Gender economic studies and global gender indexes are primarily focused on labor market inequalities and particularly gender wage gaps (Kalabikhina and Rebrey, 2022b). Comparing female and male activity, efficiency, education, experience, and personal qualities, studies conclude that the level of gender inequality is determined by gender stereotypes (Berniell et al., 2021; Morsy, 2020; Nikolaev et al., 2018; Sauliak, 2010). And from where do gender stereotypes arise? The prime institution that forms the perception of gender roles is family. Whereas orthodox economic analysis treats a family as a solid unit that does not have any internal conflict, gender economic studies apply bargaining theory to prove that bargaining power is an important element in gender allocation of power and resources in a family (Gammage et al., 2016). That is why the introduction of time-use surveys in the 1995 by Beijing Declaration and Platform of Action advanced gender economic studies greatly. Gender time use allocation depends on and epitomizes the gender norms and stereotypes in given society and provides an explanation for conditions in which women participate in paid labor. The more women are solely responsible for unpaid labor, and the less time they have on paid labor, the less valuable they are for an employer, who sees them as additional workers as paid labor is an additional responsibility for them. Hence countries with the greatest gender gap in time allocation on unpaid labor (like Pakistan, Albania, or Japan) also have the greatest gender wage gap (Appendix Fig. A1).

Moreover, family is a primary locus of socialization that forms the attitude towards gender roles inside and outside the family institution. Families with a strong division between female unpaid and male paid labor usually reproduce traditional gender norms and stereotypes. They tend to teach girls to assist in domestic chores and care, to be submissive and prioritize other’s opinions by teaching boys that their contribution to the wellbeing of the household excludes domestic chores and care because it is a “female duty.”

Despite its high efficiency in revealing gender norms and stereotypes, this indicator is crucially underappreciated and underexploited as it is not included in gender indexes. However, numerous studies prove its essential role in gender equality and birth rate growth (Da Rocha and Fuster, 2006; Lacalle-Calderon et al., 2017; Myrskylä et al., 2011; Ogawa et al., 2020; Zhou and Kan, 2019).

The labor market is the next institution that contributes to gender inequality by imbalanced allocation of finances and other resources that results in the feminization of poverty and women’s economic and financial vulnerability and dependence. In order to measure the constraints that create horizontal and vertical gender segregation, it is important to compare the share of women and men who participate in paid labor and their respective wages in general and per economic activity and occupational group. The first indicator is the labor force participation rate (LFPR) that shows what share of women/men of working age are engaged in paid labor. Further, the female LPFR and the gender wage gap in different occupational groups and economic activities are analyzed. Usually, the most feminized industries have the lowest level of wages and the lowest gender wage gap and the other way around.

Concerning agency, the participation in labor markets not only creates income that determines the level of one’s life and opportunities, but also identifies the value of one’s labor that is crucial for self-esteem.

Data on Russia’s labor force (Statistical report “Women and men of Russia”) is published by Rosstat from 1997. It defines the gender wage gap as the ratio of the average nominal wage of women to men extracted from a sample survey­ of organizations in Russia. It provides more detailed data by categorizing the average­ wage into occupational groups (ISCO‑08), types of economic activities, age groups, and level of education. It also contains the average hourly wage, excluding one-time payments, and the duration of hours spent on work. It provides comprehensive gender data on labor force participation rate and other parts of the population (students, elderly, housewives/husbands, and others), including employees’ satisfaction level when seen through the criteria of their wage, stability­, workload, working hours, condition of labor, etc.; participation in informal economy per age and many other factors.

Studies on gender wage gap in Russia mostly use aforementioned data (Eliseeva and Dekina, 2019; Konstantinova and Kudaeva, 2019; Migranova, 2018; Nikolaev et al., 2018) or “Labor and employment on Russia” statistical ­report prepared by Rosstat, that also have some data, disaggregated by gender (Sauliak, 2010). Another source, popular among researchers is the Russia Longitudinal Monitoring Survey — Higher School of Economics (Epikhina et al., 2021). However, this survey closed sections on attitudes towards women’s rights and gender inequality. Another non-governmental survey, which is particularly popular among feminist researchers, is the so-called Project Taganrog, that was conducted by the famous Soviet and Russian feminist economist Natalya Rimashevskaya for 50 years from 1967 (Kalabikhina and Rebrey, 2022a; Migranova, 2018; Rimashevskaya, 2013).

Education continues to form our identity and broadcast gender norms and stereotypes, and science is the institution that determines and provides basic principles for gender norms and stereotypes.

All the gender indexes measure gender inequality in education only through gender enrollment gaps of different levels (primary, secondary, and tertiary education) and do not measure gender inequality in science. Numerous studies show that the reversed gender gap in education on every level has become the norm in most countries of the world (Bossavie and Kanninen, 2018). However, it neither improves gender wage gap, nor balances gender time allocation. This is because education and science reproduce gender norms and stereotypes. If women are more educated than men, but still earn less, access to education does not eliminate gender inequalities within educational institutions. An educational institution not only educates children, but it also socializes them and shapes their agencies. Thus, depending on gender inequality within the educational system and educational programs particularly, education affects women and men differently. Whereas men are taught their greatness, women are taught their invisibility.

To identify gender stereotypes within the curriculum, an analysis of the gender expertise of textbooks and programs is required. This analysis of Russian textbooks affirms that the curriculum does not have enough positive female examples. In addition to the curriculum, there is a so-called hidden curriculum: the organization of the school or university itself, gender relations at work, gender stratification of the teaching staff; the content of the subjects; the style of teaching. These three dimensions of the hidden curriculum not only reflect gender stereotypes, but also support gender inequality by favoring the masculine and dominant and underestimating the feminine and atypical (Ryabova, 2005; Voronina, 2005; Yarskaya-Smirnova, 2000).

Quantitative methods have also proved its efficiency in examining the gendered results of education through the gender gap in PISA⁵ score in reading, math and science (Appendix Fig. A2). Whereas girls show better results in reading in every country of the world, higher scores in math and science are shown only in countries with a high level of gender equality, because the girls there were not taught their incapability in STEM. Another sign of gender stereotypes within the educational system is the division of female and male fields of studies, where 70–80% of humanities’ students are girls and 70–80% students in STEM are boys. That’s why gender gap in PISA results (in math and science particularly) and the share of female students in STEM are representative indicators for gender inequality within education.

Science is the core institution that creates the theoretical basis of socio-economic policy, produces, and reproduces gender norms and stereotypes. The process of knowledge creation is itself a gendered process because knowledge is created within a social hierarchical framework (May, 2008a). That is why the share of women in science is not enough to assess the gender inequality in science and to be supplemented by the share of women in science in decision-making positions. The development of gender studies and the implementation of gender studies research in curriculum is another essential sign of egalitarian and inclusive science.

The gender diversity in governance is crucial for its effectiveness both in state and corporate sectors because of its importance for the representation of different individual preferences, needs, and backgrounds (Adams and Ferreira, 2009; Hoogendoorn et al., 2013), and for team performance (Bear and Woolley, 2011; Hoogendoorn et al., 2013). The extent of representation of women matters particularly. A group reaching a critical mass of 20% to 40% of women will outperform either all-male groups or those with a smaller representation of women (Kanter, 2008). That is why many countries (Norway, France, Italy, Germany, etc.) have introduced 30–40% gender quotas (Seierstad et al., 2017). A simple and illustrative indicator is the share of women in corporate boards and the share of women in state governance (ministers, members of parliament).

Women in governance provide positive examples that inspire other women and girls and represent female interests in policy making, creating better conditions for female agency to thrive.

Axial institutions, respective indicators and the sources are presented in Table 1.

After understanding how axial institutions shape women’s agency, the research proceeds with examination of agency and addresses how agency functions within those institutions, providing a better understanding of causes and impacts. There are different ways of measuring agency. It is viewed as bargaining power and measured as the capability to make independent decisions at a personal level, in the household and in the community (Ibrahim and Alkire, 2007; Samman and Santos, 2009). Along with specifically developed surveys, limited by the scope and the longevity, databases such as Demographic Health Survey (DHS) are used. However, DHS does not include developed economies, or Russia. Neither does it include data on men and on employment, thus limiting research options (Hanmer and Klugman, 2016), particularly for Russia (Rebrey, 2022).

Another method to assess agency is Rotter’s locus of control (Rotter, 1954) that divides people into those who are inclined to explain what is happening by external factors or their own behavior (Abbas, 2016). An economic locus of control­ assesses the extent to which an agent associates his economic well-being with internal or external factors (Furnham, 1986). Earlier studies show that Russian women have weaker agencies as they “are more likely to exhibit an external locus of control and need for affiliation,” whereas “men are more likely to exhibit an internal locus of control and a need for challenge” (Semykina and Linz, 2007). However, that division of external and internal locus of control does not show what determines it.

The World Value Survey presents a valuable source of data to analyze agency as it includes a question about self-assessed level of freedom and control over one’s life, which is used as a proxy to measure one’s agency and factors that determine it (Rebrey, 2022). Factors are categorized per capitals (financial, human, social and emotional), domain (family and work) and attitude towards women’s rights and capabilities, and violence, are presented in Table 2.

According to the time survey, conducted by Rosstat in 2019, the gender gap in time allocated on unpaid labor (domestic chores and childcare) is 183%. Therefore, the gender gap is reversed in time allocated on paid labor, education, sport, and leisure (Fig. 1).

Fig. 1.

Gender gap in time allocation on paid and unpaid labor, education, leisure, culture and sport in Russia, 2019 (female/male, %).

Source: Rosstat. Selective observation of the use of the daily fund of time by the population in 2019. https:// gks.ru/free_doc/new_site/population/urov/sut_fond19/index.html (in Russian).

According to UNSD, the gender gap in time spent on unpaid labor in Russia is slightly bigger — 228% (Appendix Fig. A1), but Russia still has the same result as Central Europe — the first region among emerging economies (after North America, Western Europe and Oceania) ranked by the indicator.

Studies show that for women cultural factors prevail over economic ones in time allocation on paid and unpaid labor (Kalabikhina and Shaikenova, 2018) even during crisis (such as Covid, economic crisis and isolation regime), but for men economic factors determine their participation in domestic chores and childcare (Kalabikhina and Rebrey, 2020). In other words, the time that women spend on domestic chores and childcare does not change drastically for working women. Working women tend to compensate for the lack of time spent on domestic chores and childcare on evenings and weekends, creating the double burden effect.

Women account for almost half of the labor force (48,7%). 70% of women of working age are engaged in paid labor, which is a very high proportion by international comparison (Fig. 2). Women’s active participation in the labor force is a legacy from the Soviet economic system, where everyone, irrespective of gender, was building communism. Actually, early stages of industrialization widely exploited the female labor force in most countries and the USSR was no exception. The difference is in the type of industrialization. Market economies began to industrialize with light industries, such as textile or tobacco, where the female labor force is preferred due to its lower price, the lack of a need for a qualification, and the ability to do patient monotonous manual work. Soviets embarked on developing heavy industries (as industrialization of light industries happened in Russian Empire), that are widely perceived as a male area. But in the USSR, it was not. However, in modern Russia only 11% of the female labor force is employed in manufacturing (versus 17,3% of male labor force). Engineering — the most popular profession for both women and men in the USSR — is now perceived in Russia as a male domain.

Fig. 2.

Labor force participation rate, female as share of female population aged 15–64 in Russia, comparing to high, middle, low income economies, 1990–2019 (%).

Source: Author’s calculations based on ILOSTAT database (https://ilostat.ilo.org/data/).

The gender gap in LFPR in Russia is 78%, 6–7 p.p. less than in developed economies, except for Sub-Saharan Africa where a very high female LFPR is a result of low education and early entrance into labor force (Fig. 3).

Fig. 3.

Gender gap in labor force participation rate (female/male, %).

Source: Author’s calculations based on ILOSTAT database (https://ilostat.ilo.org/data/).

Women in Russia are mostly engaged in trade (19,7%), education (16%) and health (13%), whereas men work in manufacturing (16%), logistics (13,3%), and trade (11,7%). The highest paid economic activity — mining is predominantly male. The second highest paid economic activity for men is IT. It has the largest gender wage gap (31,3%) and is famous for its aggressive environment towards women. Despite the dynamic development of IT and remote work, female developers receive less remuneration, worse grades and lower ratings compared to men for similar projects (Vilkova, 2020).

Education is assumed to be a female area and has one of the lowest wages but also the smallest gender wage gap (4,8%). In the 19^th century, women’s emancipation in Russia and their engagement in the labor force led many to pursue a career in teaching. To become a governess, or a nanny, was one of the few viable options for a woman to earn money independently. Another female area is healthcare. The wage level and the gender wage gap are also quite low (11,7%). Women engaged in healthcare rather early — in the late 19^th century, which was very unusual in that era and surprised more emancipated Europeans. However, there is still a division on male and female specialization with men taking higher paid positions (like surgeons) and also in governance.

In terms of the gender structure of occupational groups (ISCO 08), Russia is a very egalitarian society with women accounting for the majority of professional (63%) and technical 59% workers. However, the structure of female participation in diverse economic activities shows that the majority of women among professional and technical workers are involved in economic activities with rather low wages (such as education and healthcare). Thus, this structure, despite its egalitarian appearance, does not provide equal wages. Another burning issue in Russian occupational group structure is that women account for the majority (82%) of administrative workers who are rapidly being substituted by AI.

The gender wage gap in Russia is 25–30%, increasing to 35–37% during an economic downturn and showing no downwards trend. The Taganrog project shows a higher gap — 33% (in 2014), versus Rosstat — 27,4% in 2015 (Migranova, 2018). According to ILO, the gender wage gap in Russia is 25,3% — average for emerging economies and rather high compared to Western Europe and the US. The gender estimated income gap is larger: according to WEF’s Global Gender Gap report it is 41,1%. However, compared to other countries the difference between the wage gap and the estimated income gap is not that impressive (Fig. 4). The gender mean potential wage gap calculated by Ogloblin and Brock (2005) is 42%. Studies name stereotypes and the lack of gender-oriented economic policy as factors that determine the gender wage gap (Konstantinova and Kudaeva, 2019; Migranova, 2018).

Fig. 4.

Gender wage gap (ILO) and gender estimated income gap (WEF) (%).

Source: ILOSTAT database (https://ilostat.ilo.org/data/) and WEF, (2021).

Women’s access to education and higher education was a long story of struggle during the XIX century. Full access to education was one of the pillars of the Soviet Union. The principles of education of the Soviet Union were formulated as early as 1903 in the Program of the Russian Social Democratic Labour Party (RSDLP), announced at the II Congress of the RSDLP: universal free compulsory education for children of both sexes up to 16 years; liquidation of class schools and restrictions in education on national grounds; separation of education from church; learning in the native language, the abolition of corporal punishment, etc. The late 1970s saw full literacy in the USSR.

Nowadays, in Russia there is a reverse education gender gap, which means that women are more educated than men. Female employees are also better educated, as 39% of employed women graduated higher school, whereas among employed men this share is only 29,7%. Girls in Russia show better scores in reading and in science (reverse gender gap is accordingly 5,4 and 0,2%), but math has a small gender gap — 1% (Appendix Fig. A2). Higher education has strict divisions on female humanitarian sciences and male technical sciences. The reverse gender gap in education for graduation in all fields in bachelor degrees in Russia is 17%, whereas in engineering manufacturing and construction the gender gap is 62%, which is high, but still lower than the OECD average (–67%).

Scientific establishments are core institutions because their academic discourse defies economic, social, and political agenda and content, including gender inequalities. Women in R&D in Russia account for 40%, according to OECD data, and 42%, according to Rosstat, which is a very high ratio by international comparison. Russian women got access to work in research and development in 1920s — early, compared to Western world. But their share was not higher than 30%. The share of women in Russian science has been gradually increasing since the collapse of the USSR, particularly in 1990s — early 2000 their share was more than 50%. The main reason was the brain drain — male scientists relocated abroad searching for higher wages and better living conditions (Pushkareva, 2010).

Despite the feminization of science, women are in the minority among professors, executives and academics of Russian Academy of Science. Women are frequently seen as pedagogical and administrative workers, not purveyors of new knowledge. Vertical segregation is explained by the double burden effect, particularly in dual-earner families, the gender-blind policy of universities, gender stereotypes in curriculum, conservative pedagogical practices, the lack of integration of gender and feminist research with mainstream academic discourse and curriculum, gender stereotypes among researchers, and the low share of female researchers and pedagogues in STEM (Pushkareva, 2010; Ryabova, 2005; Yarskaya-Smirnova, 2000).

Women in Russia represent almost half (45%) of legislators, senior officials and managers. However, data on executives include not only executives themselves, but also their deputies, which explains why this bears well for Russian statistics. Although women account for 74% of state employees, they account only for 13,3% of senior legislators and for 82% of deputies and counselors, according to Rosstat.

Corporate governance is perceived to be a male field; hence women account for just 12% of corporate boards (Muravyev, 2017). However, research shows that corporate board gender diversity matters for the performance of Russian companies. Companies with gender-diverse boards have higher market values and better profitability, particularly with at least three women directors (Garanina and Muravyev, 2021).

According to the World Values Survey, Russian women evaluate their freedom and control over their life as rather low — 6,4 out of 10, which places Russia the 8^th from bottom. Also striking is a large gender difference in that evaluation — 0,6, which places Russia in the 2^nd place together with Jordan and Egypt (see Appendix Table A1). The low self-evaluation of agency is not consistent with one of the highest level of education in the world and the largest share (51%) after Finland (53%) of women — main breadwinners in the household.

Logistic regression shows (see Appendix Table A2), that the most positive criteria on female agency in Russia values are the priority of work and friends in life, whether the husband is unemployed or part-time employed, and positive attitude towards women’s rights and gender equality (Rebrey, 2022). However, education has a very low positive impact on female agency, half that of males, contradicting other research, which claims that Russian women, particularly high-paid women, benefit more from education than men, due to higher intellectual capabilities (Eliseeva and Dekina, 2019). Not taking into account intellectual capabilities, higher paid women with high levels of education might have better prerequisites like higher educated and richer parents, higher social capital and connections. Education appears to be less beneficial for women as it preserves and reproduces patriarchal values which discriminate against women and their capabilities.