This chapter demonstrates how gender-based discrimination in social institutions impedes sustainable and inclusive development. It first describes to what extent legal barriers and discriminatory social norms and practices reduce economic growth. It then emphasises how such discrimination compromises women’s empowerment throughout their lives, notably by hindering their school-to-work transition, leading to a high proportion of young women not in education, employment or training, and by increasing the vulnerability of elderly women to poverty, as evidenced by gender pension gaps.
SIGI 2019 Regional Report for Eurasia
Chapter 2. The development cost of discriminatory social institutions
Abstract
Women’s economic, social and political empowerment is critical for meeting political commitments towards Agenda 2030. No Sustainable Development Goals can be achieved if women are left behind. Efforts to abolish discriminatory laws and reshape gender norms in all spheres of Eurasian societies are not only essential to fulfil the fundamental rights of half of the population (i.e. women), but they also support strategies to promote sustainable and inclusive growth.
Leaving no one behind, as called for by the SDG framework, recognises the importance of addressing women’s needs throughout their life cycle, from childhood to old age. The international community has shown increasing commitment to reducing NEET rates (youth not in education, employment or training)and building inclusive social protection systems, including pension schemes, to reduce the vulnerability of women at all stages of their lives. Target 8.6 of the 2030 Agenda aims to “substantially reduce the proportion of youth not in employment, education or training” by 2020, and Target 1.3 to “implement nationally appropriate social protection systems and measures for all, including floors, and by 2030 achieve substantial coverage of the poor and the vulnerable”.
Discriminatory social institutions have a high economic and social cost for the region. Gender gaps in education and employment outcomes slow economic growth. Difficult school-to-work transitions for young women and the risk of poverty for older women create huge social challenges. The first section of this chapter estimates the economic cost of discriminatory social institutions, while the second and third sections illustrate how discriminatory social institutions affect women’s choices and outcomes at specific stages of their lives: before entering the labour market and after retiring.
The economic cost of discrimination
Gender-based discrimination in social institutions impedes economic growth. Discriminatory social institutions constrain women’s opportunities through their influence on the unequal distribution of power between men and women in the family, in the economic sphere and in public life (Ferrant and Kolev, 2016[1]). For example, the practice of early marriage limits girls’ access to education, which has an impact on their future employment opportunities (OECD, 2019[2]). In Kyrgyzstan, 20% of out-of-school girls are not attending school because they got married (DHS, 2012[3]). Similarly, threats to women’s physical integrity can transform schools and workplaces into unsafe spaces. In Moldova, one in five women have been subjected to sexual harassment at school, and the same proportion at their workplace (Partnership for Development Centre, 2018[4]). The absence of child and elderly care facilities or family-friendly job policies, combined with the unequal distribution of caring responsibilities, also creates barriers to women’s full participation in economic life. In Georgia, 22% of women who have a part-time job (but 0% of men) cannot work more hours because their family obligations do not allow them to do so (CRRC, 2018[5]). In Armenia, 14% of economically inactive women (but 0% of men) are not working because they are unable to find suitable childcare facilities (CRRC, 2018[6]).
Billions of dollars are lost due to gender-based discrimination. Losses due to discrimination in Eurasia’s social institutions are estimated at USD 39 billion, or 7.5% of the regional income. This loss amounts on average to USD 888 per capita.1 After taking into account other geographic, economic and institutional factors that also explain economic growth, regional income losses associated with current levels of gender-based discrimination in social institutions are significant: about USD 5 billion in the Caucasus (USD 944 per capita); USD 13 billion in Eastern Europe (USD 830 per capita); and USD 21 billion in Central Asian economies (USD 890 per capita) (Figure 2.1). Discrimination against women is particularly costly for some economies: the GDP loss is greater than USD 1 000 per capita in Azerbaijan (USD 1 305), Turkmenistan (USD 1 349), Belarus (USD 1 414) and Kazakhstan (USD 1 981).
Gender-based discrimination in social institutions hampers global development through three main channels: reduced women’s human capital, reduced women’s labour-force participation and lower levels of investment. The growth literature suggests that a country’s level of economic growth depends on its levels of physical and human capital, as well as on total factor productivity (Mankiw, Romer and Weil, 1992[7]; Solow, 1956[8]). Given a similar distribution of innate abilities between men and women, the exclusion of women from educational opportunities and the job market artificially reduces the pool of talent from which employers can draw, and therefore decreases countries’ ability to accumulate physical and human capital and to innovate (Ferrant and Kolev, 2016[1]).
Discriminatory social institutions like child marriage and son preference lower women’s human capital by 16%. Almost all countries in the region have attained gender parity in school enrolment at the primary, secondary2 and tertiary3 levels (World Bank, n.d.[9]). Yet discriminatory practices make it more complicated for women and girls to invest in their own human capital, notably due to the higher prevalence of child marriage among girls than boys, early pregnancy, discriminatory attitudes and practices towards girls’ higher education, and caring and domestic responsibilities.
Girls in the region are four times as likely as boys to be married before their 18th birthday. Yet all countries but Turkmenistan legally allow girls to marry before the age of 18. This is of particular concern in countries where more than one in ten girls marry early: Georgia, Kyrgyzstan and Tajikistan (14%), and Moldova (11%). High gender gaps in early marriage rates are related to high gender gaps in secondary school completion rates (Figure 2.2). In Moldova, for instance, 26% of girls and women with secondary education married before the age 18, compared to 3% of those who pursued higher education (UNICEF, 2014[10]). This correlation between child marriage and high female school drop-out rates is exacerbated by rurality and poverty.
Child marriage is closely linked with adolescent pregnancy: 90% of the 16 million adolescents who give birth each year are married (UNFPA, 2015[11]). In Eurasia, there were 27 births per 1 000 adolescent girls in 2016. This is below the world average of 45, but the adolescent fertility rate is preoccupying in the Caucasus (46), especially in Azerbaijan (53) and Georgia (47) (World Bank, n.d.[9]), because a high prevalence of early pregnancy is linked to greater inequality in secondary school enrolment (OECD, 2014[12]).
Discriminatory attitudes towards girls’ higher education can reduce their average years of schooling: 28% of the population in eight countries4 think that a university education is more important for a boy than for a girl. Discriminatory attitudes towards girls’ higher education are found among 37% of the Central Asian population, and up to 41% in Kyrgyzstan and 49% in Uzbekistan (Inglehart et al., 2014[13]).
The unequal distribution of domestic responsibilities within the household results in “time poverty” for women and girls, who have less time for school, studies and paid work (Ferrant and Thim, 2019[14]). In Kazakhstan, boys aged 10-14 spend one hour a day on domestic tasks, compared to one hour and a half for girls (Committee of Statistics of Kazakhstan, 2014[15]). Due to domestic responsibilities, 20% of Eurasian women between ages 15 and 24 are not in education, employment or training, compared to only 2% of men (see next section). Domestic responsibilities prevent 25% of young women in Armenia, 28% in Kyrgyzstan and 31% in Georgia from undertaking studies or paid work (UNECE, n.d.[16]).
Discriminatory workplace legislation, norms and practices, such as the absence of paid paternity leave or gender-based violence, reduce women’s labour-force participation by 12%. Across the region, women represent 44% of the economically active population, despite accounting for 51% of the working-age population. Women in Eurasia represent a larger share of the workforce than women globally (39%). However, the gender gap in labour-force participation is in favour of men in all 12 Eurasian countries: from 4 percentage points in Moldova (where 45% of women and 49% of men are economically active) to 28 percentage points in Tajikistan (where 48% of women and 76% of men are economically active) (World Bank, n.d.[9]). The lower participation of women is notably related to discriminatory laws and practices, as well as social expectations underestimating women’s economic role and confining them to reproductive and caring activities, while threatening their physical integrity.
In all countries but Armenia and Georgia, discriminatory laws restrict women’s employment opportunities across sectors. Women are prohibited from working the same night hours as men in five countries5 and from entering certain types of jobs deemed hazardous, arduous or morally inappropriate in ten countries.6 In Kazakhstan, for instance, women are barred from performing 380 jobs in fields such as construction, manufacturing industry, transport, water supply and sanitation or natural resources extraction. Kazakh firms in the sectors of mining and quarrying, construction, and transport and storage have around 80% of men among their employees (ILO, n.d.[17]).
The large gender pay gap in the region may discourage some women from seeking paid employment. On average, women’s monthly earnings are 30% lower than those of men across the region (UNECE, n.d.[16]). In Ukraine, women’s hourly wage rates are on average 18% lower than men’s, independently of the hours worked, the type of activity or the type of occupation. This gap reaches 25% in Belarus, 27% in Kyrgyzstan, 33% in Armenia and 46% in Azerbaijan. The gender pay gap is partly explained by the under-representation of women in better paid positions (for example, only 35% of all managers in Eurasia are women); their over-representation in lower paid positions (59% of service and sales workers are women); and among part-time workers (23% of employed women and 13% of men work part-time in the region) (ILO, n.d.[17]; UNECE, n.d.[16]). The pay gap also stems from direct gender discrimination, where employers pay men and women a different wage for work of equal value. All countries but Georgia mandate equal pay for equal work; however, this limits application of the equal pay principle to work done by two individuals in the same area of activity and within the same working unit. Belarus and Tajikistan are the only countries where the law mandates equal remuneration for work of equal value, which covers broader cases where women and men carry out different work in different sectors (World Bank, 2018[18]). Moreover, no country in the region foresees sanctions for non-compliance or legally mandates companies to report on how they pay women and men.
In many cases, discriminatory norms confine women to the home, while men are expected to earn money for the household. For example, 32% of the population believe that if a wife earns more money than her husband, it is almost certain to cause problems within the marriage (Inglehart et al., 2014[13]). Discriminatory norms are particularly prevalent in Central Asian countries, such as Azerbaijan and Uzbekistan.7 Larger gender gaps in labour-force participation are observed in countries where negative attitudes towards working women are widespread (Figure 2.3).
These discriminatory attitudes are reflected in the distribution of domestic responsibilities across the region. Women spend close to five hours a day performing household chores and taking care of relatives, compared to just over two hours for men. In Armenia, women spend five times more time per day than men on unpaid care work. The absence in five Caucasus and Central Asian countries8 of paid paternity or parental leave for fathers reinforces these gender stereotypes. All in all, higher inequalities in unpaid care work are related to higher gender gaps in labour-force participation (Ferrant, Pesando and Nowacka, 2014[19]). In Georgia and Armenia, respectively 22% and 7% of women who work part-time declare that they do not have enough time to work more than they do because of family obligations, compared to 0% of men in both countries (CRRC, 2018[6]; CRRC, 2018[5]).
Threats to women’s physical integrity are common and further restrict their economic participation. Fertility preferences for sons in the Caucasus have led to a missing women phenomenon, decreasing the size of the female labour force: 170 000 young women are missing in Azerbaijan, Armenia and Georgia (UNFPA, 2012[20]). One in six women in the region has suffered domestic violence; up to one in three in Mongolia and one in two in Moldova. No country has yet enacted laws to protect women from all forms of violence, without exceptions and in a comprehensive manner. Domestic violence has a wide range of adverse consequences beyond physical and psychological injuries. It leads to absenteeism, reduced productivity and higher health care and criminal justice costs (Duvvury et al., 2013[21]; CDC, 2003[22]) In Ukraine for example, violence against women is estimated to cost the economy USD 208 million per year, or 0.23% of the annual GDP (UNFPA, 2017[23]). In Moldova, government spending on social assistance (e.g. counselling, shelter and food for survivors), health care and legal services for victims of domestic violence amounted to USD 1.8 million in 20159 (Women’s Law Center, UN Women and WHO, 2016[24]).
Restricted access for women to entrepreneurship, financial resources and investment opportunities reduces physical capital accumulation by 8%. Economic growth requires investment in physical capital (machinery, buildings, raw materials, etc.). Physical capital accumulation is mainly driven by firms and entrepreneurs and is thus hampered by restrictions on female entrepreneurship. Only 15% of firms across the region have majority female ownership (World Bank, 2017[25]), and 19% of working women are own-account workers, compared to 25% of men. The gender gap in entrepreneurship in the region is lowest in Eastern Europe (12% of working women and 16% of men are own-account workers), followed by the Caucasus (24% of women and 28% of men) and Central Asia (29% of women and 36% of men). The gap reaches up to 15 percentage points in Georgia and 17 in Kyrgyzstan (ILO, n.d.[17]). Women’s entrepreneurship and their contribution to physical capital accumulation are lower than men’s because women face gender-specific discrimination when accessing financial capital or assets.
Women are less likely to access bank financing, and if they do they are more likely to pay higher interest rates. Across the region, 16% of women-led firms that applied for a loan saw their request denied, compared to 10% of men-led firms. In addition, firms led by women are often required to provide higher collateral: 218% of the loan amount on average, compared to 197% for men-led firms (World Bank, 2017[25]). The gender gap in required collateral is particularly pronounced in Kazakhstan, where women-led firms are on average asked to provide collateral 51% higher than men-led firms; Belarus (33%); and Mongolia (29%).
Women’s ability to provide collateral to secure a loan is restricted by their lower ownership of land and non-land assets. The legacy of discriminatory privatisation and restitution land schemes in former Soviet republics, as well as patrilineal inheritance systems and the common registration of assets in a man’s name, result in gender inequalities in asset ownership. As financial institutions often demand collateral guarantees to grant a loan, women are disadvantaged. All countries in the region present a gender gap in obtaining credit. It is particularly pronounced in the Caucasus, and reaches 8 percentage points in Georgia, where 28% of men and 20% of women borrowed from a financial institution in 2017 (Demirgüç-Kunt et al., 2018[26]).
Business networks and associations are generally male-dominated and more difficult to access for women (Sattar, 2012[27]). As men have traditionally been over-represented among entrepreneurs, they are also more present than women in informal networks. In addition, women’s domestic responsibilities can result in their having limited time to attend events and gatherings outside of working hours. Yet these networks are crucial for providing entrepreneurs with support, training, information, business exposure and access to funding.
Women’s lower access to learning opportunities may result in lower female financial literacy, which can prevent some women from navigating complex loan application procedures or obtaining fair interest rates. An international survey of financial literacy revealed that 51% of adult women and 60% of adult men in Georgia are able to reach the minimum target score on financial knowledge, compared to 56% of women and 69% of men in OECD countries (OECD, 2016[28]). Differences in financial literacy might stem from segregation in higher education.
Gender parity represents an immense economic opportunity. Reducing gender-based discrimination in social institutions through appropriate policy measures could yield substantial economic benefits. A gradual reduction of gender-based discriminatory social institutions by 2030 could increase the regional annual GDP growth rate by 0.4 percentage points over the next 11 years (Figure 2.4). In other words, the regional GDP per capita in 2030 is estimated at USD 5 858 without a reduction in gender-based discrimination in social institutions, compared to USD 8 889 if discriminatory social institutions were totally eliminated. This represents a gain of USD 2 961 per capita. Reaching parity in social institutions would add USD 2 750 to the GDP per capita in Eastern Europe, USD 2 936 in Central Asia and USD 3 203 in the Caucasus.
Box 2.1. A life-cycle approach to women’s empowerment in the region
Gender-transformative policies with multisectoral entry points, going beyond standard gender mainstreaming, are needed in order to leave no one behind and fully benefit from women’s economic contribution. This makes the case for including social norm policies and programmes in national growth strategies and adopting an integrated approach. Here are some recommendations:
Non-discriminatory and gender-responsive laws are the first step towards challenging discriminatory social institutions.
Prohibit child marriage under any circumstances.
Criminalise all forms of violence against women, enforce existing legislation and prosecute perpetrators.
Allow women to apply for the same jobs as men and reduce the gender wage gap by legally mandating companies to report on how they pay women and men.
Introduce or strengthen paid parental leave schemes and family-friendly labour-market policies such as flexible work schedules or government-supported child and elderly care services.
Equalise the legal retirement ages of women and men.
However, laws are not enough and must be accompanied by preventive approaches and enforcement measures
Include soft skills more systematically in educational and training systems. Beyond fundamental skills such as literacy and numeracy, these include self-confidence, communication and decision-making skills.
Support women who wish to shift from informal economic activities to the formal economic sector or to start an economic activity (facilitate access to credit, increase financial literacy, promote joint assets titling for married couples in order to facilitate women’s access to financial services).
Apply and include a gender perspective in the design of all public policies, such as employment policies, pension schemes or retirement benefit programmes. For example, guarantee that extended leaves or interrupted employment trajectories do not penalise women’s access to minimum contributory pensions.
Recognise the care economy and compensate for time allocated to unpaid care work and childbearing through pension credits.
Ultimately, policies and programmes must seek to eliminate or shift discriminatory social norms.
Encourage girls to enrol in traditionally male-dominated fields of study such as the STEM subjects (science, technology, engineering and mathematics).
Promote an egalitarian vision of the role men and women can play in a society, notably by challenging stereotypes stigmatising working women and by advocating for better sharing of domestic responsibilities between women and men.
Discriminatory social institutions and young women NEET
Women are over-represented in the Eurasian NEET population. Across the eight Eurasian countries with available data,10 20% of youth aged 15-24 are not in education, employment or training, compared to 22% at the global level (ILO, 2017[29]). The over-representation of women and girls among NEETs is lower in Eurasia, at 58%, than at the global level, at 77% (ILO, 2018[30]). Yet in all Eurasian countries but Moldova, women are more likely than men to be NEET (Figure 2.5). Some 24% of young women in Eurasia are not in education, employment or training, compared to 15% of men, and women represent 1.9 of the 3.4 million NEETs. This gender gap is particularly pronounced in two Central Asian countries: Tajikistan (30% of men and 52% of women) and Kyrgyzstan (12% of men and 30% of women). The region’s female NEET rates are highest in Tajikistan (52%), Armenia (38%) and Kyrgyzstan (30%), and lowest in Kazakhstan (11%) and Belarus (14%) (ILO, 2018[30]).
Gendered patterns among NEETs shed light on young women’s needs. All NEETs are outside the education system and neither in training nor working (including not in informal employment). They can be separated in two categories: economically inactive non-students (outside the labour force) and unemployed non-students (part of the labour force). The majority of women NEETs in the region are inactive non-students (“inactive” is here employed in its economic definition, that is to say neither working nor unemployed), while men are more likely to be unemployed non-students (without work but ready to work), and therefore considered part of the labour force. For example in Armenia, 69% of non-student young women are inactive, while 31% are unemployed. The pattern is opposite for men: 36% are inactive and 64% unemployed (ILO, 2014[31]).
Women NEETs represent an untapped economic potential. Women NEETs could contribute to sustainable and inclusive development through work or by enhancing their human capital. These women would contribute to an increased GDP directly through their employment and/or their high-skill status, but also indirectly through an increase in tax revenues and a decrease in social allowance expenditures. In Moldova, for instance, 25% of young women are NEETs, representing an opportunity cost in tax revenue and foregone earnings of 2.5% of the country’s GDP, or USD 1 314 per female NEET in 2016 (OECD Development Centre, 2018[32]).
Women NEETs also represent an unrecognised economic resource. Youth NEETs are commonly considered “inactive” or “unproductive” when not looking for a job. Yet a large proportion of them, especially women, perform unpaid housework and produce non-market goods and services that are essential for their households’ consumption and wellbeing, thus generating value. While female NEETs performing housework remain unpaid, they allow other members of the family to work and, at the same time, can be considered as substituting for domestic workers. Since the production of goods for own final consumption is excluded from GDP calculations, NEETs’ contribution to the economy is invisible. By using time-use, labour-force and income survey data, it is possible to estimate NEETs’ contribution to the national economy through their unpaid care work. In Mongolia in 2015, 20% of women and girls and 14% of men and boys aged 15-24 were NEET (ILO, n.d.[17]). On average that year, they spent respectively 3 hours and 48 minutes and 1 hour and 24 minutes per day on unpaid care and domestic work (NSO Mongolia, 2015[33]). If they had been remunerated for these activities at the average wage of Mongolian paid domestic workers, they would have contributed 1.3% of GDP (NSO Mongolia, n.d.[34]; World Bank, n.d.[9]). This contribution is mostly based on female labour (1%).
Action is needed beyond closing gender gaps in education. Closing these gaps has not been enough to ensure a smooth school-to-work transition for girls due to discriminatory social institutions. Although almost all countries have attained equality in educational enrolment at the primary and secondary levels, this has not translated into gender-balanced labour-market outcomes (Figure 2.7). The role of discriminatory social institutions notably includes the unequal distribution of domestic responsibilities, which is detrimental to young women’s time available for market activities, and societal and institutional barriers to accessing educational and employment opportunities, such as early marriage and pregnancy.
Young women’s caring and domestic responsibilities appear to drive female NEET rates up. The expectation that women will be the ones taking care of their family members’ well-being constrains their economic empowerment (Ferrant, Pesando and Nowacka, 2014[19]). In Moldova for example, 80% of men aged 15-24 participate in household chores, compared to 93% of women. Young men who participate dedicate on average 2 hours and 24 minutes each day to these activities, compared to 3 hours and 36 minutes for young women (NBS, 2012[35]). Across five countries,11 20% of young women are disengaged from the labour market because they have domestic responsibilities, compared to only 2% of men (Figure 2.6). This situation concerns up to 28% of women 15-24 not in the labour market in Kyrgyzstan and 31% in Georgia. In all countries with available data, women represent the large majority, if not all, of the young people who are neither working nor unemployed because they are engaged in household chores: from 86% in Ukraine to 100% in Georgia (UNECE, n.d.[16]).
Early marriage and pregnancy are linked to female school and labour-market drop-out rates, especially in rural or poor areas, while having children usually increases male economic activity rates (ILO and UNICEF, 2018[36]). In the region, 8% of girls got married before their 18th birthday and there were 27 births per 1 000 adolescent girls in 2016 (World Bank, n.d.[9]) Family status combined with discriminatory family norms can impact a young person’s labour-market choices. Starting a family and having children cost time and money. Young mothers are often pressured to stay at home to care for the household, while young fathers are expected to take up any available job to earn a living. In Azerbaijan, for example, 52% of mothers aged 15-29 are not in the labour market, compared to 17% of young fathers; 45% of young mothers are employed, compared to 74% of young fathers (Matsumoto and Elder, 2010[37]).
A pronounced gender segregation in higher education results from lower expectations for girls’ performance, a lack of female role models and the lack of encouragement from families and/or teachers. Girls’ choices of tertiary education programmes do not reflect the increasing labour opportunities in science, technology, engineering and mathematics. For example, only 32% of Eurasian graduates in STEM fields of study are women (UNESCO, n.d.[38]). This proportion is lowest in Belarus (27%) and remains below 50% even in the best performing country (Georgia, with 44% of female STEM graduates). In contrast, women represent 63% of graduates in social sciences, journalism and information (from 48% in Kyrgyzstan to 79% in Belarus). Gender segregation in education affects female employment rates, as women get fewer job opportunities and those available are often in lower paid positions (ILO and UNICEF, 2018[36]).
In all countries except Armenia and Georgia, discriminatory laws prohibit women from working the same night hours as men12 or from entering certain types of jobs13, which decreases their employment prospects.
In many cases, discriminatory norms limit women to their reproductive and domestic roles and discourage them from seeking paid employment: 16% of the region’s population do not think it is acceptable for women in their family to work outside the home, and 47% think that when jobs are scarce, men should have more right to a job than women (Inglehart et al., 2014[13]). In addition, a woman’s salary at the start of her career might not be sufficient to compensate for the high cost of childcare services, and this may discourage her from seeking paid employment. This is particularly true for single parents, of whom the large majority are women: in Armenia, Azerbaijan, Georgia, Ukraine and Uzbekistan, between 85% and 97% of one-parent families are headed by a woman (UNECE, n.d.[16]) These attitudes are reflected in the characteristics of NEETs in the region. Men are more likely to be unemployed, while women are more likely to be inactive (in the economic sense, that is to say neither working nor unemployed). For example in Moldova, 86% of female NEETs are inactive non-students, compared to 63% of male NEETs (ILO, 2016[39]).
The difficult school-to-work transition for women has a domino effect. This effect can continue throughout a woman’s life cycle, reinforcing the negative impact of discriminatory social institutions. Women NEETs are particularly vulnerable to social and labour-market exclusion, as they are neither gaining experience through employment nor improving their future employability by investing in their own skills. They then become more vulnerable to discriminatory social institutions that exclude women from the economic and public spheres. This domino effect culminates when elderly women receive lesser pensions (see next section). The exclusion of working-age women from the economic sphere is reflected in labour outcomes of the overall working-age population.
Discriminatory social institutions and the gender pension gap
Eurasian women are disadvantaged in terms of social protection at retirement. In eight countries14 where data is available, 91% of women of pensionable age receive a pension, compared to 96% of men. While the gender pension gap has been closed in Kyrgyzstan, it stands at about 24 percentage points in Tajikistan. In the Caucasus and Central Asia, 82% and 94% of women above retirement age receive a pension, compared to 87% and 98% of men respectively (ILO, 2016[40]).
Box 2.2. International legal frameworks on women’s rights to social protection
A number of international documents have been ratified over the last 70 years to ensure the right of women to social protection.
The Universal Declaration of Human Rights (1948) enshrines the right to social protection taking into account gender- and age-related vulnerabilities (Art. 22-25).
The International Covenant on Economic, Social and Cultural Rights (1976) recognises the right of everyone to social security, including social insurance (Art. 9).
The CEDAW (1979) reaffirms that states should “take all appropriate measures to eliminate discrimination against women in the field of employment in order to ensure, on a basis of equality of men and women, the same rights”, and in particular “the right to social security, particularly in cases of retirement, unemployment, sickness, invalidity and old age and other incapacity to work, as well as the right to paid leave”.
The ILO Social Protection Floors Recommendation No. 202 (2012) recognises the importance of social security to prevent and reduce poverty, inequality, social exclusion and social insecurity, and to promote equal opportunity and gender and racial equality. Member States are encouraged to regularly collect, compile, analyse and publish an appropriate range of social security data, statistics and indicators, disaggregated, in particular, by gender (Para. 21).
The gender pension gap increases women’s vulnerability to poverty. Addressing this gap is all the more crucial because women comprise the majority of older persons: women aged 65 and older constitute 10% of the total female population in Eurasia, while elderly men constitute 7% of the total male population. In addition, the difference between women’s and men’s life expectancy is greater in Eurasia than in the rest of the world: Eurasian women live on average eight years longer than men, compared to the global average of four years (World Bank, n.d.[9]). Women’s greater longevity raises women-specific micro and macro challenges (Figure 2.8). On the one hand, women need to achieve higher levels of savings throughout their lives to have an adequate standard of living when they reach retirement age. On the other, elderly women may require higher social expenditures, as they are more likely to benefit from their own pensions and those of their deceased husbands for longer periods of time. Indeed, most of them will outlive their husbands and be more likely to live alone without a carer (OECD, 2018[41]). In Armenia, Azerbaijan, Georgia and Uzbekistan, women represent from 74% (Uzbekistan) to 84% (Armenia) of one-person households aged 65 and older (UNECE, 2015[42]).
Gender gaps in the labour market fuel the gender pension gap. Pension schemes in Eurasia have failed to address women’s specific needs and career paths, reinforcing the marginalisation effect of discriminatory social institutions. The region’s pension schemes are still based on the male-breadwinner model, which is not in line with the typical life course of women and tends to reproduce existing inequalities. These pension schemes penalise older women for the accumulation and overlap of inequalities experienced throughout their working lives. The design of social protection policies has not successfully compensated women for disadvantages in the labour market due to discriminatory laws, social norms and practices. Therefore, gender gaps in labour-market outcomes translate into gender gaps in pensions:
Discriminatory laws and social norms impede women from participating in the labour market on an equal footing with men, consequently increasing the gender pension gap. Legal restrictions in labour laws continue to prohibit women from working the same night hours and from pursuing the same professions as men. In addition, stigmatisation and negative attitudes towards women’s paid work outside the home affect women’s employment opportunities. As noted above, 16% of the population think it is not acceptable for a woman to work outside the home for pay, with this figure increasing to 28% in Uzbekistan. As a result, women in Eurasia are less likely than men to participate in the labour force: 71% of men were in the labour force versus 53% of women in 2018, a gap of 18 percentage points (World Bank, n.d.[9]). As many pension schemes in seven countries15 in Eurasia are based on a combination of contributory and non-contributory participation, women’s under-representation in the labour market leads to lower social benefits after retirement (ILO, 2017[29]).
Gender stereotypes and negative attitudes towards women’s leadership often result in occupational segregation, glass ceilings and gender pay gaps, which in turn affect the absolute level of women’s pensions. Across eight countries,16 56% of the population consider that men make better business executives than women do (Inglehart et al., 2014[13]). Such gender biases and stereotypes affect women’s employment outcomes. Women account for only 9% of members of the boards of central banks and 35% of managers. Only 13% of female workers are employed in the industry sector compared to 30% of men, and they earn 30% less than men on average (OECD, 2019[2]; UNECE, n.d.[16])
Discriminatory workplace laws and women’s burden of unpaid care and domestic work incentivise them to engage in informal jobs, consequently decreasing their likelihood of benefitting from a pension after retirement age. Women in the region spend an average of five hours a day on unpaid care and domestic work, notably childcare, as only 46% of children aged three to five attend an early childhood education programme (UNICEF, 2017[43]). Informal jobs often offer women better work-life balance conditions, such as flexible work schedules and part-time working arrangements. This is an important incentive, as it allows women to reconcile family and workplace responsibilities. In five Eurasian countries where data is available, 48% of employed women were working in the informal sector, ranging from 26% in Moldova to 73% in Tajikistan (ILO, 2018[30]). Women’s participation in informal work makes them less likely to benefit from social protections offered through formal employment, such as pensions.
Social expectations about women’s caring responsibilities lead to fewer years in the workforce compared to men, and consequently to fewer opportunities to save money and lower contributions to retirement plans. In Armenia, for instance, 87% of men declare that they would not take paternity leave after the birth of a child, compared to 23% of women. Career interruptions and their consequences on women’s savings and pension contribution are not compensated by gender-responsive pension schemes in Eurasia. Moreover, the lack of accessible and affordable childcare facilities exacerbates the burden of unpaid care and domestic work and diminishes women’s ability to return to full-time employment. However, two-thirds of the countries17 in the region have taken measures to improve women’s pensions, such as offering pension credits to compensate for the time spent on childcare (World Bank, 2019[44]).
Differences in retirement ages between women and men still persist due to gender- and age-based discrimination. In many countries, the established retirement age for women is up to five years earlier than that of men (UN Women, 2015[45]). A mandatory earlier retirement age contributes to reducing women’s pension income relative to that of men, as women live longer than men and have shorter career ladders due to family-related employment interruptions. In all Eurasian countries except Armenia, the ages at which men and women can retire with full pension benefits are not equal (World Bank, 2019[44]). A lower retirement age for women translates into lower monthly pension entitlements, as women have fewer years than men for accumulating pension contributions and more years of retirement (UN Women, 2015[46]). In Turkmenistan, for instance, women have access to a state pension at age 57 and men at age 60. Pensions are granted to women after 20 years of service, compared to 25 years for men, and the amount paid corresponds to the time worked.
References
[22] CDC (2003), Costs of Intimate Partner Violence Against Women in the United States, Centers for Disease Control an Prevention, Atlanta, https://www.cdc.gov/violenceprevention/pdf/IPVBook-a.pdf (accessed on 22 March 2019).
[15] Committee of Statistics of Kazakhstan (2014), Slide 1 EWJM1 time use surveys можно time budget surveys. В интернете нашла time use study и time budget survey, https://unstats.un.org/unsd/gender/Mexico_Nov2014/Session%204%20Kazakhstan%20ppt.pdf (accessed on 29 April 2019).
[6] CRRC (2018), Respondent’s sex | Women’s economic inactivity and engagement in the informal sector in Armenia | Caucasusbarometer.org | Online Data Analysis, https://caucasusbarometer.org/en/gs2018am/RESPSEX/ (accessed on 29 April 2019).
[5] CRRC (2018), Respondent’s sex | Women’s economic inactivity and engagement in the informal sector in Georgia | Caucasusbarometer.org | Online Data Analysis, https://caucasusbarometer.org/en/gs2018ge/RESPSEX/ (accessed on 29 April 2019).
[26] Demirgüç-Kunt, A. et al. (2018), The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution, World Bank Group, Washington, http://documents.worldbank.org/curated/en/332881525873182837/pdf/126033-PUB-PUBLIC-pubdate-4-19-2018.pdf (accessed on 22 March 2019).
[3] DHS (2012), Kyrgyz Republic Demographic and Health Survey, National Statistical Committee of the Kyrgyz Republic, Ministry of Health and ICF International, https://dhsprogram.com/pubs/pdf/FR283/FR283.pdf (accessed on 19 March 2019).
[21] Duvvury, N. et al. (2013), Intimate partner violence: Economic Costs and Implications for Growth Development, World Bank Group, Washington, http://www.worldbank.org/gender/agency (accessed on 22 March 2019).
[1] Ferrant, G. and A. Kolev (2016), M A Does gender discrimination in social institutions matter for long-term growth? Cross-country evidence OECD DEVELOPMENT CENTRE CENTRE DE DÉVELOPPEMENT DOCUMENTS DE TRAVAIL, http://www.oecd.org/dev/wp. (accessed on 29 April 2019).
[19] Ferrant, G., M. Pesando and K. Nowacka (2014), Unpaid Care Work: The missing link in the analysis of gender gaps in labour outcomes, http://www.oecd.org/dev/development-gender/unpaid_care_work.pdf (accessed on 29 April 2019).
[14] Ferrant, G. and A. Thim (2019), Measuring Women’s Economic Empowerment: Time Use Data and Gender Inequality, OECD Development Policy Papers, No.16 , Organisation for Economic Cooperation and Development, http://www.oecd.org/dev/development-gender/MEASURING-WOMENS-ECONOMIC-EMPOWERMENT-Gender-Policy-Paper-No-16.pdf (accessed on 22 March 2019).
[30] ILO (2018), ILOSTAT Database, https://data.worldbank.org/indicator/SL.TLF.CACT.FE.ZS (accessed on 1 March 2019).
[29] ILO (2017), Global Employment Trends for Youth 2017: Paths to a better working future, International Labour Organization, Geneva, https://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/---publ/documents/publication/wcms_598669.pdf (accessed on 19 March 2019).
[39] ILO (2016), Labour market transitions of young women and men in the Republic of Moldova: Results of the 2013 and 2015 school-to-work transition surveys, Work4Youth Publication Series, International Labour Organization, https://www.ilo.org/wcmsp5/groups/public/---ed_emp/documents/publication/wcms_498766.pdf (accessed on 22 March 2019).
[40] ILO (2016), Women at Work Trends 2016, International Labour Organization, Geneva, https://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/---publ/documents/publication/wcms_457317.pdf (accessed on 24 March 2019).
[31] ILO (2014), Labour market transitions of young women and men in Armenia, Work4Youth Publication Series, International Labour Organisation, https://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/documents/publication/wcms_314022.pdf (accessed on 22 March 2019).
[17] ILO (n.d.), ILOSTAT, International Labour Organisation, Geneva, https://www.ilo.org/ilostat (accessed on 18 March 2019).
[36] ILO and UNICEF (2018), GirlForce: Skills, Education and Training for Girls Now, International Labour Organisation and the United Nations Children’s Fund, Geneva and New York, https://www.ilo.org/wcmsp5/groups/public/---ed_emp/documents/publication/wcms_646665.pdf (accessed on 22 March 2019).
[13] Inglehart, R. et al. (2014), Wolrd Values Survey: Round Six- country-pooled Datafile, JD Systems Institute, Madrid, http://www.worldvaluessurvey.org/WVSDocumentationWV6.jsp.
[7] Mankiw, N., D. Romer and D. Weil (1992), “A CONTRIBUTION TO THE EMPIRICS OF ECONOMIC GROWTH*”, https://eml.berkeley.edu/~dromer/papers/MRW_QJE1992.pdf (accessed on 29 April 2019).
[37] Matsumoto, M. and S. Elder (2010), Characterizing the school-to-work transitions of young men and women: Evidence from the ILO School-to-work transition surveys Country Employment Policy Unit Employment Policy Department, http://www.ilo.org/publns (accessed on 3 April 2019).
[35] NBS (2012), Time use indicators for population aged 15 years and over, National Bureau of Statistics of the Republic of Moldova, Chișinău, http://statbank.statistica.md/ (accessed on 22 March 2019).
[33] NSO Mongolia (2015), Time Use Study 2015, National Statistics Office of Mongolia, Ulaanbaatar, http://web.nso.mn/nada/index.php/catalog/108/related_materials (accessed on 22 March 2019).
[34] NSO Mongolia (n.d.), Monthly average wages and salaries, National Statistics Office of Mongolia, Mongolian Statistical Information Service, http://www.1212.mn/ (accessed on 22 March 2019).
[2] OECD (2019), SIGI 2019 Global Report: Transforming Challenges into Opportunities, Social Institutions and Gender Index, OECD Publishing, Paris, https://dx.doi.org/10.1787/bc56d212-en.
[41] OECD (2018), OECD Pensions Outlook 2018, OECD Publishing, Paris, https://dx.doi.org/10.1787/pens_outlook-2018-en.
[28] OECD (2016), OECD/ INFE International Survey of adult financial literacy competencies, OECD, Paris, http://www.oecd.org/finance/OECD-INFE-International-Survey-of-Adult-Financial-Literacy-Competencies.pdf (accessed on 22 March 2019).
[12] OECD (2014), Social Institutions and Gender Index 2014 Synthesis Report, OECD Publishing, Paris, https://www.oecd.org/dev/development-gender/BrochureSIGI2015-web.pdf (accessed on 22 March 2019).
[32] OECD Development Centre (2018), Youth Well-being Policy Review of Moldova, EU-OECD Youth Inclusion Project, Paris, http://www.oecd.org/dev/inclusivesocietiesanddevelopment/Youth_Well-being_Policy_Review_Moldova.pdf (accessed on 19 March 2019).
[4] Partnership for Development Centre (2018), CUM PREVENIM ȘI REDUCEM HĂRȚUIREA SEXUALĂ LA LOCUL DE MUNCĂ ȘI STUDII Recomandări de politici, http://www.progen.md/files/9870_cpd_cdf_analiza_hartuirea_sexuala_final.pdf (accessed on 29 April 2019).
[27] Sattar, S. (2012), Opportunities for Men and Women: Emerging Europe and Central Asia, World Bank Group, Washington, http://documents.worldbank.org/curated/en/479131468250293544/pdf/659310WP00PUBL065737B0Gender0Report.pdf (accessed on 22 March 2019).
[8] Solow, R. (1956), “A Contribution to the Theory of Economic Growth”, Source: The Quarterly Journal of Economics, Vol. 70/1, pp. 65-94, http://piketty.pse.ens.fr/files/Solow1956.pdf (accessed on 29 April 2019).
[45] UN Women (2015), Protecting women’s income security in old age: Toward gender-responsive pension systems, Policy Brief No.3, United Nations Entity for Gender Equality and the Empowerment of Women, http://www.unwomen.org/-/media/headquarters/attachments/sections/library/publications/2015/unwomen-policybrief03-protectingwomensincomesecurityinoldage-en.pdf?la=en&vs=553 (accessed on 24 March 2019).
[46] UN Women (2015), The gender dimension of pension systems: Policies and constraints for the protection of older women, United Nations Entity for Gender Equality and the Empowerment of Women, New York, https://socialprotection-humanrights.org/wp-content/uploads/2015/08/ARZA-Fin.pdf (accessed on 3 April 2019).
[42] UNECE (2015), One person household by Age, Sex, Measurement, Country and Year. PxWeb, United Nations Economic Commission for Europe, https://w3.unece.org/PXWeb2015/pxweb/en/STAT/STAT__30-GE__02-Families_households/09_en_GEFHOnePerHous_r.px/ (accessed on 24 April 2019).
[16] UNECE (n.d.), UNECE Statistical Database, United Nations Economic Commission for Europe, https://w3.unece.org/PXWeb2015/pxweb/en/STAT/STAT__30-GE__03-WorkAndeconomy (accessed on 15 March 2019).
[38] UNESCO (n.d.), UNESCO Institute for Statistics Education Database, United Nations Educational, Scientific and Cultural Organization, http://uis.unesco.org/ (accessed on 22 March 2019).
[23] UNFPA (2017), Economic costs of violence against women in Ukraine, United Nations Population Fund, New York, https://ukraine.unfpa.org/sites/default/files/pub-pdf/Economic%20Costs%20of%20Violence_2017_3.pdf (accessed on 22 March 2019).
[11] UNFPA (2015), Girlhood, not motherhood: Preventing Adolescent Pregnancy, United Nations Population Fund, New York, https://www.unfpa.org/sites/default/files/pub-pdf/Girlhood_not_motherhood_final_web.pdf (accessed on 22 March 2019).
[20] UNFPA (2012), Sex Imbalances at Birth, United Nations Population Fund, Bangkok, https://www.unfpa.org/sites/default/files/pub-pdf/Sex%20Imbalances%20at%20Birth.%20PDF%20UNFPA%20APRO%20publication%202012.pdf (accessed on 15 March 2019).
[43] UNICEF (2017), Early childhood development and early childhood education data, United Nations Children’s Fund, New York, https://data.unicef.org/resources/dataset/early-childhood-education/ (accessed on 25 March 2019).
[10] UNICEF (2014), Republic of Moldova Multiple Indicator Cluster Survey 2012 Final Report Europe World Health Organization Ministry of Health of the Republic of Moldova C N S P REGIONAL OFFICE FOR Republic of Moldova Multiple Indicator Cluster Survey, http://www.unicef.org/moldova (accessed on 29 April 2019).
[24] Women’s Law Center, UN Women and WHO (2016), Report on costing of domestic violence and violence against women in Moldova, Women’s Law Center, United Nations Entity for Gender Equality and the Empowerment of Women, and World Health Organization, http://www2.unwomen.org/-/media/field%20office%20moldova/attachments/publications/2016/report%20costing%20of%20violence%20-%20en.pdf?la=en&vs=2637 (accessed on 22 March 2019).
[44] World Bank (2019), Women, Business and the Law: Getting a Pension, World Bank Group, Washington, http://wbl.worldbank.org/en/data/exploretopics/getting-a-pension (accessed on 24 March 2019).
[18] World Bank (2018), “Women, Business and the Law 2018”, http://dx.doi.org/10.1596/978-1-4648-1252-1.
[25] World Bank (2017), Enterprise Surveys Indicators Data, World Bank Group, Washington, http://www.enterprisesurveys.org/data (accessed on 22 March 2019).
[9] World Bank (n.d.), World Development Indicators (WDI), World Bank Group, Washington, https://datacatalog.worldbank.org/dataset/world-development-indicators (accessed on 15 March 2019).
Notes
← 1. The estimated cost of gender-based discrimination in social institutions in the Eurasian region was computed following Ferrant and Kolev (2016), using SIGI 2019 updated data.
← 2. With the exception of Turkmenistan, where there were 96 girls per 100 boys in secondary education in 2014.
← 3. With the exception of Tajikistan, Uzbekistan and Turkmenistan, where there were respectively 75, 61 and 64 girls per 100 boys in tertiary education in 2017. Data for Turkmenistan is for 2014.
← 4. Azerbaijan, Armenia, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Ukraine and Uzbekistan.
← 5. Azerbaijan, Moldova, Tajikistan, Turkmenistan and Ukraine.
← 6. Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Mongolia, Tajikistan, Turkmenistan, Ukraine and Uzbekistan.
← 7. In Azerbaijan, 22% of the population do not think it is perfectly acceptable for women in their family to work outside the home; 79% think that when jobs are scarce, men should have more right to a job than women; and 38% believe that if a wife earns more money than her husband, it is almost certain to cause problems. In Uzbekistan, 28% of the population do not think it is perfectly acceptable for women in their family to work outside the home; 59% think that when jobs are scarce, men should have more right to a job than women; and 60% believe that if a wife earns more money than her husband, it is almost certain to cause problems (Inglehart et. al, 2014).
← 8. Armenia, Georgia, Kyrgyzstan, Mongolia and Turkmenistan.
← 9. Total government spending on domestic violence in Moldova amounted to MDL 36 092 000 (Moldovan leu) in 2015, or USD 1 830 232 at the 31 December 2015 exchange rate.
← 10. Armenia, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Mongolia, Tajikistan and Ukraine.
← 11. Armenia, Georgia, Kyrgyzstan, Moldova and Ukraine.
← 12. Azerbaijan, Moldova, Tajikistan, Turkmenistan and Ukraine.
← 13. Azerbaijan, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Mongolia, Tajikistan, Turkmenistan, Ukraine and Uzbekistan.
← 14. Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Mongolia, Tajikistan, Ukraine and Uzbekistan.
← 15. Armenia, Azerbaijan, Belarus, Kyrgyzstan, Moldova, Tajikistan and Turkmenistan.
← 16. Azerbaijan, Armenia, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Ukraine and Uzbekistan.
← 17. Armenia, Belarus, Kazakhstan, Kyrgyzstan, Moldova, Tajikistan, Ukraine and Uzbekistan.