South Caucasus and Central Asia, jobs in Southeast Europe are more likely to be decent, and less likely to be precarious, than in these subregions. (It should also be noted that both Belarus and Ukraine perform quite well in terms of these “working poor” and “vulnerable employment” indicators.) The countries with the largest shares of employment in lowproductivity agriculture may face the most problems with the quality of employment.

Labour productivity, inernational comparison 2012 Output per worker (constant 2005 international USD)

200 000 180 000 160 000 140 000 120 000 100 000 80 000 60 000 40 000 20 000 0 m xe Lu

bo

t y y g s a d a ic IS nia key an LD nia tvia rica sia tion ania aria onia rus stan cific tan sia ijan rica enia rgia stan tan ur rwa lan ate EU Eas eni aki ubl an s A ba is la v v a &C sto Tur ibbe OR hua La lg h d t A ra Af Af rm ki ki o m er eo St erm and le lo Slo ep U) N E Be zak e P men uth zer an r G zbe Taji d Bu ace th Eas ede Ro A W Lit itz ed S R a G E d s o r i a or k C A h th F S a M r ie U n Sw nit c M K N h e d o R U Tu an ze om th (n Sa an si C FY d on bia pe us an Ec R Su ro As a u d t c i e as tE er op -E as el Am th -E ev th ou tin D u a S o L &S tr. en C

Source: ILO Global Employment Trends 2014

However, alternate measures of labour market vulnerability may produce different results. For example, data produced by the Eurostat-compatible Statistics on Income and Living Conditions (EU-SILC) surveys that have been administered in Serbia and the former Yugoslav Republic of Macedonia have found that those “at risk of poverty or social exclusion” were 28% and 35% % of the working population, respectively.23 While these figures are higher than the shares of working poor reported for these countries in figure 8, they are close to ILO estimates of vulnerable employment.

Public opinion surveys that gather information on individual perceptions of their employment status may also provide insights into the quality and precariousness of employment. For example, Caucasus Barometer data24 indicate that fewer people report having a job than what would be suggested by the employment rates generated from national labour force survey data. In Armenia, these figures were 44% (Caucasus Barometer) compared to 53% (labour force survey); in Azerbaijan they were 41% (Caucasus Barometer) compared to 63% (labour force survey); in Georgia they were 40% (Caucasus Barometer) compared to 56% (labour force survey).

23 24

EUROSTAT, figures for 2013.

Caucasus Barometer, 2013.

36

These disparities may reflect popular beliefs that informal engagement in agriculture is more a coping mechanism than a form of employment.

Figure 9. Balkan Barometer 2015 How confident are you in your ability to keep your job in the coming 12 months?

How confident are you in having a job in 2 years' time?

SRB

SRB

MNE

MNE

MKD

MKD

KOS

KOS

BIH

BIH

ALB

ALB 0%

25%

50%

75%

100%

0%

25%

50%

75%

100%

A similar survey in the West Balkans also found some (albeit smaller) disparities between official and self-reported employment rates.25 Many respondents also reported high levels of uncertainty regarding their future employment status (Figure 9 right). This study concluded that the categories of employment, informal employment, unemployment, discouraged worker status, and inactivity should be viewed as points on a continuum rather than as discrete categories. Significant movement between these categories may exist, and the boundaries between them may be very fluid. Still, there can be little doubt that many workers in the region labour in conditions of informal, precarious, and vulnerable employment.

These results are consistent with previous estimates of those vulnerable to falling into poverty, (i.e., those who are located not far above poverty thresholds). Slay et al (2015) use poverty thresholds of PPP$5.40/day and PPP$10/day and POLCALNET data to show that the vast majority of the population in Tajikistan, Kyrgyzstan, Georgia, Armenia and Moldova has been either poor or vulnerable to income poverty over the last two decades. They also find that, despite improvements in poverty (measured using the PPP$4.30/day threshold), there has been little progress in reducing the numbers of people vulnerable to poverty (measured using the PPP$10/day threshold). Approximately 67 million people in the 15 countries examined were found to be living in poverty, or vulnerable to poverty, using the PPP$4.30/day and the PPP$5.40/day thresholds, respectively. (Slay et al, 2015, pp29-39). Assuming that labour income accounts significant shares of vulnerable household incomes, low quality employment can be assumed to be affecting the vulnerability risk of quite sizeable shares of the population.

Labour migrants

25

World Bank, 2015, Promoting Labor Market Participation and Social Inclusion in Europe and Central Asia’s Poorest Countries.

37

Labour migration is another response to unequal access to employment opportunities in the region.

Migration varies in character (formal, informal), nature (seasonal, circular, permanent), and vis-à-vis state borders (internal versus external migration). But for many vulnerable households—especially in rural areas— external migration has become a primary coping strategy in response to the lack of decent work opportunities.

Likewise, remittances have become a substitute for social protection systems for migrants’ families.26

Figure XX—Shares of population outside of the country of origin (2013) 45%

43%

40%

26% 25%

22%

21%

18%

17%

15% 13%

12%

12% 7%

7%

5%

4%

3%

UNDP calculations, based on UNDESA migration (country of origin) and population data.

Migration and remittance flows are particularly important in Central Asia: as of mid-2015 citizens from Kyrgyzstan, Tajikistan, and Uzbekistan accounted for around one third of registered foreigners in Russia (despite the absence of common borders) and for nearly three quarters of registered foreigners in Kazakhstan.27 Whereas Russia is the primary destination for migrant workers from the Caucasus and Central Asia, EU countries are the primary destination for migrants from the Western Balkans—more than 100,000 temporary residence permits are issued annually in EU countries for citizens from the Western Balkans. Migration flows from Ukraine and Moldova are more evenly split. Remittance flows from Russia to these countries are likewise substantial: four CIS countries (Tajikistan, Kyrgyzstan, Moldova, and Armenia) are typically among the world’s largest recipients of remittances (relative to GDP); data indicate more than 90% of these flows come from Russia.28

Figure 10. Remittances inflow as share of GDP in 2013

26

International Organization for Migration, 2015, Migration Facts and Trends: South-Eastern Europe, Eastern Europe and Central Asia.

As a result of high labour migration, some of the region’s economies have become highly reliant on remittance incomes: remittance flows are among the highest in the world - Armenia, Kyrgyzstan, Moldova and Tajikistan are all among top 10 countries for remittances as a proportion of GDP 27 UNDP, 2015, Labour Migration, Remittances, and Human Development in Central Asia.

28 UNDP, 2015. Georgia, Kosovo, and sometimes Uzbekistan are often in the world’s top 20 by this indicator.

38

60%

50%

Global country rank of share of remittances in GDP

1

40% 2 30%

4 7

20%

10%

16 24

36 74

18 29

19 34

60

47

0% ALB ARM AZE BLR BIH GEO KAZ KOS KGZ MKD MDA MNE SRB TJK TUR TKM UKR UZB

Source: World Bank staff calculations http://go.worldbank.org/092X1CHHD0

These migration and remittance flows can clearly help to reduce poverty. In Kyrgyzstan, for example, household budget survey data indicate that remittances yearly reduce the numbers of people living below the poverty line by 250,000-300,000. One study finds that labour migration is absorbing a third to one half of Kosovo’s new labour market entrants every year. Kosovar migrants report that spending time abroad improves their prospects for finding decent employment upon returning home.29 However, these flows also have their drawbacks. For one thing, they are strongly pro-cyclical, meaning that an economic downturn or tighter migration rules in Russia can lead to dramatic declines in remittance flows. Because much of this migration is highly irregular, workers often have no choice but to engage in more precarious forms of migratory employment, without social protection. Migration may also increase disparities between remittance-receiving and other households.30 And because migrants workers rarely contribute to social insurance funds in either countries of origin or destination, migration flows are likely to mean growing future pressures on the financial sustainability of old-age pension systems.

Youth employment Young people often have particularly unequal labour market status in the region. Only one third of the youth population is employed, and a recent ILO study funds that youth unemployment is expected to increase in the next five years.31 Labour force participation rates among the youth are often well below 50%; in some countries, such as Moldova, it is as low as 20% (Figure 11 below). While low participation rates among the youth do not necessarily imply poor labour market performance (many young people may choose to study longer), low youth employment rates in the region are often accompanied by high rates of youth not in education, employment or training (NEET).32 The labour market impact of the 2008-2009 global financial crisis within the

29

UNDP, 2014, Kosovo Human Development Report 2014: Migration as a force for development.

See Falzoni, A. and Soldano, K., 2014, Remittances and inequality in Eastern European countries; and Peterski, M. and Jovanovic, B., 2013, “Do Remittances Reduce Poverty and Inequality in the Western Balkans? Evidence from Macedonia”.

31 ILO, 2015, Global employment trends for youth 2015: scaling up investments in decent jobs for youth.

32 Mauro, J. A. and Mitra, S., 2015, Understanding out-of-work and out-of-school youth in Europe and Central Asia. Figures for 15-24 age group, post-2009.

30

39

region was much greater for youth than for other workers.33 Youth employment rates continue to decline or are stagnant.

The highest rates of youth unemployment are reported in Southeast Europe: in Bosnia and Herzegovina, Serbia, and the former Yugoslav Republic of Macedonia more than half of young people are unemployed. These are some of the highest youth unemployment rates reported globally. The youth labour market situation is particularly severe in the former Yugoslav Republic of Macedonia, where a recent study found that only about a third of youths are economically active (of which more than one-half is unemployed)—and only a sixth are in regular employment.34 Three quarters of those seeking a job have been doing so for more than a year. While many youth who are not in employment are studying, one-quarter of the youth population is both out-of-school and out-of-work.

Labour market exclusion concerns are also apparent in the South Caucasus and Western CIS countries, where the labour participation rate for youth fell from 55% in 2000 to 37% in 2013. Youth unemployment rates likewise range from around 30% (in Armenia and Georgia) to 14% (in Moldova)—slightly above the global average of 13%. In all of these counties except for Moldova, over half of this youth unemployment has a longterm character (one year or longer).35 Migration is also a common coping strategy—particularly in Armenia and Moldova (which typically rank in the world’s top 10 countries in terms of the ratio of remittance inflows to GDP).

Youth unemployment rates tend to be particularly high among the less-educated: in Ukraine, for example, close to 70% of youth with only primary education are unemployed.36

Figure 5. Youth labour force participation (left), employment rate (right) 50

Youth participation

Youth employment 40 Central Asia Central Asia

45 ECIS* 40

35

30

35

ECIS*

South Caucasus and Western CIS

South Eastern Europe*

30

South Caucasus and Western CIS South Eastern Europe*

25

33

ILO, 2014, Global Employment Trends. Figure for 2013. ILO regional estimates include Croatia and the Russian Federation.

Elder, S., Novkovska, B., Krsteva, V., 2013, Labour market transitions of young women and men in the former Yugoslav Republic of Macedonia. See also Mojsovska, S. and Janeska, V., 2014, Economic and Social Implications of the Youth Unemployment in the Republic of Macedonia. Journal of Social Policy, 7(11), 11-44.

35 Elder, S., Barcucci, V, Gurbuzer, Y., Perardel, Y. and Principi, M., 2015, Labour market transitions of young women and men in Eastern Europe and Central Asia. Based on a survey of five countries of the region (Armenia, Moldova, FYR Macedonia, Ukraine, Kyrgyzstan), and Russia. Figure for Georgia is obtained from ILO KILM 8th ed.

36 Ibid.

34

40

Youth unemployment 20

South Eastern Europe*

15

ECIS* 10 Central Asia South Caucasus and Western CIS 5

Source: Calculations based on ILO, 2015, KILM 9th ed. * except for 2012, averages do not include Kosovo under UNSCR 1244.

Figure 6. Youth labour force in 2014 100%

100%

90%

90%

80%

80%

70% 70%

60% 50%

60%

40%

50%

30%

40%

20%

30%

10%

20% Central Asia

South Caucasus and Western CIS

South Eastern Europe*

ECIS*

Employment rate Unemployment as % of population Inactive

10% 0%

ALB ARM AZE BLR BIH GEO KAZ KOS* KGZ MKD MDA MNE SRB TJK TUR TKM UKR UZB

0%

NEET 2009

NEET 2013

NEET 2014

Source: Calculations based on ILO, 2015, KILM 9th ed. *Averages do not include Kosovo under UNSCR 1244; Kosovo data for 2012.

Youth labour force participation data may be misleading in that young people may improve their job market prospects by remaining in school rather than actively seeking employment. However, in most of the region, between a quarter and a third of youth populations are “not in employment, education, or training”

41

(NEET). NEET rates reported in the region range from around 40% (Armenia, 2009) to around 12% (Belarus), with many countries in the 25-30% range (Figure 12).37 In most of the region, young women are more likely to be out-of-work and out-of-school than young men. This difference is particularly pronounced in Central Asia, where the sub-regional NEET average is 37% for women compared to 19% for men.38 A similar pattern is apparent in Turkey: whereas female NEET rates reach 35%, for young men they are around 15%. Young men are more likely to be unemployed non-students, while young women tend to be inactive non-students: young men are looking for (regular) jobs while young women are not.

While unemployment and NEET rates among youth in the region are worrisome, the quality of employment of those who are working may be of equal concern. The data that are available suggest that youth are more likely to work informally, without written employment contracts (in Armenia this is the case for almost one in four youth employees39), or as contributing workers in their families’ businesses—often without social protection or regular remuneration. In Armenia and the former Yugoslav Republic of Macedonia, this form of employment has been assessed at 17% and 22% of total youth employment, respectively.40 In Kyrgyzstan, one study found that more than a third of young people in rural areas were working on family farms (or in family businesses) six years after leaving education.41

Groups at particular risk of labour market exclusion UNDP’s 2011 Regional Human Development Report found that individuals living with disabilities, or who are members of an ethnic minority, are at greater risk of economic and social exclusion. However, whether these risks are translated into actual exclusion depends on how they interact with risk drivers (i.e., institutions, norms, policies) and contexts (i.e., such local factors as residence in rural or urban areas, as well as in mono-company towns; access to public transport and economic infrastructure). When policies to promote inclusion (or the institutional capacity needed to implement such policies) are absent, labour market exclusion can trigger vicious circles of social and economic exclusion—further depressing prospects for labour market inclusion.42 Drivers of labour market exclusion may differ between countries. Barriers to employment can arise from systemic exclusion based on gender, ethnicity, or geography. In Montenegro, geography is an important factor as long-term unemployment rates in the country’s rugged northern interior are more than double those reported in the southern coastal regions.43 The position of Roma—one of the region’s largest ethnic minorities—is an illustrative example of a group facing an elevated risks of labour market exclusion, and from there exclusion more broadly. Survey data indicate that Roma unemployment rates in 2011 in much of the Western Balkans reached 50%—well above not only national unemployment rates, but also the unemployment rates reported for non-Roma communities located in close proximity to Roma neighbourhoods or settlements (Figure 13). These survey data also show that joblessness rates (reflecting both the unemployed and discouraged workers) reported for Roma women were well above those for Roma men—as well as for non-Roma women (Figure 14).44

Figure 13. Roma and Non-Roma Unemployment, and national unemployment rate, 2011

37

Mauro, J. A. and Mitra, S., 2015. Tajikistan data from 2007 and 2009.

Ibid. Sub-regional averages use available data; some country data is missing.

39 Youth Studies Institute, Armenia, 2013.

40 Elder, S. et al. 2015. SWTS surveys 2012-2013.

41 ETF (2013), Transition from school to work in Kyrgyzstan. Results of the 2011/12 transition survey, Turin.

42 UNDP, 2011, Beyond Transition: Towards Inclusive Societies.

43 ETF, 2011, Long-Term Unemployment in Northern Montenegro: From Analysis to Action.

44 The UNDP/WB/EC Regional Roma Survey, 2011 compared socio-economic position of Roma communities with non-Roma communities living in close proximity in Albania, BiH, Kosovo, Macedonia, Moldova, Montenegro and Serbia (and New EU Member States) 38

42

60%

54%

53% 49%

50% 44% 37%

40% 30%

30%

27%

30%

27%

23% 20%

18%

20%

10%

0% ALB

BIH

MKD

Roma unemployment rate

MDA

MNE

Non-Roma unemployment

SRB

National unemployment rate 15+

Source: UNDP/WB/EC Regional Roma Survey 2011.

Unequal employment outcomes are also apparent in the wages earned by those Roma who do manage to find jobs—which in 2011 were found to be 45%-80% of the wages earned by non-Roma. Roma women’s wages were found to amount to only 45% of those earned by non-Roma men, and 54% of the wages earned by nonRoma women. Roma youth are likewise at greater risk of experiencing labour market exclusion than non-Roma youth: the 2011 survey data indicate that unemployment rates for Roma youth are well above national and nonRoma unemployment rates (Figure 16).

Figure 14. Roma joblessness rates, male and female Jobless rates of male Roma and nonRoma (%, 2011)

Jobless rates of female Roma and non-Roma (%, 2011) 90

69

63

59 42

38

63

55

49

36

34

89

85

83

81 73

67 59

56

57 50

41

38 26

Roma

Non-Roma

Roma

Non-Roma

Source: UNDP/WB/EC Regional Roma Survey 2011.

43

The 2011 survey data also suggest that discrimination contributes to Roma labour-market exclusion. As the data in Figure 15 show, differences in joblessness between Roma and non-Roma living in close proximity to Roma settlements are minimal for persons with no formal education. However, while joblessness rates decline as education levels rise for both Roma and non-Roma, these declines are much steeper for non-Roma. Since neither education levels nor location can explain these differences, employer reticence to hire “the other� may offer at least a partial explanation.

Figure 15. Joblessness rates by education levels in Southeast (and Central) Europe, 2011 40

Post-secondary

24 52

Upper secondary

40 66

Lower secondary

51 69

Primary education

61 80

No formal education

76 0

10

20

30 Roma

40

50

60

70

80

90

Non-Roma

Source: UNDP/WB/EC Regional Roma Survey 2011.

Figure 16. Youth Roma and Non-Roma Unemployment, and national youth unemployment rate, 2011 80%

69%

70%

71% 65%

61% 56%

60%

56% 47% 43%

50% 40%

49%

50%

39% 37%

30% 20% 10% 0% ALB

BIH

Roma unemployment rate

MKD

MDA

Non-Roma unemployment

MNE

SRB

National unemployment rate 15+

Source: UNDP/WB/EC Regional Roma Survey 2011.

44

These survey data also point to extensive Roma engagement in the informal economy. In Albania, 87% of working Roma men, and 79% of Roma women, were employed informally in 2011. The intensity of informal employment was particularly strong in Bosnia and Herzegovina, as well as in Montenegro (Figure 17). As formalsector employment is a precondition for eligibility for many forms of social protection, Roma households’ extensive engagement in the informal sector may also imply their exclusion from social protection and social services. More than one half of Roma respondents participating in the 2011 survey reported difficulties in acquiring medicines, compared to one in four non-Roma survey respondents.45

Figure 17. Ratio of Roma to non-Roma prevalence of informal employment 7

5.1

4.8

4.6

4.3

3.9

3.1

2.6

2.8

2.6 1.3 1.5

BiH

Macedonia

Montenegro Male

Serbia

Albania

Moldova

Female

Source: UNDP/WB/EC Regional Roma Survey 2011. Involvement in informal employment is defined as the percentage of workers (15-64) who are not paying health or pension contributions.

The above analysis strongly suggests that significant numbers of workers in the region are facing significant risks of labour market exclusion, which can easily translate into risks of social exclusion more broadly.

The problem is not just lack of jobs—it is a lack of decent jobs. These numbers correspond to estimates of the numbers of individuals who have incomes close to poverty lines, and who could easily slip into poverty—which, given the predominance of precarious and vulnerable employment in the region, could easily happen. Since wages are the main source of income for poor and vulnerable households, shifting the pattern of growth so that the benefits accrue most robustly to low-income households requires, first and foremost, the accelerated creation of well-paying income- and employment-generation opportunities.

Policies and programming for labour market inclusion In some respects, prospects for generating significant numbers of decent jobs in the region depend on factors beyond government control. These include in particular growth rates in key global and regional export markets, the prices of key exports, and the like. However, governments can undertake measures to increase employers’ willingness to higher workers in the formal sector. These include: 

45

Reducing social-security and other taxes on labour. These revenue losses can be offset by: (i) higher taxes on carbon-intensive and other environmentally unsustainable activities; (ii) reductions in tax

UNDP / Ivanov, A., Kagin, J., 2014, Roma poverty from a human development perspective.

45

breaks or budget subsidies that accrue primarily to wealthy households; and (iii) more aggressive measures to reduce the diversion of budget revenues to tax havens. 

Raising the profile of employment policies within overall policy frameworks. While “getting the overall growth framework right”, and improvements in business and commercial environments are clearly necessary condition for employment growth, they are not sufficient conditions. Whole-of-government approaches, in which responsibilities for implementing national employment strategies are clearly assigned to all relevant government bodies needed instead. In practice, however, employment is typically “embraced by everyone, but owned by no one”.



Investments in state capacity are often needed in such areas as public employment services, national labour policy coordination structures, and platforms for dialogue and employment partnerships between the private sector, government, and civil society partners (including labour unions). Public employment services in particular have particularly important roles to play in addressing labour market exclusion. Stronger regional- and local-level presences, better use of employment-relevant egovernance platforms, and stronger abilities to coordinate and partner with other institutions—in the state (e.g., social service offices, vocational training centres), private sector (employers) and in civil society (e.g., NGOs representing vulnerable groups)—all this (and more) is needed.



Be willing to address labour-market discrimination, particularly as concerns ethnic minorities (e.g., Roma) but also women. In some cases, improvements in institutional capacity among labour offices and NGOs may be enough to redress deep-seated labour market exclusion. In other cases, however, public awareness campaigns and other, legal measures to tackle discrimination may be needed.

Social protection and social inclusion Inequalities in employment opportunities, and their links to social exclusion, have important implications for social protection systems. The emergence of extensive informal employment has put considerable financial strain on poorly-financed social protection systems. At the same time, employment and social protection systems that were designed to work in near-full employment conditions have not been flexible enough to meet the needs of those most at risk of labour market or social exclusion. This combination has commonly led to the design and implementation of social policy reforms that have focused on reducing the size and coverage of social assistance benefits—despite the paucity of decent jobs.

When combined with labour market policies, social protection has the double role of: (i) promoting decent employment (with social insurance coverage); and (ii) providing income support to those who find themselves without employment. When social protection systems are ineffective, the loss or lack of employment can create vicious cycles of exclusion. These in turn can be aggravated by the lack of reforms in, and inadequate coordination between, public employment services and social protection agencies—with the latter focusing on mediation, and the former on administration of benefits. Vocational education, labour market, and social protection policies are often fragmented across different sectors, with inadequate instruments for interdepartmental coordination. The significance of these problems can be further magnified by the fact that labour market data and indicators are not always “fit for purpose” (as explained above).

Social protection can be understood in different ways. Here we refer to social insurance (pensions, maternity leave, sick leave, invalidity pension) based on contributory schemes; (ii) social assistance based on taxfinanced support to the poor or vulnerable; (iii) locally provided social support services to households (including for the elderly living alone, families with members who have disabilities); and (iv) active labour market measures aimed at helping the unemployed population find a job.

46

In all the countries of the region except Turkey, broad social protection systems featuring both contributory social insurance46 components and non-contributory47 components were in place prior to the 1990s. Combined with generally tight labour market conditions, the subsidies for basic goods and services that were available prior to the 1990s, and extensive public investment in the provision of health, education, and other social and communal services (some of which were provided by the state- or socially owned enterprises, or public administration, in which most people worked), these systems provided households with high degrees of economic security—much of which was codified in legal/constitutional “rights” to “free” health, education and other services. However, these systems were also quite bureaucratic in nature, and were less effective in resolving problems of social exclusion that required local solutions, or could not otherwise be addressed by regional development or public works programming.

The economic transitions that took hold in the 1990s presented huge challenges for these social protection systems. The emergence of extensive labour-market informality and irregular migration flows, often combined with demographic trends that have increased the numbers of pensioners relative to the workforce, have threatened the financial sustainability of contributory pension schemes and left growing numbers of workers uncovered by social insurance systems. Social assistance programmes have been expanded, in order to both address these challenges and compensate for reductions in labour market security and in subsidies for basic goods and services. However, fiscal considerations, concerns about further weakening incentives for labour force participation, and technical difficulties in setting appropriate eligibility criteria (minimizing errors of inclusion and exclusion) have limited the scope and effectiveness of these programmes. Moreover, some countries have emphasized the provision of social assistance to “deserving” social groups (e.g., war veterans) whose members may not necessarily be among the most poor or vulnerable.

The World Bank’s ASPIRE data base can be used to address questions about the size and nature of the resulting gaps in social protection coverage. Data in Figure 18 indicate that both social insurance and social assistance programmes reduce poverty and inequality (Gini) indicators across the region. However (apart from in Azerbaijan), social insurance (presumably pensions) has the greater impact—reflecting relatively large benefit sizes and numbers of beneficiaries. However, the data in Figure 19 indicate that in most countries, less than quarter of all social protection beneficiaries are in the poorest quintile—suggesting large coverage gaps among the most vulnerable. Moreover, non-contributory social assistance covers only a small proportion of the poorest 20%. Social protection systems in Kazakhstan, Kyrgyzstan, and Tajikistan seem to be particularly lacking: in coverage of the poorest, spending, and in poverty and inequality impact. By contrast, Ukraine and Belarus appear to achieve impressive reductions in poverty and inequality thanks to higher-than-average spending and good coverage of the poorest quintile.

Social protection in Central Asia. Coverage of both social insurance and social assistance in Kazakhstan, Kyrgyzstan, and Tajikistan is the most limited in the region—particularly for the poorest section of the population (Figure 19).48 The importance of formal labour market status in determining eligibility for many forms of social insurance excludes significant portions of the labour force in the latter two countries, who engage in irregular migration. Moreover, support for the so-called working poor (i.e., households with employed adults) is almost total absent. Remittance inflows therefore serve as a substitute for formal social protection systems (at least in Kyrgyzstan and Tajikistan). However, the labour migration that generates these inflows also reduces contributions to social insurance systems, which both reduces their financial sustainability and deprives migrants of access to future pensions and other benefits. Social protection systems in Tajikistan and Kazakhstan appear to be quite ineffective in relieving poverty among the poorest, while Kyrgyzstan can report moderate success in this respect (Figure 19). Tajikistan in particular is facing urgent challenges of better targeting social assistance to poor families that do not receive remittances.49 46

Insurance against risks of unemployment, employment injury, disability, sickness, maternity, and old age.

Social assistance of last resort; social pensions, some disability related allowance, child and birth allowance, housing and utility support.

48 Comparable data for Turkmenistan and Uzbekistan are not available.

49 Amir, O. and Berry, A., 2013, Challenges of Transition Economies: Economic Reforms, Emigration and Employment in Tajikistan. In: UNDP, Social Protection, Growth and Employment: Evidence from India, Kenya, Malawi, Mexico and Tajikistan, 2013.

47

47

Social protection in Southeast Europe. With the exception of Kosovo, social protection systems in this sub-region are poorly targeted, with the poorest quintile often receiving less than 20% of total benefits (Figure 19 top left). This results in part from the presence of categorical benefits that are not linked to income status. In Bosnia and Herzegovina, for example, over half of all social protection spending is allocated to war veterans; high spending on categorical benefits is also present in Albania and Serbia.

48

Figure 18. Impact of Social Protection on Inequality and Poverty50

50

In these scatter plots, country points are color-coded by sub-region: SEE – orange; CA – green; SC and WCIS – blue.

49

Figure 19. Social protection for the poorest 20 per centError! Bookmark not defined.

Source: World Bank ASPIRE database. No data for MKD, UZB and TKM. ALB 2012; ARM 2013; AZE 2008; BLR 2012; BIH 2007; GEO 2011; KAZ 2010; KSV 2011; KGZ 2011; MDA 2013; MNE 2011 SRB 2010; TJK 2011; TUR 2012; UKR 2013. Adequacy is defined as the amount of transfers received by the poorest quintile divided by the total income or consumption of the beneficiaries in that quintile. Beneficiary incidence is defined as the number of beneficiaries in the poorest quintile relative to the total number of beneficiaries in the population.

Bottom-left: AZE excluded from trendline calculation

Throughout the Western Balkans, large numbers of elderly are not covered by any kind of pension (Albania—where old-age pension coverage is quasi-universal—is a notable exception51). In Serbia, up to onethird of the over-65 population elderly may not be covered by any kind of pension.52 In Kosovo, by contrast, a complete re-design of the social protection system seems to have contributed to improvements in poverty and inequality (Figure 19Error! Reference source not found. top)—thanks in part to the introduction of a simple, universal old-age pension. Eligibility for unemployment benefits tends to be quite broad in this sub-region, and registering and receiving unemployment status makes further benefits available 51 52

European Commission, 2009, Social Protection and Social Inclusion in the Western Balkans: A Synthesis Report.

European Commission, 2008, Social Protection and Social Inclusion in the Republic of Serbia: Executive Summary.

50

(child/maternity/welfare/veteran benefits, as well as health insurance and pensions). This is not the case in Turkey, where only unemployment benefits are available for the registered unemployed. In the former Yugoslav Republic of Macedonia, however, access to unemployment benefits is very restricted. In Albania, as well as in the former Yugoslav Republic of Macedonia, individual farmers cannot register for unemployment benefits53—a particular issue in Albania, where some 40% of the workforce is engaged in agriculture. On the other hand, recipients of unemployment benefits in other countries may be involved in informal economic activities.

However, those unemployed for long periods of time are often ineligible for adequate support. A recent European Commission study which included fYR Macedonia, Serbia, and Turkey found that most services addressing the long-term unemployed are not particularly effective.54 Social protection in the South Caucasus and Western CIS. Wide variance in social protection performance is apparent in these countries. On the one hand, in Ukraine and Belarus both social assistance and social insurance programmes enjoy relatively good coverage of those most in need (Figure 19 bottom), and are overall quite successful in both reducing poverty and inequality (Figure 19 top). However, the replacement rates of social insurance (contributory) programmes, and in particular of unemployment insurance, are low—reducing their effectiveness. (This is particularly the case in Moldova, where the entitlement period is very short and where contributions are limited by high rates of labour emigration.) While poverty in Belarus and Ukraine is far less widespread than in other parts of the region, it is more concentrated in certain social groups—such as those without formal incomes, or people living with disability.

In the South Caucasus countries, by contrast, social insurance systems (i.e., pensions) appear to have generous coverage among the poorest—but social assistance is much less effective. Oil-rich Azerbaijan is an exception, where over 90% of the poorest receive some sort of benefit (Figure 19 top right), and where social protection makes up over 80% of the poorest quintile beneficiaries’ consumption (Figure 19 top left). Many structural shortcomings are apparent in these systems—in Georgia, for example, unemployment benefits are non-existent. While unemployment benefits exist in the other South Caucasus countries, their levels are quite low. Moreover, because these are financed on a contributory basis, workers in the informal sector who do not contribute to the unemployment compensation fund are unable to claim benefits from it.

While social protection systems across the region have generally retained their coverage and scope on paper (see Annex 1), large gaps in coverage and quality have emerged in practice. Inequalities in labour market access are in this way extended and amplified as social exclusion. Limitations on state abilities to deliver on social protection obligations are often offset via such coping mechanisms such as remittances, precarious employment, and family support. This “informalized” social protection55 can also lead to large out-of-pocket spending for required services, further diminishing equality of opportunities and outcomes and increasing risk of social exclusion.

Social protection and labour market policies—Getting the links right Extensive labour market informality in the region excludes significant numbers of workers from social protection systems and threatens their financial sustainability. Many governments have sought to address these challenges by (further) raising already high social security taxes: a recent World Bank report56 notes that, in the Western Balkans, social security levies and other taxes in labour account for over 30% of wages. This tax wedge is even larger for low-wage and part-time workers. However, these high taxes themselves play a major role in

53

ETF, 2011, Activating the Unemployed: Optimising Activation Policies in the Western Balkans and Turkey. European Training Foundation.

54 Bouget, D., Frazer, H., and Marlier, E. with Peña-Casas, R. and Vanhercke, B., 2015, Integrated support for the long-term unemployed: A study of national policies. European Commission.

55 Drahokoupil, J. and Myant, M. (2009) Varieties of Capitalism, Varieties of Vulnerabilities: financial crisis and its impact on welfare states in Eastern Euroe and the Commonwealth of Independent States. Historical Social Research 35, 266-298.

56 Arias, O., and Sánchez-Pármo, C., 2014.

51

driving employment, and economic activity, into the informal sector. Efforts to break this vicious cycle must therefore focus on reducing this tax burden on labour.

Box 3. Does it pay to formalize informal employment in Serbia?

In Serbia, the formalization of informal employment means that social security contributions (e.g., to the pension and health funds, unemployment insurance fund) will have to be paid by both workers and employers. It means that income tax will be withheld from worker’s pay checks. Given the high tax wedge and low progressivity of labour taxation in Serbia, the effective tax rate is high. Furthermore, unlike in the former Yugoslav Republic of Macedonia and Bosnia and Herzegovina, social security contributions in Serbia do not vary with hours worked, so part-time workers are disproportionately affected. This can theoretically result in negative net wages for part-time workers. If it leads to the reporting of incomes that would otherwise be hidden, formalization can also mean losing social assistance payments that are linked to formal reported income levels.57 As a result, a Serbian worker who takes a low-wage formal job and loses eligibility for unemployment benefits can see 90% of the nominal increase in income due to engaging in formal employment be lost, due to higher taxes and unemployment benefits foregone.58 For many working people in Serbia, formal employment simply does not pay. One study found that more than 40% of informal workers in Serbia were earning less than the legal minimum wage in 2008.59 Despite the low earnings of informal work, their net income was still higher than what was available in formal jobs.

For these reasons, many workers in Serbia choose to remain in precarious informal employment. Faced with similar circumstances and incentives, the fact that many workers in other countries of the region behave in a similar manner should not come as a surprise.

This vicious cycle also suggests that concerns that social assistance may reduce incentives for labour force participation may be exaggerated. Instead, it is the anticipated loss of unemployment (or other) benefits, combined with the high taxation of labour in the formal sector, that reduces incentives for workers to abandon informal labour (see Box 3). A number of studies from the region bear this out. In Armenia, for example, the receipt of social assistance seems not to have an impact on participation in the formal labour force.60 In Tajikistan, social assistance has been found to have a positive effect on employment rates in female-headed households—suggesting that such transfer payments can actually promote social inclusion by strengthening incentives for formal labour force participation.61 When aligned with well designed active labour market policies, social protection systems can further strengthen incentives for formal labour force participation, reducing social exclusion.62 Other labour marketrelated social services that can promote social inclusion include the care of children, the elderly, and others who are unable to fully take care of themselves. Unfortunately, public provision of childcare is not available in some countries of the region, namely Azerbaijan, Kazakhstan, Tajikistan and Turkey.63 Support for part-time formal 57

Koettl, J., 2013, Does Formal Work Pay in Serbia? The Role of Labor Taxes and Social benefit Design in Providing Disincentives for Formal Work. In: C. Ruggeri Laderchi and S. Savastano (eds.) Poverty and Exclusion in the Western Balkans.

58 Arias, O., and Sánchez-Pármo, C., 2014.

59 Comparison of 2008 LFS and HBS in Koettl, J., 2013.

60 World Bank, 2011, Armenia: Social Assistance Programs and Work Disincentives.

61 World Bank, forthcoming, Ethnicity, Conflict and Development Outcomes in the ECA Region. Cited in Arias, O. and Sánchez-Pármo, C., 2014 62 See Kuddo, A., 2009, Employment Services and Active Labor Market Programs in Eastern European and Central Asian Countries.

World Bank, Social Protection Discussion Paper No. 0918. See also Lehmann, H. and Murayev, A., 2010, Labor Market Institutions and Labor Market Performance: What Can We Learn from Transition Countries? Working Paper 714, Dipartimento Scienze Economiche, Universitá di Bologna.

63 World Bank, 2012, Women Business and the Law Database http://wbl.worldbank.org/.

52

employment is other means through which formal employment can be increased, particularly for women and youth whose other obligations do not allow for full-time labour force participation. This means adjusting the tax burden or social contributions to hours worked, and allowing for a flexible range of part-time contracts in terms of duration.

Of course, many of these measures have fiscal implications. However, alternative sources for funding social services and labour market policies that can reduce social exclusion, and which can offset revenues losses from reductions in taxes on labour, exist. These may include: 

higher taxes on environmentally unsustainable activities (e.g., the use of high-sulphur coal to generate electricity);



reductions in budget subsidies that support environmentally unsustainable activities (e.g., fossil fuel production and consumption subsidies), or which accrue primarily to the middle class (e.g., categorical benefits for war veterans) or the wealthy;



more aggressive measures to reduce the diversion of budget revenues to tax havens;64 and



more robust direction of budgetary procurement and contracting resources to companies (e.g., social enterprises) that explicitly promote social inclusion.

64

The most recent report of the Global Financial Institute on Illicit Financial Flows from Developing Countries: 2004-2013 finds that the countries in the region on average lose $65 billion annually in illicit financial flows. If five percent of these flows could be captured as taxes, this would generate an additional $3.2 billion in budget revenues. (For more, see Dev Kar and Joseph Spanjers, Illicit Financial Flows from Developing Countries: 2004-2013, Global Financial Institute, December 2015.)

53

Appendix 1. Overview of national social security systems Country Number of social security policy areas covered by at least one programme South Caucasus and Western CIS Armenia Azerbaijan Belarus Georgia Moldova, Republic of Ukraine Central Asia Kazakhstan Kyrgyzstan Tajikistan Turkmenistan Uzbekistan Western Balkans Albania

Existence of programme(s) anchored in national legislation Sickness Maternit Old Employmen Invalidity Survivor Family (cash) y (cash) age t injury s allowance s

Unemplo yment

Comprehensive scope of legal coverage |8 Comprehensive scope of legal coverage |8 Comprehensive scope of legal coverage | 8 Semi-comprehensive scope | 7 Comprehensive scope of legal coverage | 8 Comprehensive scope of legal coverage | 8

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

● ●

● ●

● ●

● ●

● ●

● ●

● ●

▲ ●

●

●

●

●

●

●

●

●

Comprehensive scope of legal coverage |8 Comprehensive scope of legal coverage | 8 Limited scope of legal coverage | 5 to 6 Comprehensive scope of legal coverage | 8 Comprehensive scope of legal coverage | 8

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

● ●

● ●

● ●

X ●

● ●

● ●

X ●

● ●

●

●

●

●

●

●

●

●

Comprehensive scope of legal coverage | 8

●

●

●

●

●

●

●

●

54

Bosnia and Herzegovina Kosovo

Comprehensive scope of legal coverage | ● ● ● ● ● ● ● ● 8 Comprehensive scope of legal coverage | ● ● ● ● ● ● ● ● 8 Macedonia, Comprehensive scope of legal coverage | ● ● ● ● ● ● ● ● FYR 8 Montenegro Comprehensive scope of legal coverage | ● ● ● ● ● ● ● ● 8 Serbia Comprehensive scope of legal coverage | ● ● ● ● ● ● ● ● 8 Turkey Semi-comprehensive scope | 7 ● ● ● ● ● ● None ● ● At least one programme anchored in national legislation; ▲ Limited provision; X Not available. Source: SSA (Social Security Administration of the United States); ISSA (International Social Security Association). Social security programs throughout the world (Washington, DC and Geneva), Data for 2012. Adapted from ILO (2014) World Social Protection Report 2014/201

55

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Chapter 3—The economic dimensions of gender inequalities65 Key messages 

Economic growth and women’s empowerment are closely linked. Economic development liberates women’s energies; the full use of the human development potential represented by a country’s female labour force is a prerequisite for solid economic growth. Market economies work better when they are supported by efficient welfare states, with social protection systems that can meet the needs of both women and men provide a cushion in times of economic stress and uncertainty.



While the region compares favourably to many other parts of the developing world in terms of gender equality, it also lags behind global best practices in many areas. Moreover, pre1990s progress in gender equality that had been attained in many countries—many of which featured relative equality between men and women—has come under growing threat.



Gender-based inequalities are today among the most serious forms of inequalities in the region, and are a significant threat to its development prospects. Gender-based inequalities tend to intersect with, and magnify the impact of, other forms and dimensions of inequalities, based on class, race, age, ethnicity, disability, occupation and income. Unequal labour market outcomes in particular can have major implications for broader gender inequalities and the exclusion of women. Women’s unequal access to social capital or their inferior position in the networks that constitute social capital (which are more marked in some countries in the region than in others) is both a cause and a manifestation of inequality.



Key policy and programming directions to address these challenges include: o

Remove legal and regulatory barriers to women’s economic empowerment.

Although substantial progress has been made, pervasive gender-based occupational restrictions continue to prevent women from engaging in employment and entrepreneurship.

o

Increase budgetary resources supporting policies to address women’s care and domestic responsibilities, in order to reduce women’s labour market exclusion.

Programmes providing access to affordable and reliable child care, child subsidies and public childcare provisioning are an effective approach for improving women’s labour market outcomes and earnings in developing and transitioning economies.

o

Strengthen national capacities for the collection and analysis of sex- and agedisaggregated data for gender analysis, for better social policy and programmes.

More context-specific knowledge on the use of time by men and women is needed to fully assess gender inequalities. National statistical agencies must improve data collection to allow full mainstreaming of gender in macroeconomic studies.

o

Strengthen impact evaluations of proposed policies, along gender (as well as environmental and social) dimensions. Impact evaluations are key to providing a new evidence-based framework for gender equality.

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Please send comments on this chapter to Bharati Sadasivam (bharati.sadasivam@undp.org) and Ben Slay (ben.slay@undp.org).

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o

Increase investments in agriculture and rural development. Gender inequalities in the region tend to be sharpest in rural areas—where many women are engaged in unpaid work as contributing family workers. Improving the productivity of agricultural labour is key to reducing gender gaps in rural areas.

o

Use the job creation potential of the green economy to reduce industrial segregation. Many countries in the region are in a strong position to use the job creation potential of the green economy to reduce occupational segregation by gender (OECD 2011). However, corresponding investments in education will be needed to realize this potential.

o

Support women entrepreneurs. All countries of the region will benefit from efforts to support business development activities by women, as well as promote women’s access to commercial networking opportunities and credit.

o

Support women’s political participation: support efforts to ensure that an equitable proportion of women are elected and/or appointed to government leadership positions throughout the region. Ensuring that women participate proportionately in the political process and in leadership positions is essential to addressing gender disparities in the region. In addition, efforts should be made to invite the participation of women in elected and/or appointed positions who reflect the demographic composition of the constituencies they serve.

o

Address and combat gender stereotypes. Campaigns against sexist stereotypes that show positive, successful role models for women can both increase confidence in women’s capabilities and weaken the gender biases that often underpin educational and occupational segregation.

Introduction Most countries in the region have experienced deep political, economic and social changes over the past 25 years. The collapse of the Soviet-type and Yugoslav development models triggered deep changes in gender relations in countries where relative equality between men and women was a key legacy of the socialist past. In contrast to the other countries covered here, Turkey did not experience a similar pre-1990 levelling of gender differences. Nevertheless, Turkey did experience dramatic economic changes during this period, but in spite of economic growth and important social changes, significant inequalities, particularly gender inequality, persist. Inherited similarities notwithstanding, the economic, social, and political dimensions of gender inequality vary greatly between countries and even within them, and they can have different roots and causes.

Women in the region continue to score relatively well in terms of human development indicators. However, as is the case elsewhere in the world, men in the region continue to earn higher incomes, have more decision-making power, and control more resources. As elsewhere in the world, men are in a dominant position; they receive a larger share of resources and they have more decisionmaking power (women occupy less than 20% of parliamentary seats in the region.)

Women’s labour force participation rates remain below those of men. Women’s employment also tends to be less secure, and they are underrepresented both as wage earners and employers. In countries with high rates of self-employment, more women than men labour as contributing family workers. Throughout the region, women still earn significantly less than their male counterparts. As

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entrepreneurs, women face greater barriers in accessing finance and credit and tend to have weaker social and commercial networks. In agriculture, women are less likely to be landowners than men.

They typically own smaller plots of land and are more likely to engage in subsistence agricultural production. In the Caucasus, Western CIS and Central Asia region, legal frameworks contribute to these outcomes.

Women in the region score relatively well in terms of human development indicators.

However, in spite of generally high education levels, women’s participation in the labour market in most countries of the Western Balkans, Caucasus, Western CIS and Central Asia still faces challenges.

In the 25 countries in Eastern Europe and Central Asia, the gender gap in labour force participation remains high: it is above 30 percent in eight countries, between 10 and 29 percent in 13 countries and below 10 percent in only four countries. Rural women are particularly vulnerable due to failing infrastructure, lack of basic services and unequal access to land, property and assets. Despite progress in strengthening legal frameworks, violence against women and girls remain pervasive. Migration, an important feature of the region, has an increasingly female face with women representing just over half of total migration from Eastern Europe and Central Asia. Women employed as domestic workers, in most cases without contracts, account for significant proportion of intra-regional migrants.66 The dimensions of gender inequality, whether they are economic, social or political, vary greatly between countries and even within them, and they can have different roots and causes. The multiplicity of factors and challenges notwithstanding, gender inequalities in economic, social and political participation are pervasive throughout the region. Such gender disparities limit the prospects for robust, sustainable and inclusive growth. Reducing gender inequalities has the potential to contribute to inclusive growth, higher human development and to the achievement of the Sustainable Development Goals in the region.

This chapter focuses on the economic dimension of gender inequality in the region, its various causes and indicators, and its implications for women and men’s participation in the labour market. It analyzes inequalities in income, hourly wages, total earnings and access to capital and examines issues related with the economic dimension of gender equality, such as the availability of care and other social services, time use for men and women, access to education, migration and participation in decision-making.

Key concepts and understanding of inequality For UNDP, gender equality is grounded in international human rights, norms and standards.

The fulfilment of women’s and men’s civil, cultural, economic, political and social rights is central to the UNDP human development framework and is vital to achieving sustainable development.67 Box 1. Gender Equality “Refers to the equal rights, responsibilities and opportunities of women and men and girls and boys. Equality does not mean that women and men will become the same but that women’s and men’s rights, responsibilities and opportunities will not depend on whether they are born male or female. Gender equality implies that the interests, needs and priorities of both women and men 66

Humanity Divided: Confronting Inequality in Developing Countries. UNDP (2013). http://www.undp.org/content/dam/undp/library/Poverty%20Reduction/Inclusive%20development/Humanity%20Divided/ HumanityDivided_overview.pdf 67 UNDP Gender Equality Strategy 2014-2017: The Future we Want: Rights and Empowerment http://www.undp.org/content/dam/undp/library/gender/GenderEqualityStrategy2014-17.pdf

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are taken into consideration—recognizing the diversity of different groups of women and men.

Gender equality is not a ‘women’s issue’ but should concern and fully engage men as well as women. Equality between women and men is seen both as a human rights issue and as a precondition for, and indicator of, sustainable people-centred development.” UNDP Gender Equality Strategy 2014-2017 UNDP places gender inequality in the context of broader social and economic inequalities. The reduction of inequalities is a key priority, and UNDP underscores that the distribution of income and other key resources between men and women is directly linked to growth.

Women’s lower incomes and their more limited access to other resources required to secure a livelihood, such as land, credit and assets, reduce their bargaining power within households. Data series by sex tend to be available mostly in developed countries. Where data is available, country-level studies show that gender distribution of wealth, land and credit is more unequal than the distribution of income.

Moving the female labour force out of the domestic production of goods and services paid with uncertain intra-family transfers toward more efficient production in industry and services makes society wealthier. However, the domestic production of care has its own value, even if it is not accounted for in mainstream economics, thus rendering the work of women invisible. When addressing gender inequality and labour participation, the importance of care must not be overlooked.

Gender inequality is often associated with equal opportunity, but as the report pointed out “frameworks that focus on the inequality either of outcomes or of opportunities by themselves are inadequate for addressing inequality in human well being, given the interdependency between opportunities and outcomes and how this is played out in the context of a market economy... There is a false dichotomy between outcome and opportunity inequality... Development policy focusing on inequality reduction must address both.” (p. 26) Well-being is a multidimensional notion that goes beyond material dimensions such as income, educational attainment and health to also include agency and empowerment, as well as subjective well-being. Within this framework, gender differences are evaluated in three key domains: capabilities, livelihoods and agency.

Recent developments in economic thought can offer important insights into problems of gender equality, including in the region. Traditional distinctions between “standard” neoclassical economics (which took “first world” market capitalist economies as the relevant institutional paradigm), “comparative” economics (which contrasted the above with “second world” economic systems of socialist and communist countries), and “development” economics (which studied “third world” economies) have given way to the realization that all countries face challenges of inequalities and institutional imperfections—in both the public and private sector. Feminist economics, which focus on women as an object of study and gender relations as a conceptual framework to understand economic activities, have contributed to new, more integrated and people-centred approaches to socio-economic analysis. The proposition that differences between the sexes—in terms of power relations and policy implications—should be made explicit is now widely accepted.

Gender disparities in the labour market Gender-differentiated labour force participation and employment rates are key measures of gender inequality. The positive relationship between women’s labour force participation and

60

employment rates on the one hand, and economic development on the other (as measured by percapita income or UNDP’s human development index), is an empirical fact. Societies that promote women’s skills acquisition and engagement in the labour force not only have more and better workers and economic prospects: they also benefit from helping half the population to realize their potential as human beings. Countries with low labour force participation and employment rates are shortchanging both their women and themselves. Gaps in labour force participation and employment rates can therefore serve as indicators of deeper gender inequalities and development potential at risk.

As explained in the previous chapter, the countries of Southeast Europe report very low (by international standards) labour force participation and employment rates—for both women and men.

While the gender gap in employment rates is particularly large in Turkey (where only one woman works for every three working men), large gaps are also present in Serbia, Montenegro, and Bosnia and Herzegovina. In most of the countries of the Southern Caucasus, Western CIS, and Central Asia, gender gaps in terms of labour force participation rates have either remained stable or widened.

Azerbaijan and Kazakhstan—where women’s participation rates have caught up with those of men— are exceptions.

Employment to population ratio, male/ female (%, ages 15+) in Montenegro & Serbia for 2000-2014 period 100

percentage

80 60

Montenegro Male ; 47%

40 20

Serbia Male ; 49%

Serbia Female; 33%

Montenegro Female; 34%

0

Montenegro Male

Montenegro Female

Serbia Male

Serbia Female

Graph 2 Source: World Bank: http://data.worldbank.org/indicator/SL.EMP.TOTL.SP.MA.ZS http://data.worldbank.org/indicator/SL.EMP.TOTL.SP.FE.ZS Retrieved in January 2016

Gender-disaggregated unemployment rates also vary across the region. In Armenia and Georgia, they remain well above 15 percent. In Belarus, Moldova and Ukraine, women’s unemployment rates are lower than men’s. In Central Asia and South Caucasus, on the other hand, as well as in Albania, Bosnia and Herzegovina, the former Yugoslav Republic of Macedonia, and Turkey, unemployment rates have generally been higher for women than for men.

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80

Labor Force Participation Rates, by Gender 76.2

74.0 70.8

75.5

75.3

73.5

69.1 65.4

60

76.7

66.9

65.9

62.7

60.5

58.1

55.9 52.7

54.9 50.5

52.3 49.9

40

46.9

47.6

49.6

0

20

43.3

ARM AZE GEO BLR MDA UKR KAZ KGZ TJK TKM UZB ECS male

female

average for 2000 - 2013

Graph 3 Source: World Bank: http://data.worldbank.org/indicator/SL.UEM.TOTL.FE.ZS http://data.worldbank.org/indicator/SL.UEM.TOTL.MA.ZS Retrieved in January 2016 Unemployment, male/female (% of male/female labor force) in Albania, Macedonia, FYR & Turkey for 2000-2014 period 40 35

30 percentage

Albania Male 25

Albania Female

20

Macedonia, FYR Male

15

Macedonia, FYR Female

10

Turkey Male

5

Turkey Female

0

Creating a gender-equal legal frameworks is an important pre-condition for addressing gender inequities in employment and entrepreneurship. Out of the 11 countries in the Caucasus, Western CIS and Central Asia region, only Armenia has no legal differences between women and men in any of the areas reported in the World Bank’s Women, Business and the Law 2016 report. Countries in these

62

countries were judged to have “the world’s most extensive job restrictions on women, keeping women out of many occupations.”68 In Kazakhstan, women are prohibited from 299 jobs while in Belarus, gender discrimination is imposed on 182 jobs. Such restrictions contribute to the persistence of occupational segregation and gender wage gaps.

Private sector growth is generally seen as playing a key role in generating employment in transition countries. In the countries of the Southern Caucasus, Western CIS, and Central Asia, the private sector share of employment ranges from 25% (in Turkmenistan) to 75% (in Armenia, Azerbaijan, Georgia and the Kyrgyz Republic). But because own-account and contributing family workers continue to dominate private sector employment, labour market conditions have not necessarily improved much. Overall, however, the region enjoys an active entrepreneurial culture.

Female business ownership stands at one-third or more in the Caucasus and Central Asia, according to the World Bank Enterprise Survey. However, the ratio of women in leadership positions remains lower. Moreover, women account for about half of all own-account and contributing family workers. Female-managed firms are usually smaller in size than businesses run by men, but they tend to hire more female workers. In Georgia, for instance, 2009 data shows that almost 60% of full-time workers in firms with female ownership participation were women, whereas this ratio was 31 percent in companies with no female ownership. (A World Bank survey of the motivations that lead men and women to become entrepreneurs suggests that own-account work is often driven by necessity, as an alternative to being unemployed.)

Relatively unfavourable access to credit may play a particular role in limiting the growth of female-owned businesses. The 2014 Global Findex survey suggest a gender gap, wider in Belarus and Ukraine than in the other countries of the Caucasus, Western CIS and Central Asia, among individuals who have borrowed to start, operate or expand a farm or business. Women traditionally also have weaker networks to draw upon when setting up and running their businesses. Alleviating these constraints can increase the potential for employment growth. As the data in Figure 2 below suggest, considerable “latent entrepreneurial” potential (Atasoy, 2015), for both women and men, may be present in the region—if constraints posed by underdeveloped financial markets, administrative complexity, political and economic instability, and lack of trust in institutions can be addressed.69

68

Link: http://www.worldbank.org/en/news/press-release/2015/09/09/europe-and-central-asia-region-makes-big-stridesin-gender-equality-but-extensive-job-restrictions-remain-says-wbg-report].

69 (Source: http://wol.iza.org/articles/latent-entrepreneurship-in-transition-economies.pdf)

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Gender-based occupational segregation is an important aspect of inequality in the region. This is particularly apparent in the relatively large numbers of women engaged in (often subsistence and contributory) agricultural labour, as well as working in the service sector. By contrast, men are much more likely to work in industry.

World Bank gender statistics

A closer examination of the gender characteristics of agricultural work offers further insights into problems of inequalities in the region. Women in rural areas across the region are more likely to be working as own account farmers and contributing family workers than men. They are also more likely to engage in less profitable agricultural activities than men: a 2009 Moldovan farm survey showed that, whereas 75% of women viewed vegetable cultivation as their primary responsibility, 66% of men focused on higher value-added vineyard cultivation. Gender gaps in land ownership are

64

also present: in Georgia, Armenia and Moldova, around 30% of land holders are female; this rate drops to 17% in Tajikistan and 12% percent in Kyrgyzstan.

Gender-based inequalities in labour force participation and employment, and occupational segregation, translate into gender-based inequalities in income. Women across the region earn less than men—as is shown below.

Gaps in women’s income (per-capita GNI), relative to men’s

-22%

-43% -42%

-39% -38% -40% -40%

-33% -36% -34%

-48% -47% -50% -50% -50% -56% -64%

Calculations based on HDRO data for 2011, using purchasing-power-parity exchange rates.

Roots of gender inequalities Human capital and education. In the countries of the Southern Caucasus and Western CIS, there is close to full gender parity at the primary and secondary school levels. In Central Asia, however, and especially in Tajikistan, the enrolment of girls remains substantially lower than boys’. At the secondary level, girls tend to outperform boys in all countries where PISA assessments have been conducted. At the tertiary level, women dominate in the South Caucasus, Western CIS, Kazakhstan and Kyrgyzstan; young men are present in larger numbers in Tajikistan, Turkmenistan and Uzbekistan.

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150

Ratio of Female to Male Enrollment, by Level of Education 1 48 .8

1 40 . 0 1 3 5 .8

1 3 4 .8

1 26 . 5 1 21 . 8

1 2 0 .6

1 14 . 7

100

1 1 2 .2 1 0 7 .2 1 0 1 .3 9 7. 3

9 8 .5

1 0 3 .0 1 00 .1

98. 3

9 9 .2

9 8. 9 9 6. 9

1 0 0 .3

9 8. 2

1 00 . 3 1 00 .8

98. 9

1 0 0 .0

9 8 .4 9 6 .4

98. 1 9 6. 3

9 8. 9

9 7. 5

9 7 .9

85. 2

73. 0

50

6 3. 6

0

49. 9

ARM AZE GEO BLR MDA UKR KAZ primary tertiary

KGZ

TJK

TKM UZB ECS

secondary

average for available years

This picture masks some gender-specific specialization by fields of study—which may translate into gender difference in labour market outcomes. In the majority of countries in the region, women comprise more than 70% of graduates in education and more than 65% of students in health and welfare. By contrast, women are underrepresented in degree programmes that prepare students for careers in engineering, manufacturing, and construction (as well as agriculture). Women graduates of secondary and post-secondary education institutions in the region are therefore less likely to have the skills and training most demanded by employers. In this respect, the skills mismatches that exacerbate problems of labour market exclusion across the region pose particularly difficult challenges for women.

Time use. Gender disparities in labour force participation and employment rates also reflect the fact that domestic and care responsibilities in the region fall predominantly on women. Data presented in UNDP’s 2015 Human Development Report Work for Human Development indicate that women in the Albania, Armenia, Serbia, and Turkey devote larger shares of their time to unpaid work (e.g., care for children and the elderly, domestic cooking and cleaning) than do women in other parts of the world (Figure XX). Moreover, because female labour force participate rates in the region are relatively high, the combination of paid and unpaid labour means that women in these countries, as well as in the Kyrgyz Republic, spend more time working than men (Figure YY).

These data also underscore the importance of increased budget funding (and/or more favourable tax treatment) for social care service provision, in order to reduce women’s labour-market and social exclusion (see Box 2). Expanded provision of social care services can also boost female entrepreneurship, by allowing women to expand their businesses and hence address the small size constraint.

Share of unpaid (care) work in total work

Additional time worked by women compared to men (paid + care work combined)

66

39%

Women

Men

85% 76%

73%

70%

24%

64%

19% 39%

17%

15%

13%

28%

25% 18%

17%

Calculations are based on data provided for the most recent year available, as presented in UNDP’s 2015 Human Development Report <<Work for Human Development>>.

Evidence from the South Caucasus, Western CIS and Central Asian countries suggests the gender gap in time use is lower in rural than it is in urban areas. This does not necessarily mean that men and women share household responsibilities better in rural areas; it could also be a reflection of greater gender specialization in unpaid work activities in rural areas. In childcare, however, the gender gap is greater in the countryside as men in rural areas appear less likely to spend time taking care of their children. But women in rural areas also spend less time taking care their children than their urban counterparts. Evidence from Moldova suggests parents in rural areas are less likely to focus on child enrichment and educational activities.

Box 2. Investing in Social Care Infrastructure to Create More Jobs (Ipek Ilkkaracan, Istanbul Technical University, Women’s Studies Centre)70 Among OECD countries, Turkey has by far the lowest rate of access to early child care and preschool education (social care) services. Not coincidentally, it also has the OECD’s lowest labour force participation rate for working-age women (15–64), at 34%—barely half the OECD average.

For most mothers in Turkey, the potential monetary gains from paid work are much lower than the costs of purchasing child care and household services. This results in part from underinvestment in social care services—the government spends just 0.18% of GDP on these services, compared to the OECD average of 0.8%.

In addition to exacerbating gender inequalities, this underinvestment in social care reduces Turkey’s long-term economic potential by reducing the labour force and reducing childhood development opportunities. What is less well known, however, is that expanding social care 70

For the full report, see: www.levyinstitute.org/publications/the-impact-of-public-investment-in-social-care-services-onemployment-gender-equality-and-poverty-the-turkish-case; or http://www.kaum.itu.edu.tr/en/wpcontent/uploads/2015/09/rapor-son-eng.pdf. See also “The Purple Economy: A Call for a New Economic Order beyond the Green Economy,” in LIFE e.V. /GenaNet (ed). Green Economy and Green Growth: Who Cares? Approaching the linkages between Care, Livelihood and the Green/Sustainable Economy, Berlin: Life e.V./German Federal Ministry for the Environment, 2013, pp: 32-38; and Ilkkaracan, I. 2016, “A Feminist Alternative to Austerity: The Purple Economy as a Gender Egalitarian Strategy for Jobs Generation in Europe” in G. Cozzi and S. Himmelweit (ed.s), Recovery for Whom?

Austerity Policies, Gendered Impacts and Policy Alternatives for Europe, London: ZED Books, forthcoming.

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services can also produce considerable short-term economic benefits, in terms of employment creation and reductions in gender inequality and poverty.

Raising Turkey’s early child care and preschool enrolment rate to the OECD average through a publicly funded expansion of ECCPE would require an expenditure of 20.7 billion Turkish lira (in 2014 prices). This would require the creation of 3.27 million places in preschool programmes, which would generate 719,000 social care jobs, directly and indirectly. This is more than 2.5 times the total number of jobs that would be created by devoting the same amount of budget funds to construction/infrastructure projects (290,000). An estimated 84% of the workers hired into these social care jobs would have permanent contracts of unlimited duration (versus 25% in construction); 85% would have social security coverage (compared to 30% in construction).

Most of these social care jobs (73%) would go to women, compared to only 6% in the case of construction spending. Yet in absolute terms, spending in the social care sector would still create nearly 200,000 jobs for men—72% of the total number created for men in the construction scenario. A higher proportion of the construction-generated jobs would go to the unemployed, but in absolute terms more unemployed persons would find jobs in the case of social care expansion. The majority of those receiving jobs would be women previously excluded from the labour market and engaged in domestic work.

In both scenarios, incomes increase the most for households in the bottom 40% of Turkey’s income distribution. But when the impact of the expansion of social care services on labour force participation rates is taken into account, investment in social care would have the more durable economic impact. In addition to creating income for those employed in the expanded social care sector, investments in this sector also enable parents (mothers) who would otherwise be occupied with full-time care responsibilities to enter the workforce. A programme targeted at poor mothers of small children could potentially reduce Turkey’s relative poverty rate by 1.14 percentage points, compared to only a 0.35 percentage point decrease in the case of construction.

Finally, because investments in social care services produce more and better quality jobs in the formal sector than investment in construction, they are likely to produce higher income and social security tax revenues that minimize the net burden on the state budget. An estimated 75% of the initial outlays required to bring Turkey’s social care spending up to OECD levels would ultimately be recovered through higher tax revenues, compared to only 52% in the case of construction spending. Investments in decent jobs can pay dividends for all concerned.

The labour force participation of women with children depends on the availability and affordability of social service infrastructure—particularly for child care and early childhood education.

In Belarus and Ukraine, all 3 to 5 year-old children are enrolled in pre-school and in Moldova, the enrolment rate stands at 82%. In the South Caucasus and Central Asia, however, pre-school enrolment ranges drops to 9% in Tajikistan. Better access to these social care services in the Western CIS countries could be an important explanation for the relatively low rates of income inequalities reported in these countries.

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School Enrollment, 3- 5, preprimary (% gross) 120

104

101

100 82 80 63

58

58

60

46

40

25

25

25

20

9

0

ARM

AZE

GEO

BLR

MDA

UKR

KAZ

KGZ

TJK

TKM

UZB

source: UNESCO database, latest available year since 2008

Source: World Bank: http://data.worldbank.org/indicator/SE.PRE.ENRR Gross enrolment ratio, pre-primary, both sexes (%) in Western Balkans and Turkey 80 70

percentage

60 50 40 30 20 10 0 2000 Albania

2005 Macedonia, FYR

2010 Montenegro

Serbia

2013 Turkey

Migration and gender inequalities As the analysis in the previous chapter showed, most countries in the region report significant shares of domestic populations living (and working) abroad. This is true for both male and female migrantsâ&#x20AC;&#x201D;both of whom tend to engage in precarious, vulnerable jobs and entrepreneurial activities characterized by high degrees of irregularity, and which are largely outside of formal social protection systems.

The impact of migration on men and women is different, in both countries of origin and destination. Less-skilled women migrants from the region tend to provide care work in wealthier countries where female labour force participation rates are relatively highâ&#x20AC;&#x201D;thereby allowing women in these countries work outside of the household. They also tend to be involved in petty trade and other small-scale service sector activities with high degrees of informality. Male labour migrants are

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more likely to work in construction, agriculture (seasonally) and other (manufacturing) sectors. Better trained migrants (women and men) by contrast move to wealthier countries in order to ply their skills for greater remuneration—often raising “brain drain” concerns in countries of origin.

The consequences of migration are also gendered in the country of origin. Both sexes perform an essential economic function by sending remittances and thus boosting consumption and reducing poverty. In social terms, migration creates big gaps in the social network and in the care provision structures when one or both parents become labour migrants. A 2009 IOM study found that up to one third of the married men who leave Tajikistan for migrant labour abroad do not return home (International Organization for Migration, 2009a)—and that, once “abandoned”, their wives face grave difficulties remarrying (owing to the stigma of divorce). Moreover, if their marriages were not formally registered with the civil authorities, these women may not have legal claims upon their (former) husbands’ property or rights to child assistance payments. Survey research conducted by UNICEF 2010-2011 on the effects on the “children left behind” by migrating parents also highlights the deleterious impact of migration on family structures in Tajikistan. This study found that, even in households where the remittances sent by migrants were seen as having an overall positive effect, “children are often affected negatively by the absence of a parent, with a particular impact on their psycho-social well-being” (UNICEF (2011), p. x).

Box 1—Who are the Central Asian migrants in Russia?

Recent (July 2015) data posted on the Russian Federation Migration Service website offer a snapshot of the gender and age profiles of Central Asian migrants in the Russia. In particular: 

Citizens of the Kyrgyz Republic, Tajikistan, and Uzbekistan comprise about a third of the registered migrants in Russia. (If citizens of Kazakhstan and Turkmenistan are added, this “Central Asian” share rises to 40%.)



Migration flows to Russia from Tajikistan and Uzbekistan are dominated by men, who comprised 84% and 82% of the total numbers of registered migrants from these countries, respectively.71 By contrast, women constitute larger shares of migrants from the Kyrgyz Republic (39%), as well as from Kazakhstan (42%). (Women constituted 32% of the total number of migrants in the Russian Federation at this time.) Men from Uzbekistan accounted for nearly one in four (24%) of all registered migrants in Russia.



The age profiles of migrants also differ by country. Whereas 92% of the migrants from Uzbekistan (and 88% from Tajikistan) were between the ages of 17 and 59, the share fell to 81% for migrants from the Kyrgyz Republic, and to 73% for migrants from Kazakhstan. (By way of comparison, migrants between the ages of 17 and 59 constituted 82% of the total number of migrants in the Russian Federation.)

Data from the National Statistical Committee of the Kyrgyz Republic show that some 60-65% of the migrants from that country came from Bishkek City and Chui region during the 2011-2014 period. These two northern, industrial regions also reported the highest intensity of emigrants (per 1000 inhabitants) during this time; this indicator for Osh City was also above the national average. By contrast, labour force

71

The gender dimensions of migration from Central Asia to Russia therefore differ significantly from migration patterns globally, where roughly half the migrants are women (United Nations Department of Social and Economic Affairs, 2013).

70

survey data indicate that more than three quarters of Tajikistan’s external migrants in 2004 and 2009 came from rural areas (IOM, 2015, p. 110).

In sum, these data suggest that migrants in the Russian Federation from Tajikistan and Uzbekistan are most likely to be young, male, working in construction (see Figures 29, 30) and—at least for Tajikistan (and, according to anecdotal evidence, for Uzbekistan as well)—come from rural areas. These trends differ significantly from migration patterns globally, where roughly half the migrants are women (UNDESA, 2013). They may also underscore concerns about “abandoned wives” (IOM, 2009a), and about gender imbalances in rural villages, in which young women may be less likely to find eligible husbands or enjoy equal intra-household status after marriage. Rural women may also be forced to take up the hard physical labour that would otherwise be done by the young men who have migrated to Russia or Kazakhstan (Malyuchenko, 2015).

By contrast, the portrait of migrants from the Kyrgyz Republic is somewhat more balanced in terms of gender and age cohorts. The urban/rural origins of migrants from the Kyrgyz Republic also seems to be more balanced, with relatively large shares of migrants coming from urban areas. Also, the data shown in Figure 23 suggest that the Kyrgyzstani diaspora in the Russian Federation may be somewhat larger (compared to labour migrants from the Kyrgyz Republic), relative to diasporas from Tajikistan and Uzbekistan.

In contrast with Tajikistan and Uzbekistan, the more balanced, “diversified” nature of migration from the Kyrgyz Republic (in terms of gender, age, and locational characteristics), and the (perhaps) somewhat larger Kyrgyzstani diaspora, may help explain the relatively mild reported declines in remittances to the Kyrgyz Republic from the Russian Federation in 2014.

Health, demographics, and gender One of the more surprising aspects of the region’s dimensions are the declines in male life expectancy that took hold during the 1980s in a number of the former Soviet republics, and accelerated in the 1990s, before stabilizing after the new millennium and recovering somewhat in the last few years. Men in Moldova, Kazakhstan, and Ukraine today live about as long as their fathers did; in Belarus, they live about as long as their grandfathers did. By contrast, life expectancy for women in the region remains well above levels reported during the Soviet period.

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Figure 27â&#x20AC;&#x201D;Differences in life expectancy in the Western CIS, relative to global averages (in number of years, 1960-2012) 15

Figure 28â&#x20AC;&#x201D;Differences in life expectancy in Central Asia, relative to global averages (in number of years, 1960-2012) 8

Men Women 10

6

Men Women

4 2

5 0

0

-2 -4

-5

-6

UNDP calculations of unweighted averages, based on World Development Indicators data.

However, when global improvements in life expectancy are taken into account, both men and women are losing ground in most of the region. Whereas men living in (what are now) the Western CIS countries in 1960 lived 12 years longer than global averages, by 2012 their lifespan was on average two years less than the global average (Figure 27). A similar (but not quite as steep) decline for women in the Western CIS countries is likewise apparent: whereas a woman in (what are now) the Western CIS countries in the early 1960s on average lived more than 14 years longer than women in other countries, by 2012 this differential had dropped to about two years. While these declining trends seem to have bottomed out, for men they have stabilized at levels that remain below global averages for male longevity.

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Figure 29—Differences in life expectancy in the Southern Caucasus, relative to global averages (in number of years, 1960-2012) 14 12

Figure 30—Differences in life expectancy in Southeast Europe, relative to global averages (in number of years, 1960-2012) 7

Men Women

6

Men Women

10 8

5

6

4

4 3 2 0

2

-2

UNDP calculations of unweighted averages, based on World Development Indicators data.

Similar trends are apparent in Central Asia (Figure 28).72 Central Asian women, who in 1960 on average lived six years longer than women in other countries, by 2012 were living some six months less. In the Southern Caucasus, declines in female and male life expectancy differentials seem to have bottomed out somewhat above global averages (Figure 29). It is only in Southeast Europe that women have more or less retained their position, relative to women in other countries. Likewise, the deterioration in men’s relative position in Southeast Europe has been rather moderate (Figure 30).

Turkey’s performance within this sub-region is quite impressive for both men and women (Figure 31), and stands in sharp contrast with the rest of the region.

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Trends in the Russian Federation also correspond to this pattern.

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Figure 31—Differences in life expectancy in Turkey, relative to global averages (in number of years, 1960-2012) 6 Men

Women

3

0 1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

2010

2012

-3

-6

-9

UNDP calculations, based on World Development Indicators data.

These unfavourable male mortality trends have been attributed to alcoholism—which may also account for higher suicide rates. (In Belarus, men are five times more likely than women to commit suicide.) Men may also be less likely to seek medical help and to pursue preventive care.

Surveys conducted in Kazakhstan and Uzbekistan, for example, showed that only 18% of primary care patients were men. While women’s overall health outcomes are generally better, female alcohol consumption as well as substance abuse also seem to have increased. In case of substance abuse, women are less likely to seek treatment. One study found that they account for only 2% of people being treated for addiction in Georgia and 10% in Kyrgyzstan.

Maternal mortality rates in Europe and Central Asia (2013) 210 170

75

61 44

41

36

29

26

26

23

21

21

21

20

16

8

7

7

1

Maternal deaths per 100,000 live births. Source: World Bank World Development Indicators data.

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Maternal mortality, an indicator directly related to female health, increased immediately after the collapse of the Soviet Union in many countries of the region due to the deterioration of health services. The ratios have improved since then, and generally compare favourably with global trends.

However, maternal mortality rates are especially high in Central Asia. This seems to be due to decline in maternity health care use, as well as to the surprisingly poor knowledge of maternal care among both the general population and care providers.

Gender and social attitudes Attitudes toward gender roles can reinforce gender inequalities and hinder (or facilitate) the implementation of policies aimed at reducing them. Literature shows that significant biases shape perceptions of menâ&#x20AC;&#x2122;s and womenâ&#x20AC;&#x2122;s abilities, which requires specific interventions to be overcome. The countries of the region vary greatly in their gender norms and their attitudes toward female engagement in economic, political and household spheres. One of the notable developments in the aftermath of the collapse of the Soviet Union was the resurgence of traditional norms and practices, especially in the countries of the Southern Caucasus and Central Asia. Both men and women in these countries tend to hold more conservative social views than their counterparts in other parts of the region. This is apparent in the data shown below, indicating that large numbers of women in the Southern Caucasus and Central Asia believe that men need jobs more than they do. Survey research also indicates that close to half of both men and women in the Southern Caucasus believe that children suffer when a mother works for pay. In Georgia, more women hold that view than men. Such views, which may limit the effectiveness of social care support policies in raising female labour force participation, are much less common in other parts of the region.

Agreement with the statement: When jobs are scarce, men should have more right to a job than women

85%

73%

men

65%

women

66%

55%

55% 51%

49%

48%

44%

41%

41% 37%

38%

23% 16%

Azerbaijan

Armenia

Belarus

Georgia

Kazakhstan Kyrgyzstan

Ukraine

Uzbekistan

A striking development in the South Caucasus has been the spike in the ratio of male to female births since the 1990s. Although the disparity has been reduced slightly in the past decade, these countries still record 110 male births for every 100 female births. This situation reflects a strong preference for having sons, leading to sex selection thanks to the availability of ultrasound technology and access to abortion. The gender imbalance at birth appears to follow a pattern similar to that of

75

other countries in which the ratio of male births increases initially among urban well-off individuals, and is later followed by poor or rural dwellers. By contrast, some of the Western Balkan countries (particularly Montenegro and Albania) show a loss of male populationâ&#x20AC;&#x201D;mostly likely due to male emigration.

Cultural attitudes toward abusive behaviour against women are also changing. Survey data indicate that the shares of individuals who feel that husbands are sometimes justified in beating their wives has declined in countries for which time series data are available, but there are still wide variations across the region. Whereas only 4% of women hold that view in Belarus, the share rises to 60% in Tajikistan. Income also appears to play are role in womenâ&#x20AC;&#x2122;s willingness to tolerate domestic abuse. In Armenia, women who provide at least 50% of their household income were found to be less likely to view wife beating as an acceptable practice.

Political participation and empowerment Despite policy measures to eradicate gender discrimination, women in the region remain under-represented in political life, as well as in managerial positions in commerce. Efforts to remove the obstacles that stand in the way of women playing more active roles in public and commercial decision-making should play important roles in gender equality policies.

At present, about 20% of the seats in the regionâ&#x20AC;&#x2122;s national parliaments are held by women.

With the exception of Belarus, this share is lower in the Caucasus, Western CIS, and Central Asia compared to the rest of the region. The same can be said for for women in ministerial positions. It is worth noting that neither female nor male politicians constitute homogeneous groups. It is crucial to understand and identify the specific causes that keep women from reaching decision-making positions and getting elected. The unequal division of domestic labour may prevent women from devoting enough time to civic participation. Women often have little of the necessary social capital to embark on a political career. Lack of confidence and social pressure to conform to traditional gender roles also play a role.

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Chapter 4—Inequalities, health, and HIV/AIDS73 Key messages 

High or rising HIV incidence rates can serve as proxy indicators for official and societal willingness to address difficult but important social exclusion challenges. They can also be seen as the consequences of failures to include such at-risk groups as people who inject drugs, prisoners, and commercial sex workers. Unfortunately, the numbers of people living with HIV in the region are estimated to have risen from 900,000 in 2004 to 1.5 million in 2014.



Efforts to address the challenges posed by the HIV/AIDS epidemic in the region face significant funding constraints—which could easily sharpen with anticipated reductions in donor funding.

These would make the financing of national HIV/AIDS responses increasingly dependent on high social security systems—the high tax rates for which are a major cause of the informality that threatens the region’s social inclusion prospects. This underscores the importance of measures to improve access to HIV prevention and treatment services for incarcerated populations.



Policy and programmatic measures to address these challenges should focus on: o

Creating more inclusive legal environments that emphasize public health over punishment and stigmatization, as well as better access to justice for at-risk social groups;

o

Addressing institutionalised stigma and discrimination, inter alia by sensitizing law enforcement and health-service personnel to the circumstances and needs of people who living with HIV/AIDS, as well as of those at risk of contracting the infection.

o

NGOs. The role of NGOs in outreach and service provision activities as a complement (and not a substitution) to public services should be further emphasized.

Introduction The numbers of people living with HIV in the region are estimated to have risen from 900,000 in 2004 to 1.5 million in 2014. The HIV prevalence rate rose correspondingly from 0.52% in 2004 to 0.93% in 2014 (UNAIDS (2015)). According to UNAIDS, most new cases are reported from Russia (66%) and Ukraine (21%); these countries also exhibit the highest numbers of AIDS-related deaths in the European Region (UNAIDS (2015). With adult HIV prevalence around 1.2%, Ukraine has the highest reported infection level of the 53 countries in the WHO European Region (Kruglov et al (2008)), and is experiencing the region’s fastest-growing epidemic. By the end of 2014, Ukrainian authorities reported a cumulative total of 290,000 adult HIV cases (UNAIDS (2014b)). The current socio-economic crisis in Ukraine, which has led to dramatic reductions in budget funds for health care, almost certainly exacerbated these problems in 2015.

Injecting drug use has traditionally been the predominant mode of HIV transmission in the region, with new infections occurring among people who inject drugs (PWID) estimated at 26% in 2013 (ECDC (2013)). Yet, recently heterosexual transmission is gaining traction, with an estimated 30% of new HIV infections transmitted heterosexually as of 2013 (ibid.). Particularly in mature epidemics, 73

Please send comments on this chapter to Christoph Hamelmann (christoph.hamelmann@undp.org) and Ben Slay (ben.slay@undp.org).

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increasing proportions of women are getting infected (EuroHIV (2011)). WHO data indicate that antiretroviral treatment coverage in the region remains low: in most countries for which data are available, less than a fifth of people estimated living with HIV receive anti-retroviral therapy (Albania is a notable exception).

HIV/AIDS epidemiological trends in the region are important in at least four respects. First, they are important in and of themselves—particularly for individuals living with HIV/AIDS, and for their families and communities. Second, because HIV/AIDS affects predominantly young people, and because it can pose major burdens on public health and social protection systems, HIV/AIDS can have significant labour market and social policy implications. Third, because people living with HIV/AIDS are often infected with other communicable diseases (e.g., venereal diseases, tuberculosis, hepatitis), people living with HIV can pose greater public health risks than might otherwise be the case. More than a third of those living with HIV, including more than half of those also injecting drugs, are estimated to be co-infected with hepatitis C (Aceijas and Rhodes (2007)). The prevalence of multidrugresistant tuberculosis among people living with AIDS is particularly high in Moldova (62%), Kazakhstan (58%), Uzbekistan (56%), Kyrgyzstan (55%), and Belarus (54%) (ECDC (2015)).

Fourth, and perhaps most importantly, the people most at risk of becoming infected with the HIV virus in the region—injecting drug users, commercial sex workers, inmates in correctional institutions, men who have sex with men—are themselves often victims of stigma, discrimination, and other forms of social exclusion. Because stigmatization and discrimination often work against effective management of the epidemic (e.g., the scale of the epidemic among these groups is widely regarded as under-reported—see Bozicevic et al., (2009)), high or rising HIV incidence rates can serve as proxy indicators for official and societal willingness to address difficult but important social exclusion challenges. They can also be seen as the consequences of failures to include the excluded.

At-risk groups and social exclusion People who inject drugs. The stigma, discrimination, and other forms of social marginalization experienced by people who inject drugs limits their access to quality prevention and treatment services and thereby magnifies the impact of the epidemic. (Appendix Table A1 summarizes the inequities experienced by this risk group.) Because people who inject drugs in the region tend to be young and sexually active, their propensity to transmit HIV to their sexual partners and to the general population is relatively high (Kalichman et al (2000), Kelly et al (2003)). Moreover, recent studies indicate that people who inject drugs and are also unemployed are at greater risk of HIV infection than those with jobs (Platt et al (2013)). Unemployment (or low incomes) can lead people who inject drugs to exchange sex for procuring drugs, which further increases the risk of contracting HIV. Lang et al (2012) find that women may be at increased risk of contracting HIV as a consequence of being forced to have sex with an infected partner. Qualitative evidence from Ukraine, for instance, has shown that this is particularly the case among women who inject drugs (Platt et al., (2013)). Moreover, according to the same source, having an abusive partner may also limit a woman’s ability to negotiate safer sex practices due to fear of further abuse. The link between violence, abuse and HIV risk can trap vulnerable women in a vicious cycle, whereby—in an effort to cope with the shock of gender based violence—victims may engage (further) in substance use, which in turn may lead to sexual risk taking, hence increasing the risk of contracting HIV. In addition to stigma, discrimination, and other feckless social attitudes, a number of policy and institutional barriers constraint the effectiveness of outreach efforts vis-à-vis injecting drug users—and, if infected, treatment care and services. These include the criminalization of injecting drug use—which, in some countries, are linked to widespread police extortion and intimidation of people

78

who inject drugs. They also include legal constraints on the procuring and distribution of harm reduction supplies (which are sometimes inappropriate in character or of poor quality); informal and other payments; and compulsory registration and loss of confidentiality in service delivery settings (Spicer et al (2011)). The interplay of these barriers heightens risks of acquiring the virus among people who inject drugs; and, if infected, reduces their access to anti-retroviral therapy. While injecting drug users made up 61% of HIV cases in Ukraine n 2008, they constituted only 24% of anti-retroviral therapy recipients (Platt et al (2013)).

About a third of the countries in the region have repressive or prohibitionist drug policies and laws, which in some cases are linked to police extortion and intimidation of people who inject drugs (Table 1). Police harassment (as well as fear of harassment) can be a key barrier to prevention measures, including especially access to needle and syringe programmes and opium substitution therapy. For example: 

A study in Ukraine found that police harassment outside of narcology clinics and other locations where needle and syringe programmes and opium substitution therapy were administered deterred many injecting drug users from benefitting from these services (Boltaev et al., (2013)).



Based on interviews with drug users in Kazakhstan, Human Rights Watch reported that police often arrest clients of harm reduction services, confiscate drugs and syringes and extract bribes for possession of syringes/needles (Terlikbayeva et al., (2013)).



Booth et al., (2013) found that fear of police is described as one of the main barriers of treatment and prevention services, with HIV-positive injecting drug users reporting much more frequent negative experiences with the police.



Research results from the region highlight the links between policing practices (including extra-judicial police violence) and increased risk to HIV exposure, and therefore inequitable access to quality services and poor health outcomes. Platt et al., (2013) link the likelihood of police contact and arrest with increased odds of syringe sharing among injecting drug users (Platt et al (2013)).

The prohibition of drug possession often leads to incarceration of the injecting drug users— further heightening their risk of acquiring HIV. Jolley et al., (2012) find that between half and threequarters of people who inject drugs in the region have been arrested at least once. For those injecting drug users who are not infected with HIV, incarceration in prisons and other closed settings can increase HIV risk (Platt et al., (2013)). While drug use may continue in prison, access to harm reduction and anti-retroviral therapy is often reduced, with risk levels consequently higher (Milloy et al., (2011)).

These findings are also supported by the findings made by the Global Commission on HIV and the Law, which also find that incarceration exposes detainees to sexual assault and unsafe injection practices (UNDP (2012)).

In addition to these structural barriers to access to medical services, people who inject drugs often face stigmatization and discrimination from health care providers—reducing trust in the integrity of these services and their use. Terlikbayeva et al., (2013) describe the problems resulting from not ensuring the confidentiality of injecting drug users HIV test results. Viale (2010) finds that fear of the disclosure of positive HIV status among people who inject drugs in Kazakhstan—due to breaches in confidentiality and a consequent backlash from families and communities—prevents these individuals from accessing prevention and treatment. (Terlikbayeva et al., (2013) found that lack

79

of anonymous and confidential counselling for people who inject drugs in Kyrgyzstan contributed to reductions in the frequency of HIV testing among this group.

80

Table 1. Central and Eastern European countries: laws in place pertaining to groups vulnerable to HIV Laws that criminalize same laws that sex sexual activities Laws that criminalize criminalize HIV between consenting adults any aspect of sex work non-disclosure

Albania Armenia Azerbaijan Belarus Bosnia and Herzegovina Bulgaria Croatia FYR Macedonia Georgia Kazakhstan Kyrgyzstan Moldova Montenegro Romania Russia Serbia Slovenia Tajikistan Turkmenistan Ukraine Uzbekistan

Law restrictions on entry, stay or residence

No

Yes

NA

NA

No

Yes

Yes

No

No

Yes

Yes

No

No

Yes

Yes

Yes

No

Yes

No

No

No

No

No

No

No

Yes

No

No

No

Yes

NA

No

No

Yes

Yes

No

No

No

NA

Yes

No

No

Yes

No

No

Yes

Yes

No

No

Yes

Yes

No

No

Yes

Yes

No

No

Yes

Yes

Yes

No

Yes

Yes

No

No

No

NA

No

No

Yes

NA

No

Yes

Yes

NA

Yes

No

Yes

Yes

No

Yes

Yes

Yes

No

Source: AIDSInfo. Data for 2014. NA - no info on the topic for the selected countries.

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These problems underscore the importance of the following policy recommendations: 

Make legal environments more inclusive by emphasizing public health over punishment and stigmatization (Cohen and Csete (2006), UNDP (2012)). Such legal environments should also include support for access to justice for those people who inject drugs whose rights are violated. Some progress in this respect among some of the countries in the region has already been noted (Beletsky et al., (2013)).

In this spirit, the Global Commission on HIV and the Law recommends reforming criminal justice approaches towards drug use, and increasing injecting drug users access to anti-retroviral therapy (UNDP (2012)).



Address institutionalised stigma and discrimination. Such policies would entail inter alia sensitizing law enforcement and health-service personnel to the circumstances and needs of people who inject drugs (UNAIDS (2014)). Some steps in the right direction in that respect have already been taken in some of the countries in the region (e.g., Kyrgyzstan’s experience with police training suggests that police trainings have the potential to improve the integration of policing and public health efforts targeting atrisk groups (Beletsky et al (2013)).



NGOs matter. The role of NGOs in outreach and service provision activities as a complement (and not a substitution) to public services should be further emphasized. There are many success stories in the region that could serve as good practice examples of NGO involvement in outreach and service provision activities (EHRN (2015)). For instance, under the auspices of the project “HIV, Rights and Universal Access in Eastern Europe”, a regional HIV legal network has been established, which, inter alia provides free legal services to people living with HIV and monitors HIV-related right violations (HIV Legal aid (2015)).

Commercial sex workers. Although they are below the rates for injecting drug users, HIV prevalence rates among sex workers in the region still higher relative to the HIV prevalence in the general adult population (Figure 2). Moreover, research indicates that commercial sex workers in the region are relatively likely to injecting drugs (Somlai et al (2002)), thereby facilitating the epidemic’s spread to the general population (Abdala et al., (2008)).

As shown in Table 1, almost all the countries in the region criminalize sex work. As with the criminalization of injecting drug use and possession, the criminalization of sex work has been linked to increased police violence and harassment, thus further heightening the risk of acquiring HIV among sex workers (Platt et al., (2013), World Health Organization (2009)). Fear of police harassment and violence further entrenches the stigma attached to sex work. Police violence can increase HIV risks both directly (by confiscating condoms as evidence or forcing women to have sex) and indirectly (e.g., by reducing sex workers’ income through the enforcement of bribes, which may lead to increased numbers of risky sexual encounters—Platt et al., (2013)).

Moreover, the fear of police violence forces women to work in unfamiliar locations to avoid police harassment as well as working longer hours and hurrying to negotiate with a client and thus reducing the time available to assess the potential risks.

A study by Lang et al. (2012) on sex workers in Armenia found that roughly 57% of the women interviewed suffered some form of gender based violence during their lifetime. A systematic review by Platt et al., (2014) found that 16% of street and off-street sex workers in Kosovo reported being forced to have sex in the last 12 months.

These issues underscore the importance of the following policy recommendations: 

Decriminalize sex work. The criminalization of “the world’s oldest profession” leaves sex workers vulnerable to violence as an occupational hazard, as well as incidents of police harassment and mistreatment. The United Nations has therefore called for the decriminalization of sex work and elimination of the unjust application of laws and regulations against sex work (UNAIDS (2013), UNDP (2012)).

82



Support stigma-reduction programmes. Anti-stigma programmes are most effective when they address relevant individual, organizational, and public policy factors simultaneously.



Support structural interventions that promote community mobilization, in order to help sex workers to defend their rights vis-à-vis the police, brothel owners and clients—including the right to implement HIV interventions at work (Platt et al (2013)).



Strengthen enforcement of laws against human trafficking, to punish those who use force, dishonesty or coercion to procure people into commercial sex, or who abuse migrant sex workers through debt bondage, violence or deprivation of liberty (UNDP (2012)).

Men who have sex with men. Institutionalised homophobia heightens the risk of acquiring HIV among the region’s gay communities. Homosexual acts remain criminalized in Turkmenistan and Uzbekistan, with penalty and imprisonment ranging from two to 10 years (Table 1, Itaborahy (2012)). Because HIV prevalence rates in correctional institutions are generally above those in the general population, and because access to harm reduction and anti-retroviral treatments is generally lower, the criminalization of any activity increases the risk of contracting HIV. Moreover, Platt et al., (2013) find that the criminalization of homosexuality encourages clandestine networks of casual sex partners that do not provide the social capital of regular partnerships.

Repression may therefore increase “casual” sexual interactions that carry increased risk of HIV, while preventing long-term monogamous relationships that can reduce HIV incidence (Platt et al., (2013)).

Available survey data show high levels of discrimination and violence towards men who have sex with men. One study found that the reporting of physical violence as a result of sexual orientation ranged from 10% of men who have sex with men in Georgia to 23% in Turkey (Bozicevic et al., (2009)). Even in countries in which homosexuality is not criminalized, significant barriers to access to services remain, mainly due to social stigma (HRW (2013), Latypov et al (2013), Labrys (2010)). In some of the countries in the region (for example, Central Asia), service providers and HIV programmers have reported this to be a significant barrier to reaching those who may be at risk for HIV infection (Alisheva et al (2007)).

These issues underscore the importance of the following policy recommendations: 

Decriminalize homosexuality, and strengthen the legal protection of homosexuals.



Strengthen public outreach to counter homophobia and stigmatizing myths (UNAIDS (2014a)).

HIV in prison settings. HIV prevalence rates in the region are relatively high among inmates in correctional institutions—particularly among prisoners who inject drugs. Dolan et al., (2007) found that the HIV prevalence rate among prisoners in Ukraine (about 10%) was 15 times higher than among the general population. Azbel et al., (2014), and Izenberg et al., (2013), find that injecting drugs is the single most significant correlate of HIV infection among prison inmates in Ukraine. While injecting drug use may continue in prison, access to harm reduction and prevention services is generally lower than for the general population—thereby increasing the risk of infection (Milloy et al., (2011)). Access to anti-retroviral therapy in correctional institutions is likewise reduced.

This underscores the importance of measures to improve access to HIV prevention and treatment services for incarcerated populations.

Financing HIV programming in the region Compared to general national health financing, HIV programmes in much of the region are still dependent on substantial external funding. In Armenia and Kyrgyzstan for example, donors provide more than

83

three quarters of the funding for HIV programmes (Table 2). Other lacunae in national financing frameworks include the under-funding of efforts to improve legal and regulatory frameworks and engage NGOs in providing outreach services to key at-risk populations; and weak cost controls over the procurement of medical products and services (De Horovitz et al., (2014), Government of Tajikistan (2014)).

Economic volatility in the region (especially in CIS countries), competing demands within the health sector (e.g., for financing response to non-communicable disease threats) and beyond, and tightening of national eligibility criteria for financing from the Global Fund (Katz et al., (2014)) could further limit funding of national HIV programmes. These possibilities place a premium on efforts to expand fiscal national space, to address the financial sustainability of HIV programming.

Table 2. International funding as % of total funding for HIV programmes Country Armenia Belarus Georgia Kazakhstan Kyrgyzstan Moldova Russia Ukraine

79.39 29.00 47.60 16.78 76.87 67.63 9.76 47.10

data as of (year) 2012 2013 2014 2013 2013 2013 2008 2010

Source: UNDP

Conclusions Although HIV/AIDS incidence and prevalence in the region has been rising, the epidemic remains largely concentrated in marginalized at-risk groups (some of which, at least, overlap): people who inject drugs, commercial sex workers, prison inmates, and men who have sex with men. This underscores how many of the people living with HIV and AIDS, as well as those who are at particular risk of contracting HIV, are themselves victims of social exclusion, suffering from multiple deprivations and inequalities. Policy responses to these threats could be improved via the adoption of more inclusive legal and regulatory frameworks that decriminalize activities between consenting adults and more strongly protect the rights of those who are often victims of discrimination and stigma. In these (and many other) areas, increased cooperation between state agencies and NGOs—for outreach to and service delivery vis-à-vis vulnerable groups—in many countries could be an important part of the answer.

As is the case with other components of social protection systems in the region, efforts to address the development challenges posed by the HIV/AIDS epidemic face significant funding constraints. These could easily sharpen with anticipated reductions in donor funding, and make the financing of national HIV/AIDS responses increasingly dependent on high social security systems—the high tax rates for which are a major cause of the informality that threatens the region’s social inclusion prospects. This once again underscores the importance of finding other ways to finance social protection in the region.

84

Table A1. SEEDs and dimensions of inequity for the 'key' population groups in Eastern Europe and Central Asia People who inject drugs

Sex workers

MSM

Prisoner population

Main dimensions of inequity

Disability Ethnicity Gender Lifecourse stage Marginalized groups Place of residence Sexual orientation Socio-economic status/household wealth HIV relevant SEEDs for Health

Access to affordable housing Access to education Access to healthcare Access to social services Biodiversity Business development services Child protection Cildhood education Community participation Discrimination/stigma Drug abuse Early childhood development Economic accountability/governance Effective policing Energy efficiency Exposure to hazardous substances Exposure to violence Family composition Flood defences Food security Fresh water security Greenhouse gas emissions Healthcare infrastructure Healthcare quality Housing quality Human rights Income level/poverty Income protection at the family/community level Indoor air quality Investment in community development Job creation Job secuirty (temporary/no contract) Lack of control over individual family planning Land use Level of crime Lifelong learning (skills/training/other) Maternal health and well being Outdoor air quality Participatory processes Poor nutrition Post conflict reconstructions Psychosocial working conditions Public amenities Public building quality Rural conservation Social cohesion Soil pollution Trade Treatment adherence Transparency and accountability in governance Transport infrastructure (roads/rail/air) Urban planning Waste management Water sanitation Wealth distribution/poverty reduction Welfare policy for social protection Workplace safety

85

Chapter 5—Natural Capital, Inequalities, and Sustainable Human Development74 Key messages 

The measurement of natural capital and environmental sustainability, and their links to inequality and human development, are complex, and multi-faceted. Moreover, most of the literature on these questions has focused primarily on developed economies, as well as large developing economies from other regions. Finally, relevant data for assessing these issues in the transition and developing economies of Europe, Turkey, and Central Asia are sometimes missing. Statements about the sustainability of current development trends in the region should be made with some modesty.



When viewed through the prism of such sustainability indicators as adjustable net savings, the ecological footprint, and the sustainable human development index, the data that are available suggest that the depletion of natural capital, and environmental sustainability concerns more broadly, are relatively pronounced in the region’s lower-middle income countries—which are concentrated in the Caspian Basin. In addition to being the site of the region’s (and one of the world’s) largest man-made ecological disasters (the Aral Sea tragedy), development models in many of these countries are based on the extraction and processing of non-renewable fossil fuels, minerals, and non-ferrous metals. This points to a certain geographic inequity—environmental risks to sustainable development tend to be concentrated in the eastern parts of the region.



The combination of environmental risks, significant food and energy insecurity among less wealthy households, and significant shares of the population living below or close to the poverty line, underscores the fragility of these countries’ development accomplishments. It also underscores the inequalities with which vulnerability and opportunities are distributed within many of these countries.

Introduction Global and regional discussions of inequalities have largely overlooked questions of inequalities in access to and use of natural capital. The literature on linkages between natural capital and inequalities focuses largely on the role and implications of non-renewable natural resources—particularly minerals and energy, but also land, biodiversity, water, and soils—in the economies of nations, regions, and households. Issues of measurement and quantification are often contentious, as we measuring current progress or future sustainability.

This chapter focuses on tensions between the region’s natural capital endowments and the economic development models being pursued. It argues that these tensions are significant and could undermine future development prospects. It also suggests that many of these tensions are apparent in inequalities in access to and use of a variety of types of natural capital. These tensions can explain in part how individuals or groups of individuals gain access to, or are excluded from resources that are central to their human development prospects. It proposes new “sustainable human development” indicators, and it examines the various channels through which the social benefits and costs of using natural capital are distributed.

Measuring natural capital and its links to development in the region Natural capital becomes a resource when it enters the economic cycle. Natural capital includes land, minerals and fossil fuels, solar energy, water, living organisms, and the services provided by the interactions of all these elements in ecological systems” (UNEP 2007: 521). The degree to which those “assets” are seen as “capital” (and, respectively, the degree to which maintaining the “capital stock” is seen as a priority) is indicative 74

Please send comments on this chapter to George Bouma (george.bouma@undp.org) and Ben Slay (ben.slay@undp.org).

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of how “sustainability” and “sustainable development” is understood by various stakeholders. Natural capital is treated here as a public good, which societies have the right and responsibility to use sustainably in meeting their development challenges. While natural capital constitutes an important component of national wealth and is a principal source of income for most countries in the region, the measurement of this wealth and its utilization is often not a priority.

Figure 1: Natural capital rents (% of GDP, excl. agriculture, 2013)

As Figure 1 shows, natural capital makes a significant contribution to GDP. While the relationship between per-capita income and the ratio of mineral and energy resources to GDP in the region is not particularly clear (Figure 2), per-capita income does tend to correlate more closely—and negatively—with endowments of non-mineral and non-energy natural capital are getting more important in resource-poor countries (Figure 3).

That is—less wealthy countries tend to be less reliant on land, water, and forestry resources than more wealthy countries.

Figures 2 and 3: Relationship between non-renewable and renewable resources and GDP

Box 1: Land degradation in Tajikistan

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Agriculture is a key economic sector in Tajikistan, representing 27% of GDP (2013), 94% of the total natural capital wealth, and employing up to 60% of population. It has an important socio-economic role as 43% of the rural population is living below $2.15/day and food security and nutrition issues are prominent.

Close to 97% of all agricultural land suffers from some degree of erosion and 21% of arable land is severely degraded. This is mainly due to unsustainable agricultural practices on steep slopes and marginal land, inefficient and poor irrigation system, overgrazing, and deforestation. Land provides a number of benefits and ecosystem services beyond what are captured by the market. By contrast, degraded land causes not only environmental damage but also social and economic losses—both “off-site” (due to reduced water quality, increased flood risks, and habitat degradation), and “on-site” (lower crop yields, increased fertilizer costs, repairs of damaged structures, loss of soil carbon). An assessment by PEI Tajikistan1 estimated the total annual on-site costs of land degradation at 8% of GDP in 2010. The costs of future natural disasters were estimated to reach up to 70% of Tajikistan’s GDP.

High shares of natural resources in GDP may be problematic in the long run. Existing research suggest that in many countries in the world the share of natural resources in total exports is negatively correlated with the growth rate (Bravo-Ortega, de Gregorio 2005: 20). It means that countries well-endowed with natural resources may enjoy greater welfare in the short run but the export concentration might erode the prospects for sustainable improvement in human development. Gill et al. (2014) find Central Asian countries to be least efficient in turning resource rents into wealth. Accordingly, although resource-rich countries in the region generate high rents, they are less adept at collecting government revenues from them and are least efficient in raising “adjusted net savings” i.e. building capital faster than depleting non-renewable resources. This suggests that the real return on natural capital (at least in the region) is underestimated.

Measuring trends in natural capital consumption Adjusted net savings (ANS) can be defined as the net national savings plus expenditures on education minus energy depletion, mineral depletion, net forest depletion, and carbon dioxide and particulate emissions damage. ANS attempts to bring under one common heading different forms of capital, in order to assess the extent to which natural resources are being transformed into other forms of capital—or have been simply squandered. The region’s energy exporters and Ukraine experienced negative ANS balances until early 2000s, whereupon more positive trends took hold.

30.0 Azerbaijan

20.0 10.0

Kazakhstan

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Figure 4: ANS trends in the region’s energy exporters and Ukraine (ANS/GDP)

The majority of net energy importing countries of the former Soviet Union depict quite steady trends with no severe peaks and falls in the ANS/GDP ratio, except for Georgia in the 1990s (Figure 5).

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40.0 Armenia

30.0 20.0

Belarus

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Figure 5: ANS trends in the former Soviet Union energy countries (ANS/GDP) Albania and the former Yugoslav Republic of Macedonia have experienced increases in the ANS/GDP ratio since the early 1990s (Figure 6).

25.0 20.0 15.0 10.0 5.0 0.0 -5.0 -10.0 -15.0 -20.0 -25.0 -30.0

Albania Bosnia and Herzegovina Croatia Montenegro Serbia

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Figure 6: ANS/GDP trends in the Western Balkans

Examining the data above highlights that it is the energy-exporting non-renewable resource dependent countries (for which data are available) that are drawing down their stock of natural capital. By contrast, the energy-poor countries seem to do better.

Ecological footprint. In 2011 UNDP and the Global Footprint Network undertook an assessment of the links between resource constraints and economic performance in the region. The ecological footprint measures the area of biologically productive land (usually measured in global hectares) and water that is required for the production and extraction of all resources and the disposal of all the waste created. In per-capita terms, the ecological footprint can be viewed as a measure of the burden placed on a countryâ&#x20AC;&#x2122;s natural capital by one of its citizens. Biocapacity is the ability of a given ecosystem or territory to regenerate and meet human demandsâ&#x20AC;&#x201D;to support our consumption and absorb our waste.

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When the biocapacity credit/deficit trend is examined for the region, it can be concluded that the region is in biocapacity deficit, as shown by the line which represents the global biocapacity per person. Countries below the line are consuming more than the global average. Within countries, ecological footprints tend to increase with income levels. These differences may be particularly pronounced in developing countries, where the consumption behaviour of rich households often differs qualitatively as well as quantitatively from poor households’ (Islam, 2015).

As in other regions, ecological footprint per capita is the highest in the region’s wealthiest countries (with highest consumption levels), as well as in its resource-rich countries (Figure 7). In the Western Balkans and Turkey the ecological footprints per capita from country to country are largely similar with no visible outliers.

To some extent, the ecological footprint show similarities to ANS insomuch as many countries in the region may be utilizing their natural resources unsustainability—both from the perspective of converting natural capital in to tangible assets (World Bank, 2011), but also in terms of undermining the stock of ecosystem services that are available (UNDP, 2011). But are these indicators credible? Sustainability measurement has always been contentious.

While ANS has the benefit of following an explicit accounting method, it may problematic in that: (1) the “net national savings” component may be artificially inflated by the unsustainable natural resource exports; and (2) the estimates of “net forest depletion, and carbon dioxide and particulate emissions damage” may be arbitrary, since the ecosystem assets to which they are linked are not valued via markets. Likewise, biocapacity/ecological carrying capacity is extremely difficult to measure, and aggregate across countries, with a high degree of certainty. Rather than rejecting these concepts outright, these caveats argue for using multiple measures of environmental sustainability.

World Biocapacity per person 1,7 gha

Figure 7 Human development versus ecological footprint

The sustainable human development index. UNDP (2011) projected that the potentially adverse effects of global warming on human development (via reductions in agricultural production as well access to improved water and sanitation systems, as well as via pollution) could by 2050 reduce the global human development index by 8-15% (relative to baseline scenarios). Such projections underscore the inter-generational equity

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dimensions of the sustainable development paradigm, which was defined by the World Commission on Economic Development as “meeting the needs of the present without compromising the ability of future generations to meet their own needs” (WCED, 1987). The people-centred dimensions of sustainable dimension were further underscored in the sustainable development principles that were approved by the world’s governments at the 1992 Earth Summit in Rio de Janeiro—especially Rio Principle 1, which specifies that “Human beings are at the centre of concerns for sustainable development. They are entitled to a healthy and productive life in harmony with nature.”

Sustainable development is therefore a close cousin to the human development paradigm, which emphasizes “expanding the richness of human life, rather than simply the richness of the economy in which human beings live. It is an approach that is focused on people and their opportunities and choices.” Today, sustainable development is broadly understood as a three-pillar concept—embracing in an integrated manner social and economic sustainability, as well as environmental sustainability concerns (UN, 2012). The sustainable development goals, which were approved by the world’s governments as the global framework for monitoring national progress towards sustainable development at the UN Sustainable Development Summit in September 2015, likewise reflect a three-pillared, integrated approach towards sustainable development.

These developments have profound implications for measuring human development and UNDP’s human development indicators. This especially pertains to the human development index (HDI), whose components tracking personal income, life expectancy, and education attainment offer a fuller (than per-capita GDP) measure of human progress—one that explicitly addresses social development concerns. The advent of the inequalityadjusted human development index (IHDI), which shows reductions in the HDI that can be attributed to inequalities along each of its three components, further strengthens the abilities of human development indicators to measure and monitor national progress towards sustainable development.

In order to better capture the “sustainability” aspects of sustainable development, the family of human development indicators can be further expanded, in two respects. First: an additional component can be added to the HDI, to capture the environmental dimensions of sustainable development. Second: other dimensions of the HDI can be modified to reflect the sustainability of the development results they represent. For example, a country that achieves rapid economic growth by running unsustainable large fiscal deficits should have the percapita GNI component of its HDI downgraded—relative to a country that has managed to combine economic growth with the retention of fiscal and economic balance.75

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See Ivanov, Peleah, 2013 for methodological background and discussions.

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Figure 21. Sustainable Human Development Index and losses due to non-sustainability in Europe and Central Asia and EU countries.

The results of this “sustainable human development index” (SHDI), which are shown above, indicate that degrees of sustainability in development results achieved differ significantly across the region. Due to largely relatively unsustainable natural resource management practices,76 for example, Turkmenistan’s SHDI is 81% below its HDI. Losses of 68% and 66% are registered for Moldova and Uzbekistan, respectively. At the other extreme, the HDI losses for Albania, Georgia, and Montenegro due to environmental sustainability factors are around 20-25%. (Reductions in the HDI due to possibly unsustainable aspects of the health, education, and economic dimensions are much smaller by comparison—see Figure 22 below.)

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These include indicators for the shares of renewables in national energy balances, shares of national lands devoted to protected areas, the extent of water withdrawals, energy efficiency levels, and the like.

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Figure 22. Economic, Social and Environmental non-sustainability and their contribution to total nonsustainability.

Box: The Aral Sea tragedy Once the world’s fourth largest inland sea (roughly the size of Ireland), the Aral Sea has become better known for being one of the biggest man-made ecological disasters of the 20th century. Due to the unsustainable exploitation of the rivers that flow into it (due largely to cotton and rice cultivation, and to population growth), the Aral Sea lost 90% of its volume between the 1960s and 1990s. In addition to almost significant biodiversity loss, the Aral Sea’s desiccation has meant the collapse of local economies (which had been based on the Aral fisheries and tourism), deteriorating health conditions among local communities, as well as extended desertification and land degradation. Sand storms pollute vast areas, lifting chemical- and salt-saturated dust as far as Antarctica (where traces of Aral chemicals have been found in the penguins’ blood). Since the Aral Sea’s disappearance has removed a moderating influence on the region’s continental climate, summers are now hotter and winters colder.

The core driver of the disaster has been economic development that subordinated future environmental cost considerations to current economic benefits. While the roots of the tragedy can be traced back to central planning decisions of the 1950s, the dissolution of the USSR has brought little relief. And while Kazakhstan has succeeded in restoring part of the watershed by constructing a series of dams, this has done little to reverse the bulk of the tragedy (which lies south of Kazakhstan’s borders).

The Aral Sea disaster underscores how large-scale development projects can lead to tragedy if the complex interlinkages between natural capital and human development are not fully taken into account. It shows how putting too much pressure on an ecosystem can lead to its collapse—with devastating consequences for the people involved. New inequalities—between those whose livelihoods depend on devastated ecosystems and those who do not—and their associated tensions and risks can appear. Such lessons are best not forgotten.

Natural capital, inequality, and human development Inequality and sustainability. Numerous studies have focused on the links between inequality in environmental sustainability. For example, using cross-country data, Wilkinson and Pickett (2007) and Wilkinson et al., (2010) show a positive correlation between country-level income equality and such measures of sustainability as the environmental compliance score (i.e., the importance business leaders ascribe to their governments’ compliance with international environmental agreements), CO2 emissions per $100 of income, and proportion of waste that is recycled. Dorling (2010a, 2010b) found a positive correlation between income inequality (measured by the ratio of the income of the top 10% to that of the bottom 10%) and consumption of resources and waste generation per person.

Neumayer (2011) argues that increases in income inequality may reduce social capital, as more inequality threatens the “social fabric” when the very poor feel disenfranchised and envious of the very rich.

Such increases in inequality may be particularly challenging for societies experiencing fundamental social transformations from deeply egalitarian and collectivist tradition to more market-based, individualist societies.

The longer the socialist period, the further the values and behavioural pendulum may swing from one (collectivist, egalitarian) extreme to another (individualist, “capitalist”).

Wilkinson et al. (2010) identify three mechanisms through which inequality may contribute to of unsustainability. Firstly, inequality may promote materialistic values and increase consumerism, thus leading to a heavier burden on the environment. In a related vein, societies are likely to cooperate more with environmental protection policies that are perceived to be fair. Secondly, more equal societies tend to be more cohesive and have higher levels of mutual trust, which create better grounds for acting in the common good, such as for environmental quality. Furthermore, equality may be crucial for political action to tackle

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environmental unsustainability. Lastly, sustainability requires societies that are more adaptive, and capable of technological innovation and creative solutions. As higher equality is often correlated with high levels of human capital, more equal societies might be better equipped to move towards sustainability.

There is a general view in the literature that more equal societies are more cohesive and have higher levels of trust. These can be prerequisites for the collective action needed to strengthen environmental sustainability. Unequal societies may have higher consumption and waste generation per person, as well as higher pollution levels (Dorling 2010, Torras &Boyce 1998).

UNDP (2011) found some support for the hypothesis that a rise in inequality is associated with subsequent economic crises, but that high inequality is not always linked to crisis. It also found that, since poorer countries that are most effected by the consequences of environmental unsustainability (e.g., floods, drought) are also more limited in their capacities to adapt and/or mitigate their impacts, they may be particularly vulnerable to these consequences. Global inequalities may therefore be exacerbated: the intensification of environmental risks could reverse convergence in human development indexes between developed and developing countries after 2050.

Inequality and natural resource abundance. Natural resource abundance may correlate with higher levels of corruption, rent-seeking, lax enforcement of property rights, and “bad” institutions in general (Papyrakis and Gerlagh, 2004; Gylfason and Zoega, 2006), which in turn may adversely affect economic growth. Vatural resource rents (especially when coupled with ill-defined property rights, missing/imperfect markets, inadequate legal enforcement, etc.) may create opportunities for rent-seeking behaviour that crowd out more socially beneficial activities. In addition, higher levels of natural capital may reduce incentives to create wealth through good policies and institutions, since wealth can be extracted relatively easily from natural resources (Gylfason and Zoega, 2002a; 2002b). These authors also find that unequal distributions of income or land (as measured by Gini coefficients) or education (measured by gender differences in secondary-school enrolment) are directly related to the share of natural resources in national income when the ownership of natural resources is more unequal than the distribution of other forms of wealth.

Do these patterns hold among the developing and transition economies of Europe, Turkey, and Central Asia? On the one hand, the countries with the most equal distributions of income (as measured by the Gini)— Belarus, Moldova, Ukraine—are energy importers; while income inequalities in energy-exporting Kazakhstan are higher. However, the highest levels of income inequalities are reported among relatively resource-poor, energyimporting countries like Georgia, the former Yugoslav Republic of Macedonia, and Turkey.

Papyrakis et al. (2009) find that resource-rich countries tend to experience higher levels of gender inequality (measured by the relative average years of schooling between females and males) than other countries. They also find that while gender inequality in education acts as a channel for resource dependent growth, institutions play a significantly larger role in promoting economic growth in resource-rich countries.

Oniyangi (2013) also focuses on the relationship between natural resource endowments and gender inequality, and show that both point (oil, minerals) and diffuse (agriculture) resource-intensive economies tend to suffer from higher levels of gender inequality. Moreover, higher point source intensity and strong legal institutions increase gender inequality, whereas the presence of weak legal institutions and high point source resources reduce gender inequality.

Inequality and biodiversity. Can a relationship between inequality and biodiversity loss be established?

Data on the issue (particularly from countries in the region) are fragmented. A number of studies however suggest that societies with more unequal distributions of income experience greater losses of biodiversity.

Holland et al. (2009) find that inequality has a stronger independent effect on the proportion of threatened species than GDP per capita. Mikkelson, Gonzalez, and Peterson (2007) find that a 1% increase in the Gini is associated with an almost 2% rise in the number of threatened species. Holland, Peterson, and Gonzalez (2009) likewise conclude that the influence of inequality on species loss is stronger than the impact of GDP per capita.

This trend may also hold true in the region (Figure 10).

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Figure 10: Biodiversity and income inequality in the region Inequality and land. Agriculture and rural livelihoods, which are of fundamental importance in the region, are closely linked to land management. Land degradation can therefore endanger sustainable development prospects and cause social instability. Volraith (2007) found that a reduction in Gini coefficients for land ownership by one standard deviation corresponds to an increase in land productivity of 8.5%, holding constant such variables as aggregate input use, land quality, human capital, and institutional quality. With such high land inequality in Caucuses and Central Asia the reformation of land markets in the transition period has significant implications for social inclusion and livelihoods (Spoor, 2004). The slower pace of land reforms compared to Central and Eastern Europe are likely to also have implications for rural inequalities and poverty.

These findings are consistent with a widely held view that high inequality and perceptions of exclusion occur in countries of Central Asia and Caucuses.

Figure 11: Land Gini and Gini Indexes (Source: FAO cited in IMF 2014)

Threats to sustaining human development. UNDP (2011) argued that rising greenhouse gas emissions linked to unsustainable growth patterns could jeopardize progress in human development (as measured by the HDI) in recent decades. Unsustainable management of land, water, forests, and other ecosystems could pose additional threats. Poor countries have been shown to bear many of the costs of unsustainable resource

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management. For example, low HDI countries have relatively large population shares living on degraded land (Figure 15).

Figure 15: Shares of population living on degraded land (2010) (source HDRO)

Women and girls are often the most affected, because they bear the burden of securing shelter, food, water and fuel, while facing constraints on their access to land and natural resources. Environmental degradation puts small agriculture holders under economic pressures. Men are more likely to migrate in times of difficulty, while women are left to labour on increasingly unproductive land while being responsible for care and family duties. Roma in Southeast European communities, are more likely than non-Roma community members to be exposed to hazardous wastes and chemicals, as well as to flood risks. They are likely to have less access to improved water and sewage systems, as well as proper waste management systems.

The main findings of this section include: 

There is a high level of inequality in life expectancy in resource rich countries by comparison to other countries in the region.

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Consistent with the literature, Gini coefficient provides a positive correlation with share of endangered species highlighting the likelihood of reducing biodiversity as inequality increases.

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Water inequalities exist at the household level and have a significant correlation to inequality in life expectancy.

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While there is a paucity of data on environmental sustainability we can verify that urban air pollution adds to human inequality (IHDI).

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Chapter 6—Inequalities and Inclusive Governance Introduction Just, peaceful and inclusive societies drive sustainable development. The inclusion of Sustainable Development Goal (SDG) 16 in the 2030 Agenda is an unprecedented recognition of this and of the growing demand for global efforts to tackle rising levels of inequality – both real and perceived. This paper on Inequalities and Inclusive Governance takes available data related to key targets of SDG 16 as a framework for analysis of the threats to equality that arise due to governance deficits in the Europe and Commonwealth of Independent States (ECIS) region. It also provides key policy recommendations for action to overcome these structural barriers towards more just, inclusive and peaceful societies.77 The 17 Sustainable Development Goals and 169 targets seek to end poverty, combat inequalities and promote prosperity, while protecting the environment by 2030. SDG 16 aims to promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels.78 The Goal stems from the recognition that sustainable development cannot be realised without peace and security. The Agenda stresses the need to redouble efforts to resolve or prevent conflict and to support post-conflict countries, including through ensuring that women have a role in peacebuilding and state-building.79 The new Agenda also recognizes that equal access to justice based on respect for human rights (including the right to development), and on effective rule of law are critical to making progress on sustainable development and remain challenges for many countries. National, sub-national and local democratic governance and transparent, effective and accountable institutions lie at the heart of whether states will be able to make sustainable progress. Factors which give rise to violence, insecurity and injustice, such as inequality, corruption, poor governance and illicit financial and arms flows, are addressed in the Goal. These aims are also reflected in the views of people throughout the world. The importance of an honest and responsive government was top 3 of the priorities for development rated by the more than 7 million people who participated in My World, a global United Nations survey.

To achieve SDG 16, there are 12 ambitious targets, which are intended to reflect the many facets and dimensions of inclusive and peaceful societies. While not entitled a governance goal, SDG 16 concerns itself with the institutions, rules and norms through which policies are developed and implemented, disputes or conflicts are peacefully resolved, and accountability for the use of power and resources in society is enforced. In its Strategic Plan 2014-2017, UNDP aims to assist countries to maintain or secure peaceful and democratic governance, either when faced with large-scale changes or confronting specific challenges such as reforming constitutions, organizing credible elections or strengthening parliaments.

Reflecting this understanding, five of the twelve targets for SDG 16 were selected to provide a framework for analyzing regional inequalities and governance trends for this paper. These are:     

16.1 Significantly reduce all forms of violence and related death rates everywhere 16.3 Promote the rule of law at the national and international levels, and ensure equal access to justice for all 16.5 Substantially reduce corruption and bribery in all its forms 16.6 Develop effective, accountable and transparent institutions at all levels 16.7 Ensure responsive, inclusive, participatory and representative decision-making at all levels

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Equality and Non-Discrimination at the Heart of the 2030 Agenda: Towards a UN System-Wide Policy and Joint Plan on Addressing Inequalities and Human Rights for Sustainable Development HLCP Positioning Paper UN, 3 October 2015 https://undg.org/wpcontent/uploads/2015/10/ITEM-2-HLCP30-CRP-2-Inequalities_Human-Rights.pdf 78 https://sustainabledevelopment.un.org/?menu=1300 79 Outcome Document of the United Nations Summit August 2015 http://www.un.org/pga/wpcontent/uploads/sites/3/2015/08/120815_outcome-document-of-Summit-for-adoption-of-the-post-2015-development-agenda.pdf

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This paper uses some of the data sets that are currently available for these targets and their proposed indicators to measure SDG16 and links them to dimensions along which the current inequalities exist in the ECIS region and the direction in which they are heading. The focus of the particular trends are related to horizontal rather than vertical inequalities, understood as disparities across culturally defined population groups within societies. The paper is premised on an understanding that inequalities extend beyond economic, to also encompass social, political, legal, cultural and environmental dimensions. Income inequalities have been well linked in the literature to other unequal outcomes, such as in health, education and nutrition.

The 2011 Regional Human Development Report for ECIS, Beyond Transition: Towards Better Societies, concludes that one of the drivers for inequality and social exclusion is structures and institutions.80 This was reinforced at the Dialogue on Inequalities where it was acknowledged that governance institutions, both formal and informal, have a key role to play in addressing the threat of rising inequalities in the region.81 The role of institutions and governance deficits are seen as being among the general causes of increases in inequality or of lack of progress in effectively addressing inequality in many of the countries of the region.

Considerable global research and literature posits that inequalities are linked to the levels of resilience, effectiveness and inclusiveness of political, economic and social institutions within societies. It is widely acknowledged that inequalities are deeply entrenched by structural drivers and barriers that can intersect and reinforce each other, leading to systemic exclusion from generation to generation.82 Governance institutions, rules and processes, both formal and informal, which mediate use of power, force, and resources, are increasingly recognized as critical to this challenge; either as a key cause of inequalities or barrier to progress in the case of governance deficits, or alternatively with inclusive governance as a driver of change towards more sustainable development.

The first section of the paper provides the background and the trends in the ECIS region focused particularly on horizontal inequalities and governance. The second section will then draw conclusions based on existing research and data, as to the governance deficits that are driving those inequalities, or creating barriers to effectively address them. The third and final section provides some key policy recommendations emerging from the analysis.

Background and regional trends The ECIS region has undergone intensive political, economic, and social transformations over the past decades. Pre-1990, poverty and inequalities in the ECIS region were partly mitigated by the social policies of the state. The transition processes, however, have resulted in new distributions of income and wealth, which have caused a growing income gap (as seen in Chart 1 below) as well as the rise of the new rich.

The implications of this are country specificâ&#x20AC;&#x201D;as the countries are extremely diverse in terms of size, level of development, historical background, and social and political structureâ&#x20AC;&#x201D;and are related to the characteristics of the regimes.83 Despite this diversity, there are governance related trends in the region, which are risk factors for causing or exacerbating inequalities. Governance consists of the traditions and institutions by which authority in a country is exercised. This includes the process by which governments are selected, monitored and replaced; the capacity of the government to effectively formulate and implement sound policies; and the respect of citizens 80http://www.undp.org/content/dam/undp/library/Democratic%20Governance/Beyond%20Transition-

%20Towards%20Inclusive%20Societies.pdf 81 http://www.eurasia.undp.org/content/rbec/en/home/ourwork/sustainable-development/development-planning-and-inclusivesustainable-growth/dialogue-on-inequalities/ 82 Global Thematic Consultation on Inequalities, Post 2015 agenda

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and the state for the institutions that govern economic and social interactions among them. As can be seen from Chart 2 below (where the ECIS region is broken into rough sub-regions of about equal size - Central Asia, Eastern Europe, the Caucuses, Turkey and Cyprus, and the Western Balkans), people in many countries in the region do not have a voice in the government. While most of the countries have limited variability in their scores, it is notable that Cyprus has the highest level of voice and accountability in the region, half of the island is in the European Union. Similarly expected trends, based on existing political situations, are seen in places such as Central Asia and Belarus where the countries have extremely low scores, as well as in Turkey where a 7 point decline in voice and accountability over the period from 2006 – 2014 can be clearly seen.

Chart 1 – Gini Coefficients, All Available Countries, 2012 Gini coefficient is a measure of income inequality. The coefficient ranges from 0 (perfect equality) to 100 (complete inequality).

Source: World Bank World Development Indicators

Chart 2 – Voice and Accountability 2006-2014 Voice and accountability captures the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media.

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Source: Worldwide Governance Indicators

The region overall suffers from inadequate systems of governance and weak institutions, which are commonplace in many, but not all countries. The lack of experience and professionalism in governing a newly formed sovereign state, unfavourable economic conditions, the constantly changing political environment, the lack of political will and fear of making major steps towards market reforms and the existence of conflict or frozen conflict in some territories are all likely contributors to the poor level of governance in the ECIS region.

Existing metrics indicate that political and economic institutions in the region are essentially ineffectual and noncompetitive (see Chart 3), and many of them also have a low level of transparency.

Chart 3 â&#x20AC;&#x201C; Government Effectiveness, Selected Countries 2006-2014 Government effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies.

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Source: Worldwide Governance Indicators

Despite some progress in certain sub-regions, such as the Western Balkans where countries are seeking integration in the European Union, trends in the region are point to continuing challenges with inadequate systems of governance and weak institutions, which impact on the provision of services. Across the region the data demonstrates that the sub-regions are closely aligned in their governance measurements, and that with a few notable exceptions the effectiveness of the government has either remained static or risen slightly.

The notable exception to that incremental increase can be seen in Ukraine, which has a large fluctuation over the period. Ukraine had a score of 35 in 2006 then lost 10 points by 2010, then climbing 15 points to a score of 40 in 2014. This fluctuation is noteworthy, as it is in line with research that suggests a causal relationship between insufficient services, inequality and violence or conflict.84 The corruption situation in the region is characterized by the common heritage of post-communist transition, which brought a significant increase in public corruption, to the point of becoming pervasive in many countries, in particular during the early transition period, when economic liberalization and privatization of stateowned assets were introduced in the absence of effective institutional and policy safeguards. Among all countries in the ECIS region the issue of corruption is ranked highly in the concerns of the population and is often ranked second only to the economy/low standard of living. Moreover, people living in the ECIS region do not think that their governments are doing enough to combat corruption, as seen below in Chart 4.

Chart 4 â&#x20AC;&#x201C; Ineffectiveness of Anti-Corruption Efforts, All Available Countries, 2013 Percentages of respondents who believe their governmentâ&#x20AC;&#x2122;s actions to fight corruption are ineffective or very ineffective.

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World Bank. (2011). World Development Report: Conflict, Security & Development. Washington DC.

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Source: Transparency International Global Corruption Barometer 2013, Question 5

Looking over the span from 2006 to 2014 in Chart 5, there has not been marked improvement in the control of corruption across the region, a trends which seems indicative based on the perception of government effectiveness with corruption. While there are a few standouts that have improved their control of corruption (Georgia with a 17 point increase, Belarus with an 18 point increase, and the former Yugoslav Republic of Macedonia with a 15 point increase), the levels in most of the countries and territories in the region have remained rather static.

What does standout though is the variability in the control of corruption between the different subregions, with the Central Asian countries having the lowest average score of control of corruption at 12 and the region of the Caucuses, Turkey and Cyprus having the highest average score for control over corruption at 50.

The main finding though in comparing the data is that there appears to be a disconnect in many of the countries in the region, between the public’s perception of their government’s control of corruption and the actual level of control exerted by the government.

Chart 5 – Government Control of Corruption 2006-2014

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Source: World Bank World Development Indicators Much of the region is also characterized by a sizeable underground or shadow economy, which could be driven by an increased burden of taxation (direct and indirect), combined with (labour market) regulations and the quality of public goods and services as well as the state of the “official” economy. The weighted average size of the shadow economy (as a per cent of "official" GDP) in 2007 in the region was 41.1 per cent compared with 19.4 per cent in high-income countries.85 An increase of the shadow economy can lead to reduced state revenues, which in turn reduce the quality and quantity of publicly provided goods and services. The provision and especially the quality of the public sector services is a crucial causal variable for people’s decision whether to work in the shadow economy.86 The region is also diverse consisting of a range of ethnic, religious and linguistic groups. While some of the countries in the region have highly ethnically homogenous structures, many others are comprised of a more ethnically diverse society. For example, according to the 2011 census in Albania, less than 2 per cent of the population belongs to minority groups.87 Similarly, as shown in their last censuses, Armenia is 98.1 per cent Armenian and 91.6 per cent of Azerbaijan’s population is Azeri. Conversely, Bosnia and Herzegovina is comprised of 48.4 per cent Bosniaks, 32.7 per cent Serbs, 14.6 per cent Croat and 4.3 per cent others, according to its 2013 census. Kazakhstan is comprised of 63.1 per cent Kazakhs, 23.7 per cent Russians, 2.9 per cent Uzbeks, 1.4 per cent Uighur, 1.3 per cent Tatar, 1.1 per cent Germans and 4.4 per cent others, according to its census in 2009.

Chart 6 – Ethnic Diversity, All Available Countries, Latest Available Year

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New Estimates for the Shadow Economies All over the World (PDF Download Available). Available from: http://www.researchgate.net/publication/227346997_New_Estimates_for_the_Shadow_Economies_All_over_the_World [accessed Dec 7, 2015].

86 New Estimates for the Shadow Economies All over the World (PDF Download Available). Available from: http://www.researchgate.net/publication/227346997_New_Estimates_for_the_Shadow_Economies_All_over_the_World [accessed Dec 7, 2015].

87 http://www.instat.gov.al/en/census/census-2011.aspx

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Source: CIA World Factbook

Many of the countries in the region have large ethnic minority groups, such as the Roma, in Central and South Eastern Europe and the Kurds in Turkey. The Roma in particular face discrimination on a daily basis and are often excluded or marginalized from society wherever they are located throughout the region.

The region overall also faces the legacy and pockets of on-going protracted conflict, linked in large part to ethnic or minority divisions. The ethnic composition of many of the counties in the region led to a series of inter-ethnic wars since the 1990s (former Yugoslavia, Tajikistan, Kyrgyzstan, South Ossetia, Georgia, Transnistria, Abkhazia and more recently the Crimea). Other countries are faced with on-going, minority related tensions, such as Turkey, which has had a conflict with its Kurdish population since 1978, with renewed warfare since July 2015. The predominant form of conflict involves separatist movements, along ethnic lines, attempting to break away from one of the successor states of the former Soviet Union or former Yugoslavia. These conflicts have largely ended in stalemate or without a peace treaty, and hence are frozen conflicts or areas of disputed sovereignty. It can also be argued that the situations in much of the Balkans, including the Republika Srpska in Bosnia and Herzegovina, northern Kosovo and fRY of Macedonia remain protracted, though frozen unresolved conflicts.

The conflicts in the ECIS region have resulted in hundreds of thousands of conflict-related deaths, injuries, refugees and internally displaced persons (IDPs), while many thousands of persons still remaining missing. For example, in Bosnia and Herzegovina, as of July 2015, there were still 6,805 refugees and 84,500 IDPs.88 Just over 100,000 people lost their lives in the 1992-1995 conflict, which includes approximately 31,500 missing persons.89 The conflict in Nagorno-Karabakh from 1988-1994 resulted in over 30,000 deaths and 5,000 missing, with 724,000 displaced Azerbaijanis from Armenia, Nagorno-Karabakh and surrounding areas and 300,000â&#x20AC;&#x201C;500,000 displaced Armenians from Azerbaijan, Nagorno-Karabakh and the Armenian border areas.90 In Turkey, it is estimated that up to 30,000 people have been killed since the start of the conflict, with 17,000 people still remaining missing and as many as 3 million persons displaced.91 The Ferghana Valley in Central Asia, consists 88

Data taken from UNHCR www.unhcr.org International Commission on Missing Persons http://www.icmp.int/where-we-work/europe/western-balkans/bosnia-andherzegovina/ 90 Uppsala University Conflict Data Programme http://www.ucdp.uu.se/gpdatabase/gpcountry.php?id=9&value= 91 "Conflict Studies Journal at the University of New Brunswick". Lib.unb.ca.

89

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of a patchwork of ethnicities, with a population of approximately 10 million people. Since independence in 1991, the former Soviet republics of Kyrgyzstan, Tajikistan and Uzbekistan partitioned the area with border lines that form a complex, indecipherable and implausible knot, with many contested border areas. This has caused continuous tension and outbreaks of violent conflict such as in 2010, when 40,000 people were displaced, or in 2005 when Uzbek forces opened fire on protestors, killing up to 1,000 people. These days, the conflict tends to be a result of the deterioration of social infrastructure that has deprived many people of access to affordable education, adequate health care and basic services such as potable water and irrigation systems for agriculture.92 Although the ethnic tensions in the region are well known, less well known is the discrimination that occurs in many countries in the region along ethnic lines. Using UNICEFâ&#x20AC;&#x2122;s MICS data, it is clear that a variety of outcomes in the ECIS region are affected by ethnicity. Although limited by the range of survey questions covered

by MICS, there are a range of education related questions that can help reveal how educational outcomes are varying along ethnic lines within each country. One such outcome is the attendance rates of children in secondary school. Looking at this metric, an interesting case is that of fRY of Macedonia. Chart 7 below shows how secondary school attendance there varies along ethnic lines for two years, 2005 and 2011.

Chart 7 - Secondary School Attendance by Ethnicity, FYR Macedonia, 2005-2011

Source: UNICEF Multiple Indicator Cluster Surveys (MICS)

The data reveals the rate of attendance varies significantly with ethnicity, although attendance for all ethnicities increased strongly between 2005 and 2011 since the Ohrid agreement (signed in 2001) that ended a brief period of inter-ethnic violence. Along with large increases in attendance, the gap between Macedonians and other ethnicities closed by 10 percentage points. This story is not unique in the Balkans. Montenegro also shows strong increases in secondary school attendance across different ethnicities. Like fRY of Macedonia, the data also showed the ethnicities with the lowest attendance in the first year (2006 in this case) closed the gap in 2011.

In the Central Asian countries on the other hand, attendance rates tend to be higher and more equal across ethnicities. Chart 8 below shows the attendance rates for Kazakhstan.

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http://www.irinnews.org/report/24448/central-asia-focus-on-conflict-prevention-in-ferghana-valley

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Chart 8 - Secondary School Attendance by Ethnicity, Kazakhstan, 2005-2011

Source: UNICEF Multiple Indicator Cluster Surveys (MICS)

Although other countries in the region such as Kyrgyzstan and Turkmenistan do have more variation across ethnicities than Kazakhstan, the ethnicities with the lowest attendance rates in 2006 still had higher attendance rates than the Balkan nations in 2011.

Inequalities can also be found across other traditionally marginalized groups, including in particular for women, but also persons with disabilities and the lesbian, gay, bi-sexual, transgender community. Outcomes for women remain unequal in many areas of life, despite equality between women and men being guaranteed in the constitutions of all countries in the ECIS region. Discrimination in public life, gender-based violence, stereotyped gender roles and a strong patriarchal society all fuel continuing worse outcomes in a number of dimensions for women in the region.

Early and forced marriage persists in the region, in South-Eastern Europe predominantly among low income ethnic minorities, and in Central Asia, the Caucasus, and Turkey more generally, limiting employment and educational opportunities for girls and women and exposing them to significant health risks. The trafficking of girls and young women remains a problem.93 However, some progress can be seen in outcomes for women in key areas across the region. For example, the Gender Inequality Index (GII) presents a composite measure of gender inequality using three dimensions: reproductive health, empowerment and the labour market.94 Chart 9 shows the GII scores for countries in the ECIS region for which data is available, as compared to values for selected high-income countries.

Chart 9 â&#x20AC;&#x201C; Gender Inequality Index for All Available ECIS Countries, 2013

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http://eeca.unfpa.org/sites/default/files/pub-pdf/UNFPA_EuroAsia_Factsheet_20140902.pdf Human Development Report 2015 â&#x20AC;&#x201C; Work for Human Development; UNDP; http://hdr.undp.org/sites/default/files/2015_human_development_report_0.pdf 94

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Source: World Bank World Development Indicators

Although no country in the region (for which data was available) has reached a GII score equal to western European nations such as Germany and France, several countries have better scores than the United States (0.29).95 Additionally, even the country with the highest score in the region, Tajikistan (0.38), is closer to the United States than to Saudi Arabia (0.63), or 2013â&#x20AC;&#x2122;s worst performer, Yemen (0.74). Another positive is that GII scores have been falling across the region. As shown in Chart 10, GII scores for ECIS countries have fallen from an average of just over 0.50 in 1995 to 0.28 in 2013.

Chart 10 - Gender Inequality Index for All Available ECIS Countries, 1995-2013

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We should also use a skeptical eye when comparing these GII scores. The high score for the US in particular looks out of place given countries such as Oman (0.28), Bahrain (0.25) and the UAE (0.23) all have lower GII values.

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Source: World Bank World Development Indicators

Chart 11 below shows that every country in the region except two (Turkey and Tajikistan) has a higher percentage of women enrolling in tertiary education. This would indicate that in many countries in the region, it is not a lack of education holding women back, but a lack of employment opportunities.

Chart 11 â&#x20AC;&#x201C; Tertiary Enrolment by Gender, Selected Countries 2013

Source: World Bank World Development Indicators

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The ECIS region has the world’s most extensive job restrictions on women, keeping women out of many occupations. Such restrictions can significantly reduce women’s earning potential and labour force participation, exacerbating the gender wage gap. Many women still face difficulties in accessing basic services. For example, in Kyrgyzstan and Armenia, the maternal mortality rate is 70 and 61 women per 1000 births respectively, compared to the ECIS average of 28.7 per thousand.

Women’s access to justice is limited, which in part stems from their lack of legal recognition as well as the cultural and social perception of women’s legal rights.96 Women’s ownership of land and its associated resources is often restricted by statutory, customary and religious laws.97 In Georgia and Azerbaijan, for example, 30 per cent of agricultural holdings are owned by women, while in Kyrgyzstan this is only 14 per cent. 98 In addition, while there are no explicit legal restrictions limiting women’s access to formal credit, in many countries in the region, it is rare that a woman can develop a business through accessing credit.99 Access to financial services and resources can help women to expand their businesses and over time improve their socio-economic well-being.

Chart 12 – Female Participation Rate100, All Available Countries, 2013

* Modeled ILO estimate not available, national estimate used instead Source: World Bank World Development Indicators

Women are also not well or equally represented in positions of power and influence. As shown in Chart 13, underrepresentation of women in positions of power is particularly stark in the ECIS region, where all countries except two have smaller percentages of female parliamentarians than the OECD average, which in itself is an unimpressive 28 per cent.

96

Closing the Gap: An Overview of UNDP Results in Gender Equality in ECIS, UNDP Istanbul Regional Hub, 2015 http://www.eurasia.undp.org/content/dam/rbec/docs/UNDP%20Gender%20Report%202014%20ECIS%20region-1.pdf 97 World Bank, FAO Aim to boost women’s land ownership in Central Europe, 2014 98 FAO Gender and Land Rights http://www.fao.org/gender-landrights-database/en/ 99 FAO Rural Women in Eastern Europe and Central Asia, 2014, p.3 100 Labour force participation rate, female, % of female population ages 15+, modeled ILO estimate

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Chart 13 - Percentage of Women in Parliament

Source: World Bank World Development Indicators Drilling down further to look at the number of women in ministerial positions, the picture is worse. When it comes to the percentage of women in ministerial positions, only Albania has a higher percentage than the OECD average (see Chart 14).

Chart 14 - Percentage of Women in Ministerial Positions

Source: World Bank World Development Indicators

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However, female representation in parliament is increasing. As shown in Chart 14, all ECIS countries except four increased the number of female parliamentarians between 2006 and 2015. In six countries the increase represented a more than doubling (i.e. greater than 100 per cent increase) of female parliamentarians.

Chart 15 – Change in Percentage of Women in Parliament, 2006-2015

Source: World Bank World Development Indicators In the ECIS region people under the age of 25 make up 22 per cent of the region’s population. 101 Commitment to the development and promulgation of policies to address the needs of young people varies widely across the region, with ideological, political, and resource issues all coming into play.102 Youth unemployment rates in the region vary considerably. They are among the world’s highest in Armenia and fYR of Macedonia at 30 and 43 per cent, respectively. In comparison, unemployment rates in Moldova (14 per cent), the Russian Federation (12 per cent) and Ukraine (17 per cent) look more moderate and are closer to the global average of 13 per cent in 2014 (for 15-24 year-olds).103 The shares of the young population (up to 24 years) for Turkmenistan, Tajikistan and Kyrgyzstan exceed 50 per cent against less than 30 per cent in Russia, Ukraine and Belarus.104 Meanwhile, in Albania young people make up 70 per cent of the population, making it the second youngest in the ECIS region, after Kosovo.105 The youth bulge is associated with propensities for conflict, violence, and criminality particularly when other external factors such as unemployment or overall poor economic performance are in play.106 However,

101

See more at: http://eeca.unfpa.org/publications/focusing-adolescents-and-youth-eastern-europe-and-centralasia#sthash.te92IS4I.dpuf 102 See more at: http://eeca.unfpa.org/publications/focusing-adolescents-and-youth-eastern-europe-and-centralasia#sthash.te92IS4I.dpuf 103 Labour Market Transitions of Young Men and Women in Eastern Europe and Central Asia, International Labour Organisation, March 2015 http://www.ilo.org/employment/areas/youth-employment/work-for-youth/publications/regional-reports/WCMS_357353/lang-en/index.htm 104 http://ec.europa.eu/eurostat/statistics-explained/index.php/EU-Commonwealth_of_Independent_States_(CIS)__statistics_on_population,_employment_and_living_conditions 105 http://www.youthpolicy.org/factsheets/country/albania/ 106 United Nations Department of Economic and Social Affairs. (2011). United Nations World Youth Report 2011: “ Youth Employment : Youth Perspectives on the Pursuit of Decent Work in Changing Times ” (pp. 1–174). Retrieved from http:// unworldyouthreport.org

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worries about youth as a politically destabilizing political force are also linked closely to debates over immigration in light of the relative youth of many migrants.107 The Youth Development Index108 measures the status of 15-29 year-olds in 170 countries according to five key domains: Education, Health and Well-being, Employment, Civic Participation and Political Participation.

Scores range from 0-1, 0 being the lowest youth development and 1 the highest. In the ECIS region, it can be seen that scores and ranking range from 0.452 and 0.474 in Uzbekistan and Belarus respectively and 0.750 and 0.741 in Kyrgyzstan and Kazakhstan respectively. These latter countries are ahead of the global averages and when compared to France receive higher scores and rankings.

Chart 16 – Youth Development in the ECIS Region 2014

Source: Commonwealth Youth Development Index

Spatial inequalities are also prevalent in the region. In the ECIS region, 40 per cent of the total population live in rural areas and agriculture remains an important source of income in most countries. The agricultural share of GDP in Uzbekistan and Kyrgyzstan is 28 per cent and 27 per cent respectively, while in Kazakhstan and the Russian Federation it is as little as 6.8 per cent and 5 per cent respectively.109 The share of the rural population in Central Asian countries is significantly higher (73.4 per cent for Tajikistan, followed by 64.5 per cent for Kyrgyzstan and 63.8 per cent for Uzbekistan) than in European CIS countries (24.1 per cent for Belarus for instance), with the exception of Moldova (55.1 per cent). Access to and the quality of public service provision is a key issue for rural populations.

107

Constance Flanagan & Ronald Youth Civic Engagement in Kassimir, ‘the Developing World: Challenges and Opportunities’ in Handbook of Research on Civic Engagement in Youth, 2010, Lonnie R Sherrod, Judith Torney-Purta (ed), Constance A. Flanagan, Wiley & Sons, New Jersey, p. 98.

108 The Commonwealth Youth Development Index (YDI) measures the status of 15-29 year-olds in 170 countries according to five key domains: Education, Health and Well-being, Employment, Civic Participation and Political Participation. YDI scores range from 0-1, 0 being the lowest youth development and 1 the highest. http://www.youthdevelopmentindex.org/views/index.php#OVER 109 FAO Rural Women in Eastern Europe and Central Asia, 2014, p.3

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Overall, the region still suffers from low levels of the rule of law.110 Chart 17 shows that there are many countries where weak rule of law is clearly a challenge, most notably in the Central Asian countries where the rule of law has extremely low scores. Yet on a positive note it is apparent that across the ECIS region the strength of rule of law is increasing overall, albeit with fluctuations.

Chart 17 – Rule of Law 2006-2014

Source: World Bank World Development Indicators

Governance deficits and linkages with inequalities in the region Various governance deficits impact on inequalities, and are arguably the key threat to the progress made in development terms in the ECIS region since the 1990s. Using key targets of SDG 16 has a framework, this section explores the more prominent linkages between governance deficits and inequalities and the evidence supporting those linkages.

Ensure responsive, inclusive, participatory and representative decision-making at all levels. There is a high level of imbalance in the power among the branches of government within the political structures of the countries of the ECIS region. Democratic governance is premised on three branches of government – the executive, the legislative and the judiciary – placing limits on each other’s power and maintaining a balance that ensures government continues to function under the rule of law, and remains representative of the people.

However, in many countries throughout the ECIS region, the executive branch has obtained more power than the other branches of government, creating an imbalance. As a result, the executive is often unaccountable to opposition parties, the media, civil society and citizens in general. The weak systems of checks and balances, in addition to this limited oversight, means governments are able to maintain a tight grip on power, largely to the exclusion of dissenting voices.

110

Oscar Vilhena Vieira.2007 “Inequality and the subversion of the Rule of Law”.http://www.scielo.br/scielo.php?pid=S180664452007000100003&script=sci_arttext&tlng=en

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Conventional wisdom is that as governments become more autocratic, inequalities within the country will increase. Specifically, the control of power by a small group of people is believed to result in greater economic inequality as those people position themselves to collect economic windfalls and the proceeds of corruption. Autocratic regimes are also generally thought to increase horizontal inequalities as a way of maintaining power – providing benefits and incentives to segments of the population at the expense of others.

However, both the experience of numerous countries in the ECIS region, along with the empirical evidence provides mixed support for the idea that the transition to democracy lowers inequalities.

Empirical evidence suggests the linkage between democracy and inequality is more complex. Timmons (2010)111 finds no systematic relationship between economic inequality and democracy, while Hanson (2013)112 concludes that the economic inequality observed within a country is the result of existing underlying horizontal and vertical pressures that rulers navigate in order to remain in power.

Moving away from economic inequality, Fox and Sandler (2003)113 analyzed how the type of government (autocracies, semi-democracies and democracies) impacted on the discrimination of non-religious and religious minorities. They find that there was no significant difference in discrimination levels for non-religious minorities across the different types of government, while semi-democracies were found to have the lowest discrimination levels for religious minorities (followed by democracies).

In terms of gender inequality, Beer (2009)114 finds that democracy makes a significant contribution to increasing gender equality. However, the model used takes into account the length of time the democracy had been in place and the length of time women have been participating in that democracy.

Chart 18 – Years of Full Women’s Suffrage, All ECIS Countries, 2016

Source: Multiple Sources

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Timmons, Jeffrey F. 2010. “Does Democracy Reduce Economic Inequality?” British Journal of Political Science 40, no. 4: 741-757.

Hanson, Jonathan. "Loyalty and acquiescence: Authoritarian regimes and inequality outcomes." 2010 APSA Annual Meeting Paper.

2013.

113 Fox, Jonathan, and Shmuel Sandler. "Regime Types and Discrimination against Ethnoreligious Minorities: A Cross‐Sectional Analysis of the Autocracy–Democracy Continuum." Political Studies 51.3 (2003): 469-489.

114 Beer, Caroline. "Democracy and gender equality." Studies in Comparative International Development 44.3 (2009): 212-227.

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Chart 18 – Percentage of ECIS Countries with Full Women’s Suffrage, 1910 – 1970

Source: Multiple Sources

One of the impacts of an overpowered executive branch is that the government becomes much easier to influence by vested interests. Without the checks and balances provided by the other branches, vested interests can use their relationships, corruption and other means to pursue policies that specifically benefit them, without concern of being blocked by the legislature, or fear of being prosecuted by an independent judiciary.

Once the ability to influence policy has been established, economic elites, including companies, often drive discrimination and inequality by ensuring the rules remain rigged in their favour, which in turn further increases their influence. This growing influence often reinforces existing social structures, perpetuates inequality and excludes large sections of the population from an equitable share in prosperity.

However, the motivation of elites often extends past simply building wealth and power. For example, Bourguignon and Verdier (2000)115 provide evidence that suggests elites face conflicting interests when it comes to the education of the general population. Although elites benefit from a more educated population in a broad sense, they have strong incentives to prevent the population reaching a high level of education, as a more educated population is likely to seek democratic institutions and accountability from government.

The growing influence of vested interests can also have impacts beyond increasing inequalities.

Acemoglu, Johnson, and Robinson (2004)116 show how the distribution of political power can impact the effectiveness of economic institutions. Their findings suggest that when political power is unevenly distributed, those with power will use it to influence economic institutions to their own (economic) benefit. The other interesting finding from this research suggests that growing influence by elites also tends to lead to lower growth rates in the economy as a whole – something that has plagued the ECIS region in general.

Chart 19 – Perception of State Capture vs. Government Effectiveness

115

Bourguignon, François, and Thierry Verdier. "Oligarchy, democracy, inequality and growth." Journal of development Economics 62.2 (2000): 285-313.

116 Acemoglu, Daron, Simon Johnson, and James Robinson. "Institutions as the Fundamental Cause of Long-Run Growth." (2004).

115

Perception of state capture is measured as the percentage of respondents who believe their government is ‘largely’ or ‘entirely’ run by a few big entities acting in their own best interests.

Sources: Transparency International Global Corruption Barometer 2013 and World Bank Governance Indicators

The ability for vested interests to increase inequality can also occur through unintentional channels.

Reinikka and Svensson (2004)117 provide evidence from Uganda where grants provided to schools are often diverted to the benefit of local officials. However, the amounts being diverted away from schools varied significantly. The explanation for this variance was that the schools were exerting pressure for officials to provide the school with a larger share of the grant money. Unfortunately from an equality standpoint, the schools that were able to extract the largest shares were often the ones with the most resources in the first place. This, in effect, increased the disparity between poor and rich schools.

For the countries of the ECIS region, the data (as shown in Chart 19) does suggest a negative correlation between government effectiveness and the perception of state capture. With the exception of Cyprus, countries with higher proportions of people believing the government is run for the benefit of vested interests generally have lower levels of government effectiveness. Although, as Cyprus indicates, perceptions do not always match reality, they do influence how people interact with their government. Countries in which people perceive the government is not being run for their benefit are also likely to find it much more morally acceptable to participate in bribery and other forms of corruption.

The capture of political processes by elites often extends to control of the media. Petrova (2008)118 finds evidence to suggests that in economies where higher inequality creates larger incentives for those in power to manipulate the preferences of voters, “the result is a decrease in the overall level of taxation and a smaller welfare state.” However, the findings also indicate that the role of the media as a tool for influence is much more important in democracies than autocracies, potentially because there is less need to influence public opinion to maintain power.

117

Reinikka, Ritva, and Jakob Svensson. "Local capture: evidence from a central government transfer program in Uganda." The Quarterly Journal of Economics (2004): 679-705.

118 Petrova, Maria. "Inequality and media capture." Journal of Public Economics 92.1 (2008): 183-212.

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This finding has interesting implications for the ECIS region where most countries are at least nominally democratic. In countries where political leaders are elected, the manipulation of the media is often a necessary tool for maintaining power, even if elections are far from free. This media manipulation may help to explain some of the data in Transparency International’s Global Corruption Barometer. Looking at Chart 20, it is notable that participants for several countries in the ECIS region believed their government was less beholden to vested interests than the citizens of most developed nations. Given the inequality, corruption and economic inefficiency are all at relatively high levels across the region, it is difficult to see how this conclusion could be reached without the complicity of media outlets.

Chart 20 – Perception of Government, All Available Countries, 2013 Percentage of respondents who believe their government is ‘largely’ or ‘entirely’ run by a few big entities acting in their own best interests.

Source: Transparency International Global Corruption Barometer 2013

Looking more broadly at these findings, there are several conclusions that can be drawn. The first conclusion is that the cyclical nature of incentives for elites in developing nations makes reversing the trends very difficult. As elites attempt to increase their influence, their efforts result in greater inequality, which provides those elites with more resources and incentives to increase their influence. This also helps to explain why the problem of vested interests is so persistent in the region. The second conclusion is that this particular deficit is primarily linked with economic inequality. That said, in the ECIS region, the overlap of various horizontal inequalities with economic inequality is likely to mean that any increase in economic inequality will translate to the exacerbation of inequalities along numerous dimensions.

Promote the rule of law at the national and international levels, and ensure equal access to justice for all. Another outcome of the overconcentration of power in the executive branch of government is, in many cases, the politicization of the other branches of government. For the judiciary, the result is that it is unable to place effective limits on executive power and is often used to persecute political opponents, as well as ensure political allies are never brought to account for criminal activity. This reflects the foundation of weak rule of law.

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Chart 21 – Perceptions of Judicial Corruption, All Available Countries, 2013 Percentage of respondents who believe the judiciary in their country is ‘corrupt’ or ‘extremely corrupt’

Source: Transparency International Global Corruption Barometer 2013

However, in addition to supporting dominant executive branches, judicial corruption can also influence inequality via more direct routes. Glaeser, Scheinkman, and Shleifer (2003)119 provide a model that suggests corruption of the courts by vested interests can undermine property rights for those with less influence. This, in turn, leads to a decrease in investment as those people lose confidence in the courts upholding their property rights. With only an influential elite willing to invest, not only is investment severely curtailed, but inequality is increased as those elites benefit from increased economic rents.

In the ethnically diverse countries of the ECIS region, it seems probable that this form of judicial corruption also impacts along ethnic and gender lines. If the courts often treat ethnic minorities, women and members of other disadvantaged groups unfairly when it comes to issues of property rights and contracts, it provides a strong disincentive to invest and accumulate capital. This lack of investment and capital accumulation restricts the ability of those populations to improve their economic situation, perpetuating cycles of poverty.

Chart 22 – New Business Registrations vs. Rule of Law Score 2014 New business registrations normalized using population of countries and taken for latest available year.

119

Glaeser, Edward, Jose Scheinkman, and Andrei Shleifer. "The injustice of inequality." Journal of Monetary Economics 50.1 (2003): 199-222.

118

Sources: World Bank Governance Indicators and World Bank World Development Indicators

BOX: Addressing Inequalities among the Roma Community in the former Yugoslav Republic of Macedonia To address inequalities in the former Yugoslav Republic of Macedonia, Fund for an Open Society Macedonia has supported the development of two legal empowerment delivery models: community paralegal programmes and â&#x20AC;&#x153;lawyers for the marginalizedâ&#x20AC;? (socially excluded groups). Both models are addressing health and human rights violations of socially excluded groups: Roma, drug users, sex workers, transgender and people living with HIV. The community based paralegal model, introduced in 2011, supports Roma civil society organizations in providing paralegal services to local Roma communities in the area of health protection, health insurance and patientâ&#x20AC;&#x2122;s rights protection. Unique from two perspectives, the model addresses health rights violations that exacerbates inequalities in service provision and creates sustainability by using paralegals that originate from Roma communities who are familiar with community needs and cultural specifics. Throughout the year, paralegals provide legal assistance, on issues such as gaining health insurance, obtaining social payments/ benefits, cases dealing with issues of health care access, all of which cause or exacerbate inequalities, to more than 1,000 people.

Source: Open Society Foundation, October 2015

Throughout the region, an aspect of lowering inequalities that is often overlooked is the impact that lack of access to justice is having on marginalized groups. Discrimination can take many forms and is often difficult or impossible to halt through legislation alone. Signage and information not being available in minority languages often means ethnic minorities are less likely to access services or be aware of their rights under the law. A lack of maternity leave and flexible working hours often means women are disadvantaged in the workplace. PWDs are often unable to access government buildings and workplaces due to a lack of disabled access points.

In the ECIS region, there are several examples of how the lack of proactive policies that aim to reduce inequalities, or the failure to apply those policies, has real world impacts. In Serbia, in relation to the employment of national minorities in public service, the majority of public administration authorities and services do not apply

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the regulations, do not plan to take measures to increase the number of minority employees and do not keep records of the ethnic structure of employees. This situation is mirrored throughout the region in the countries/territories studied.120 Discrimination often also influences the services received by disadvantaged groups. Again in Serbia, a survey of professionals highlighted issues with personal documentation and access to information in minority languages. Another issue raised was a shortage of qualified and certified interpreters, the search for which often leads to the prolongation of a case. This situation is typical in the region despite most countries safeguarding the right to speak in their mother tongue in the constitutions, and in other legislation such as criminal and civil procedural codes and specific minority protection legislation.

Community Law Centers in Ukraine Ukraine has a large rural population with limited access to public services or information and people have little knowledge of their rights. Few mechanisms exist for ensuring compliance with the state’s legal framework. While ostensibly democratic, in reality decision-making processes in Ukraine are closed with a bureaucracy that is difficult to navigate and major sources of instability, including the ongoing armed conflict in the Eastern regions, increase in existing inequalities between urban and rural populatio and against specific marginalized groups.

Independent Community Legal Centers (CLCs) created and administered by NGOs provide primary legal aid in over 45 localities, across 20 regions. While some CLCs have ceased operating in conflict-affected zones of Ukraine, others still continue. Staffed locally and operating as separate entities the organizations belong to a national network.

CLCs enable lawyers to provide quality legal aid to the most marginalized and vulnerable populations in society, including Roma, people who use drugs, people living with HIV, people in prison, and internally displaced persons.

The CLCs also address inequalities by educating citizens of their rights and providing advice and assistance on a range of legal issues.

Specific CLCs operate in Roma settlements; employing young Roma specialists and helping them develop a system of primary legal aid in their communities. While focused on Roma specific issues (anti-discrimination, restoration of ID papers, land property, humanitarian aid), they are still included in the general CLC network.

Most CLCs focus on social security, property rights, labor rights, public services, and other administrative matters.

Rising concerns of the network are IDPs rights and military mobilization, due to the armed conflict in Eastern Ukraine. CLCs have adapted to the new issues and new categories of clients as local authorities are often too weak or corrupted or unprepared to respond to these increased demands. The Dnipropetrovsk CLC is actively working with IDPs, providing complex legal aid and support cooperation with the regional council. This model has been shared with other regions that have an increased number of IDPs. Five centers in Chernihiv, Bila Tserkva, Kovel, Kherson and Chuhuev joined their efforts to ensure legal aid to mobilized persons and participants of anti-terrorist operations with in-field visits to military bases and positions.

Source: Open Society Foundation, October 2015

Throughout the region, many countries/territories have constitutions that prohibit discrimination against persons with disabilities (PWDs). However, the reality on the ground often reveals a range of barriers for PWDs. In Kosovo for example, none of the court buildings were found to have full access for PWDs, while 38 percent had no access for PWDs at all. In Serbia, even though discrimination on the basis of disability in the area of access to public buildings and premises is strictly prohibited by the Law on the Prevention of Discrimination against Persons with Disabilities, the majority of the court buildings in Serbia neither have appropriate entrances for PWDs nor layout within the court buildings to support PWDs.121 Often, discrimination comes as a result of lack of awareness of various issues. In a survey of legal professionals in the region, many identified a lack of sufficient awareness and knowledge among judges,

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Strengthening Judicial Integrity through Enhanced Access to Justice, UNDP, 2013 HANDIKOS – association of PWDs in Kosovo, supported by the EC Liaison Office has conducted a survey on the adaptability of public buildings for PWDs in Kosovo “A Suitable Environment – a society for all, 2010”. The survey addresses the concerns on accessibility and furthermore it provides clear technical guidance and instructions for the adaptation of buildings for the needs of these groups. http://www.handi-kos.org/en.

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prosecutors and police, and among the general population on what constitutes gender-based violence. For example, in Kyrgyzstan, no court protective orders were issued for persons who committed spousal assault between 2003 and 2010.122 These types of issues are often in addition to a range of other issues such as sexual and workplace harassment that disproportionately affect women over men.

Develop effective, accountable and transparent institutions at all levels. The quality of political, economic, social, and other institutions within a country is a key determinant of how successful a country is, both economically and socially. Economic institutions are vital for economic growth, business confidence and the general stability of the economy. Political institutions are vital for ensuring citizens have access to decisionmaking and preventing the power of individuals from subverting the democratic process. Unfortunately, in many ECIS countries, the abilities of these institutions are often inadequate due to a range of reasons including politicization, inefficient and complex regulatory environments, and a lack of resources. In many cases, these institutions also remain opaque and/or function without significant oversight, making corruption and petty internal politics commonplace.

Another factor that has historically being linked with a lack of functioning institutions in a growing body of, mostly empirical, literature is ethnic heterogeneity. For example, William and Levine (1997)123 found that ethnic heterogeneity is associated with poorer growth-promoting public good provision (education and infrastructure) in a cross section of up to 107 countries. La Porta et al (1999)124 show a negative association between ethnic heterogeneity and most government quality indicators in a cross section of up to 157 countries.

Based on a cross section of around 80 countries, Easterly, Ritzen and Woolcock (2006)125 also find that ethnic fractionalization reduces a range of governance indicators including civil liberties, government effectiveness, freedom from graft, bureaucratic quality and law and order.

The mechanism for the decrease in governance quality is largely believed to lie in competition between ethnic groups for limited resources. In ethnically heterogeneous societies, groups that gain power have an incentive to use state institutions to improve their position vis-à-vis other ethnic groups. This suggests that more heterogeneity will lead to more interventionist and less efficient institutions (institutions serve the redistributive interests of ruling groups), fewer public goods (to prevent strengthening other groups) and lower political freedoms (to reduce the risk of losing power).

However, the relationship between ethnic fractionalization and government quality overlooks other cleavages within a society that may also be impacting on the quality of governance. In many countries, particularly in the ECIS region, ethnic differences overlap with a range of economic and other inequalities. In other words, what really matters for government quality is likely to be inequalities between ethnic groups, rather than just the number of ethnic groups.

There is significant evidence to support this hypothesis. Baldwin and Huber (2010)126 find that betweengroup inequality is a much more important predictor of public goods provision than ethno-linguistic fractionalization or cultural fractionalization. Kyriacou (2012)127 similarly finds that “accounting for regional disparities reduces the estimated impact of segregation and trust on the quality of government and reduces the statistical robustness of ethnic segregation”. Finally, Alesina et al (2012)128 present simple correlations between 122

Strengthening Judicial Integrity through Enhanced Access to Justice, UNDP, 2013 Easterly, William and Ross Levine (1997). Africa’s Growth Tragedy: Policies and Ethnic Divisions. Quarterly Journal of Economics, 112(4): 1203–50.

124 La Porta, Rafael, Florencio Lopez-de-Silanes, Andre Shleifer and Robert Vishny (1999). The Quality of Government. Journal of Law, 123

Economics and Organization, 15(1): 222–279.

125 Easterly, William, Josef Ritzen and Michael Woolcock (2006). Social Cohesion, Institutions and Growth. Economics and Politics, 18(2): 103–120.

126 Baldwin, Kate and John Huber (2010). Economic Versus Cultural Differences: Forms of Ethnic Diversity and Public Good Provision.

American Political Science Review, 104(4): 644– 662.

127 Kyriacou, Andreas (2012). Ethnic Segregation and the Quality of Government: The Importance of Regional Diversity. Constitutional Political Economy, 23(2): 166–180.

128 Alesina, Alberto, Stelios, Michalopoulos and Elias Papaioannou (2012). Ethnic Inequality. Preliminary draft. March.

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their measures of ethnic group inequality and two governance indicators provided by the World Bank (Control of Corruption and Rule of Law). They find these correlations to be negative and suggest that the impact of ethnic inequality on economic development is also likely to run through its effect on institutional quality.

The relationship between ethnic heterogeneity and government quality may be mediated by trust.

Countries with higher levels of trust have higher government quality partly because trust increases the political engagement of citizens and ultimately makes government more accountable. Moreover, trust can enhance cooperation among public officials and decrease corruption. Conversely, to the extent that ethnic groups are crosscut by other societal cleavages, this can reduce one’s group allegiance and, as such, undermine the salience of ethnicity in social interaction.

The positive aspect of these findings is, if accurate, policies that “level the playing field,” may additionally improve governance and enhance growth prospects.129 The empirical findings presented by Kyriacou (2012)130 in particular suggest “policies designed to facilitate the access of underprivileged ethnic groups to economic and social opportunities can, through their salutary impact on institutional quality, also promote economic development”.

BOX: Oxfam’s Supports Women’s Access to Economic Resources in Tajikistan The equality of women in Tajikistan is a crucial goal, recognized by the national government in its adoption of the National Strategy on Activating the Role of Women’s in Tajikistan 2011-2020.

Inequality and discrimination pervade all aspects of Tajik women’s lives, and women’s access to economic resources is still highly restricted. The situation is particularly critical in rural areas where resource access is significantly influenced by existing customs and traditions. Based on research undertaken by Oxfam Tajikistan, lack of access by women to economic resources not only limits their economic rights, but is also one of the reasons for violence against women in the family.

Women whose rights to economic activity are being violated have limited access to justice as well as material problems, such as no money to pay for attorney fees or legal cost. Women frequently do not know who to appeal to, are unable to write an application to the court independently, and lack legal literacy and awareness. Compounding this is a weak normative framework, inefficient mechanisms to implement the law, low levels of gender sensitivity and awareness agencies for women’s legal protection.

Oxfam Tajikistan supports vulnerable women in rural districts through the provision of packages to improve agricultural production, better access to markets and business activity development, forming self-help groups to provide them with sustainable means of support, as well as ensuring better access of rural female farmers to the markets. At the policy level, Oxfam Tajikistan is addressing the reform of financial institutions in order to improve women’s access to markets, extending women’s rights to own property and special measures to extend credit facilities to women-entrepreneurs.

Source: Oxfam 2015

Weak economic and regulatory institutions in the region can also be linked to prevalence of the shadow economy, which includes all market-based legal production of goods and services that are deliberately concealed from public authorities to avoid a range of taxes, fees and other obligations. This includes the payment of income, value added or other taxes; payment of social security contributions; compliance with certain legal labour market 129

World Bank Development report, 2006, http://wwwwds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2005/09/20/000112742_20050920110826/Rendered/PDF/322040World0Dev elopment0Report02006.pdf 130 Kyriacou, Andreas (2012). Ethnic Segregation and the Quality of Government: The Importance of Regional Diversity. Constitutional Political Economy, 23(2): 166–180.

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standards, such as minimum wages, maximum working hours, safety standards, and compliance with certain administrative procedures, such as completing statistical questionnaires or administrative forms.

Shadow economies often thrive in environments where the costs of doing business legitimately are high.

In this context, high costs can refer to monetary cost (high taxes, fees, requirements for informal payments and/or high labour costs) and the cost of time (complex administrative and compliance requirements). The higher the costs of doing business in the official economy, the greater is the incentive to avoid these costs and operate in the shadow economy.

Many countries in the ECIS region suffer from a lack of functioning institutions and services, have high rates of informal payments, and have complex and poorly understood requirements for registering and running a legitimate business. As a result, many of the countries in the region have a sizeable underground or shadow economy â&#x20AC;&#x201C; which has several impacts on the underlying population.

Chart 23 â&#x20AC;&#x201C; Size of Shadow Economy, All Available Countries 2007

Source: New Estimates for the Shadow Economies all over the World

The immediate impact is that the population working in the shadow economy is not entitled to social assistance and protection from the state. Requirements with regard to working conditions, working time and minimum wages are often not met. Basic benefits provided to ordinary workers such as breaks, sick leave, public holidays and payments into the pension system, are also typically forgone. Importantly, these benefits are often much more vital for people at the bottom end of the income spectrum. Although the shadow economy generates income for the participants and members of their families, who in many cases may not have any source of income, these illicit businesses often crowd out other legitimate businesses due to the lower operating costs.

Due to this crowding out of legitimate businesses, the effect of the shadow economy on inequality has a second impact. Not only are workers in the shadow economy robbed of income and benefits directly, but the government does not collect the tax that an equivalent business would generate. The resulting lower tax revenues leaves the state with less funds for stimulating economic development, building or improving infrastructure, and inequality reduction measures â&#x20AC;&#x201C; all of which, again, disproportionately impact on the most vulnerable people in society.

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Counterproductively, the response of governments to declining revenues is often to increase the tax burden for firms and individuals in the official sector. This, in combination with a deterioration in the quality of public goods (such as infrastructure) and of the administration, provides even stronger incentives to participate in the shadow economy.131 Substantially reduce corruption and bribery in all its forms. As a result of the substandard state of many institutions and the infrequent and/or unreliable provision of services, informal payments and bribing have become commonplace in many countries in the ECIS region. The existence of deficiencies and bottlenecks in the public sector, as a cause of corruption, is confirmed in numerous UNODC studies in the region. For example, in Croatia, more than a third of citizens (35 per cent) participate in a bribery act to speed up a procedure, while almost one in five (18 per cent) does so to receive better treatment.

Chart 24 â&#x20AC;&#x201C; Prevalence of Bribery, All Available Countries, 2013 Percentage of respondents that paid a bribe to any of the 8 listed government services. 132

Source: Transparency International Global Corruption Barometer 2013

Unfortunately, this system of informal payments often serves to heighten existing inequalities. As the poor are less able to provide the required amounts needed, they are provided with substandard services, or in some cases, no services at all. Additionally, members of ethnic and other minorities may be asked to pay more for access to equivalent services, essentially serving as a tax on already disadvantaged groups.

There is significant empirical research providing evidence of the connection between corruption and inequality â&#x20AC;&#x201C; although there is some disagreement about which direction causality flows. Several research papers,

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New Estimates for the Shadow Economies All over the World (PDF Download Available). Available from: http://www.researchgate.net/publication/227346997_New_Estimates_for_the_Shadow_Economies_All_over_the_World [accessed Dec 7, 2015].

132 Education, judiciary, medical and health, police, utilities, land services, tax or customs, registry and permit services

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including Gupta, Davoodi and Alonso-Terme (2002)133, find that corruption increases inequality through a variety of mechanisms, including those described above.

However, there is research that suggests the causality can also flow the other way. You and Khagram (2005)134 find evidence that higher levels of inequality can also lead to higher corruption. This is believed to be due to the poor in highly unequal societies being unable to hold the wealthy and powerful to account. Similarly, Uslaner (2010)135 argues that increasing inequality is likely to lead to increased corruption through a deficit of trust. Both these papers suggest that people are more likely to circumvent laws and regulations when they are considered illegitimate and point to social inequalities as one important source of illegitimacy. Inequality, therefore, is likely to increase petty corruption by making it morally ambiguous, with corruption then further contributing to inequality. The relationship between the prevalence of bribery and perceptions of corruption can also be observed in data for the region, using data from Transparency International’s Global Corruption Barometer (see Chart 25).

Chart 25 – Prevalence of Bribery vs. Perceived Corruption of Public Officials Maps the percentage of respondents that paid a bribe to any of the 8 listed government services 136 against the percentage of respondents that think public officials/civil servants are corrupt or extremely corrupt.

Source: Transparency International Global Corruption Barometer 2013

Furthermore, using a simple linear model to predict the perceived corruption of public officials using the prevalence of bribery reveals two interesting pieces of information. The first is that the y-intercept of the model is 28, which suggests that even in the complete absence of bribery, 28 per cent of respondents in ECIS countries would believe public officials to be corrupt or extremely corrupt.

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Gupta, S., H. Davoodi and R. Alonso-Terme (2002), "Does Corruption Affect Income Inequality and Poverty?", Economics of Governance, Vol. 3: 23-45.

134 You, Jong-sung and Sanjeev Khagram (2005). A Comparative Study of Inequality and Corruption. American Sociological Review, 70: 136–157.

135 Uslaner, Eric (2010). Corruption, Inequality and the Rule of Law. Cambridge University Press.

136 Education, judiciary, medical and health, police, utilities, land services, tax or customs, registry and permit services

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The second conclusion can be derived by comparing the predicted level of perceived corruption of public officials, based on the prevalence of bribery, with the actual level of perceived corruption (see Chart 26).137 This comparison reveals that there is a range of attitudes towards public officials across the region. In Kazakhstan and Turkey, the level of perceived corruption of public official is similar that to respondents in the United States, despite the prevalence of bribery being many multiples higher. At the other extreme, Serbia and Armenia are revealed to have a high level of distrust of public officials for the prevalence of bribery in those countries.

Chart 26 – Predicted Perceived Corruption of Public Officials vs. Actual Values Using a simple model to predict the level of perceived corruption of public official based on the prevalence of bribery, the predicted values are compared to the actual values. Negative values suggest a low level of trust in public officials for the given level of bribery.

Source: Transparency International Global Corruption Barometer 2013

Much of the research again links increased corruption (patronage and nepotism) with ethnic heterogeneity. Glaeser and Saks (2006)138 conclude that ethnic heterogeneity increases corruption because voters are more likely to support corrupt politicians if they are from their own ethnic group due to the expectation that the latter will, in turn, use the state to benefit them. However, as covered earlier, simply linking ethnic heterogeneity with corruption is likely to miss the more complex interactions with ethnic inequalities.

The combination of generalized, entrenched corruption with lack of capacity or political will to adopt meaningful anti-corruption measures creates a vicious circle that undermines citizens’ trust in, and the legitimacy of state institutions. One particular weakness in this sub-region is the insufficient awareness and understanding of corruption prevention as an essential part of any effective anti-corruption policy; anti-corruption is by and large understood as a law enforcement activity (as can be seen among others from the set-up of anti-corruption agencies in Central Asia, as primarily police and prosecutorial units).

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These conclusions do have a caveat: by relating bribery to corruption, the analysis does overlook the other forms of corruption that may be more prevalent in other countries. For example, despite the low level of bribery in the US, the high level of perceived corruption among public officials may be a result of other forms of corruption.

138 Glaeser, Edward and Raven Saks (2006). Corruption in America. Journal of Public Economics, 90: 1053–1072

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That said, there are positive signs. While the corruption situation in the ECIS region remains very serious in most countries, meaningful steps are being taken – partly due to external EU pressure – to address the problem. The experience of the EU’s New Member States from Central Europe demonstrates a correlation between the scrutiny exercised during the pre-accession phase and the anti-corruption efforts of the governments – as visible in their high scores in the Global Integrity Index, in particular for Romania. If these efforts are genuine and sustained, they are likely to lead to actual reduction of corruption levels.

UNODC and UN Women Addressing Gender and Corruption Issues in Albania In Albania, as in many other ECIS countries, women are family members with the primary responsibility for interacting with social service providers such as local health services and social security offices. Women are thus more likely to be confronted with and affected by corruption in their day-to-day lives. Conversely however, women are often less willing to come forward to report acts of corruption from which they have suffered, as they often struggle to have their voice heard in relation to the development and implementation of anti-corruption measures. As a result, specific corruption challenges faced by women are not addressed.

The United Nations Convention against Corruption recognizes that in order to effectively prevent and combat corruption, States must take an inclusive approach and involve all relevant stakeholders, including women, in their anti-corruption efforts. In this context that UNODC, in cooperation with UNWOMEN and the Republic of Albania produced ten key recommendations for addressing the impact of corruption on women in Albania. A key recommendation stated that government and women’s groups should work together to: “Promote the reporting of acts of corruption, for example through the virtual on-line platform that is being developed by the Government and by raising awareness of the existence of other means, such as toll-free numbers and in-person reporting.”

The finding that women are reluctant to come forward to report incidences of corruption impacted the draft Albanian Whistleblower Act 2014 to include greater protection of whistleblowers. Women’s organizations were also actively engaged in screening the draft legislation, discussing how it addressed the priorities and concerns of women’s groups and making specific recommendations.

Source: UNODC October 2015

Significantly reduce all forms of violence and related death rates everywhere. In the ethnically and otherwise diverse countries that typify the ECIS region, conflict has, unfortunately, been a regular occurrence.

There are several proposed reasons for the regular occurrence of conflict in the region.

A key concept linking inequality to conflict is relative deprivation, which captures the extent to which people’s expectations about what they should be achieving exceeds their actual levels of achievement. There is a positive association between an ethnic group’s level of economic inequality and the likelihood that it will initiate a conflict. The positive association between an ethnic group’s level of economic inequality and the likelihood of conflict initiation is particularly strong for those groups that are excluded from power and/or significantly better or worse off economically than the average ethnic group of a country.139 A large body of research supports this conclusion. Cederman, Wimmer and Min (2010)140 analyse 124 ethnic conflicts occurring between 1946 and 2005 and test the link between ethnic groups’ access to power and conflict. The results show that “the frequency of conflict increases roughly with the degree of exclusion. Excluded groups are much more likely to experience a rebellion in their name compared with groups in power.” The research considered “excluded groups” and income levels and found that “excluded groups across all income levels are three times more likely to initiate conflict against the state as compared with included groups that enjoy representation at the centre.”

In the ECIS region there are numerous examples where the exclusion and/or disenfranchisement of ethnic populations from the political process was a factor in conflict and instability. The exclusion of ethnic Albanians from the politics and institutions in Kosovo was a significant driver of the separatist movement and 139

Unequal We Fight: The Impact of Economic Inequality Within Ethnic Groups on Conflict Initiation Patrick Kuhn & Nils Weidmann, March 2013, Princeton University 140

Cederman, L., Wimmer, A., & Min, B. (2010). Why Do Ethnic Groups Rebel: New Data and Analysis. World Politics, 62(1), 87-119.

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1999 conflict. In the current day, the disenfranchisement of the Kurdish population (both inside and outside the country) continues to drive tension in southeast Turkey. In the Caucuses, minorities in Chechnya, Abkhazia and South Ossetia are a continuing cause of tension for the region. Providing these minorities with a political voice is an important step in defusing conflict before relations between groups are damaged beyond repair.

Eurasia Partnership Foundation’s Work in Addressing Inequalities Among Youth and with Social Enterprise Development in Conflict Areas in Georgia Since 2008, the Eurasia Partnership Foundation’s (EPF) Youth Integration Programme has contributed to addressing inequalities, through increased civic engagement of young people residing in 29 communities of Georgia.

EPF follows the Youth Bank (YB) methodology. The youth banks are groups of young people (aged 16-21) who are empowered through access to training and resources in order to find, fund, and oversee small youth-led initiatives to address local community issues, such as cleaning a community park or preparing first-time voters for elections.

During 2008-2015, the Programme trained more than 470 young grant makers, who mobilized more than 4,122 volunteers and engaged in 72 community initiatives outside the EPF-funded projects. The Programme involved 17 local governments, 11 local businesses, and more than 60 schools or local NGOs to support the youth initiatives either with in-kind or financial contributions.

For eight years, EPF has also supported social enterprise (SE) development in Georgia that contributes to increased civic engagement and inclusive growth and addresses inequalities among the most vulnerable groups in Georgian society. To date, ten social enterprises have been set up with grant support from EPF, employing more than 100 individuals representing the most socially vulnerable groups in Georgia (e.g. PWDs, IDPs, women, rural population).

In 2012, for example, the Abkhazian Blind and Deaf and Dumb Union Hera established a social enterprise - Audiomulti Studio Hera, aimed at employing disabled IDPs and providing blind, visually impaired, deaf, and hearingimpaired beneficiaries equal access to literature and information. The enterprise currently employs 15 beneficiaries, including IDPs, war veterans, and other socially vulnerable people. Another example is in 2011, the Coalition for IDP’s Rights established a social enterprise – National Crafts Workshop Ikorta – in the Tserovani IDP settlement, which houses more than 6,400 individuals, who were internally displaced as a result of the 2008 war with Russia. The social enterprise, which aims at fostering both social and economic integration of IDP women currently, employs 11 IDP women.

Source: Eurasia Partnership Foundation, October 2015

Inequalities in social service provision have also been suggested as a significant driver of conflict. A survey cited by the World Bank141 suggests a causal relationship between insufficient services, inequality and violence.

Citizens in the six countries surveyed named poverty/poor education and justice/inequality/corruption as the two primary drivers of conflict.

There are also numerous qualitative examples of inequalities in service provision fuelling conflict. For example, a participatory conflict analysis by Saferworld142 in Kosovo found that electricity provision was perceived as a driver of conflict. Scheduled and unscheduled power cuts, uneven distribution of electricity throughout Kosovo and difficulties paying electricity bills were causing resentment and frustration. Sadly, these negative sentiments were often directed against other communities rather than the Kosovo Energy Corporation (KEK). The research identified the clear risk that differences in energy provision for different communities could contribute to resentment between them.

Unfortunately, conflict rarely results in an improvement for disadvantaged populations. In fact, there is a well-established literature on the role of violence, conflict and fragility in exacerbating inequalities of various kinds. For example, the OECD and other academics have reported on the role of violence in exacerbating political exclusion, with one consequence of conflict and violence being that “political voice and social accountability from the bottom up is often severely undermined.”

141

World Bank. (2011). World Development Report: Conflict, Security & Development. Washington DC. Saferworld. (2011b). Drawing Boundaries in the Western Balkans (Unpublished Paper). Retrieved from the website of Saferworld: http://www.saferworld.org.uk/downloads/pubdocs/Drawing%20boundaries%20in%20t he%20Western%20Balkans.pdf 142

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Using data from 128 countries for the time period 1960-2004, Bircan et al (2010)143 find inequality increases “during war and especially in the early period of post-war reconstruction.” They also find this inequality, on average peaks 5 years after the end of the conflict and then declines to pre-war levels. The experience of many nations in the ECIS region correlates with these findings - sharp rises in economic inequalities in most of the Balkan nations after the conflicts in the 90s now seem to be decreasing, as they are across much of the region.

Tackling inequalities through strengthening the anti-discrimination framework in Serbia Since 2005, UNDP has been addressing discrimination in Serbia with a view to decreasing inequalities in the country. Although protection from discrimination was enshrined in the Constitution in Serbia, the conflicts in the Balkans during the 1990s had increased discrimination, in particular against ethnic minorities, with the 2005 HDR Report showing an increase in ethnic distance in Serbia.

UNDP supported the Government in adopting the Law on the Prohibition of Discrimination in 2009. The Law introduced positive measures for countering discrimination, such as reversed burden of proof in processing cases and the formation of a specialized, independent equality body – the Commissioner for Protection of Equality (CPE). Based on the new Law, UNDP supported and advocated for the establishment and operations of the CPE, and actively advocated for an operational budget through the Ministry of Finance making the leading the CPE to be the first independent body in Serbia relying on regular resources.

As an independent body the CPE establishment of the Commissioner for Protection of Equality has great importance, with the responsibility for raising public awareness, promoting equality and non-discrimination and providing adequate assistance, support and protection for victims of discrimination. To support the CPE’s mission, UNDP also focused on awareness raising, using innovative mechanisms such as entertainment-education to raise awareness against discrimination.

Discrimination is measurably decreasing in Serbia. In the 2011 census recorded there was an unprecedented 40 per cent increase of Roma registering, as compared to the previous census in 2002, which suggesting that Roma feel less fear and are more secure to express their ethnicity. Recent public opinion polls conducted by UNDP show a significant decrease (from 22 percent in 2009 to 16 percent in 2012) in personal experience with discrimination.

While 22 per cent of respondents were directly exposed to discrimination in 2009, the figure decreased to 16 per cent in 2012. And while a 2014 UNDP survey on the attitudes of representatives of public institutions on discrimination found that 40 per cent of complaints received by the CPE relate to citizens interactions with state bodies, ethnic distance towards Albanians and Roma decreased by about 8 percentage points in comparison to the period before UNDP’s interventions, indicating that the society in Serbia is now to a less ethno-centric, more equal and more tolerant society.

Source: UNDP Serbia

The extent of openness in societies that enable strong civil society is also linked to conflict and inequalities. Restrictions on civil society often lead to minorities and disadvantaged groups having little or no ability to have their voices heard within political institutions. This, in turn leads to tensions within the society and forces these groups to resort to other means – conflict, corruption and emigration being just three of the possible outcomes.

Although civil society organizations can be a force for good, there is evidence to suggest that, particularly in multi-ethnic or identity diverse countries like those of the ECIS region, the impact of civil society organizations may not always be a positive one. Varshney (2001) looks specifically at the relationship between civil society and ethnic conflict and finds that the impact can be positive or negative, depending on the environment and the interests the civil society organizations represent. Specifically, he finds that what matters for ethnic violence “is not whether ethnic life or social capital exists but whether social and civic ties cut across ethnic groups. Stated differently, trust based on interethnic, not intraethnic, networks is critical.”

This is a particularly relevant finding for parts of the ECIS region where the development of civil society has been considered a priority for some time. This evidence suggests that more priority may need to be placed 143

Bircan, Cagatay; Brück, Tilman; Vothknecht, Marc (2010): Violent conflict and inequality, Discussion papers // German Institute for Economic Research, No. 1013

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on forming civil society organizations that cut across ethnicities and other divisions in society. Put in another way, forming civil society organizations that only serve the interests of certain ethnic or group identity populations may be counterproductive.

In more recent years, the incidence of conflicts in the region has declined from the relatively chaotic period in the aftermath of the collapse of the former Soviet Union and Yugoslavia, with the recent exception of Ukraine. However, in most countries, ethnic tensions, divisions along minority language and political identity lines and disputes remain unaddressed, maintaining a high risk of reigniting into full conflict. The prevention of a reescalation through enhanced political engagement and the lowering of inequalities should be a priority across the region.

The Illustrative Governance Pilots of SDG 16: Lessons Learnt Constraints around collecting, identifying and prioritizing indicators: Each pilot country selected a range of indicators for measurement, but there is a need for better or greater categorization of the range of indicators for measurement of some targets. To capture more robust information on progress towards the realization of Goal 16, a wide range of data types and sources, including administrative data, experiential, factual and perception-based surveys as well as expert assessments need to be used. An indicator framework should draw on both official and reliable third party data sources, including data produced by the UN and other multilateral institutions, civil society organizations, research institutions, academia and the private sector.

The importance of localization at the sub-national level vis- Ă -vis universalization and harmonization of indicators: Not all indicators can be applicable in the same way everywhere. Therefore, it is important to balance the prerogative of being specific and contextualized in choosing indicators that capture the richness of information at the national and sub-national levels, whilst still being internationally comparable and harmonized across countries. It is also important not to exclusively focus on a handful of indicators that are universally accepted to the exclusion of collecting more localized information that would be relevant in a specific country.

Achieving data reliability and disaggregation: Some countries do not yet have the capacity to collect information at the local level given a large population, disparities between regions and the sheer number of provinces and districts from which to collect data. Capacities of stakeholders are still limited at the subnational level, making it sometimes difficult to align local-level planning mechanisms and programmes with the targets of Goal 16. Meanwhile, selected indicators may not be equally applicable in all regions or districts within countries, leading to a sampling bias and unrepresentative results. For other countries, anticipated sampling bias may result from potential differences between the sampling strategy followed for the collection of governance-related data necessary to monitor progress on Goal 16 versus the strategy followed when administering other socio-economic or household surveys usually collected by the National Statistics Office.

Reconciling an emphasis on indicators with appropriate policies and processes that lead to change: A focus on goal monitoring and related tasks should not crowd out thinking around open-ended or processoriented understandings of achieving better governance. This includes various policies and policy instruments, and a recognition of local limitations on policy-making that will take countries to their ultimate aims. In fact, countries have organized themselves in very different ways at the institutional level to begin the process of implementing a governance-related goal. Therefore, change will appear different within every country context and national strategies and indicators should reflect this.

Preliminary conclusions: The experiences of pilot countries thus far demonstrate that while countries have faced similar challenges and bottlenecks in piloting a governance goal, they have pursued very different models for incorporating the proposed goal(s), targets and indicators into their measurement and monitoring frameworks. Goal 16, therefore, allows for some flexibility in terms of how countries choose to implement

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and localize its targets. In addition, convergence has taken place between the targets and indicators chosen by the pilot countries and the targets of Goal 16. This suggests that some consensus is emerging around measurement issues, with evidence from the use of national, regional and international data sets indicating that it is possible to measure aspects of Goal 16 in the short-term. Finally, the piloting process has highlighted that the implementation of Goal 16 offers the unique opportunity to raise the technical and political capacities necessary for the development of transparent, participatory and accountable governance frameworks within countries.

Source: The Illustrative Governance Pilots of SDG 16, Interim Report, UNDP 2015

Policy Recommendations Based on the analysis of the linkages of governance deficits with many dimensions of inequalities in the region, the following policy recommendations emerge as ways to make progress related to SDG 16 in a manner that can secure gains to date and prevent risks of deterioration in development outcomes across the region.

These need to be aligned with the generation of data and development of indicators to effectively monitor progress. A key challenge today is that data for many of the indicators and targets in SDG 16 are not disaggregated by income, gender, age, ethnicity, race, religion, migration status, disability and geographic location or other characteristics relevant in national contexts. With this, the linkages between disparities and inequities and governance policies are not clear, and can be masked by aggregate numbers, obscuring the real situation of the worst off.

Improve transparency in and expand access to government institutions and services particularly at the local level. There are several different ways in which poor service delivery and restricted access to services is damaging to a society. From encouraging petty corruption and the growth of the shadow economy, to directly resulting in tension and conflict between groups. This has been identified as a key failing in many countries throughout the ECIS region, particularly when it comes to providing health, education and access to justice for disadvantaged groups such as women, ethnic minorities and PWDs. Focusing on improving services can help to increase trust in government, reduce corruption and reduce incentives to avoid tax. In particular, reducing the size of the shadow economy through improvements to institutions and services should be considered a priority by many countries in the region.

Additionally, prioritizing health, education and access to justice, with a focus on reducing inequalities, is expected to have positive flow on effects in terms of improving institutional capabilities, raising business investment and strengthening participation in government decision-making especially at the local level where services and government lie closest to home. This is particularly important for improving outcomes for rural communities.

Focus on norms, policies and new technologies to prevent corruption. Corruption damages trust in societies, both at the highest levels where the corruption of government elites undermines good policy and the provision of services, and at the lowest levels where the requirement of informal payments often prevents access to government services for the most disadvantaged members of societies. However, many anticorruption efforts in the region have focused on finding and prosecuting past corruption, rather than on corruption prevention, with many anticorruption agencies, in particular in Central Asia, being set up as primarily police and prosecutorial units. These types of actions are often undermined and ineffective because those leading the enforcement actions have participated in corruption at some point themselves, or are aware of the involvement of friends and/or family.

Alternatively, there are ways that governments and societies can use technology, data and forwardthinking policy to make corruption more difficult without triggering the self-preservation instincts of politicians and bureaucrats. For example, policies that make government tender processes and the resulting contracts more

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accessible to the public using technology and open data make procurement fraud much more difficult to accomplish and hide. Electronic payments of salaries for public officials and civil servants can help to prevent managers and executives garnishing wages paid in cash. Rigorous asset declaration processes for politicians and high-ranking public officials can help to discourage corruption amongst political elites.

These are some limited examples of how corruption can be minimized in a proactive way. The best examples of these policies are those that ensure not only that corruption is more difficult to participate in, but also that significant improvements are made to the transparency and efficiency of government processes.

Use human rights-based policies and promote fundamental freedoms. A common theme throughout the region is the ability of the executive branch of government, and vested elites, to curb civil and political freedoms and use the government apparatus for their own benefit. In many cases, this situation persists because the general population is denied access to, or lacks awareness of, their rights. This is particularly true when it comes to the awareness of ethnic minorities, women in rural areas and young women and men of their rights and political power.

Policy and legislation that helps to protect civil and political rights, and education policies that help to create awareness of those rights can play a big role in curbing the power of the executive branch, electoral corruption and vote buying. These efforts are likely to be significantly more effective if focused on disadvantaged groups in each country, as they typically provide the greatest scope for improvement.

Human rights-based policies also help historically discriminated against groups to overcome the vicious cycle of inequality and participate more fully in political, social and economic spheres. Proactive steps to provide opportunities are particularly important for those who suffer from intersecting forms of discrimination, such as minority women. Such policies have proven to successfully contribute to more representative government decision-making and better development outcomes.

The aim over time of strengthening democratic governance is to curb the power of the executive and encourage the development of meaningful political opposition so that decision-making processes are inclusive and representative of the society as a whole â&#x20AC;&#x201C; creating a true contest of ideas.

Enable the formulation of a healthy civil society as an active participant in decision-making and conflict resolution. Civil society has a key role to play in improving the cohesiveness of society and giving voice to the concerns of minorities as well as women and youth who still often lack access to political power and decision making. Currently in the ECIS region, many countries have an undeveloped civil society sector. The lack of a developed civil society sector contributes to political disenfranchisement, interethnic or identity-based tensions and a general lack of awareness of issues facing disadvantaged groups such as PWDs. Developed civil society organizations help to not only bring influence to the political landscape, but also to raise awareness of the issues â&#x20AC;&#x201C; such as the negative impact of sexual and gender-based violence on families and societies â&#x20AC;&#x201C; for the general population.

That said, it should be noted that it is important that the right types of civil society organizations are formed. CSOs that simply consolidate existing fault lines within society are unlikely to be helpful in improving the political dialogue or generating inclusive policy. CSOs, for example, that unite women across ethnic lines, or that protect the interests of business owners regardless of their gender or class, can help to bring attention to their specific issues as well as create bonds across societal divides.

Strategies should be employed to encourage the development of CSOs, especially CSOs that cut across ethnic, religious and other social or political divisions, finding common interests and encouraging dialogue between different groups within a society.

Increase investment in new business and in the small and medium size private sector. A key problem holding back many countries in the ECIS region is the lack of investment, particularly in new businesses, including

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those owned by women. One of the results of this lack of investment is high unemployment rates in many countries in the region, particularly among young women and men. High levels of unemployment in turn leads to a range of other problems including increased crime rates, higher risks of conflict and the destruction of public property. Policies that encourage business investment and capital formation in the region can help, not only to grow the economy, but also to reduce unemployment and increase tax revenues. All these in turn have positive flow on effects such as a reduction in ethnic and other social tensions, an improvement in service provision and a reduction in incentives to participate in corruption.

There are several avenues through which increased incentives to invest can be pursued. Many countries have large flows of remittances that, through taxation policy, could be at least partially diverted into investment rather than used simply for consumption. Improving the strength and independence of the judiciary can help to strengthen property rights, giving investors more confidence that money invested will not be forfeited to vested interests. Well targeted tax and fiscal policy can be used to provide incentives for individuals to save and invest in small businesses, rather than consume. Streamlining of the compliance and administrative burdens of running a business can also play a large role in encouraging business development. Finally, governments can work with development agencies to provide training, business expertise and other resources to help people start businesses and create a more fairly competitive and entrepreneurial culture.

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