Tag: Generations and Gender Survey

Intergenerational Occupational Mobility in Belarus

20221113 Intergenerational Mobility Belarus Image 01 representing Intergenerational occupational mobility

This brief presents an analysis of the magnitude of the intergenerational occupational mobility in Belarus, taking into account a differentiated gender effect. The analysis considers movements along the occupational scale for individuals with respect to their parents, both through an aggregate magnitude (using transition matrices and mobility rates) and in detail (using a multinomial logit model), using data from the 2017 Generations and Gender Survey for Belarus. The findings show, firstly, that the downward intergenerational changes of occupational status have a strong gender bias: downward mobility is higher for men than for women. Secondly, the probability of moving up the social ladder is higher for women than for men in Belarus. Additionally, the results verify the important role of education as a mechanism towards reaching a society with more equal opportunities. In particular, the effect is more intense for individuals with higher education.

Introduction

Intergenerational social mobility is defined as the movement of individuals from the social class of the family in which they lived when they were young (the origin class) into their current class position (the destination class), where social class is determined by as decided by income, occupation, education etc. (Ritzer, 2007; Scott and Marshall, 2009).

One of the main results from the economic literature on intergenerational social mobility shows that the degree of social mobility depends on the characteristics of an individual’s family background. These characteristics include an individual’s choice to acquire human capital and corresponding type of education, innate and acquired abilities, gender differences, or the knowledge people acquire through lifelong learning or work experience (Behrman & Taubman, 1990; Dutta, Sefton & Weale, 1999).

However, such characteristics may encourage children to work in the same occupations as their parents, slowing down intergenerational change. Research on intergenerational mobility can help identify and remove barriers to mobility which could improve the effective distribution of human skills and talents, in turn increasing productivity and promoting competitiveness and economic growth.

This brief summarizes the results of the first research focused on intergenerational occupational mobility in Belarus (Mazol, 2022). The research attempts to obtain new empirical evidence on intergenerational social mobility in Belarus by examining the movements of individuals along the occupational scale in relation to their parents, while taking into account other relevant factors such as gender differences and educational background of the individuals. Two specific gender dimensions are introduced: on the one hand, this study analyzes whether mobility in occupational categories differs for men and women; on the other hand, it examines whether there is a difference in the transmission of occupational categories from fathers to sons in comparison to mothers to daughters.

Data and Methodology

The study makes use of data from the Generations and Gender Survey (GGS) conducted in Belarus in 2017 by the United Nations Population Fund (UNFPA) and the United Nations Children’s Fund (UNICEF) within the framework of the Generations and Gender Program of the United Nations Economic Commission for Europe. The survey provides information on a range of individual characteristics (age, gender, marital status, educational attainment, employment status, hours worked, wages earned, etc.) as well as household-level characteristics (household size and composition, religion, land ownership, location, asset ownership, etc.).

The research considers the subsample of respondents between 25-79 years old and utilizes the information on occupation of the respondent and his/her parents. In order to evaluate the intergenerational occupational mobility, occupations are ranked by their position in the occupational ladder according to the National Classification of Occupations, based on the International Standard Classification of Occupations (ISCO-08) This defines a ranking of occupations based on the performance area and qualification required to carry out the occupation, from armed forces occupations (ranking the highest), through  a manager, a professional, a technician or professional associate, a clerk, a sales worker, a skilled agricultural worker, a craft worker a plant and machine operator, ending with an elementary occupation ranking the lowest. The influence from the father’s/mother’s occupation on that of the son’s/daughter’s is then estimated.

The analysis is carried out partly by estimation of transition matrices and mobility rates, and partly by the use of a multinomial logit model that aims to analyze the impact of a set of covariates on intergenerational occupational mobility. The explanatory variables are: the highest degree of education an individual has achieved (educational attainment), gender, potential labor experience (calculated as the number of years an individual has regularly worked), status in the labor market (full-time or part-time), and region of residence. The choice of these independent variables relies on channels identified from relevant sociological and economic literature.

Figure 1. Intergenerational occupational transitions in percent, by gender lines

Source: Author’s estimates based on GGS.

The intergenerational transmission of occupational immobility is almost equal for men and women (31 percent and 30,1 percent respectively). Occupational upward mobility is far more common as compared to downward mobility. 39.7 percent of men, compared to their father’s, and 50.6 percent of women, compared to their mother’s, have better occupations. The gender differences may be explained by the high proportion of women with higher educational levels in Belarus.

The estimates of the marginal effects obtained by the multinomial logit model indicate that social occupational mobility in Belarus depends on personal and labor characteristics. Three possible states are considered in relation to father-son and mother-daughter gender lines: the individual experiences downward intergenerational occupational mobility as compared to their parent of the same gender (Y = 0); they remain in the same occupation (immobility) (Y = 1) or they experience upward intergenerational occupational mobility (Y = 2) (see Table 1).

Table 1. Estimates of the marginal effects corresponding to the multinomial logit model

Notes: Estimates reflect weighted data. Standard errors in square brackets. Significance: *** – 1% level, ** – 5% level, * – 10% level. OV – omitted variable. Source: Author’s estimates based on GGS.

As evident from Table 1, gender is an important determinant of intergenerational occupational mobility. In particular, the results show that women are more likely to move up the social ladder than their male counterparts, as men are 10 percentage points less likely to have upward occupational mobility than women with similar (on average) socio-economic characteristics, with all coefficients being statistically significant.

In terms of educational attainment, the findings show that, on the one hand, higher educational attainment has a positive and significant influence on upward occupational mobility, with the highest values displayed for higher education. The probability of moving up to the occupational ladder is around 27 percentage points higher for an individual within this educational group than for an individual with primary studies and similar (on average) socio-economic characteristics. On the other hand, higher education has a negative and significant influence on downward occupational mobility, indicating that the probability of moving down the occupational ladder is around 13 percentage points lower for a highly educated individual compared to an individual with primary education.

Considering human capital, there is a positive impact of potential labor experience on upward intergenerational occupational mobility. Specifically, the probability of moving up along the occupational ladder increases on average by about 0.3 percentage points for every additional year of labor experience.

Finally, the results show that full-time workers are more likely to move up the social ladder than their part-time counterparts. Full-time workers are about 12 percentage points more likely to experience upward occupational mobility and 11 percentage points less likely to face downward occupational mobility compared to their part-time working counterparts.

Conclusion

This brief summarizes the findings for the first study on intergenerational occupational mobility in Belarus.

Firstly, the findings indicate, from a gender perspective, that the probability of moving up the social ladder is higher for women than for men in Belarus.

Secondly, the research results verify the important role of education as a mechanism to reach a society with more equal opportunities. In particular, the effect is more intense for individuals with higher educational attainments.

Thirdly, potential labor experience positively influences the upward intergenerational occupational mobility. This may reveal an underlying effect from training (however an unobservable variable given the data provided by the GGS).

Lastly, the impact of employment status on intergenerational occupational mobility in Belarus depends on the stability of labor relations, where possessing a part-time job worsens one’s probability of accomplishing a social class advancement.

References

  • Behrman, J., and P. Taubman. (1990). The Intergenerational Correlation between Children’s Adult Earnings and Their Parents’ Income: Results from the Michigan Panel Survey of Income Dynamics. Review of Income and Wealth, 36(2), pp. 115-127.
  • Dutta, J., Sefton, J., and M. Weale. (1999). Education and Public Policy. Fiscal Studies, 20(4), pp. 351-386.
  • Mazol, A. (2022). Intergenerational Occupational Mobility: Evidence from Belarus. BEROC Working Paper Series, WP no. 79.
  • Ritzer, G. (2007). The Blackwell Encyclopedia of Sociology. Malden: Blackwell Publishing Ltd.
  • Scott, J., and G. Marshall. (2009). A Dictionary of Sociology. Oxford: Oxford University Press.

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

The Gender Wage Gap in Belarus: State vs. Private Sector

20190830 The Gender Wage Gap in Belarus FREE Network Policy Brief Image 02

This brief is based on research that studies gender difference in wages in Belarus using survey data from 2017. According to the results, the unconditional gender wage differential equals 22.6%. The size of the wage gap is higher in the state sector than in the private sector. Additionally, it increases in the state sector throughout the wage distribution and accelerates at the top percentiles, indicating the presence of a strong glass ceiling effect.

Introduction

The causes and consequences of the gender wage gap in the labor market, that is the difference between the wages earned by women and men, continue to attract increasing attention in empirical studies worldwide.

Belarus’ labor market is not an exception and faces the problem of wage inequality like other neighboring and transition countries. According to the National Statistical Committee of the Republic of Belarus (Belstat), the average gender wage gap in terms of monthly wages was 19% in 2000, it increased up to 23.8% in 2015, and reached 25.4% in 2017.

In this regard, this brief updates the estimates of the gender wage gap in Belarus. And it summarizes the results of the study on what the role of the state and private sectors are in the distribution of gender wage differences in Belarus (Akulava and Mazol, 2018).

Data and methodology

The data used in the research is from the Generations and Gender Survey (GGS) conducted in Belarus in 2017. This survey is a nationally representative dataset that is based on interviews of about 10,000 permanent residents of Belarus, aged 18–79, covering the whole country disaggregated by regions. The GGS contains information on a range of individual (age, gender, marital status, educational attainment, employment status, hours worked, wages earned etc.) and household-level characteristics (household size and composition, land holding, location, asset ownership etc.).

The analysis is based on the typical Mincer model of earnings that estimates individual wage income as a function of various influencing factors using the OLS approach (Mincer, 1974). Specifically, the Mincerian wage equation is defined where the log of the hourly wage rate is regressed on a set of male and female workers’ personal and job characteristics (educational level, working experience, occupational type, organization type, family characteristics, and region).

Next, we use the Oaxaca-Blinder (OB) methodology (Oaxaca, 1973; Blinder, 1973) to identify and quantify the contribution of personal characteristics and the unexplained component (which is referred to as differences in returns) to the wage difference between males and females.

Finally, we apply the Machado-Mata (MM) technique (Machado and Mata, 2005) to look into the nature of the wage gap at various points of the income distribution and also to test the difference for individuals employed in the state or private sectors. For the Machado-Mata procedure, we estimate our specifications at the 10th, 25th, median, 75th and 90th percentiles of the wage distribution.

Results

The analysis shows that women’s wages are lower than men’s wages all over the wage distribution. The average raw gender wage gap equals 22.6% and it increased substantially compared with 9.0% in 1996 and 17.8% in 2006, the numbers obtained in the study conducted by Pastore and Verashchagina (2011).

Figure 1. Gender differential by quantile of the wage distribution

Source: Authors’ estimates based on GGS.

The level of female earnings is lower than the male regardless of the occupational type, educational background, work experience and organizational type. Moreover, the underpayment of women is lower for low earning workers, but increases up to the end of the wage distribution (see Figure 1).

The OB decomposition shows that female educational attainment and job-related experience help to decrease the level of the wage gap slightly (see Table 1).

Table 1. Oaxaca-Blinder decomposition results

Source: Authors’ estimates based on GGS.

However, the occupational choice is leading to an expansion of the difference in earnings. However, its effect is also small, indicating that occupational segregation plays a minor role in explaining the gender wage gap. The major share of the gender wage gap is formed by the unexplained part, which is likely to be attributed to discrimination.

Next, the level of remuneration is higher among private companies. However, contrary to other countries in transition, the average gender wage gap in Belarus in the private sector is lower than in the public sector.

Moreover, the MM decomposition estimates presented in Table 2 demonstrate that the gender wage gap in the state sector shows evidence of the glass ceiling effect (the size of the total wage gap expands at the top of the wage distribution), while no evidence of either glass ceiling or sticky floor (the size of the total wage gap increases at the bottom of the wage distribution) in the private sector.

The negative coefficient near the characteristics part in the private sector shows that female endowments outweighs their male counterparts. Thus, controlling for personal characteristics, if the labor market rewards males and females equally, the wages of females in the private sector should be substantially higher (see Table 2).

Table 2. Machado-Mata decomposition of the observed gender wage gap by organization type

Source: Authors’ estimates based on GGS.

Finally, the results also suggest that female workers are better off being in the private sector at the lowest and the highest percentiles (i.e. the size of the gender wage gap is lower there compared to the 25th and 50th percentile).

A possible explanation for all the above is that institutional differences seem to play a crucial role here. First, Belarusian private firms work under stronger regulation than in other transition economies which makes it harder for them to set low wages. Second, they also operate under stronger competition (compared to state companies), which force them to identify individual productivity more correctly, narrowing the gender difference in pay. In contrast, the paternalistic attitude to women left as a legacy from the Soviet Union further increases the gender wage gap in the public sector.

Conclusion

In this brief, we present new evidence on the existence of a gender wage gap in the Belarusian labor market and analyze the differences in its distribution between the state and private sectors.

Our results show that the unconditional gender wage gap in terms of hourly wages equals 22.6%. Thus, jointly with a previous study (see Pastore and Verashchagina, 2011) and recent official indicators, all these indicate that the pace towards gender equality in Belarus seems to be sluggish. For the moment, all institutional changes accomplished by the Belarusian government to reduce gender discrimination are not enough and require additional efforts to cope with that problem.

However, the gender wage gap is shown to be much wider in the public sector than in the private sector. At the same time the private sector appears to be more attractive than the public sector in the country in terms of the level of remuneration. Therefore, additional structural shifts of the economy accompanied by the growth of competition are needed to induce a further reduction of the gender wage gap.

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.