Research Article
Research Article
Gender inequality in Russia: Axial institutions and agency
expand article infoSofia M. Rebrey
‡ MGIMO-University, Moscow, Russia
Open Access


This research measures gender inequality in Russia in axial institutions: household and labor markets, education and science, state and corporate governance and relates it to agency, measured on the World Values Survey. Russian women are actively engaged in labor markets, including healthcare, science and other fields, which are widely viewed as male, as a legacy of the Soviet era. The gender income and the wage gap stem from the double burden and “maternity fee.” Demographic policy reinforces women’s role as prime caregivers, multiplies “maternity fee” and increases gender inequality, which consequently lowers the birth rate. Women are highly educated; however, education does not necessarily serve women’s career and success due to patriarchal values in the hidden curriculum. Many women are engaged in science, accounting for 43% of scientific workers, particularly in humanitarian sciences. However, the main reason is low wages. And ­science still functions within patriarchal traditions, while gender and women studies remain heterodox and have low impact on mainstream academic discussion. Governance remains a male field, while women account for deputies, and mostly languish in administrative­ jobs and are only entrusted with decision-making capabilities both in state and corporate governance.


gender inequality, Russian economy, gender wage gap, time-use.

JEL classification: J16, J22, O43.

1. Introduction

Gender inequality is one of the most complex challenges that humanity faces, and an essential part of sustainable economic development. Gender equality is not just one of the Sustainable Development Goals (SDGs) — it interlinks with most of them in all three dimensions (social, economic and ecological) and hence is the foundation for sustainable development (Rebrey, 2021).

Gender inequality impedes sustainable development in many different ways. Apart from abusing human rights, it decreases the quantity of the labor force and the quality of human capital through ineffective allocation of talents and feminization of poverty. This undermines not only women’s capabilities, but also children’s capabilities, as mothers are proven to be major investors in children’s health and education (May, 2008b). The double burden effect lowers women’s performance both at work and at home, which leads to lower quality of work and lower quality of care (Kalabikhina and Shaikenova, 2018; Nakamura et al., 2020). This adversely affects future generations. In the era of talentism, and amid the fourth industrial revolution, where countries compete in science and technology, the quality of human capital is crucial. Moreover, gender inequality negatively affects fertility (Da Rocha and Fuster, 2006; Lacalle-Calderon et al., 2017; Myrskylä et al., 2011; Ogawa et al., 2020; Zhou and Kan, 2019). Gender inequality facilitates other types of inequalities (racial, ageist). Intersectional inequalities form vulnerable groups in the population. Elderly women present one of the most vulnerable, poor, and fast-growing groups in aging societies. Inequality has ­deleterious economic consequences by depressing demand and supply, and by limiting the entrepreneurship capabilities of women and oppressing business diversity. Gender inequality in science and technology hinders development as it does not provide a healthy environ­ment for women and men to thrive. Gender socialization, and many obstacles on the “male path,” demotivate talented women from pursuing a career in STEM,1 resulting in an underutilization of women’s talents. Gender diverse teams are proved to be more efficient (Bear and Woolley, 2011; Hoogendoorn et al., 2013). The share of women in the team is particularly important: when it reaches a critical mass of 20% to 40%, the team outperforms either all-male groups or those with a smaller representation of women (Kanter, 2008).

Even though gender inequality is a well-known phenomenon and has become the focus of attention of economists and researchers in the middle of the last century, it is still not clear how to measure it. As inequalities are produced and reproduced by institutions, institutional analysis is one of the most effective tools to examine and measure inequalities.

The first institution that was scrutinized by gender economic studies is labor markets (Boserup, 2007). The gender wage gap, which is easy to calculate, proves demonstrably that gender inequality is persistent worldwide. However, further research showed that the reasons for gender inequality are not only attitudes towards women and stereotypes, but the gender imbalance in the allocation of domestic responsibilities (Kalabikhina and Shaikenova, 2018). A woman is widely viewed as a major caregiver, who bears most of the responsibilities of childcare and domestic chores. After introducing time use surveys and obtaining data concerning gender time-use allocation, the connection between gender wage gap and gender time allocation on paid and unpaid labor has become obvious. Thus, labor markets and households have become the focus of gender economic research. Other institutions or domains that are regarded as essential for measuring gender inequalities are education, health and, sometimes, governance. However, usually the studies are focused on one particular institution or even an indicator and examine it in detail.

Complex analysis is suggested by global gender indexes that produce global ­ratings of gender inequalities. Each index has a different composition of subindexes­ that cover key domains. Those domains are labor market (Global Gender Gap, GGG — economic opportunity subindex), household (SIGI2), education and health (GGG, SIGI, GEI3, GII4), state governance (GGG political empowerment subindex). These indexes provide valuable information concerning gender gaps (GGG) or inequalities in social institutions (SIGI). However, this approach presents­ a global glance that lacks in-depth analysis. It also omits the most important and impactful indicator — gender time allocation on unpaid labor. Another flaw is a shallow analysis of gender inequalities in education, which is measured only through the gender enrollment gap. However, the tertiary enrollment gender gap is reversed — the world average is 114%, which means that more women go to universities or colleges than men worldwide. But that does not result in a reversed gender wage gap, proving that access to education is not enough. That is why it is essential to examine educational institutions from within and address why education does not bring women equal remuneration.

Institutions are structures that form the social constraints, but who forms the institutions? Complimentary to institutional structure that expresses collective identity of agents is agency. Agency is the capacity of an agent to choose a goal, to choose tools to pursue it and, finally, reach it (Sen, 1985). Agency shows how different agents function in institutions, thus agency research proceeds from studying the environment to studying how the environment impacts people and their capacities, depending on what group they belong to (gender, race, age, etc.). Furthermore, the concept of agency expands the generally accepted method of measuring well-being, focused on income, by adding other aspects of human life, such as health, education (Ibrahim and Alkire, 2007; Kabeer, 2008; Samman and Santos, 2009; Sen, 1985), social capital (Ambrey et al., 2017; Puga and Soto, 2018), and psycho-emotional intelligence (Samman and Santos, 2009), etc.

Russia presents a particularly interesting case for gender analysis. The USSR pioneered gender equality in the early 20th century by granting women equal rights, including the right to vote, to access education, and to work. Moreover, the USSR was the first to introduce state facilities for childcare, unburdening women and promoting their participation in paid labor. Consequently, gender inclusive policy making almost doubled the labor force and accelerated industrialization.

The first woman in the Soviet government Alexandra Kollontai advocated for the introduction of free childcare facilities that would release women from the burden of childcare and domestic chores to become a part of the labor force. Thus, the USSR was the first country that tackled the problem of female unpaid labor at state level to spur economic growth and industrialization. However, the 1930s saw a backlash with I. Stalin reinforcing women’s role as mothers. Thus, in the Soviet era childcare was partly covered by state facilities, but women remained major caregivers.

Russia holds middle positions in global gender ratings, by combining the highest­ level of gender equality in labor markets, education and health and the lowest in governance (political empowerment). Why does the high level of female labor force participation rate and of female education not decrease the gender wage gap? Why does the reversed education gap not increase the number of women in decision making positions? The answers to these questions are important for gender studies as well as for Russian competitiveness on the world arena.

The geopolitical crisis, the division of the world into Western and non-Western spheres, and the sanctions imposed on Russia in 2022 create a more challenging environment for Russian economic development. Technological development sprouts from human capital and gender equality is essential to the quantity of population, the quality of the labor force, including future generations, the effectiveness of talent allocation, and the diversity of production, etc.

Present research suggests a new methodology of complex analysis of gender inequality in a country that is based on institutional and agency analysis. It aims to measure the level of gender inequality in Russia by studying its axial institutions (household and labor markets, education and science, corporate and state governance) and agencies. The objectives are to introduce the term axial institutions and explain why this composition of institutions and indicators present an effective tool to measure gender inequality in the economy, and to apply this methodology to Russia.

2. Methods

A. Sen’s capabilities approach presents a theoretical basis of following analysis. By incorporating agency into economic analysis, Sen argues that economists’ focus on income is too narrow and omits many human issues that can’t be purchased in the marketplace, such as health, relations, etc. (Sen, 1985). Axial institutions are viewed as an environment that forms agency. What institutions play an essential part in human life, form their identity and determine one’s capabilities, thus presenting the axis around which key dimensions of one’s life rotate? Axial institutions are household and labor markets, education and science, corporate and state governance. Agency and institutions are complementary structures. Thus, the axis presents the agency. If an agent benefits from all the axial institutions, their agency increases, bringing them more capabilities and power to change institutions in their favor and otherwise. An agent can have different agency in different institutions (Ibrahim and Alkire, 2007).

The main method of research is gender comparison. The key question is how to measure gender gap in every institution and in agency. Indicators should be representative and accessible. The accessibility requires the data on both genders and, preferably, international comparison. The representativeness means that the indicator catches the core factors of gender inequality. The choice of indicators is based on a rich body of gender economic research and gender data from various international organizations, such as the World Bank, International Labor Organization, Demographic and Social Statistics, United Nations, Russian national organizations such as Federal State Statistics Service (Rosstat), websites of State Duma, the Russian Academy of Sciences, etc. Further, critical literature review and comparative indicator analysis in each pair of axial institutions follows. The method of agency analysis is logistic regression, performed in Jupiter Notebook (Python), the data — World Values Survey (Haerpfer et al., 2022).

2.1. Household and labor market

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).

2.2. Education and science

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.

2.3. State and corporate governance

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.

Table 1

Indicators of gender inequality of Russian axial institutions.

Axial institution Indicator Source
Labor markets Gender wage gap per occupational group ILOSTAT database
Gender gap in labor force participation rate in general and per economic activity Women and men of Russia, Rosstat
Gender wage gap per economic activity Women and men of Russia, Rosstat
Family Gender time allocation on paid and unpaid labor, education, leisure, culture and sport Time use survey, Rosstat
Education Gender gap in math and science PISA (OECD, 2019)
Gender gap in enrollment in primary, secondary and higher education World Bank Open Data
Ratio of women and men in humanitarian and technical fields of higher education Women and men of Russia, Rosstat
Science Share of women among Doctors of Sciences and Candidates of Sciences Women and men of Russia, Rosstat
Share of women — researchers Women and men of Russia, Rosstat
State governance Share of women in parliament Website of the State Duma
Share of women — ministers Website of the Russian Government
Corporate governance Share of women on corporate boards Muravyev (2017)
Share of women among legislators, senior official and managers ILOSTAT database

2.4. Agency

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.

Table 2

Features of agency.

Category Indicator
Financial capital Income level, social class, income satisfaction
Human capital Level of education (including parents’ and spouse’s), level of health, age
Social capital The priority of friends in life, membership in various organizations, membership in any organization
Emotional capital Life satisfaction, happiness
Family Number of children, cohabitation with parents, marital status (married, divorced (including widowed), single), family priority in life, main breadwinner in the family
Work Employment type (permanent, temporary / self-employment, unemployed), priority of work in life
Attitude towards women’s rights Attitude towards women political or corporate leaders, abortion
Attitude towards violence Attitude towards domestic violence against women, attitude towards physical abuse of a child, attitude against violence

3. Results

According to Global Gender Gap Index 2021 (WEF, 2021), Russia holds the 81st place, and post-Soviet states (Eastern Europe and Central Asia) hold the 2nd place among emerging economies after Latin America and the Caribbean, less than 1 p.p. behind. However, a more detailed look at the subindexes reveals that Russia actually holds very high positions in three of four subindexes. In Economic Participation and Opportunity Eastern Europe and Central Asia hold the 2nd place after North America, leaving Western Europe behind due to the high level of female labor force participation rate, particularly among professional and technical workers, where Russia holds the first place in the world, and legislators, senior officials, and managers (21st place), but, on the other hand, gender income gap remains huge (87­th place). Educational attainment and Health and Survival subindexes also have Russia holding the 1st place due to measuring educational attainment, sex ratio at birth and life expectancy rather than gender discrimination within educational systems and health level of women and men. The last sub­index Political Empowerment is the one that holds Russia behind Latin America and most other regions and countries (133st place out of 156) as women play very little part in government. Even more disturbing is that the level of female participation in state government decreases. Why do Russian institutions show such a contradictory level of gender inequality: wide economic opportunities and active economic participation on the one hand, and one of the lowest levels of political empowerment of women on the other hand?

3.1. Household and labor markets

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:// (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 (

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 (

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 19th 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 19th 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 ( and WEF, (2021).

3.2. Education and science

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).

3.3. State and corporate governance

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).

3.4. Agency

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 8th from bottom. Also striking is a large gender difference in that evaluation — 0,6, which places Russia in the 2nd 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.

4. Conclusion and discussions

The USSR launched the transition from a patriarchal to egalitarian society; however, the transition was not complete. On the one hand, women engaged in paid labor, but on the other, — men did not engage in unpaid labor — so domestic chores and childcare remained a female domain. It resulted in a double burden and promoted the conservation of patriarchal values in key public institutions — state governance, academia, and after the collapse of the USSR — corporate governance. Nowadays, in Russia, men and women share unpaid and paid labor, but a gender balance has not yet established itself. Women are overburdened by the double shift of paid and unpaid labor, and underpaid. As a result, there are few women in decision making positions in state and corporate governance and in academia.

As economic growth per se does not promote gender equality (Kabeer, 2020; Seguino, 2020), gender inclusive policy-making is crucial. And Russia has both: a solid foundation for women empowerment inherited from the Soviet Union and an economic agenda (to spur technologies and innovations and to increase birthrates).

Russian women are highly educated and actively engaged in labor markets, including healthcare, science and other “male” fields, due to the legacy from the Soviet era. Many women are engaged in science, accounting for 40–42% of scientific workers, particularly in humanitarian sciences. However, despite the feminization of science, it functions within patriarchal traditions, whereas gender and women studies remain heterodox and have low impact on mainstream academic discussion. STEM also remains the male dominant field in education and in labor markets, hindering innovative development.

Governance also remains a male field, where women account for deputies, and mostly administrative jobs, and have low decision-making capabilities, both in state and corporate governance. The lack of women in governance and academia lead to poor representation of their interests in policymaking, gender budgeting and knowledge production, including gendered data collection. Demographic policy stimulating birthrates reinforces the prime role of women as caregivers as it targets women. Whereas gender economic research advocates for finding gender balance in allocation of domestic chores and childcare by promoting inclusive fatherhood, demographic policy continues to exclude or ignore fathers.

Long parental leave protects women and is great for children and bonding. However it devalues women in the labor market, making them unreliable workers­, who can leave for 3 years or even more. The government aims to increase the flexi­bility of parental leave, allowing women to take shorter leave and receive higher payments. At first, fathers were excluded from the initiative, however, women from government and science who participated in the conference in the Civic Chamber of the Russian Federation insisted on including fathers.6 The discussion also highlighted that fathers are excluded from the vocational programs available for mothers on child leave. Fathers have the same rights to take child leave as mothers, but only 2% exploit this right. The key obstacle is economic — the gender­ wage gap. Thus, flexible terms for child leave and the amount of payment could engage more men. However, gender norms and stereotypes would still prevent most men from taking child leave, as the example of other countries show. For example, Japan and South Korea introduced one of the most generous exclusive paternal leave entitlements, but men barely use it. Sweden introduced paternal leave in the 1970s and in 1995 made it non-transferable (at first 30 days, then 60), stimulating families to use it. Another important feature that makes father-inclusive polices in Nordic states efficient is the high level of parental allowances (70–100% of salary).

Fatherhood empowerment is the most effective and the most under evaluated resource for economic and demographic potential. Concerning economic benefits, inclusive fatherhood is essential not only for unburdening women, but for creating a safe environment for a child’s healthy intellectual, emotional, and physical development, particularly in the earliest years. In other words, inclusive fatherhood is one of the pillars of human capital development. It also positively impacts men, as the more they are involved in domestic affairs, the less they choose antisocial and dangerous behavior patterns, including alcoholism. Thus, inclusive fatherhood prolongs men’s longevity. It also decreases the divorce rate and increases the chances of having more than one child, thus stimulating childbirth (Duvander et al., 2019). Indispensable paternal leave has proved to be the most efficient tool to engage fathers in childcare and domestic chores in the long term and to decrease the female burden by sharing time spent with children and childcare, and distributing the responsibility for chores more equally. Consequently, balanced gender time allocation on paid and unpaid leave reduces the gender wage gap and stimulates birthrates as the Northern Europe example shows.


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Appendix A

Table A1

Gender gap in World Values Survey answers (women / men) in Russia per wave (%).

Question Wave Answers
2 3 5 6 7
Important in life: Family 91 95 91 92 94 1 Very important
2 Rather important
3 Not very important
4 Not at all important
Important in life: Friends 105 104 104 102 103
Important in life: Work 108 112 114 108 113
Feeling of happiness 102 105 102 101 101 1 Very happy
2 Quite happy
3 Not very happy
4 Not at all happy
State of health (subjective) 111 109 113 108 108 1 Very good
2 Good
3 Fair
4 Poor
5 Very poor
Satisfaction with your life 100 91 97 98 96 1 None at all
10 A great deal
How much freedom of choice and control 93 94 93 98 92
Being a housewife just as fulfilling 105 110 110 88 104 1 Agree strongly
2 Agree
3 Disagree
4 Strongly disagree
Men make better political leaders than women do 109 122 113 114
University is more important for a boy than for a girl 103 112 108 106
Pre-school child suffers with working mother 97 100 101
Men make better business executives than women do 121 114 118
Justifiable: Parents beating children 87 85 1 Never justifiable
10 Always justifiable
Justifiable: Violence against other people 82 81
Justifiable: Abortion 108 109 117 106 105
Justifiable: Divorce 101 102 111 101 101
Highest educational level attained — Respondent’s mother (recoded) 96 1 Low
2 Medium
3 High
Highest educational level attained — Respondent’s spouse (ISCED-2011) 91 0 Early childhood education (ISCED 0) / no education
1 Primary education (ISCED 1)
2 Lower secondary education (ISCED 2)
3 Upper secondary education (ISCED 3)
4 Post-secondary non-tertiary education (ISCED 4)
5 Short-cycle tertiary education (ISCED 5)
6 Bachelor or equivalent (ISCED 6)
7 Master or equivalent (ISCED 7)
8 Doctoral or equivalent (ISCED 8)
Highest educational level attained 95 101 100
Employment status —Respondent’s spouse 86 1 Full time (30 hours a week or more)
2 Part time (less than 30 hours a week)
3 Self-employed
4 Retired/pensioned
5 Housewife not otherwise employed
6 Student
7 Unemployed
8 Other
Employment status 119 121 105 117 121
How many children do you have 100 105 125 117 116
Number of people in household 97 87
Do you live with your parents 81 75 58 93 0 No
1 Yes
Are you the chief wage earner in your house 51 66 70 76
Social class (subjective) 97 101 101 1 Upper class
2 Upper middle class
3 Lower middle class
4 Working class
5 Lower class
Scale of incomes 85 86 90 94 92 1 Lower step
2 second step
3 Third step
4 Fourth step
5 Fifth step
6 Sixth step
7 Seventh step
8 Eighth step
9 Ninth step
10 Higher step
Income level 88 89 91 96 93 1 Low
2 Medium
3 High
Table A2

Weight of agency features for women and men in Russia.

Category Feature Men Women
Attitude towards women’s rights Men make better political leaders than women do –0.11 0.11
Justifiable: for a man to beat his wife 0.02 0.03
Justifiable: abortion –0.02 0.02
Men make better corporate leaders than women do 0.10 –0.05
Work Important in life: work 0.36 0.48
Part time/self employed 0.02 –0.17
Employed full-time –0.16 –0.24
Unemployed –0.02 –0.32
Family Spouse unemployed 0.07 0.38
Spouse employed full-time –0.11 0.30
The chief wage earner 0.04 –0.01
Number of children 0.00 –0.01
Marital status: divorced –0.06 –0.03
Live with parents –0.07 –0.06
Important in life: family 0.08 –0.08
Marital status: single 0.10 –0.09
Marital status: married 0.05 –0.12
Emotional capital Feeling of happiness 0.14 0.44
Satisfaction with life 0.21 0.23
Social capital Important in life: Friends 0.08 0.36
Membership in any organization 0.02 0.01
Financial capital Satisfaction with income level 0.00 0.06
Income level –0.17 0.03
Social class 0.07 –0.13
Human capital Highest educational level attained 0.13 0.07
Age –0.01 –0.01
State of health –0.20 –0.13
Fig. A1.

Gender gap in time spent on unpaid labor and gender gap in labor force participation rate (LFPR) in Russia and per region (%).

Source: Author’s calculations based on UNSD Time-use statistics ( and ILOSTAT database (

Fig. A2.

Gender score gap in math, science and reading (%).

Source: OECD (2019).

1 STEM — Science, Technology, Engineering and Mathematics.
2 SIGI — Social Institutions and Gender Index.
3 GEI — Gender Equality Index.
4 GII — Gender Inequality Index.
5 PISA — Programme for International Student Assessment.
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