1 Introduction

While the gender wage gap (GWG) is narrowing in almost all developed countries, it remains comparatively high in many of the former Soviet Union (FSU) nations. In Belarus, it was documented to have increased over the first decade of transition (Pastore and Verashchagina 2011; Akulava 2016).

Data remains an issue in Belarus. The above-mentioned studies relied on the Belarusian Household Survey of Income and Expenditure (BHSIE), which, for quite some time, was the only source of microdata available to researchers. However, several important variables were dropped over the years (such as hours of work and sector of employment); thus, estimates are not strictly comparable over time. Despite these insurmountable difficulties, this chapter aims to summarize the evidence on the GWG in Belarus obtained from the BHSIE over the last two decades. The idea is to reconstruct the link with the policies implemented in the country over the period of this research.

The GWG in Belarus had more than doubled before the Great Recession, from as low as 8% in 1996 (when the first round of the BHSIE was undertaken) to more than 20%Footnote 1 in 2006 (Pastore and Verashchagina 2011); the crisis then widened it further. This chapter provides the evidence gathered between 2001 and 2016.

The reduction in women’s relative wages was due to the deterioration of observed characteristics (e.g. segregation in low-wage sectors). This may be largely driven by a generous childcare policy, as per which the state provides three-year paid maternity leave. The neglect of the gender dimension when implementing policies aimed at addressing the demographic crisis in Belarus has led to a different kind of problem for policymakers—women in the labor market being underpaid when compared with men. This may have repercussions not only on female participation in the labor force but also on the accumulation and use of human capital. Unless properly addressed, this unintentional effect of family policies may have long-term implications on the growth of the Belarusian economy.

2 Contrasting Patterns of the GWG Across Countries

The literature on the GWG aims to explain the reasons behind the persisting differences in remuneration for men and women (see Blau and Kahn 2017 for a recent review). These can be personal characteristics, occupational and sectoral segregation, breaks in career due to childbearing, or other reasons including discrimination.

Some studies focus on the differences in remuneration because of unequal productivity and the quality of human capital. Less experience, lack of required skills and knowledge, fewer incentives to invest in education, and working overtime all explain wage disparity to an extent (Blau and Kahn 1997; Warren et al. 2001; Booth and Francesconi 2003; Amuedo-Dorantes and de la Rica 2006; Manning and Swaffield 2008; Lemieux et al. 2009). Moreover, various differences in behavior matter: networking, voluntarism, and career aspirations affect the level of remuneration (Azmat and Ferrer 2017). Card et al. (2016) showed that it is also about sorting and bargaining—that is, firm-specific pay premiums contribute to the GWG if women are less likely to work for high-paying companies, or if they negotiate poorer wage deals with their employers when compared with men.

The issue of gender segregation, by occupation and sector, has also been explored in relation to the GWG. Women often choose non-pecuniary benefits over level of remuneration for more flexibility. Having the flexibility to work part-time to spend more time with children can sometimes explain their choice of low-paying sectors (Blau and Kahn 2017; Sorensen 1990; Reilly and Wirjanto 1999; Bayard et al. 2003; Jurajda and Harmgart 2007; Triventi 2013; Matuszewska-Janica 2014). According to Fields and Wolff (1995), around 33% of the earnings differential is explained by the cumulative effects of sectors where men and women operate.

Another factor to consider is discrimination, which accounts for the part of the GWG that cannot be explained by the observed characteristics or prices. It manifests itself in many different ways, such as lower remuneration or unwillingness to hire certain groups of workforce, or discrimination in terms of professional and educational development (Becker 1957). Depending on the country and prevailing cultural norms, it can be more or less important in driving the level of the GWG (Albrecht et al. 2004; Cudeville and Gurbuzer 2007; Livanos and Pouliakas 2012; Christofides et al. 2010; Magnani and Zhu 2012; Śliwicki and Ryczkowski 2014).

Furthermore, Goldin (2014) noted that the market itself can be blamed for the persisting GWG. The way jobs and remuneration are structured to enhance temporal flexibility is important. The author maintained that the GWG could be considerably reduced, and even eradicated, if firms did not disproportionately reward individuals working long and atypical hours. Driven by competition in many sectors, such as technology, science, and health, there are incentives for working long and atypical hours, which denies women the most lucrative jobs. It can be said that the shift to a market economy changed the nature of labor relations, and more space has been created for such practices, further widening the GWG.

The studies on FSU countries highlight a GWG of around 20–45% depending on the country, mostly due to the differences in rewards, or the unexplained component, despite the fact that female personal characteristics often outweigh male ones (Oshchepkov 2006; Ganguli and Terrell 2006; Khitarishvilli 2009). The level of the GWG varies across countries and between deciles of income distribution within countries. Much depends on the role that different institutions play and the country’s social context. For example, Kazakhstan, Ukraine, Kyrgyz Republic, and Uzbekistan report the maximum GWG at the top end of wage distribution (Ganguli and Terrell 2005, 2006; Newell and Reilly 2001; Pignatti 2012; Anderson et al. 2015). The Russian Federation and Tajikistan, on the other hand, are characterized by the highest GWG in the middle of wage distribution (Paci and Reilly 2004; Atencio and Posadas 2015). For Belarus (Pastore and Verashchagina 2011), the glass ceiling effect was reported for the earlier years of transition, but from the mid-2000s onward, it was less evident.

While the majority of FSU countries managed to narrow the GWG during the transformation period, mainly by reducing the unexplained component (Khitarishvilli 2018), the few available studies on Belarus reveal quite the opposite pattern. Pastore and Verashchagina were the first to look into the reasons behind the existing GWG using the BHSIE data for 1996, 2001, and 2006 (2005, 2011). The results showed a steady increase in the GWG; the authors suggested that differences in rewards and personal characteristics were the main reasons for it—women tend to move to low-paying sectors as well as concentrate on the state sector of the economy instead of looking for jobs in the private sector; such choices result in substantial differences in the remuneration rates of women and men. Similar findings were obtained by Akulava (2016) on the basis of the 2005–2014 BHSIE data.

The recent study by Akulava and Mazol (2018) looked at the developments in the GWG in Belarus using the 2017 GGS data (UNFPA Generations and Gender Survey). The authors suggested that the glass ceiling effect is prevalent in the state sector of the economy, but there is no evidence of it in the private sector. The reason for this could be that highly qualified female workers have started moving to the private sector. Personal characteristics of women employed in top jobs in the private sector are, in fact, substantially higher than that of their male colleagues, allowing the GWG to narrow; the situation in the state sector, however, is just the opposite. Higher level competition under which private companies have to operate force them to look for a qualified labor force irrespective of gender, while the state segment does not provide enough incentives for the professional growth of female employees. These findings are in line with the hypothesis that competition drives out discrimination (Becker 1957).

3 The Developments in the GWG in Belarus

Belarus stands out among the FSU countries in that its macroeconomic and financial sector reforms have been limited, and its labor market preserves the heritage of the Soviet past with state dominance (ETF 2018). Adherence to the full employment policy is behind low mobility, lack of motivation in the search for a new workplace or occupation, as well as low unemployment level.

Belarusian women are actively involved in the labor market notwithstanding the fact that the GWG has more than doubled over the last three decades. Evidence of this comes from two independent studies, overlapping in part, by Pastore and Verashchagina (2011), and Akulava (2016). The trend began back in the mid-1990s, when the GWG was 8%. Since then, it has increased to almost 30% (the estimate refers to 2016, which is the last year for which data is available).Footnote 2

Figure 7.1 demonstrates the unconditional and adjusted GWG using the 2001–2016 BHSIE data. Two measures of logged wages are used for the analysis: net total monthly wage from the main job, and total monthly wage that includes additional payments related to the main job. The unconditional GWG is obtained by regressing wages on gender only. The conditional GWG is obtained from the Mincerian earnings equations while controlling for other factors (educational accomplishments, work experience, marital status, and region). The evidence shows that the GWG widened all through the period (from 26.7% in 2006 to 31% in 2016) (Panel A). If only full-time employees working all 12 months of the year are considered, to exclude the effect of seasonal labor (Panel B), the level of the GWG is slightly different but nevertheless growing upward, from 27% in 2006 to 32.6% in 2016.

Fig. 7.1
figure 1

(Source Authors’ calculations using BHSIE 2001–2016 *This graph is an update for Akulava [2016], who stopped at year 2014)

The unconditional and adjusted GWG over time (2001–2016)

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The results of the decomposition analysis suggest that the GWG in Belarus is mainly due to the differences in economic returns. The presence of educated women in the labor force tends to reduce the size of the average GWG, with educational accomplishments lowering the total GWG in 2016 by around 11.7% and work experience lowering it by 5.5%.Footnote 3 Controlling for personal characteristics and allowing for equal rewards between men and women could result in higher wages for female workers, especially in the private sector. However, there is not much scope for improvement as educational background, together with work experience, remains practically the only competitive advantage for women in the Belarusian labor market. Other factors do not show any explicit influence, partly because they are becoming increasingly unavailable for analysis due to restrictions imposed by the Ministry of Statistics on data released. In particular, the information on sector and occupation choices is lacking, which is a big limitation of this research.

The size of the GWG is likely a result of crowding women out of the most lucrative sectors of the economy and their consequent concentration in low-paying jobs, thus providing fewer opportunities for professional growth. The example of a rapidly growing IT sector in Belarus, paying by far the highest wages (Fig. 7A.1 in the Appendix), is revealing in this respect. If anything, women there are at the bottom of the occupational ladder, with only one out of 10 team or tech leaders being female. Furthermore, the GWG widens with professional experience, reaching about 1,000 USD for workers who have stayed more than seven years in the sector. The average GWG specific to the IT sector was more than 40% in 2017, which is the highest sector-wise (Belstat 2018a).

Fig. 7A.1
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Source Belstat [2019c]

Average wages by sector of economy, Belarus, 2018 (BYN) (*http://www.belstat.gov.by/en/ofitsialnaya-statistika/social-sector/trud/godovye-dannye/nominal-gross-average-monthly-earnings-in-the-republic-of-belarus-since-2016/)

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A closer look at the average wage distribution in the country reveals that the GWG is the widest at the bottom and top of wage distribution, suggesting the presence of the glass ceiling effect in the Belarusian labor market. Moreover, the growing trend touches mainly upon workers found at the two extremes. At the fifth percentile, the GWG rose from 2% in 2006 to 11.5% in 2016, and at the 95th percentile, from 23.4% in 2006 to 35.7% in 2016. Those positioned in the middle experienced a relative improvement, with the GWG for the 50th percentile narrowing from 31.1% in 2006 to 24.5% in 2016. While the glass ceiling did not seem to be in place during the mid-2000s, it is becoming more real in recent years (2016). The largest increase in the GWG has been observed recently in the lowest deciles of wage distribution.

If one looks at the full-time employees working throughout the year (excluding the effect of seasonality), the widening GWG is less obvious (see Panel B in Fig. 7.1). However, the level of the GWG for them was already high at the beginning of the 2000s.

One of the reasons behind a sharp increase in the GWG around 2010, captured by both panels A and B in Fig. 7.1, could be the boom in the construction sector that year—this sector has been playing a significant role in the economy for quite some time now due to the implementation of the State Program on Housing Improvement.Footnote 4 In the 2000s, it showed a permanent growth, contributing 9.4% to the GDP in 2010. At the same time, it was known to be the most male-dominated sector in the economy (Belstat 2018b). In 2010, it comprised around 8.8% of the whole labor force, and the same year, its employment reached a maximum of almost 413,000 employees. The level of average salaries paid in this sector, not only in the capital city but also throughout the country, was much higher than the country’s averages, by 43.5 and 23% respectively, in 2010. These differences almost disappeared over the next few years following the financial crisis that hit Belarus in 2011. The economic downturn, accompanied by the shrinkage of internal demand and consequent devaluation of the Belarusian Ruble, altered the picture substantially and resulted in serious changes within the sector and Belarusian economy at large.Footnote 5 Nevertheless, salaries in the female-dominated budget sphere—that is healthcare, education, and social services—were indexed and remained stable, as opposed to the rest of the economy. Similar outcomes were observed throughout Europe, with some female-dominated occupations showing more resilience to the economic crisis (Bettio et al. 2013).

In the aftermath of the financial crisis, the Belarusian economy experienced a series of perturbations—the 2014 oil crisis accompanied by various western economic sanctions imposed on Russia due to its military actions in Ukraine had a substantial impact on it. The low level of Belarusian market diversification, its dependence on Russian markets, and lack of reforms led to a severe economic crisis. As a result, according to Urban (2016), around 60% of SMEs (small and mid-size enterprises) reported a substantial deterioration in their 2015 economic performance compared with 2014. Decreased demand for goods and services, interenterprise arrears and non-payments, and shrinkage of financial resources were the three main problems requiring solutions. Labor cost-saving as one of the potential measures for short-term improvement of the financial situation was implemented by around 50.5% SMEs (Urban 2016). A tight macroeconomic policy, demographic factors, labor hoarding, and wage cuts accompanied by an inflow of labor migrants and refugees from Ukraine led to changes in the labor market.Footnote 6 The labor supply outreached the demand for labor force, whereas the highly educated and experienced technical and IT specialists were the only group for which demand remained at the pre-crisis level.

Such high-skill and high-paying professions in Belarus have supported the high demand for education. The available estimates of returns to education in Belarus suggest that they might be high enough by international standards as well (Pastore and Verashchagina 2006). Not surprisingly, the idea prevails that the main route to a decently paying job, at the very least, is by obtaining a degree. In this respect, it is important to understand the differences between men and women vis-à-vis entry into the labor market.

4 Education

Belarus is among the world leaders in terms of access to education. Primary and secondary education is compulsory for both genders with the total enrollment being around 100%. The gender parity index (GPI) of the gross enrollment ratio for primary education is 1, indicating parity between the two genders (World Bank 2017Footnote 7). The GPI of enrollment to secondary and tertiary education is 0.98 and 1.33 respectively. The latter shows disparity in favor of women in the case of tertiary education, with substantially more women enrolled in universities than men; men are more likely to choose vocational-technical education (67.6% in the 2017–2018 academic year).

In other words, women aim high, with 36.7% of female workers in Belarus having a bachelor’s degree or higher. In contrast, 26.1% of working men have the same level of qualification (Belstat 2018a).Footnote 8 At the same time, there are significant differences in the major specializations by gender (Fig. 7A.2 in the Appendix). Women are choosing more humanitarian and socially oriented specialties, whereas men are more inclined toward technical ones. This reflects the existing practices of hiring workers, with the list of occupations prohibited for women due to harmful or dangerous working conditionsFootnote 9 comprising 181 as of 2013. This naturally narrows down women’s choices with respect to their potential future career path.Footnote 10

Fig. 7A.2
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(Source Belstat [2018a])

Graduates from higher education institutions in Belarus, by major, 2017

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5 Employment

The structure of the Belarusian labor market has changed slightly over the last few decades—21% are employed in the public sector, including healthcare, education, and government officials. The overall share of the state sector has been decreasing in recent times, from 39 down to 30% in 2018 (own estimations on Belstat 2019b). The role of the private sector, on the other hand, is growing, with around 43% of the labor force employed by private companies.Footnote 11

One important change, which has made the Belarusian labor market quite peculiar since, occurred at the end of the 1990s—Presidential Decree Number 29 of 1999Footnote 12 allowed the use of short-term contracts. This gave an employer the right to hire workers for one to five years only. By 2003–2004, the majority of paid employees were already working on fixed-term contracts.

One of the potential reasons for such changes was the authorities’ desire to keep control over the employed population and increase their level of political loyalty. The reform considerably restricted the role of trade unions, and the national campaign against short-term contracts launched by independent trade unions did not get much support from the population. The risk of unemployment, especially in regions with limited employment opportunities, precluded workers from showing any disagreement with the changes (Haiduk and Chubrik 2009).

Fixed-term contracts make employees dependent on their employers, and vulnerable in terms of job protection rights. According to the estimations of the Federation of Trade Unions, around 30% of short-term contracts are signed for a minimum of one-year period. Moreover, in 2018, out of the 260,000 officially unemployed people, around 20% lost their jobs due to their refusal to renew employment contracts without redundancy payment, while the number of officially dismissed was 13.8%.Footnote 13

In the mid-1990s, women made up around 55% of the workforce; this number went down to 50.5% in 2017. In contrast, the labor force participation rate of women (aged 15–64) was 65.2% in 1995 and rose to 74.7% in 2018 (ILOSTAT). The same for men was 74.4% in 1995 and 80.4% in 2018Footnote 14 (Fig. 7A.3 in the Appendix).

Fig. 7A.3
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(Source ILOSTAT)

Labor force participation rates by gender and age in Belarus, 1990–2018

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The gendered structure of different sectors largely follows the trends observed in education. Women are mostly placed in the low-paying sectors related to the social and budget sphere (healthcare and social services, education), while men dominate in construction, transport, and manufacturing (Table 7.1). The majority of male employees are blue-collar workers (68.3%), while 12.2% are managers and executives; the majority of women, on the other hand, occupy white-collar jobs (56.5%), and among them 9.7% are in managerial positions. Overall, in 2017, 49% managerial positions were held by women.

Table 7.1 Percentage of female workers, by sectors of economy
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The IT sector is considered to be one of the fastest growing ones in the economy. The share of ICT in the GDP in 2017 was 5.7%, while in 2009, it was only 2.3%. The share of ICT in employment is 2.2% (CEE Software Development Report, 2019). In 2018, ICT was third in terms of the number of vacancies, with a share of 11%. In the sector, developers are the most in number (51%), followed by QAs (13.2%), project leaders (11.4%), team leaders (5.5%), and analysts (4.5%). Women make up around 45% of the sector’s workforce, according to official statistics. However, they are mainly employed in various non-technical roles—according to the Ernst and Young (2017) report, women are mostly hired as HR personnel/recruiters (96%), technical writers (67%), and sales or marketing staff (55%), while men are in various technical or managerial positions, such as developers (90%), project managers (83%), team leaders (90%), and QAs (64%). The sector’s GWG depends on the level of professional experience, and reaches its maximum of 26.6% in the case of employees with a three- to five-year service period.

More active involvement of women in technological roles should be an additional factor positively impacting the sector’s growth. In that context, popularization of STEM (science, technology, engineering, and mathematics) education among women should ease their entry into the sector and have a long-term positive effect on its sustainability.

The gender differences observed in the field of education and the public sector largely explain the distribution of men and women across the different centiles of wage distribution (Table 7.2). In this respect, Belarus follows the global trend (ILO 2019) in that, while moving from the lowest income deciles to the top, the percentage of women declines substantially. In Belarus, women made up around 62% of all waged employees in the first income decile, with their number in the 10th decile being less by half (31.2%) in the latest year considered. This distribution has actually been quite stable over time, according to the BHSIE data.

Table 7.2 Share of men and women along the monthly wage distribution, 2001–2016
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The profile of female workers is quite distinct—highly educated but underpaid (sometimes also classified as the “working poor”). This has been, and remains, the main motive for women to emigrate in search for better jobs. In fact, they represent the majority among emigrants—60%. EU countries like Poland, Spain, or Italy, with a number of work opportunities in the informal sector, are the main destinations with respect to female migration (MPC 2013).

6 Migration

Natural population decline is considered a substantial threat to the demographic security of Belarus (Shakhotska 2007). Between 1996 and 2016, Belarus’ population declined by almost 600,000 people—from 10.045 million to 9.445 million (World Population Prospects 2019); therefore, growth of population has been, and remains, among the country’s top policy priorities. The goal, set by President Lukashenko, is to have a population of around 15 million people. By the end of 2018, Belarus’ population had reached 9.52 million.Footnote 15

There are two potential ways to ascertain population growth: migration inflow and increase in fertility rate. According to official statistics, over the last two decades, Belarus has observed net positive migration balance, which is mostly made up of migrants from the Commonwealth of Independent States member countries, especially Russia and Ukraine (Fig. 7A.4 in the Appendix). In fact, there was a steady growth in net migration 2005 onward; the inflow reached its peak between 2014 and 2015.Footnote 16 However, the economic stagnation and recession that followed negatively impacted the country’s appeal and slowed down migration.

Fig. 7A.4
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(Source http://dataportal.belstat.gov.by)

Net migration flows in Belarus

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Russia accounts for the main share of the overall flow as well as the labor emigration flow. This is not surprising considering the common border, language, and possibility of securing a work permit without going through various bureaucratic procedures. Overall emigration to western countries (EU, USA) is around 9% of the total emigration flow, while the labor emigration flow to the EU and Poland, in particular, has grown substantially since 2016. In 2017, almost 28% of labor migrants went to Poland.Footnote 17

It should be mentioned that the profile of emigrants and immigrants is different. According to the report by the Migration Policy Center (2013), the majority of emigrants to Europe are women with secondary and tertiary education (34 and 40% respectively). In contrast, the migration flow to Russia is mostly made up by men (around 90%) with secondary education; they are concentrated in the transport and construction sectors (Chubrik and Kazlou 2013). The immigration flow is gender neutral and mostly comprises workers with low and medium level of education (28 and 56% respectively) working in construction, agriculture, or trade sectors of the economy. Taking into account the outflow of the highly qualified and educated labor force abroad, measures to improve Belarus’ appeal as a place to work and live should be addressed to prevent the brain drain. On top of that, many who stay often get stuck in low-paying jobs, which affects family planning and reproduction.

7 Family Policy

After the collapse of the USSR, Belarus faced a severe drop in total fertility rate (TFR)—from 1.91 in 1990 to 1.23 in 2003. Thus, raising the rate became a major issue on the existing family policy’s agenda.Footnote 18,Footnote 19

In general, Belarus can be classified as a country with a pro-natalist model of family policy with mostly financial measures implemented to boost fertility (Frejka and Gietel-Basten 2016). Measures of support include a wide range of birth and child allowances (Table 7.3).

Table 7.3 Measures of pro-natal support
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Since 2015, Belarus has run a family capital program that aims at boosting the number of families with three or more children—they are allowed to receive financial support, the current amount of which equals around 10,000 USD. This is granted after the birth of the third child, and only in cases where there are two or more children aged under 18 in the family.

The current paid parental leave period in Belarus is three years and is the longest in the region (barring Ukraine’s). At the same time, employers are obliged to keep women’s positions vacant until they resume work in a role similar to what they had before going on maternity leave. As a result, most women take that opportunity and stay at home with their children until they reach the age of three. However, this is partly due to the underdeveloped daycare infrastructure for such children. According to official statistics, the current childcare capacities can admit just 39.6% of children aged under three (Belstat 2019a). Staying out of the labor market for at least three years, or even more, reduces women’s human capital and diminishes their professional qualifications (Dechter 2014). At the same time, there are no programs in place to help women adapt and return to work after a break. The absence of such a mechanism, together with the traditional division of social roles (taking care of children and using sick leave are still considered as mostly female responsibilities), might also lead to a motherhood penalty in the labor market (Akulava 2016). The available data does not allow explicit identification of whether the respondent is a parent or lives with children of other household members. Still, the 2016 BHSIE data showed that full-time (i.e. not seasonal) employed women aged 25–50Footnote 20 who have children receive around 6% less compared with women without any declared children. The motherhood penalty is substantially higher at 16.2% in the case of women employed for less than 12 months.Footnote 21

Furthermore, one should not overlook the effect of education. Mothers with tertiary education or a technical background are more penalized compared with their childless counterparts. The presence of children reduces the wages of full-time employed women with a university or higher degree by around 20%, with a technical or vocational education by 13%, and with a secondary education or lower by almost 8% (Akulava 2016). This is in line with the hypothesis introduced by Anderson et al. (2002), who claimed that the higher the educational accomplishment, the higher the costs of staying out of work.

The state has been trying to compensate for this by introducing a range of financial measures for mothers (see Table 7.3 above). This has produced some positive effects, which translated into a slight increase in the TFR, reaching 1.54 in 2017; however, this was only observed in rural areas where the current average salary is below the level of the provided support (3.1 TFR in rural areas vs. 1.34 in urban) (Fig. 7A.5 in the Appendix). Absence of a sustainable source of living and decent salary in the rural zone acts as an additional trigger for women to have children to be able to receive financial support. In the short run, this allows maintaining a sustainable level of living, but in the long run, it increases the risk of falling into the poverty trap for families (Chubrik et al. 2018). This might also occur due to deterioration in the quality of female human capital during their period of absence from the labor market, which substantially lowers their competitiveness at the moment of reentry.

8 Conclusions and Policy Recommendations

Despite the fact that educational accomplishments and professional experiences of working women in Belarus are similar to those of their male counterparts, the former’s wages are substantially lower than the latter’s. Moreover, there have been no signs of improvement in the pay conditions for wage-employed women in the last 20 years (1996–2016). The overall GWG has been relatively stable since the beginning of the 2000s, after peaking at almost 30%, from as low as 8% in the mid-1990s, when the transition to market economy had just started.

Despite Belarusian authorities’ declared adherence to gender equality, the reality is far from expectations. Substantial vertical and horizontal segregation of women limits their possibilities in the labor market and prevents them from improving their living standards both for themselves and their families. This has been recognized as a global problem (ILO 2019), driven by the fact that women are less likely to choose technological subjects as their major. Admittedly, the STEM subjects are providing better professional opportunities with higher remuneration compared with the traditional female-dominated professions. Thus, more active development of STEM programs for girls and young women might be beneficial for reducing the GWG and diversifying professional pathways for women. In this regard, careful reconsideration of occupations forbidden to women might also be called for as such restrictions often reduce professional opportunities for women and strengthen existing stereotypes. At the same time, measures to involve more men in female-dominated sectors could have a counterbalancing effect, leading to further equalization in the labor market. This should not only spread to the professional environment but also in the family context.

The existing family policies mainly target women who have traditionally been the main caregivers, be it for children or elderly members of the family. These measures include financial support for mothers, which often translates into lower labor market involvement on their part. This is a short-sighted view, as growth in fertility rate should not be achieved by sacrificing female employment and, as a result, supporting the persistent GWG.

The acceptable level of allowances for children is often above the average wage level in the area, and basically pushes less-qualified women toward having multiple children. In the short run, it allows families to maintain a sustainable standard of living; however, in the long run, it has a severe negative effect on the quality of female professional development, and makes women more vulnerable by increasing their risk of being forced into poverty, besides widening the GWG.

This also happens due to the continuing traditional division of social roles in society. Household chores and taking care of children are still considered as mostly female responsibilities, resulting in the so-called “double burden” for women. According to current statistics (Belstat 2018a), Belarus’ women spend around two hours more per day on various types of housework. In this regard, certain policies and reforms aimed at transforming the existing perception of gender roles could lead to a more equal division of domestic responsibilities. This would be beneficial for women and increase the level of their labor market attachment.

Promotion of more equal parental leave and division of care responsibilities, too, will ease women’s return to work after maternity leave, improve employer’s attitude toward women of childbearing age, and raise female career prospects. Together with the development of childcare facilities and daycare services, it has the potential to become an effective measure for decreasing the level of motherhood penaltyFootnote 22 and the GWG in general in the economy.