BELARUS COUNTRY GENDER PROFILE 2016 Update November 2016 World Bank TABLE OF CONTENT SUMMARY ....................................................................................................................................... 1 CHAPTER 1: AGENCY........................................................................................................................ 4 1. LEGAL AND INSTITUTIONAL FRAMEWORK........................................................................................... 4 2. VOICE AND REPRESENTATION .......................................................................................................... 7 3. SOCIETAL VIEWS ON GENDER ISSUES ................................................................................................. 8 4. VIOLENCE AGAINST WOMEN ......................................................................................................... 10 CHAPTER 2: ENDOWMENTS .......................................................................................................... 12 1. HEALTH ..................................................................................................................................... 12 A. WOMEN’S REPRODUCTIVE HEALTH ................................................................................................. 16 2. EDUCATION ............................................................................................................................... 17 3. FINANCIAL AND TIME ASSETS ......................................................................................................... 20 A. TIME ......................................................................................................................................... 21 CHAPTER 3: ECONOMIC OPPORTUNITIES ..................................................................................... 22 1. LABOR MARKET INCLUSION ........................................................................................................... 22 2. EMPLOYMENT ............................................................................................................................ 24 3. ENTREPRENEURSHIP .................................................................................................................... 28 4. EARNINGS .................................................................................................................................. 31 5. GENDER AND POVERTY ................................................................................................................ 35 CONCLUSIONS AND POLICY RECOMMENDATIONS ....................................................................... 37 REFERENCES .................................................................................................................................. 39 APPENDIX ...................................................................................................................................... 41 FIGURES Figure 1: female representation in the House of Representatives and the Council of the Republic ............. 8 Figure 2: Mean value of indicators showing agreement in gender-related statements by sex, 2008 ........... 9 Figure 3: Agreement by age and sex with statement "When jobs are scarce, men should have more right to a job than women" ......................................................................................................................... 10 Figure 4: Agreement by age and sex with statement "If a woman earns more money than her husband, it’s almost certain to cause problems” ..................................................................................................... 10 Figure 5: Share of individuals 15-49 that believe a husband is justified to beat his wife under any of the specified conditions ............................................................................................................................ 11 Figure 6: Share of population by age groups and sex (2015, thousands) ..................................................... 12 Figure 7: Life expectancy at birth by sex (2014) ........................................................................................... 13 Figure 8: Life expectancy at birth by sex and regions (2013) ....................................................................... 13 Figure 9: Mortality rate per 1000 adults by gender, 2004, 2011 and 2014 ................................................. 15 Figure 10: Age-standardized death rates per 100,000 by cause and sex in 2012 ........................................ 15 Figure 11: Share of population by age group and sex reported as obese (2011-2016) ............................... 15 Figure 12: Abortions incidence per region (abortions per 100 live births) .................................................. 16 Figure 13: Tertiary education enrollment levels (gross) per sex .................................................................. 17 Figure 14: Enrollment in higher education among population age 17-24 by consumption per capita quartiles (2014) (%) ............................................................................................................................. 18 Figure 15: Share of female student by field of study among the 10 fields with higher enrollment (academic year 2014/2015).................................................................................................................................. 19 Figure 16: Borrowing behavior by sex (2014) ............................................................................................... 20 Figure 17: Saving behavior by sex (2014) ..................................................................................................... 20 Figure 18: Average time distribution (hours and minutes) by sex –total population 10 years and above .. 21 Figure 19: Total available leave for mothers, includes maternity and parental paid and unpaid leave not required to be taken by the father ..................................................................................................... 23 Figure 20: Number of preschool institutions and share of children (0-5) enrolled in preschool institutions, per academic year (2000-2016) .......................................................................................................... 24 Figure 21: Female and male labor force participation rate by country (%) 2014 ......................................... 25 Figure 22: Labor force participation by sex and year (%) ............................................................................. 25 Figure 23: Employment ratios across age groups by sex, 2010 (%) .............................................................. 26 Figure 24: Employment ratios across education levels by sex, 2010 (%) ..................................................... 26 Figure 25: Unemployment rates by sex and educational attainment (2014) ............................................... 27 Figure 26: Share of female ownership and management in Belarus and ECA (2013) .................................. 30 Figure 27: Share of female ownership and management by firm size (employees) in Belarus (2013) ........ 30 Figure 28: Female Ownership and Management by Economic Sectors in 2013, % ...................................... 30 Figure 29: Log monthly wages by sex (2014) ................................................................................................ 31 Figure 30: Predicted wages by education categories (Heckman model, 2014)............................................ 33 Figure 31: Household headship by household type ..................................................................................... 35 Figure 32: Monthly income per capita by gender of head of household and the type of household .......... 36 Figure 33: Monthly income per capita by gender of head of household and age group among single person and single parent households ............................................................................................................. 36 TABLES Table 1: State-level stakeholders of gender policy and legislation ................................................................ 6 Table 2: Women and men engaged in organizations by economic activity (percent of total) ..................... 27 Table 3: Ratio of wages and salaries of women to wages and salaries of men by sector, % ....................... 32 Table 4: Oaxaca decomposition of monthly wages, 2010 and 2014 ............................................................ 34 ACRONYMS BEEPS Business Environment and Enterprise Surveys CEDAW Convention on the Elimination of All Forms of Discrimination against Women CIS Commonwealth of Independent States EBRD European Bank for Reconstruction and Development ECA Europe and Central Asia EVS European Value Study FINDEX Financial Inclusion Database HLSS Household Living Standards Survey ILO International Labour Organization MICS Multiple Indicator Cluster Survey NSC National Statistics Committee OECD Organisation for Economic Cooperation and Development STEM Science, Technology, Engineering, and Math SME Small and Medium Enterprise UNICEF United Nations International Children´s Emergency Fund WDI World Development Indicators WHO World Health Organization WVS World Values Survey Summary1 Gender equality is a core development objective in its own right, and it is also a smart development policy. Gender equality is also a key pathway to ensure lasting poverty reduction and shared prosperity.2 This update to the ‘2013 Belarus Country Gender Profile’ seeks to identify where progress has been achieved in terms of increasing opportunities for women and men in Belarus since that last assessment and where further policy action is required. As such, it understands gender equality to mean the closing of the gaps between women and men in areas that are critical for them to access and take advantage of existing opportunities namely endowments such as health and education; economic opportunities, via access to labor, land and financial markets;, and agency, including norms, representation, and freedom of violence (World Bank 2016). 3. Overall, Belarus’ ranges better than many countries in terms of gender equality. The country’s gender gaps are much smaller than those observed in other countries in the region and the world. The country ranks 30 among the 144 countries covered by the 2016 World Economic Forum Global Gender Gap Index, largely due to its good results on education outcomes and their reflection in the labor market—Belarus ranks number 1 in terms of female enrollment in all levels of education and also when it comes to having female professional and technical workers, and for women to enjoy a healthy life expectancy. However, these results are muted by the pervasive gender wage gap observed in Belarus, leaving the country at place 54 in the global ranking and the low representation of women in political positions. While the country is among the top third of countries when it comes to parliamentary representation –ranks 47 among the 144 countries with a female parliamentary representation of 27 percent, it ranks 108 when it comes to the share of women in ministerial positions, with an overall ranking of 80 for political empowerment. A more detailed study of the gender gaps in Belarus shows that if there is a critical area for policy action to close such gaps, women’s economic participation should be given priority. From the legal point of view, while Belarus legislation treats men and women equally, existing gender gaps, for example in the 182 occupations that are restricted to women might be affecting women’s access to opportunities. This is reflected in the gaps that can be observed in terms of young women’s choices of educational sectors at the tertiary level and these choices have a reflection in women’s opportunities in the labor market, and their concentration in specific 1 This report was produced by Ana Maria Munoz Boudet (Senior Social Scientist, Poverty and Equity Global Practice) and Cristina Chiarella and Carmen de Paz (Consultants, Poverty and Equity Global Practice), with inputs from Irina Solomatina (Consultant). The team benefited from the comments and reviews of Alexandru Cojocaru (Economist, Poverty and Equity Global Practice) and Irina Oleinik (Operations Officer, Belarus World Bank Office). 2 World Bank Gender Strategy 2016-20–20. 3 As specified by the World Development Report 2012 on Gender Equality and Development, and the World Bank Gender Strategy 2016-2020 1 economic sectors in the labor market. With women occupying a different economic space than men, differences in earnings and returns to education arise. Women are also still underrepresented in leading positions in firms –as owners and managers, a situation that is even more prominent when it comes to decision-making positions in public office. Belarus made great progress between 2013 and 2016 in the area of violence against women, when in 2014 it adopted the Law on the Fundamental Activities to Prevent Offenses, which criminalizes physical, sexual, and psychological violence against women and establishes specialized procedures for cases of domestic violence. However, further work is still required not only to implement the legislation but also to expand it to cover offenses outside of marriage and those that can happen in the workplace and to monitor such implementation with adequate data about violence incidence and prevalence. Belarus, as many other countries in the Europe and Central Asia (ECA) region, also faces specific disadvantages affecting men in the country. Young women outnumber young men in tertiary education enrollment, and there are more women than men with tertiary education in the labor market. Further along the lifecycle, gender differences in life expectancy arise. Women’s life expectancy is greater than men’s, and women largely outnumber men in the over-60 age group. Male adult mortality is almost three times higher than that of women and can be explained in part by the higher prevalence of non-communicable diseases and injuries among Belarussian men. The good news is that Belarus is well en-route to close gender inequalities, and the required policy efforts to ensure access to equal opportunities for women and men are smaller than in other countries. Some key policy actions suggested by the empirical evidence in the area of women’s economic opportunities include investing in reducing gender streaming in tertiary education—this can be achieved by systems such as quotas, direct outreach to girls in secondary education, role models, and mass media campaigns to tackle aspirations and provide information on benefits such as returns to science, technology, engineering, and math (STEM)-related occupations. Similar public outreach campaigns can be used to promote tertiary enrollment for young men. Efforts to make sure that legal restrictions to women’s access to occupations need to continue to ensure that educational efforts do not meet with restrictions in the labor market. An important area for expanded knowledge is to better assess the demands for skills and abilities that employers have and how that demand can be met with qualified female candidates. While this report takes advantage of existing data to assess the situation of women and men in the country, including international sources such as the European Value Study (EVS), the Global Financial Inclusion Database (FINDEX), and the European Bank for Reconstruction (EBRD)-World Bank Business Environment and Enterprise Performance Survey (BEEPS), the national sources of data were more limited. The main source of national data for this analysis is the Household Living Standards Survey (HLSS), and it was complemented with other information collected from reports by the National Statistical Committee (NSC) of the Republic of Belarus, which is valuable but insufficient. Overall, there is a lack of regular, detailed gender-disaggregated statistics in Belarus. 2 While some sources can be found publicly accessible, adequately detailed gender statistics need to be made available in a more systematic manner to better monitor gender gaps. 3 CHAPTER 1: AGENCY The ability to take advantage of existing opportunities relies on the capacity to make choices with freedom from constraints and to act on those choices so each individual—woman or man— is able to realize his/her full potential. Agency is a precondition for equitable outcomes for women and men in all domains, including economic participation and empowerment. Women’s agency is often constrained relative to that of men due to social norms and beliefs and also laws and other institutions that help perpetuate gender-based discrimination in society. The biases derived from them contribute to perpetuating gaps in access to opportunities between women and men throughout their lives (World Bank 2012). This chapter explores the gender gaps in agency in Belarus based on the most recent evidence and around the four main aspects of (1) the legal and institutional framework in the country, (2) women’s voice and representation in society, (3) the overall societal gender-related views, and (4) the resulting effects on reported, subjective well- being of women. 1. Legal and institutional framework Gender equality and gender policies are given formal priority in the Republic of Belarus (Economic Commission for Europe 2016). Indeed, Belarus ranks 12th out of 160 countries in the latest Organization for Economic Cooperation and Development (OECD) Social Institutions and Gender Index, which captures gender discrimination in social institutions. 4 This represents an improvement with regard to the 2012 measurement that gave Belarus the 15th position out of 86 countries. Belarus is among the countries included in the analysis that show the lowest levels of gender legal and institutional discrimination.5 This is also reflected in the World Bank’s Women, Business, and the Law assessment. Of its 142 indicators—organized around six areas considered key for gender equality (accessing institutions, using property, going to court, providing incentives, building credit, getting a job, and protecting women)—Belarus shows legal frameworks that are respectful of gender equality and promote women’s access to opportunities, but also that there is room for improvement in areas such as getting a job, protecting women, and providing incentives. Belarus has signed and ratified all relevant international legal frameworks, like its Optional Protocol, and many legal bodies reflect this commitment with no discrimination and equality. For example, the Belarus Constitution contains a clause of nondiscrimination and equality in Article 22 and protects the equality of spouses within marriage, further reflected in the amendments to the Code on Marriage and the Family made in 2006 to include the principle of equality of spouses 4 Formal and informal laws, social norms, and practices that restrict or exclude women and consequently, curtail their access to rights, justice, resources, and empowerment opportunities. 5 http://www.genderindex.org/ranking. 4 within marriage. 6 Women and men have the same inheritance rights under civil law, both as spouses and as descendants, and the same right to initiate divorce. The country made special progress in recent years in connection with gender-based violence, an area where it was particularly lagging behind other countries. The General Directorate of Law Enforcement and Prevention in Belarus reports that one in four women experience physical violence and four out of five women have experienced psychological violence in their families (Economic Commission for Europe 2016). To that effect, in 2014, the country adopted the Law on the Fundamental Activities to Prevent Offences, which criminalizes physical, sexual, and psychological violence against women and establishes specialized procedures for cases of domestic violence, including provisions for protection orders.7 However, this law does not protect women if the violence takes place outside of a marriage (for instance, intimate partner), and it does not include specific provisions to sanction marital rape. Sexual harassment in the workplace also remains unaddressed by the existing legislation (World Bank 2016). Despite these recent advances, different organizations (such as the Convention on the Elimination of All Forms of Discrimination against Women (CEDAW) Committee and the Women against Violence Europe Network) note that greater efforts need to be set in place to support women victims of domestic violence for the legal protection to be implemented in a more effective manner (Economic Commission for Europe 2016). While overall Belarus is one of countries in the world that shows the least number of legal restrictions on women’s employment and entrepreneurship, and its Labor Code explicitly prohibits any discrimination in labor relations (Article 14), it has the tendency observed in many other countries in the Europe and Central Asia region—of keeping in the books legal restrictions for women to work in specific industries and sectors (World Bank 2016). These restrictions include the employment of women in the areas of mining, construction, metalworking, factories, jobs requiring lifting weights above a threshold, and jobs deemed hazardous or arduous. Although in recent years Belarus reduced the number of professions in which female work is prohibited from 252 to 182, this number is much higher than the one documented in other countries in the world of similar income levels (World Bank 2016). These restrictions can have relevant effects on women’s labor participation, more so if we consider that, for example, two of these sectors, namely the industry sector—largely due to manufacturing—and the construction sector concentrated almost one-third of the total employment in the country in 2014 (24.2 percent and 8.2 percent, respectively).8 6 Article 22 reads, “All shall be equal before the law and have the right to equal protection of their rights and legitimate interests without any discrimination.” (http://law.by/main.aspx?guid=3871&p0=V19402875e) 7 http://www.pravo.by/world_of_law/text.asp?RN=H11400122 . 8 http://www.belstat.gov.by/en/ofitsialnaya-statistika/social-sector/naselenie/trud/godovye- dannye/employment-by-kind-of-economic-activity/. 5 In terms of institutions, the two main national bodies for the protection and promotion of gender equality are the Unit on Population, Family, and Gender Policy of the Ministry of Labor and Social Protection, which has the objective of promoting gender awareness, monitoring the status of women, and overseeing the implementation of the relevant international conventions,9 and the National Gender Council under the Council of Ministers. In existence since 2000, the National Council on Gender Policy, comprising representatives of legislative and executive bodies, public associations, and academics, aims to promote the development and implementation of gender policies in Belarus and plays an interdepartmental coordinating and advisory role (Ananyeu et al 2013). In addition, other ministries and agencies have set up special sub- departments for gender issues at the national level (see table 1), and local Executive Committees also have departments of targeted social assistance and gender issues.10 Table 1: State-level stakeholders of gender policy and legislation Institutional body Main tasks regarding gender equality Unit on Population, Family, and Gender Elaboration of legal regulations regarding social Policy, Ministry of Labor and Social Protection welfare; planning and monitoring family policy Department of Rendering Medical Care to Health promotion of the female and child population Mothers and Children, Ministry of Health Unit of Global policy and humanitarian Development of international cooperation collaboration, Ministry of Foreign Affairs monitoring under implementation of international recommendations Unit of Prevention in the Central Committee Prevention and elimination of domestic and gender- of law order and prevention, Ministry of based violence Internal Affairs The National Council on Gender Policy, Coordination of the projects and programs aimed at Council of Ministers achieving gender equality; improvement of interdepartmental cooperation and state-civil society collaboration Supreme Court Gender monitoring of legislation The national action plans on gender equality are the central policy instrument for the guarantee of equality between men and women in all spheres of life. Four plans have been implemented since 1995. Belarus is currently developing its fifth National Action Plan for Gender Equality in the Republic of Belarus for 2016–20. The previous (fourth) action plan revolved around ensuring parity in representation of women and men at all leadership levels, mainstreaming gender knowledge in education, building public understanding of the need for social equality between women and men in all areas of public life, and ensuring that the health needs of women are addressed (Economic Commission for Europe 2016). While no complete evaluation of its implementation has been produced, no legal reforms occurred in areas such as leadership promotion—Belarus does not have formal quota legislation for representation or candidate lists for the different levels of government (national, parliament, or local government), and no provision has been implemented to regulate women’s representation in corporate boards (World 9 OECD Social Institutions and Gender Index 2014. 10 Office for European Expertise and Communications, http://eng.oeec.by/wp- content/uploads/2015/06/Analysis-of-Gender-Sector-in-Belarus.pdf. 6 Bank 2016). It is likely to be the case, as observed in other countries, that further efforts need to be made to increase the likelihood of implementation of actions related to the action plan, increase its implementation prospects, and realize its possible impacts (Ananyeu et al 2013, Burova and Yanchuk 2014). Although limitations with regard to the data available for the monitoring and performance evaluation of gender-related national policies exist, efforts to improve the situation are under way. The NSC of Belarus is producing gender-disaggregated statistics to help informed policy- making decisions (Economic Commission for Europe 2016). In 2012, NSC, with the support of the United Nations Children´s Emergency Fund (UNICEF), conducted the Multiple Indicator Cluster Survey (MICS) to assess the situation of children and women in the Republic of Belarus (MICS 4), adding to the available data efforts, and the time-use survey conducted in 2014 also considerably expanded the gender statistics indicators available in the country (Economic Commission for Europe 2016). 2. Voice and representation Although no formal gender quota system has been legally set in Belarus, women’s political representation at the national and local levels is high in Belarus compared to other countries. Women occupy seats in the executive, legislative, and the judiciary. The proportion of seats occupied by women in the national legislature has increased significantly since the 2000 elections. At that time, 10 percent of the 97 representatives in the Lower House and 31 percent of the 61 representatives in the Council of the Republic were women. By the 2004 elections, the share of women representatives grew threefold to 31.8 percent, with the number of female members of the council remaining the same. Since then, the share of women in both bodies has remained more or less similar, although with a decline to 27 percent of representation in the Lower House since the 2012 elections (Figure 1). These figures compare favorably with the neighboring countries, such as the 12 percent and 14 percent of female parliamentarians registered for the period 2011–15 in Ukraine and the Russian Federation, respectively, or the 22 percent for Estonia, as well as the 24 percent average for the European region.11 The strides made in the legislative sector have not translated to the central executive government. Of the five deputy prime ministers, only one is female, and out of the 24 sector ministers, only 2 are women (8 percent). Such distribution compares poorly with the 46.2 percent of women ministers in Estonia and 23.1 percent in Latvia, although this is at par with the proportion of female ministers registered in Ukraine (10.5 percent) and above that of the Russian Federation (6.5 percent).12 All state committee chairs are male, and most of the deputy chairs and regional state committees’ chairs are also men. As an exception, the NSC management fully comprises women. 11 World Development Indicators (WDI). 12 Women in Politics, UN Women 2015, Belarus Government site (http://www.government.by/en/). 7 At the local level, the proportion of women in local governments has increased consistently since 2002, from 65 percent to 70 percent in 2013, although women remain underrepresented as chairs of city, town, and district committees, with the majority of these positions being held by men. On the other hand, the International Labour Organization (ILO) estimates that women made up 39.3 percent of public employees in 2015, with public employment being 58.5 percent of the total female employment.13 In the judiciary, out of the 12 justices on the Constitutional Court, 5 are women (World Bank 2016). In the Supreme Court leadership, one out of the six leaders is a woman.14 Figure 1: Female representation in the House of Representatives and the Council of the Republic 40 35 30 25 20 15 10 5 0 2010 2011 2012 2013 2014 2015 women, Council of the Republic women, House of Representatives Source: Inter-Parliamentary Union, Women in Parliament database (data as of June every year). The levels of female representation in the parliament in Belarus indicate that an informal quota agreement, as well as a commitment by the authorities to respect and implement it, goes a long way. Similar steps could be made to increase representation in leading positions at the central executive level. 3. Societal views on gender issues Men and women in Belarus report higher levels of egalitarian views on gender roles, at least according to the World Values Survey (WVS) of 2011. Both men and women tend to disagree to similar extents with some of the statements regarding gender equality, but differences can be observed, especially in areas related to opportunities and women’s empowerment. Notably, while in some areas, men’s views are more conservative than women’s, in others, it is the reverse. Figure 2 shows that reflecting on the limited number of visible female leaders, both men and women perceive men as being better equipped to take leadership roles in business and politics, with men being more in agreement with the statement. When it comes to opportunities in the 13 ILOSTAT database. 14 http://www.court.by. 8 labor market—from building skills through education to holding jobs—gender differences in views can be observed. For instance, women do not agree on the advantages of university education being greater for boys, and 84 percent of women—relative to only 59 percent of men—disagree with giving men priority when jobs are scarce. While there appears to be agreement with women gaining independence by means of a paid job, 60 percent of women think this is indeed the case, but only 39 percent of men believe so. Most men and women in Belarus still think that being a housewife is just as fulfilling as working for pay, with more women agreeing with this statement than men. These views vary also by age group, while in general, older people appear to hold more traditional views on women´s societal roles—for example, as both men and women get older, they (especially older men) increasingly agree on the fact that children suffer with a working mother. The most noticeable difference is the one observed between women and men of all ages on the statement that men should be given priority when jobs are scarce (Figure 3), a statement more men than women, regardless of age agree with, but also one where the generational views of women differ strongly, ranging from around 12 percent in agreement among women in their twenties to 24 percent in agreement among women in their sixties. With regard to the statement that women earning more than husbands can create problems (Figure 4), agreement varies by age group, reaching its peak for men in the 40–44 age group (40 percent in agreement) and women in the 35–39 age group (27 percent in agreement), and decreasing for both groups after. Figure 2: Mean value of indicators showing agreement in gender-related statements by sex, 2008 Children ***A university education is more important for a boy… Child suffers with working mother ***Men better political leaders women ***Men better business executives men Labor Market ***Woman earning more than husband is problematic ***When jobs scarce, giving men priority ***Being housewife as fullfilling as paid job ***Job best way for independence women Marr iage **Divorce acceptable 1 1.5 2 2.5 3 3.5 4 fully agree fully disagree Source: WVS 2011, World Bank staff calculations. Notes: ***Gender difference significant at 1 percent, **Gender difference significant at 5 percent, *Gender difference significant at 10 percent. Respondents have to (1) strongly agree, (2) agree, (3) disagree, or (4) strongly disagree with each of the statements above. T-test is conducted for the mean value of indicators. 9 Figure 3: Agreement by age and sex with Figure 4: Agreement by age and sex with statement "When jobs are scarce, men should statement "If a woman earns more money than have more right to a job than women" her husband, it’s almost certain to cause problems” 50 50 45 45 40 40 Men 35 35 Men 30 30 25 % 25 % 20 Women 20 Women 15 15 10 10 5 5 0 0 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+ Age group Age group Source: WVS 2011. The results of the WVS signals that there remains a substantial share of men and women in Belarus that still hold unequal views on the role of women in society and within a household. The persistence of beliefs regarding the higher capacity of men to be leaders, or the need to give priority to men in times of jobs scarcity, is of particular concern. However, as such views are more widely shared among the older age cohorts, there is an indication of some ongoing generational shift. 4. Violence against women Freedom from violence is an essential domain of agency both for its representation of respect and active protection of one of most fundamental rights, and also because it is connected to greater gender equality in opportunities and outcomes at the individual, household, and society levels. While there are not publicly available statistics on violence against women in Belarus, the latest available data, from the MICS 4 of 2012, suggests that violence against women is condemned by women and men alike in Belarus (figure 5) with very few considering violence as justifiable. Within the low levels of acceptance, neglecting the children appears as the reason with higher acceptance—at around 3.7 percent, with a notably higher level among poor men and women than among other income groups. 10 Figure 5: Share of individuals 15-49 that believe a husband is justified to beat his wife under any of the specified conditions 10 9.3 7.8 8 6 3.8 3.7 4 2 0 all poorest all poorest women men If she burns the food If she refuses sex with him If she goes out without telling him If she argues with him If she neglects the children Source: MICS 4. In terms of incidence, 11.8 percent of female respondents reported having experienced domestic or intimate partner violence, with a large difference between currently married and formerly married women (10.1 percent and 21.7 percent, respectively). Of these, 60 percent of women reported not having searched for assistance—professional or informal support from friends and family members; 70.7 percent of women victims with tertiary education, and 61 percent in the top income quintiles did not seek help, compared to less than half of women with a secondary degree, and 45 percent of the poorest women. The main cause for abuse reported by women across income, education, and age groups is alcohol consumption by their partners (78.9 percent). Belarus is among the post-Soviet countries that have introduced tougher measures against violence while simultaneously developing a platform for mediation. This is in line with views within Belarussian society that it is not only victims but also perpetrators who require assistance, although more women (40 percent) than men (30 percent) favor the introduction of more repressive legislation against perpetrators, especially urban, higher educated, and higher-income groups.15 With regard to policies, all regions in Belarus have issued a special Internal Resolution on Domestic Violence for the police force, local social services, and hospitals, with instructions on how to operate in such cases. These include requesting women who are at risk of violence to register with the police for further monitoring of their families; ensuring communication with child protection services to survey those victims who have children; and encouraging victims of violence to register in mental health clinics for further compulsory treatment. While these measures are protective by design, it is unclear whether they have led to an increase in reporting abuse, or if they refrain women from seeking assistance. 15 MICS 4. 11 CHAPTER 2: Endowments Endowments refer to key investments in human capital—education and health—and the access to basic assets, which help shape the opportunities available to both women and men to actively participate in the society and economy (World Bank 2012). Differences in endowments can have a long-lasting negative impact on children’s and adults’ outcomes, contributing to the perpetuation of the intergenerational transmission of inequalities and bearing substantial costs for societies. Gaps in access to assets such as financial resources or time also determine substantial inequalities in economic opportunity during adulthood. This chapter analyzes the situation of women in relation to men in Belarus with regard to the basic endowments of (1) health, (2) education, and (3) financial resources and time. 1. Health Belarus, as many countries in the Europe and Central Asia region, is facing a demographic trend toward population aging, with specific gender differences in the process. As shown in figure 6, the age distribution of the Belarus population is trending to almost half of its population being of individuals over 40 years of age. While among the young, the share of women and men in the population is similar, the situation changes for the oldest cohorts. Women’s higher life expectancy is evident, as the share of female population increases with age—women represent 60 percent of those 50 years and older, 65 percent of those 65 years and older, and 71 percent of those 70 years and older. Indeed, by 2014, women’s life expectancy was a year higher than men’s, at 78.4 compared to 67.8 for men (NSC 2015c). Figure 6: Share of population by age groups and sex (2015, thousands) Women Men 80+ 70-74 60-64 50-54 Age 40-44 30-34 20-24 10-14 0-4 600.0 400.0 200.0 0.0 200.0 400.0 600.0 Thousands Source: HLSS 2014. 12 The overall population has been reducing in Belarus since 1990, in line with what was observed in other post-Soviet countries, although in the last years, this trend has stalled. Moderate growth coupled with more sustainable fertility rates and an increase in life expectancy are contributing to this positive trend. The somewhat low fertility rates observed in 1990 reduced considerably up to 2005 (going from 1.91 to 1.25 children per woman) and have since risen to about 1.7 in 2014. Research suggests that this can be related to the shift on child subsidies for second- and higher-order births, as well as increased economic certainty—changes in household income appear to decrease the probability of couples having a child, especially for second- and third-order births (Basten and Frejka 2015; Amialchuk et al. 2011). The rate of marriages per 1,000 population has decreased, from 9.7 in 1990 to 8.6 in 2015. The mean age of women at first marriage and at birth of the first child have steadily increased over time, from 23 to 25 years between 2000 and 2014.16 Despite the increase in life expectancy registered during the last decade, a large and expanding gender gap in favor of women exists. Among the Commonwealth of Independent Countries (CIS) countries, Belarus ranks fourth in life expectancy after Armenia, Azerbaijan, and Georgia (Rechel 2014). Life expectancy has increased in Belarus both for men and women since 2004 (three years for women and five years for men). While the life expectancy gap between men and women has decreased from 12 years in 2004 to 10 years in 2014, it remains high, both above the average of 7 years for the Europe and Central Asia region, and 6 years for countries of similar income level, largely due to the much lower male life expectancy observed (Figure 7). Figure 7: Life expectancy at birth by sex (2014) Figure 8: Life expectancy at birth by sex and regions (2013) 82 80 80 78 78 76 76 74 74 72 72 years years 70 70 68 68 66 66 64 64 62 62 60 60 Belarus ECA Upper Belarus ECA Upper middle middle income income female male men (rhs) women (lhs) Source: WDI. Source: NSC 2013. 16 United Nations Economic Commission for Europe, NSC. 13 Regional differences exist both for men and women. Life expectancy is higher in rich urbanized regions, such as Minsk City and Brest for both men and women, although men’s life expectancy is consistently lower than women’s across all regions (figure 8). The Vitebsk and Gomel regions show both the lowest life expectancy for men and the largest gender gaps. The gender gap in life expectancy in Belarus is driven by differences in adult mortality rates. Male adult mortality is almost three times higher than that of women (261 per 1,000 adult men compared to 90 per 1,000 women in 2014). Male mortality in Belarus is almost 80 percent higher than the Europe and Central Asia regional average even when comparing with data from 2011 (latest data available for the Europe and Central Asia region), and this gap has increased over the last decade (Figure 9). High male mortality is partly explained by the higher prevalence of non-communicable diseases and injuries among Belarussian men. Although non-communicable diseases (mostly cardiovascular diseases and cancer) account for 87 percent of deaths overall, male death rates related to these factors are more than twice over those registered for females (Figure 10). Traffic accidents, suicides, and homicides are also more common as causes of death among men than women according to the NSC data (NSC 2015b). Differences in the incidence of non-communicable diseases may be related to more widespread health-risky behaviors among men. For example, 3,450 per 100,000 men were registered with health institutions as patients with alcoholism- related morbidities compared to only 765.4 per 100,000 women in 2013, and related mortality figures were also much higher among men (2,116 per 100,000 versus 649 per 100,000 for women) (NSC 2014). While 45.8 percent of men in Belarus smoked in 2015, only 0.3 percent of women did. Most of these men were reported to be daily smokers, while women were usually occasional smokers. Belarus follows Russia and Ukraine in having the most ‘risky’ patterns of drinking— ‘episodic heavy drinking’ and ‘drinking without eating’. The incidence of occupational disease and fatal injuries is also much higher among men than women in Belarus. In 2014, the new cases per 1,000 employees amounted to 0.04 for men compared to 0.01 for women. The rate of occupational injuries resulting in one or more days of incapacity or fatal per 1,000 employees was 0.8 among men compared to 0.3 for women, and that of occupational fatalities was 0.057 for male workers while it reached only 0.005 for women. Most fatalities and injuries occurred in occupations where male presence is predominant, such as agriculture, industry, and construction (NSC 2015b). 14 Figure 9: Mortality rate per 1,000 adults by gender Figure 10: Age-standardized death rates per (2004, 2011, and 2014) 100,000 by cause and sex in 2012 400 900 2004 2011 2014 Total Male Female 350 800 death rates per 100,000 700 300 600 250 500 200 400 150 300 200 100 100 50 0 All causes Cardiovasc neoplasms Injuries Malignant 0 diseases ular women men women men Belarus ECA Source: WDI and World Health Organization (WHO). Some new risks are appearing that might be related to issues such as the increased incidence of cardiovascular diseases among women. A larger proportion of women than men are overweight in Belarus. Of specific concern are the obesity levels among women over 45 years of age, where more than 40 percent of women in this age group suffer from obesity (Figure 11). In two regions, Vitebsk and Minsk, the share of people with obesity is significantly larger than the average—28 percent and 29.8 percent of the population, respectively, one of the highest rates in the European Union. Figure 11: Share of population by age group and sex reported as obese (2011 –16) 45 Women 45-64 40 Women 65+ 35 30 Women, total 25 Men, 45-64 Men 65+ 20 Men, total 15 10 5 0 2011 2012 2013 2014 2015 2016 Source: NSC 2016. 15 a. Women’s reproductive health An important gain on life expectancy is the extremely low maternal mortality observed in Belarus, which can be explained by the almost universal coverage of prenatal care services in the country.17 The share of women who have regular prenatal visits reached 96.8 percent in 2014. Although women who live in rural areas or from disadvantaged socioeconomic backgrounds are less likely to attend regular prenatal and postnatal checkups, the coverage is good, with only 16.9 percent of women living in rural areas missing postnatal care in 2014. Contraceptive use in Belarus is high for international standards. According to the MICS 4 survey (as the most recent data reported by the NSC), of all married women who sought contraception, 63.1 percent met that need, with some differences in access for rural women (about 10 percentage points lower). No data could be located regarding unmarried women (NSC 2014). Incidence of abortions has decreased in the country, with the number of induced abortions reaching 13.3 per 1,000 women in 2013. There are observable regional differences, with the Vitebsk and Gomel regions having about 17 abortions per 100 live births. Figure 12: Abortion incidence per region (abortions per 100 live births) 20 15 10 5 0 Minsk, city Brest, region Vitebsk, Gomel, Grodno Minsk, Mogilev, Belarus region region region region Source: Ministry of Health 2016. As part of the changes induced by an aging population, a special project introduced breast cancer risk assessment for women over 50 years as a systematic and more available procedure. Started in Minsk, it is expected that such screenings be expanded to other regions. The main reason for intensifying preventive treatment is the increase in the incidence of such cancer by 20 percent from 2005 to 2014 (NSC 2014). After two periods of intensive growth in the incidence of HIV/AIDS in Belarus over the mid- 1990s and early 2000s, the growth in the number of cases has moderated since. The share of people with HIV/AIDS was the largest in Minsk, and men accounted for 68.4 percent of all carriers. Although information levels regarding prevention measures are high, while about 70 percent of sexually active women got tested for HIV/AIDS in 2014, only 57 percent of men did so. The authorities have made efforts to improve the public knowledge about HIV/AIDS. Indeed, for the 17 WDI. 16 first time, in 2016Belarus officially commemorated International AIDS Memorial Day and the information campaign ‘Concern those who are not concerned’, directed to incentivize sexually active population to take the test, was also launched. 2. Education Like many comparable income countries and countries across the Europe and Central Asia region, Belarus has closed the gender gap and achieved almost universal levels of education enrollment for girls and boys alike at the primary and secondary level. Tertiary enrollment rates have also increased when compared with the 2008 levels, with Belarus showing a more stark gender gap than the region as a whole, in this case, affecting men, whose enrollment levels in tertiary education are 26 percentage points lower than women’s and who have also now reached universal enrollment (Figure 13). Figure 13: Tertiary education enrollment levels (gross) per sex 120 100 80 60 2008 40 2014 20 0 Belarus ECA Belarus ECA tertiary, female (% gross) tertiary, male (% gross) Source: WDI. Note: Gross enrollment rates can exceed 100 percent due to the inclusion of overage and underage students because of early or late school entrance and grade repetition. Although there is no official data on school enrollment across households with different wealth status, using data on students from the HLSS allows analyzing enrollment ratios in higher education18 among the population 17–24 years of age across consumption per capita quartiles (Figure 14). As expected, young men and women from the poorest quartiles are less likely to continue their education after graduating from secondary school; however, between 35 and 40 percent of them do enroll in higher education. Enrollment in higher education increases with income up to the third quartile, while it decreases slightly in the top quartile. Women have slightly higher enrollment ratios in the first three quartiles, but men have significantly higher ratios of enrollment in the top quartile. 18 Enrollment in higher education includes vocational school, secondary specialized school, higher education, and beyond higher education. 17 Figure 14: Enrollment in higher education among population ages 17–24 by consumption per capita quartiles (2014) 60 men women 50 40 30 % 20 10 0 Bottom II III Top consumption per capita quartiles Source: HLSS, World Bank staff calculations. Note: A quartile is one of the three points that divide a range of data or population into four equal parts. The first (bottom) quartile contains the poorest individuals while the last (top), the richest. When taking a closer look at the actual enrollment rates, it is possible to observe that for the past five academic years, around 56 percent of all students enrolled in tertiary education were women, a trend that continues for those students enrolling at the post-graduate level (aspirantura) but with twice the number of men continuing further to the doctorate (doktorantura) level. Men, however, have a higher presence in vocational and technical education. Professional pathways linked to academic profiles remain strongly differentiated by gender. In the 2015–16 academic year, two-thirds of all students enrolled were men, with almost half of the students enrolling in Engineering and Technology. In the case of secondary specialized education, where two-thirds of enrolled students are women, the main fields of choice are Communications, Law, Economics, Management, and Business Administration (NSC 2015a and 2016). In tertiary education, among the 10 areas that concentrate the majority of students, the share of female students is the highest in non-STEM areas. Though women form 70 percent of the students in the most popular sectors (Communications, Law, Economics, Management, and Business Administration), their presence is only 26 percent in Engineering and Technology, which is the second largest field of study. 18 Figure 15: Share of female students by field of study among the 10 fields with higher enrollment (academic year 2014/2015) Humanities Teacher Education Health Communications. Law. Economics. Management.… Art and design Natural Sciences Physical training. Tourism and Hospitality Agriculture and Forestry. Landscape Architecture Architecture and Construction Engineering and Technology 0 10 20 30 40 50 60 70 80 90 Source: NSC 2015a. Note: Figure does not include the self-employed, local Councils of Deputes, and Rural Executive Committees. Such educational choices might have an effect on the future labor market insertion of women. Women’s higher education levels are reflected in their labor market participation, with higher shares of women having more education than men. Of all the women that are employed, 33 percent have tertiary education compared with 24.6 percent of men and 26.5 percent have secondary specialized education compared with 17.6 percent of men, although unemployment levels of women with those levels of education are higher than men’s (14.2 percent versus 9.2 percent for tertiary education and 17.8 percent versus 10.2 percent for secondary specialized) (NSC 2015a). However, when looking at demand and supply of different professions, it is clear that there is a surplus of people with certain professions. According to the Ministry of Labor and Social Protection data of registered vacancies and unemployment of professionals, the number of unemployed outnumbers the available vacancies in areas such as Economics (2.15 unemployed per available vacancy) and Law (1.49 unemployed per vacancy), while for areas such as engineering, there are more vacancies than registered unemployed, same as for agronomists and veterinarians, among others. 19 In the female-dominated areas of study, higher number of vacancies can be observed for the health sector, particularly for nursing and paramedics (with about 40 vacancies per registered unemployed), and preschool teachers. 19 Reported on June 1, 2016, on http://www.mintrud.gov.by/ru/rynok as “Supply and demand for occupations that are in demand in the labor market.” The numbers reported represent a subsample of the labor market and are just indicative. 19 3. Financial and time assets Financial inclusion, measured as access to financial accounts and loans, is deeper in Belarus than the average for the Europe and Central Asia countries. According to the Global FINDEX 2014 data, while 72 percent of the population has a bank account in Belarus, only 46 percent on average do so in the Europe and Central Asia region. While 18 percent of the Belarussian population has asked for a loan at a financial institution, on average only 11 percent of the population in the Europe and Central Asia region has done the same. Moreover, people in Belarus use available accounts at high frequency, with 96 percent of those having accounts making deposits and withdrawing money once or twice per month. Although overall no significant gender gap exists in Belarus with regard to financial inclusion, there are some areas where better use of financial access could be encouraged—both for women and men with regard to using such access to save or borrow. While 40 percent of men and 38 percent of women declared having borrowed money during the past year, only 14 percent of them did so from a financial institution; 17 percent of women and 19 percent of men borrowed via store credit, and 21 percent preferred to borrow from family and friends. Similarly, while 52 percent of women and 48 percent of men saved in the past year, only 14 percent of women and 16 percent of men did so at a financial institution, although the most mentioned reason for saving (24 percent women and 20 percent men) is to prepare for old age. These figures, together with the low use and ownership of debit and credit cards (debit card use was higher at 33 percent for women and 40 percent for men, compared with credit cards at 10 percent for women and 16 percent for men; ownership figures are similar), show a relevant gap, so a larger share of the financially active population can access other tools and instruments to manage and save their financial assets. Figure 16: Borrowing behavior by sex (2014). Figure 17: Saving behavior by sex (2014) Percentage of people who have borrowed. Percentage of people who have saved. 45 60 40 35 50 30 25 40 20 15 30 10 5 20 0 Borrowed Borrowed Borrowed Borrowed 10 any money from a from a from 0 in the past financial store by family or Saved any Saved at a Saved for old year institution buying on friends money in the financial age credit past year institution Women Men Women Men Source: Global FINDEX 2014. 20 a. Time Time is a scarce resource and a critical one for women when it comes to activating their endowments into taking advantage of opportunities available to be economically active. In Belarus, as in other countries, data suggest that women have more time constraints due to household-related tasks. The recent (2014–15) time use survey reveals different time allocations between men and women (figure 18). While women allocate about 1 hour and 20 minutes lesser to household work than men during the day, they double the time allocation to household and childcare than men do, and have almost 1 hour less of free time. Of the time dedicated to household and childcare, the largest share of women’s time goes to household duties—such as cooking and cleaning—while the largest use of such time for men is on gardening and pet care. The working age group (16–54 years for women and 16–59 years for men) report spending a larger share of time at work—6 hours and 57 minutes for women and 7 hours and 38 minutes for men. Figure 18: Average time distribution (hours and minutes) by sex —total population 10 years and above Men Women 3:12 4:38 4:15 5:06 4:36 2:17 working and work-related time working and work-related time household including child care household including child care free time free time Source: NSC 2015c. Specifically, in households with children under 10 years, women spend daily almost 9 percent of their time on childcare compared to 3 percent among men. Overall, 78 percent of women and 59 percent of men care for children under 10 years, and 61 percent of women and 45 percent of men engage in teaching and education of children (NSC et al 2015). 21 CHAPTER 3: Economic Opportunities Economic opportunities refer to the employment outcomes, earnings, and productivity of individuals, which allow them to meet their full potential and make social contribution as economic agents. Across countries, differences in access to economic opportunity between women and men persist, and women appear to be concentrated in a different economic space than men, with consequences for their earning ability and economic well-being. This chapter will examine the gaps in access to economic opportunity between men and women in Belarus around (1) labor market inclusion, (2) entrepreneurship, (3) earnings, and how they reflect in (4) poverty. 1. Labor market inclusion As highlighted in chapter 1, the labor market regulation in Belarus prohibits discrimination based on gender or other individual characteristics. However, it is not neutral with regard to gender, including protection to women in the workplace—for example, for pregnant women— but also setting limits to what women can and cannot do, by establishing a list of occupations in which women are not allowed to engage. With regard to protection for parents in the labor market, Belarus has both maternity and paternity leave regulations. The length of maternity leave in the country—126 days—is high by international standards; however, it is average by European standards, the length and the fact that leave is fully paid by the Government. The median duration of maternity leave worldwide is 98 days. In addition, Belarus is among the 22 percent of countries worldwide offering parental leave. Parents are entitled to 1,095 days of partially paid parental leave—well above the worldwide median of 306 days, which, in combination with maternity leave, places Belarus among the most generous countries in this area in Europe (Figure 19). Parental leave is accessible to mothers and fathers alike, as well as other relatives, and is available for the self-employed as well as wage employees. It is not based on full replacement wages but instead on the average market wage. However, the use of parental leave by fathers is on a voluntary basis and not mandatory, with a very limited number of men making use of it. Following on the lessons from other countries, Belarus has started to consider the possibility of reducing the duration of maternity leave in consideration of the potential disincentive it might represent for women to reenter the labor market after a birth, as well as to potentially introduce compulsory leave for fathers—either as separate paternal leave or as a share of parental leave—to promote sharing of care responsibilities. Following on maternity leave protection, the Belarussian law guarantees pregnant and nursing women special workplace protection regarding dismissal, placement in an equivalent position to the one held before the leave when they return from maternity leave, and rights to a flexible schedule for both fathers and mothers. Working mothers are entitled to leave for childcare until the child reaches the age of 3 and can share this benefit with fathers (World Bank 2016). 22 After the age of 3, the law stipulates public provision of preschool education for children under the age of primary education, starting below age 1 (World Bank 2016). The NSC reports that for the school year 2015/2016, there were 3,951 institutions of preschool education, with 409,800 children enrolled, corresponding to 70 percent of children of preschool age (Figure 20). This figure reflects the steady decrease both in the number of preschool institutions and enrollment rates observed since the 2000s although keeping enrollment levels relatively high, mainly due to the almost universal enrollment in preschool for children in the 3–5 age group. However, these enrollment rates do not reflect important regional differences. Enrollment rates are at 50.4 percent in rural areas, 20 percentage points less than the average for the country (NSC 2015a). Figure 19: Total available leave for mothers, includes maternity and parental paid and unpaid leave not required to be taken by the father 2500 2000 Calendar days 1500 1000 500 0 Maternity paid Maternity unpaid Parental paid Parental unpaid Source: Women Business and the Law 2016. 23 Figure 20: Number of preschool institutions and share of children (0 –5) enrolled in preschool institutions, per academic year (2000–2016) 4500 90% 4400 80% 70% 4300 Share of children in the age 60% 4200 group enrolled in preschool 50% 4100 40% 4000 30% 3900 Number of preschool 20% institutions 3800 10% 3700 0% Source: NSC 2016 and UN 2015 Childcare speaks to one of the main constraints women face when it comes to labor market inclusion. Household and family care duties are disproportionately borne by women in Belarus, putting a strain on a limited resource: time. Indeed, as shown in the previous section, the time use survey conducted in 2014–15 indicates that important gaps exist in how men and women use their time, particularly the stark differences in time allocation by women and men to household and child care (NSC et al 2016).Time availability and the need to reconcile family duties with labor market responsibilities are at the core of some of the gender differences in labor market outcomes. 2. Employment As in many countries in the world, in Belarus and the overall Europe and Central Asia region, there is a gap between women’s and men’s labor force participation. While that gap is low for Belarus (8 percentage points), this is partly due to slightly lower levels of male labor force participation than other countries (Figure 21). Female labor force participation in Belarus has remained somewhat stable since 2009, after experiencing a decline (5 percentage points) between the late 1990s and 2009 to 62 percent for the 15–64 year age group—a similar pattern than the one observed for men of the same age group, whose participation rate reached 71 percent by 2014 (Figure 22). So women’s labor force participation rate in Belarus is in line with the OECD figures and above the Europe and Central Asia numbers, while men’s is lower than both country groups. 24 Figure 21: Female and male labor force Figure 22: Labor force participation by sex and participation rate by country (%) 2014 year (%) 100.0 100 Female labor force participation, % 90.0 90 80.0 Upper 80 middle… 70 70.0 Belarus 60 60.0 ECA 50 50.0 40 40.0 30 30.0 20 20.0 1997 1999 2001 2003 2005 2007 2009 2011 2013 20.0 70.0 Belarus women ECA women Male labor force participation, % Belarus men ECA men Source: WDI. Labor force participation by sex for ages 15–64, ILO modeled estimates. Note: Figure 21 includes upper-middle-income and selected high-income countries from the ECA region. The ECA value is all non-high-income countries. However, when it comes to employment, an employment gap in favor of men can be observed among both young and old people and across all education levels. According to the latest available data (HLSS 2010), there is a statistically significant employment gap between young men and young women—, 20–24-year–old-men are 1.3 times more likely to be employed than women in the same age group (Figure 23). This pattern is consistent across age categories, men are systematically more likely to be employed, with the exception of the 40–54-year-old category, where employment rates tend to be higher for women than for men. However, this difference is not statistically significant. The ILO modeled estimates of the ratio of the population of age 15 and above by sex who are employed also suggests a gap between men and women. Education seems to be an important determinant of employment, as employment levels increase considerably with attainment of education (Figure 24). A gender gap can also be observed when considering educational attainment. Although this gap is larger among individuals with secondary and vocational school education—men who have completed those levels of education are 1.2 times more likely to be employed than women—the observed gender gap is statistically significant across all educational levels, favoring men. However, as seen in the education section of this report, men are less likely to enroll in higher education (tertiary) than women. Hence, education achievement is not a guarantee for women’s employment—the share of unemployed women with higher education is larger than that of men, and it has increased from 12.7 percent in 2010 to 14.2 percent in 2014 (Figure 25). This is also the case with regard to secondary specialized education—in 2014, 3,231 women with such degrees were unemployed 25 compared to only 1,543 men. Interestingly, among women without professional education, the share of unemployed is smaller than among men. Overall, young women experience unemployment more often than their male counterparts. The ILO modeled data indicate a 12.8 percent unemployment rate for women 15–24 years of age and 11.4 percent for men of the same age group. According to the NSC, in 2013, 19 percent of the men and 19 percent of the women who registered with labor, employment, and social protection agencies were 16–24 years of age, the largest share for women and the second largest share of the registered for men who are older than 50 years. Women represent 40 percent of the total registered unemployed (NSC 2013). While looking only at the registered unemployed is a partial picture, it provides an indication of the constraints faced in Belarus, as in other countries, for the younger cohorts to successfully enter the labor market. Belarus recently reintroduced mandatory job placement for young graduates, with a wage premium benefit. Both young female and male graduates appear to be taking up these placements, with women doing so more than men (73.8 percent of women compared to 65.2 percent of men). Figure 23: Employment ratios across age groups Figure 24: Employment ratios across education by sex, 2010 (%) levels by sex, 2010 (%) 100 men women 100 90 men women 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 Sources: HLSS 2010, World Bank staff calculations. 26 Figure 25: Unemployment rates by sex and educational attainment (2014) Men Women higher education higher education secondary specialised education secondary specialised education special vocational training special vocational training secondary general education, 11 years secondary general education, 11 years secondary general education, 9 years secondary general education, 9 years Source: NSC 2015b. As with field of education fields, and partly as a result of it, gender segregation can be observed in the case of occupations. Women are disproportionately more engaged in organizations dealing with education, health and social work, trade, repair of vehicles, and household and personal goods (Table 2). Such differences may also be related to the legal restrictions on the types of jobs that women can undertake in Belarus, discussed in chapter 1. There are limited data on the distribution of the employed and economically active population by level of responsibility or type of work in each of these sectors. Data indicate that men are more likely to be manual workers and managers than women. Manual workers and salaried employees accounted for 57 and 43 percent, respectively, of total wage employment in Belarus in 2014, with manual workers accounting for 70 percent of total employment among men and 46 percent of employment among women in 2014 (NSC 2014).20 Table 2: Women and men engaged in organizations by economic activity (percent of total) Men Women 2010 2012 2014 2010 2012 2014 Agriculture, hunting, and forestry 14.9 14.7 14.0 8.3 8.0 7.6 Fishing and fish farming 0.1 0.1 0.1 0.0 0.0 0.0 Industry 34.6 36.3 34.9 24.0 23.9 22.6 - Mining and quarrying 0.6 0.5 0.8 0.2 0.2 0.3 - Manufacturing 27.9 29.5 27.7 21.6 21.5 20.1 20 Manual workers are equivalent to blue-collar workers and salaried workers to white-collar workers. Total wage employment does not include self-employment, employment on personal subsidiary plots, and employment on small enterprises (less than 15 workers). 27 Men Women 2010 2012 2014 2010 2012 2014 - Electricity, gas, and water supply 6.1 6.3 6.4 2.2 2.2 2.2 Construction 15.8 13.8 14.5 3.0 2.8 2.8 Trade, repair of vehicles, and household 5.8 6.5 7.2 12.3 13.2 14.5 and personal goods Hotels and restaurants 0.5 0.6 0.7 1.6 1.5 1.6 Transport and communications 9.3 9.5 9.2 5.0 5.0 4.8 Financial activities 1.0 1.1 1.1 2.6 2.7 2.9 Real state, renting, and business 5.1 4.8 5.3 5.2 4.7 4.9 services Public administration 2.8 2.1 2.1 3.3 2.3 2.2 Education 4.7 4.8 4.9 18.1 18.6 18.5 Health and social work 2.6 2.7 2.8 12.7 13.0 13.3 Community, social and personal services 2.8 3.0 3.2 3.9 4.3 4.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source: NSC 2015c. According to a recent survey, both young women and men in Belarus report experiencing discrimination in the labor market (NISEPI 2013). Approximately a quarter of all respondents reported working without employment contracts and compensation agreements, while 17.6 percent of men and 12.9 percent of women mentioned the practice of hidden wages. Among men, 24.4 percent reported experiencing work overload without compensation as did 18.9 percent of women. Women reported experiencing sex-based discrimination in the workplace (while men did not mention it) and 10.4 percent of female respondents described their job as family unfriendly, due to practices such as employers rejecting parental leave requests or requests for flexible work schedules. Young women appear to be more skeptical regarding the prospect of finding a better job after they have completed their obligatory job placement. Among women, 68.6 percent of the respondents doubted that they would find a better job after finishing their contract compared with 51.2 percent of male respondents. Moreover, 21 percent of female respondents (compared with 8.8 percent of male respondents) considered that generally there is no chance to find a good and respected job (NISEPI 2013). 3. Entrepreneurship Women are less likely than men to participate in firms’ ownership and management. According to BEEPS (2013) data, the share of firms with female ownership and management is lower than that of firms with male ownership and management. However, female firm ownership and management is much higher in Belarus than the average for the Europe and Central Asia region (44 compared with 31 percent and 33 compared with 19 percent, respectively) (Figure 26). As observed in many other countries, women are more likely to manage small firms (firms with less than 20 employees). Available data for firms with 5–19 employees indicate that about 28 37 percent of managers and 46 percent of owners of firms of that size are women. As size increases, the participation of women in the management decreases, and so does ownership, although women are as likely to be owners of firms with less than 20 employees as they are of being owners of firms with over 100 employees (Figure 27). However, while 23.5 percent of small firms are largely owned by women, only 5.1 percent of large firms have a majority female ownership. Half of the firms with majority female ownership have a female top manager and 65.5 percent of firms with women ownership (any share) also have female top managers. Firm with female owners and managers are concentrated in certain sectors: textiles, hotels and restaurants, and garments and retail. High female ownership but lower female management is observed in sectors such as food, transport, machine and equipment, other services, wholesale, and construction. Male-dominated sectors include basic metals, information technology, chemicals, plastic and rubber, nonmetallic minerals (Figure 28). Female-owned and female- managed firms tend to hire more female workers. Among the firms with a female top manager, the share of female full-time workers is 76.4 percent compared with 38.5 percent for firms with a male top manager, and this difference holds both for production workers and non-production workers. The differences in the numbers of female employees might also be related to the sector where the firms managed by women operate. The main reason why women decide to start their own business is financial conditions (Eliseev 2014). The share of Belarussian firms with a loan or a credit line declined significantly, from almost 50 percent in 2013 to 30.4 percent in 2015. While only 4 percent of female-managed firms identified access to finance as a major constraint, 16.7 percent of firms with female management had a bank loan or a credit line, compared with 36.6 percent of male-managed firms. Female-managed firms had a higher-value collateral (192 percent of loan amount compared with 144 percent for male-managed firms) and are twice more likely to have been rejected in a loan application than male-managed firms. Local research reports that small and medium enterprises (SMEs) and young firms were the most affected by the lack of bank financing, with 49 percent of SMEs and 64.1 percent of young firms that needed a loan being credit-constrained—compared to 17.5 percent of large and 39.6 percent of old firms—most of them reporting being discouraged from applying for a loan due to high interest rates. 29 Figure 26: Share of female ownership and Figure 27: Share of female ownership and management in Belarus and ECA (2013) management by firm size (employees) in Belarus (2013) 50 50 40 40 30 30 % % 20 20 10 10 0 0 Belarus ECA 5-19 20-99 100+ Female ownership Female management Female ownership Female management Source: BEEPS (EBRD and World Bank 2013). Figure 28: Female ownership and management by economic sectors in 2013, % Hotel and restaurants Garments Retail Textiles Machinery and equipme Other services Food Female management Non metallic mineral Female ownership Wholesale Construction Other manufacturing Plastics & rubber Fabricated metal prod Transport Chemicals IT Basic metals 0 20 40 60 80 100 Source: BEEPS (EBRD and World Bank 2013); World Bank staff calculations. Note: Strict weight is used. 30 4. Earnings Gender differences in time responsibilities, education levels, sectors, and occupations can also be reflected in the earnings of men and women. Despite women’s greater educational attainment, at a first glance, the gender wage gap in Belarus appears to have increased during the last decade—from 19 percent to 24 percent between 2001 and 2014, a slight change downwards from the 26 percent observed in 2011. Based on HLSS data, gross monthly wages from the main job also show that women tend to earn less than men, as shown in figure 29, where men’s income distribution is located to the right of women’s income distribution. Figure 29: Log monthly wages by sex (2014) .8 .6 Density .4 .2 0 10 12 14 16 18 Log monthly wage Men Women Source: HLSS, World Bank staff calculations. Note: Kernel density distributions. The gender difference in the distributions is statistically significant at 5 percent level based on the Kolmogorov-Smirnov equality-of-distributions test. According to the NSC data, in 2014, the ratio of female to male wages was 76.6 percent, closing the gap between female and male wages by 2 percentage points from the estimates for 2013, up from 74.5 percent in 2013. As shown in table 3, the gap was wider in male-dominated occupations—within industry, both in mining and manufacturing, while the smallest gap was observed in agriculture and female-dominated sectors such as education and health and social work (NSC 2015b). 31 Table 3: Ratio of women’s wages and salaries to men’s wages and salaries by sector, % 2013 2014 Total 74.5 76.6 Agriculture, hunting, and forestry 89.6 90.2 Fishing and fish farming 82.2 83.4 Industry 75.8 74.6 - Mining and quarrying 72.7 72.3 - Manufacturing 74.8 72.8 - Electricity, gas, and water supply 81.5 83.0 Construction 81.5 83.2 Trade, repair of vehicles, and household and personal goods 81.4 78.6 Hotels and restaurants 74.8 77.0 Transport and communications 84.8 84.6 Financial activities 75.9 78.7 Public administration 87.7 86.4 Education 77.7 81.7 Health and social work 84.8 86.6 Real state, renting, and business services 71.6 71.9 Source: NSC 2015 - Living Standards in Belarus. Men have higher predicted wages than women for almost all educational categories. Figure 30 shows the predicted values for the returns to education by sex.21 Men have higher predicted wages for each extra completed level of education, getting a significant increase for having finished higher education. Women instead do not have a significant difference in their wages for educational levels from primary or less education to specialized secondary education, but they do get a significant increase in their salaries for having completed tertiary education or above. Still, the wage gap in favor of men is present in all educational categories, but in primary education or less, women have higher predicted wages than men. The persistent wage gender gap in Belarus is explained by diverse factors. First, women are generally employed in sectors where the pay is lower. However, even in sectors where this is not the case, they are often underrepresented in higher-paid positions. In those sectors where the average earnings of women were comparable with those of males, being mainly male-dominated sectors (for example, agriculture, forest management, hunting; fishing and fisheries sector; construction), general average wages were much lower than in other sectors in 2014. 21 Results are for basic Mincer equations using the Heckman selection model. The equations were estimated using the log of labor wages and the predicted values transformed back to thousands of Belarussian rubles. Years of education were imputed using the following scheme: 2 years for those without education, 4 for primary, 9 for basic, 11 for general secondary education, 12 for vocational education, 13 for secondary specialized education, and 16 for higher education. 32 Figure 30: Predicted wages by education categories (Heckman model, 2014) 6000 5000 thousand belaruisan rubles 4000 3000 2000 1000 0 Men Women primary secondary vocatioal specialized higher Source: NSC 2016. Note: Full results available in the appendix (Table A2). Other controls include regional dummies and dummy for rural/urban areas. The Heckman selection equation is identified by using a dummy for head of household and size of the household. All presented coefficients are significant at 1 percent level. Conditional marginal effects are presented from the Heckman regression (for working women and men). Gender wage gaps can also be observed by region. The poorest regions, Brest, Vitebsk, and Mogilev, have smaller wage gaps than other regions, mainly because the average wage for women and men alike was also much lower. The largest gap in wages was observed in Minsk City and the Minsk region, two of the regions with the highest average wages and where business concentrates. More than two-thirds of the economic structure in Minsk comprises services and retail, both activities where the share of women is much larger than that of men but where gender wage gaps remain. When further looking into the reasons behind the observed gender wage gap, the Oaxaca decomposition of wages by gender reveals that observed characteristics explain an important share of the wage gap observed in Belarus. We estimate regressions explaining men’s and women’s mean monthly wages for 2010 and 2014 (Table 4)—the estimated gender wage gap is 34 percent and 30 percent, respectively, signaling a slight closing of the gap between both years.22 The main part of this gap stems from differences in returns to unobserved characteristics (unexplained part) or individual and other characteristics not covered in the data. Observed characteristics—age, years of education, and region—help explain around a third of the gap (28 22 The analysis obtained threefold and twofold Oaxaca-Blinder decomposition of gender wage gap. Detailed description of the Oaxaca-Blinder methodology and empirical application can be found in Jann (2008). 33 percent in 2010 and 38 percent in 2014)—being experience and education—the two factors that help explain the gap the most. The coefficient term—which is significant and positive—is higher than the observed gender gap, suggesting that if women had the same returns (or coefficients) to their observable characteristics—age, region, and years of education—as men, the wage gap would be reduced to the point that the wage gap would be in favor of women. Table 4: Oaxaca decomposition of monthly wages, 2010 and 2014 a) Threefold and twofold decomposition of wage a) Threefold and twofold decomposition of wage gap, original scale gap, original scale 2010 2014 Three-fold decomposition Three-fold decomposition Gender gap, % 34.07*** Gender gap, % 29.84*** Endowments −8.91*** Endowments −10.28*** Coefficients 43.90*** Coefficients 42.36*** Interaction 2.29*** Interaction 1.65 Two-fold decomposition Two-fold decomposition Explained −7.88*** Explained −9.54*** Unexplained 45.54*** Unexplained 43.53*** b) Detailed two-fold decomposition of wage gap, b) Detailed two-fold decomposition of wage gap, log of monthly wage log of monthly wage Gap 100.00 Gap 100.00 Explained −27.99 Explained −38.39 Experience −14.00 Experience −19.22 Education −13.42 Education −17.83 Region −0.57 Region −1.34 Unexplained 127.99 Unexplained 138.39 Source: HLSS, World Bank staff estimation. Note: ***Significant at 1 percent, **Significant at 5 percent, *Significant at 10 percent. Explanatory variables include age, age squared, years of education, and regional dummies. Positive sign of components indicates increase of wage gap. The limited data available in the HLSS for this estimation are reflected in the large share of the gap that remains ‘unexplained’. For example, things documented in the literature as explaining wage differences such as sector of employment, occupation, number of children in the household, and marital status, among others, if to be available and added, would likely reduce the share of the wage gap that remains unexplained. These additions will not be able to cover other factors that cannot be observed in the data—such as discriminatory practices or beliefs by 34 employers, for example, penalizing young women for the cost of future childbearing (maternity leave, absences due to child care, and so on). 5. Gender and Poverty Lower wages by the main earner of the household can have important impacts on the well- being of the entire household. A proxy for such analysis is to look at the situation of female- headed households. In the case of Belarus, the overall share of households that declare having a female head has always been high (over 55 percent in 2000 and close to 70 percent by 2014).23 Among female-headed households, the largest share are single-person households, mainly of women 65 years and above, probably due to the earlier and higher male mortality rates. Up to 79 percent of household heads who are 65 years and older are women (Figure 31). Women are also more likely to be the head of households of single-parent households across all age groups. Indeed, 96 percent of all single-parent households were headed by women. The share of female headship of households with more than one adult is around 60 percent. Figure 31: Household headship by household type 40 35 30 25 20 15 10 5 0 Single person Single parent 2 and more adults 2 or more adults 2 or more working household household with children (0-17) household (65+) age adults household (18-64) male head female head Source: HLSS. World Bank staff calculations. Female-headed households across Belarus show, on average, lower-income per capita than male-headed households. This result is consistent across single-person households, single-parent households, and households headed by pensioners. Single-parent households headed by women have the lowest income per capita across all types (Figure 32). Women heads of single-person households have lower incomes than men across most age groups, with the exception of the youngest cohort (19–24 years of age) and those in the 56–64 age group. The gap is wider for heads of households between 35 and 55 years, while women and men of 65 years and above have the lowest income compared with other households—a situation that might speak to the sole dependency on pensions, as the age at which men and women can retire and receive full benefits is 60 and 55 years, respectively (Bussolo et al 2015). This, combined with their much longer 23 The declared number of female heads is based on the order of individuals in the household members list in HLSS, where the first ordered individual is recognized as the head of household. 35 lifespan, results in a higher percentage of women pensioners in single homes who are more vulnerable to poverty than other households. The Government recently announced that maternity leave will be excluded from the years of pensionable service, potentially lowering the pension income for women who have used that benefit. While this might be compensated with the needed increase of retirement age for both men and women, the availability of employment for women between 55 and 65 years of age will become a challenge, more so as the current levels of employment for this age group are quite low (Shimanovich 2016). Figure 32: Monthly income per capita by Figure 33: Monthly income per capita by gender of gender of head of household and the type of head of household and age group among single- household person and single-parent households 6000 7000 thousand belarussian rubles 5000 6000 thousand belarussian rubles 5000 4000 3000 4000 3000 2000 2000 1000 1000 0 ***Single Singe parent Head of 0 person household household is 19-24 ***35-39***40-55 56-64 ***65+ household pensioner Male head Female head Male head Female head Source: HLSS. World Bank staff calculations. Note: Income per capita includes average monthly cash and in-kind income. ***Gender difference significant at 1 percent. The analysis of single-parent households headed by women shows that their income per capita drops sharply as the number of children increases. Single-parent, female-headed households without children below 12 years of age have an average income per capita that is double the income per capita for same headship household with three children (although this analysis does not included potential economies of scale). 24 Although such households are a smaller share in terms of numbers, they clearly benefit from incentives such as state allowances 24 Nevertheless, the robustness of results was checked by calculating income per capita using the following equivalence scale: 1 to the first adult, 0.6 to each additional adult, 0.5 to children between 6 years and 18 years, and 0.4 to children below 6 years. The results do not change and the risk of poverty still increases with the number of children. 36 to families with children and special housing benefits for families with three or more children (World Bank 2016).25 Conclusions and Policy Recommendations Belarus continues to show that is in the lead toward achieving gender equality among Europe and Central Asia countries. Belarussian law has grown to protect women and reduce discrimination, women enjoy high levels of human development—education and health—and have a high level of labor force participation. Significant progress was achieved in the past three years with the country legally protecting women from the threat of violence and different policy measures were enacted in the field of gender equality along with establishing the coordinating and advisory agency. The country is preparing a new National Action Plan for Gender Equality for the 2016–20 period, which has the potential to provide guidance to policy makers on further areas of reform. Nevertheless, this report identifies the remaining gender disparities affecting both men and women in some key areas of access to opportunities. While women continue to be more represented in higher education, their returns to such education in the labor market remain lower than men’s. Indeed, the analysis shows that although the wage gap has narrowed from 2010 to 2014, only a small share of this gap can be explained by observable differences between male and female workers. Women appear to be concentrated in specific occupations and sectors and are less likely to be firms’ owners or entrepreneurs, or firm’s managers. Besides the gap in economic participation, women have very limited participation in public office and public administration. Women over the age of 65 have the lowest income per capita among all single-person households. Women are more likely to be heads of single-person and single-parent households, and as such have lower income per capita, particularly for the case of single-parent households. When it comes to health, men have higher mortality rates and lower life expectancy than women. Young men are also less present in tertiary education. The following policy measures for the Government and the donor community may be beneficial for strengthening gender policy making in Belarus:  Expand on the success of passing the legislation to protect women from domestic violence by focusing on dissemination and awareness raising campaigns on the legislation content and protection; work on the implementation and enforcement of the domestic violence legislation; and develop a monitoring framework, including data collection and availability on prevalence, incidence, and reported cases. 25 For housing, the state repays 75 percent of mortgage after bearing the third child and 100 percent after the fourth child. 37 Additionally, expanding the law to cover violence among non-married partners would be advisable.  A system to provide information on skills demands, returns to education per sector of study, employment opportunities, for example, via the introduction of a labor market observatory, could help in tackling gender career streaming in tertiary education and change girls and boys aspirations. This will potentially have positive impacts both with regard to young women’s participation in STEM fields of study and young men’s enrollment and completion of tertiary education.  Continuous efforts need to be made to improve men’s life expectancy and years of healthy living. As Belarus continues to progress in the demographic transition toward ageing, healthy ageing becomes an imperative. The major policy issues involved are reducing major health risks like alcohol use and smoking before people get sick and strengthening preventive health services. The high incidence of cardiovascular disease reflects both unhealthy lifestyle choices (smoking, drinking, and poor diets) and the lack of the comprehensive preventive services that have proven effective in reducing disease in other countries. Several countries in Europe and Central Asia have used increased public support against smoking to implement comprehensive tobacco control policies, including bans, taxes, and public awareness campaigns.  Belarus could test introduction of measures to increase the presence of women in decision-making positions in public office. From deliberate efforts to identify and train qualified and promising female public servants and parliamentary candidates to the introduction of a transitory measure such as formal or informal quotas can support bringing more women to visible public roles.  As noted in the previous World Bank gender assessment of Belarus (Atamanov and Sattar 2014), further research is needed to identify the factors affecting the large gender gap in earnings. Greater availability of gender-disaggregated data is needed for this and other key knowledge gaps, which will allow for a better evidence-based policy design. Success of gender-related policies depends on data availability used both for identification of gender issues and monitoring success of the implementation of gender policies. Efforts such as gender-disaggregated data availability, and the recent national Time Use Survey, show significant strides by the NSC. Further work to ensure availability of relevant and regularly updated gender-disaggregated statistics in Belarus would be advisable, including making existing data and surveys accessible and available to the research community. 38 References Akulova, M. 2012. Becoming Entrepreneur in Belarus: Factors of Choice Free Policy Brief. Amialchuk, A., Lisenkova, K., Salnykov, M., & Yemelyanau, M. 2011. Economic determinants of fertility in Belarus: A micro-data analysis. Belorussian Economic Research and Outreach Center working paper No. 013. Ananyeu, D., A. Asanovich, A. Darafeyeva, V. Polevikova, V. Slavinskaya, and H. Yahorava. 2013. Country Report. Participation of Women in Public and Political Life. Belarus . East European School of Political Studies. Minsk. Atamanov, A., and S. Sattar. 2014. Belarus - Country gender profile. Washington DC ; World Bank Group Basten, S., and T. Frejka. 2015. Fertility and Family Policies in Central and Eastern Europe. Barnett Papers in Social Research 15-01, Department of Social Policy and Intervention: University of Oxford. Berg, K. 2014. “Cultural Factors in the Treatment of Battered Women with Privilege, Domestic Violence in the Lives of White European-American Middle Class, Heterosexual Women.” Affilia (29:2): 142–152. Burova S., and O. Yanchuk. 2014. Analysis of the gender sector in Belarus. Office of European Expertise and Communication. Minsk. Bussolo, M., J. Koettl, and E. Sinnott. 2015. Golden Aging: Prospects for Healthy, Active, and Prosperous Aging in Europe and Central Asia. Washington, DC: World Bank. Rechel, Bernd, Erica Richardson, and Martin McKee, eds. 2014. Trends in Health Systems in the Former Soviet Countries European Observatory of Health Systems and Policies . Eliseev, A. 2014. Social Contract: Entrepreneurs. Minsk: Belarusian Institute for Strategic Studies. Hogefoster, M., and P. Jarke, eds. 2013. Corporate Social Responsibility and Women's Entrepreneurship around the Mare Balticum. Baltic Sea Academy. Hamburg. Independent Institute for Socio-Economic and Political Studies (NISEPI). 2013. Youth of Belarus on the Labor Market and Within the System of Labor Relations. Minsk IPM Research Center. 2015. Belarus Macroeconomic Forecast 2 (11). Jann, B. 2008. OAXACA: Stata module to compute the Blinder-Oaxaca decomposition, Statistical Software Components S456936, Boston College Department of Economics, revised 25 Aug 2011. Pikulik, A., and E. Artemenko. 2014. Social Contract: Double Strategy. Minsk: Belarussian Institute of Strategic Studies. NSC. 2013. Social Status and Living Conditions of Belarus Population 2013. ———. 2014. Public Health in the Republic of Belarus. ———. 2015a. Education in Belarus. ———. 2015b. Social Status and Living Conditions of the Population in the Republic of Belarus. ———. 2015c. Yearbook. ———. 2016. Women and men in Belarus. ———. 2016. Main indicators of education. NSC, UNICEF and UNFPA. 2015. How We Use Our Time. Rees, C. J., and G. Miazhevich. 2005. “The emerging identity of women managers in post-Soviet Belarus.” Women in Management Review 20 (6): 412–428. 39 Shmidt, V., and I. Solomatina. 2016. “The attitude of feminist activists to domestic violence: strange case of epistemic injustice in contemporary Belarus.” In Investigating Gender-Based Violence, edited by Susanna Pozzolo, Giacomo Viggiani. London: Wildy, Simmonds and Hill Publishing, 2016. 130–167. Shimanovich, G. 2016. The Influence of Changes in the Social Policy of Elderly in Belarus. IPM Research Center. Smallbone, D. and F. Welter. 2010. Entrepreneurship and government policy in former Soviet republics: Belarus and Estonia compared Environment and Planning C: Government and Policy 28, 195 –210. Stead, V., and C. Elliott. 2012. “Women’s Leadership Learning: A Reflexive Review of Representations and Leadership Teaching.” Management Learning 44 (4): 373–394. United Nations. 2016. World Population Prospects: The 2015 Revision. Population Division. World Bank. 2012. World Development Report 2012. Gender Equality and Development. The World Bank. Washington, D.C. ———. 2016.. World Bank Group gender strategy (FY16-23) : gender equality, poverty reduction and inclusive growth. Washington, D.C. World Bank Group ———. 2016. Women, Business and the Law. World Economic Forum. 2016. The Global Gender Gap Report 2016. Geneva. World Economic Forum. 40 APPENDIX Table A1. Ordered probability model for life satisfaction, 2008 1 2 3 4 0.0301 0.0189 −0.155 −0.151 Female (0.054) (0.055) (0.126) (0.126) −0.0698*** −0.0692*** −0.0694*** −0.0688*** Age (0.011) (0.012) (0.011) (0.012) 0.000612*** 0.000606*** 0.000609*** 0.000604*** Age squared (0.000) (0.000) (0.000) (0.000) 0.164*** 0.155*** 0.216** 0.209** Married (0.060) (0.060) (0.100) (0.100) — — −0.06 −0.0619 Married Female — — (0.125) (0.125) −0.0146 −0.0113 −0.147 −0.146 Number of children (0.077) (0.077) (0.110) (0.111) — — 0.233* 0.237* Children Female — — (0.134) (0.135) 0.00883 −0.00567 −0.0358 −0.0339 Employed (0.071) (0.073) (0.102) (0.103) — — 0.0778 0.0532 Employed Female — — (0.116) (0.116) Education level dummies No Yes No Yes Source: EVS 2010. Note: ***Significant at 1 percent, **Significant at 5 percent, *Significant at 10 percent. The dependent variables are measured by the question: “How satisfied are you with your life in scale from 1 to 10, 1 being dissatisfied and 10 being satisfied.” 41 Figure A1. Coefficients and Confidence Intervals for Gender Dummy from Ordered Probit, 2008 a) Ordered probit regression without controls b) Ordered probit regression with controls 0.6 0.6 0.4 0.4 0.2 0.2 0 0 -0.2 Work Family Friends Leisure Politics Religion -0.2 -0.4 -0.4 -0.6 -0.6 -0.8 -0.8 coef Lower Upper coef Lower Upper Source: EVS 2010. World Bank staff Source: EVS 2010. World Bank staff calculations. calculations. Note: Controls include number of children, marital Note: Dummy takes 1 for female and 0 for men. status, employment dummy, and education. All The question states: “How important in your variables except education categories are interacted life are … in a scale from 1 to 4, 1 being very with female dummy. Positive coefficient indicates important and 4 being least important.” less importance of a particular category for women Positive coefficient indicates less importance of than men. a particular category for women than men. Table A2. Returns to education and experience, 2014 Dependent variable log of monthly average wage from the main job in 2014 (1) (2) (3) (4) (5) (6) Men Women VARIABLES OLS OLS Heckman OLS OLS Heckman 0.144*** 0.145*** 0.00135 0.152*** 0.159*** 0.0163 Age (0.02) (0.02) (0.03) (0.02) (0.02) (0.03) −0.00167*** −0.00168*** 0.0000535 −0.00172*** −0.00179*** −0.0001 Age squared (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) Years of 0.0759*** 0.0742*** 0.0253* 0.0795*** 0.0763*** 0.0516*** education (0.01) (0.02) (0.01) (0.01) (0.01) (0.01) — 0.0282 −0.0521 — −0.0927 −0.0213 Vitebsk — (0.11) (0.09) — (0.09) (0.07) — 0.178** 0.133 — 0.0076 0.00859 Gomel — (0.08) (0.09) — (0.05) (0.06) — 0.176** 0.093 — 0.000141 −0.0289 Grodno — (0.08) (0.09) — (0.07) (0.07) — 0.152 0.244*** — 0.198** 0.244*** Minsk City — (0.13) (0.09) — (0.10) (0.07) — 0.285*** 0.206** — 0.236*** 0.182*** Minsk oblast — (0.08) (0.09) — (0.05) (0.06) Mogilev — 0.0556 0.0251 — 0.105** 0.108 42 Dependent variable log of monthly average wage from the main job in 2014 (1) (2) (3) (4) (5) (6) Men Women VARIABLES OLS OLS Heckman OLS OLS Heckman — (0.09) (0.10) — (0.05) (0.07) — −0.0898** −0.157*** — −0.0483 −0.0339 Rural — (0.04) (0.06) — (0.04) (0.04) 11.16*** 11.06*** 14.89*** 10.52*** 10.36*** 13.81*** Constant (0.39) (0.44) (0.73) (0.43) (0.45) (0.67) Observations 3,072 3,072 3,072 3,524 3,524 3,524 R-squared 0.079 0.087 — 0.077 0.087 — Source: HLSS. Note: ***Significant at 1 percent, **Significant at 5 percent, *Significant at 10 percent. Marginal conditional effects are presented for the Heckman model. Table A3. Returns to education and experience, 2014 Dependent variable log of monthly average wage from 2014 Men Women 0.936*** 1.594*** Age (0.05) (0.05) −0.0116*** −0.0191*** Age squared (0.00) (0.00) 5.056*** 0.910* General Secondary (0.48) (0.53) 6.019*** 1.467*** Vocational Secondary (0.50) (0.55) 6.595*** 2.126*** Specialized Secondary (0.48) (0.53) 6.889*** 2.699*** Higher education and masters (0.50) (0.54) 0.486 0.0455 Vitebsk (0.34) (0.32) 0.339 −0.184 Gomel (0.33) (0.31) 0.375 0.338 Grodno (0.35) (0.33) −0.0254 0.493* Minsk City (0.31) (0.30) 0.761** 0.951*** Minsk oblast (0.32) (0.31) 0.144 0.0264 Mogilev (0.36) (0.33) 43 Dependent variable log of monthly average wage from 2014 Men Women 0.483** 0.0467 Rural (0.22) (0.21) −11.08*** −21.50*** Constant (0.90) (0.93) N 3,767 5,017 R-squared 0.2 0.259 Source: HLSS. Note: ***Significant at 1 percent, **Significant at 5 percent, *Significant at 10 percent. 44