resumes with randomly assigned gender, ethnicity, marital status, attractiveness, or other attributes have been conducted in many high-income countries (e.g., Levinson 1975, Riach and Rich 1987, Neumark et al. 1996, Bertrand and Mullainathan 2004, Riach and Rich 2006, Booth and Leigh 2010, Carlsson 2011, Zhou et al. 2013, Bursell 2014, Maurer-Fazio and Lei 2015, Edelman et al. 2017, Asali. et al. 2018, Chen 2019, Hou et al. 2020, Zhang et al. 2021). Some studies such as Booth and Leigh (2010), Carlsson (2011), and Zhou et al. (2013) explored whether the degree of discrimination depended on nature of the profession. Kiaušienė and Štreimikienė (2011) examined how gender stereotyping impacts men and women in the labor market. Stereotypes of gender roles are defined in the literature as “a cultural and social approach towards the very thing that is traditionally considered being ‘masculine’ and ‘feminine’ roles and functions” (Kiaušienė and Štreimikienė 2011).

The reasons and consequences of discrimination in the labor market have also been studied over several decades (e.g. Altonji and Blank 1999, Darolia et al. 2016, Bertrand and Dufflo 2017, Gaddis 2018). There are two prominent and often overlapping drivers: “statistical” forms of discrimination and “preference-based” explanations. Becker (2010) pioneered the preference-based explanations, claiming that discrimination often arises when employers have a distaste for hiring members of certain groups such as minorities, or women. In such cases, employers may decide not to hire certain groups of people because of this distaste, and if they do hire them, they are likely to pay them lesser than other equally productive employees (Becker 2010, Zhang et al. 2021). Statistical forms of discrimination are often viewed as an alternative to preference-based explanations, but in practice both can be present to some degree at the same time. Statistical discrimination describes a situation in which employers have imperfect information on potential employees’ productivity (Phelps 1972, Arrow 1973, Aigner and Cain 1977, Schwab 1986). Instead, the employer uses group-specific membership to infer potential employees’ productivity (Bohren et al. 2019, Zhang et al. 2021). In such circumstances, an employer may rationally favor an applicant belonging to the group with a higher expected productivity when faced with two applicants having the same unobservable productivity but belonging to two different groups. In practice, most correspondence studies are alone not able to distinguish between these two potential drivers of discriminatory practices.

In comparison to studies of race-based discrimination, there are relatively few correspondence studies focused on gender. According to Bertrand and Dufflo (2017), from 2005 to 2016, only around 15 field experiments addressed discrimination on the grounds of gender. The literature on gender discrimination focuses predominantly on developed states and only in the recent years have a few studies been conducted in developing countries such as China, Georgia and Turkey (Zhou et al. 2013, Maurer-Fazio and Lei 2015, Asali et al. 2018, Nas Özden et al. 2020, Zhang et al. 2021). To our knowledge, only two have been conducted in CIS countries (Asali et al. 2018, Ryabushkin and Kim 2018).

A review of the narrower literature on gender differences in receiving callbacks for on-site interviews reveals the existence of a considerable variation across different countries and occupations or industries within a country. Although it may be difficult to indicate the exact explanations for the differences in results, these differences may be attributed to a number of factors, including cultural differences, regulatory environments, labor market conditions (e.g., Kuhn and Shen 2013, Zhang et al. 2021), and the composition of specific study samples (i.e., specific types/mix of occupations and industries). For instance, previous research conducted on gender preferences in IT positions is controversial and highly variable to the country and market under study. Riach and Rich (1987) found that women were discriminated against for programmer or computer analyst jobs. But Riach and Rich 6