Higher School of Economics, Moscow October 14, 2008

1. The Gender Earnings Gap inside a Russian firm: First Evidence from Personnel Data[work in progress] Thomas Dohmen (ROA, Maastricht University, IZA and DIW) Hartmut Lehmann (DARRT, University of Bologna, IZA, CERT, WDI and DIW) Anzelika Zaiceva (DARRT, University of Bologna and IZA) Higher School of Economics, Moscow October 14, 2008

2. Outline • Motivation and background • Theoretical models • Empirical literature & this paper • Data & the firm • Methodology • Gender earnings gap at the mean and across the distribution • Potential explanations of its dynamics • Potential reasons for its existence • Concluding remarks and future research

3. Motivation • Personnel economics: industrial relations within a firm (not a Black Box) • Gender differences in pay, job assignments and promotions in the internal LM • Advantages: detailed look at the internal labor market. Disadvantages: not representative • Few empirical studies – data unavailability (wages are often missing) • No study for transition economies: interesting context because of the (exogenous) shock and change in industrial relations and family-related policies

4. Motivation cont’t • Russia is (one of) the largest transition economy (1st in terms of area, 2nd in terms of population) • After the break-up of the USSR in 1991: GWG ↑ (widening of the wage distribution) to 35% by mid-1990s, then ↓ to 15% in early 2000 (Brainerd, 2000; Reilly, 1999; Kazakova, 2007) • Occupational segregation, wage arrears, discrimination (Gerry et al., 2004; Ogloblin, 1999; Kazakova, 2007) • Not controlling for segregation at the level of establishment and jobs overstates the role of occupational and/or industry segregation in the economy (Bayard et al., 2003) • What are the patterns of the firm-level GWG in Russia? • Reasons behind GWG? Within-firm within-occupation segregation? • Gender differences in job assignments and promotions?

5. Transition-specific background • Under communism: • Gender equality (formally) • High LM participation of women • Low GWG • Segregation into “female” occupations • Economic “winners” and “losers” from transition (Brainerd, 1998) • Changes were more pronounced for women (UNICEF, 1999; Brainerd, 2000; World Bank, 2002; Malceva and Roshin, 2006)

6. Transition-specific background (cont’d) • Supply side: • collapsing welfare system and childcare facilities • sharp increase in unemployment • decrease of public employment • home production as an outside option • Demand-side: • enterprise restructuring ranged from labour hoarding to mass lay-offs • decentralised system of wage bargaining or firm-level negotiations • increasing competition and emergence of hard budget constraints ⇓ Implications for gender segregation and discrimination in the labor market

7. Theoretical models • Becker (1957): taste-based discrimination • Kremer (1993): productivity differences between men and women and sorting into firms ⇒ Both predict segregation • Becker (1985): effort is lower for females due to more extended household work and childcare (incr. returns to specialization) • Lazear and Rosen (1990): • women have a higher separation probability and need a higher ability threshold level to be promoted; • promotion rates (and thus wages) do not differ by gender at very high levels of ability; • female wages are lower because they are underrepresented in high-paying jobs (segregation) • Booth et al. (2003): promotion may not automatically mitigate the gender wage gap (upon promotion women might have less outside options)

8. Empirical literature • Using personnel data reduces unobserved heterogeneity (Kunze, 2008) • It is possible to “more credibly investigate whether wage gaps still exist when job characteristics and rank are controlled for” (Kunze, 2008) • In general, literature finds gender differences in pay, mobility and promotion opportunities within a firm in Western economies (see, among others, Ransom and Oaxaca, 2005 for the US; Jones and Makepeace, 1996 for the UK) • Barnet-Verzat and Wolff (2008) use personnel data on executives in a French firm, control for hierarchical levels and find evidence of the “glass ceiling” effect (i.e. wage gap is higher at the highest quantiles of the wage distribution)

9. This paper • Uses unique personnel data from a manufacturing firm in Russia • Documents the evolution of the GEG over 1997-2002 • Analyses potential reasons behind the gender gap and its change • Analyses gender differences in job assignments and promotion opportunities (to be completed)

10. The firm • A firm operating in one of the Central Russian oblast in the “machine building and metal works” sector producing equipment for gas and oil production and smith-press equipment • Out of 17 Central Russian oblasts, oblast, wherefirm, is 8th in terms of wage levels (2006 data) • The ratio of females’ to males’ wages (wf / wm) in this oblast in industry constituted 66% in 1999, 67% in 2001, 62% in 2002 and 64% in 2003 • In 2005, the occupational distribution of the females’ to males’ wages ratio in this oblast was as follows: • Managers: 70% • Specialists: 67% • Other employees: 65% • Workers: 50%

11. The firm (cont’d) • The firm operates in a product market characterized as follows: • 6.2% export share (CIS): the vast majority -for Russian market • no regional competitor • more than 5 competitors in the Russian market, among them firms from the EU • It was founded in the 1950s and privatized in 1992: • ownership structure (in 2002): workers/employees/managers (53.1%) former employees (21.5%), Russian entities (25.4%) • caveat: top management seems to have decisive majority (interview with CEO); • In 2007 about 3400 employees; • Formally there is collective wage bargaining at the firm but trade union officials are “in the pocket of the CEO.”

12. Data • We created electronic files based on records from the personnel archive of the firm • All employees, except for top managers • Panel data over 1997-2002 with info on wages, bonuses and arrears • Rich set of demographic and human capital variables • Financial variables are deflated to 1997 using corresponding CPIs • Sample selection: drop part-time employees (keep those who are polnaya stavkaand work full week) (13%), drop if missing explanatory variables (0.1%) • Sample size is around 3,000 observations per year • Dependent variables: • Log of average monthly wage • Log of total monthly compensation (avg. monthly wage + monthly bonuses)

13. Methodology • Estimate augmented Mincerian regressions for wages and total compensation by gender: • Controls: tenure (squared + cubed), age (squared + cubed), 6 education categories, 3 family status categories, dummies for children (0 vs. 1 vs. 2 and more children), any outside training, on the job training, internal mobility. • Perform different decompositions: • For means: Oaxaca-Blinder (1973) and Neumark (1988) /Oaxaca-Ransom (1994) • For quantiles: Machado-Mata (2005) • For changes over 1997-2002 at the means: Juhn, Murphy and Pierce (1991) • For changes over 1997-2002 at quantiles: Machado-Mata (2005) • Explanations of the GEG and its dynamics • Analysis of gender differences in job assignment and promotions (to be completed)

14. Proportion of females in the firm

15. Occupational distribution (%)

16. Earnings by gender, 1997 and 2002:All employees Workers

17. Evolution of the GEG inside the firm

18. OB decomposition, all employees

19. GEG at the means • At best one third of the gap is explained by differences in productive characteristics • GEG decreased between 1997 and 2002 by approx. 20 points • GEG for the entire workforce is driven by the earnings differentials for engineers and production workers • GEG is small and for the most part insignificant for managers (in line with Lazear and Rosen, 1990) and (in some years) for service staff • Workers have by far the highest gaps, little of which is explained by differences in observed characteristics

20. GEG at the quantiles: raw and adjusted gaps

21. GEG at the quantiles: MM (2005) total gap and gap due to coefficients 1997 2002

22. GEG at the quantiles: MM (2005) • In general, GEG has roughly an inverted U-shape profile across wage distribution, apart from 2002 • There is evidence for an increase of a “glass ceiling” effect by 2002 • The highest quantile in 1997 and the lowest in 2002 exhibit particularly low gender differentials • The main portion of the GEG is due to the differences in coefficients

23. Potential explanations of the change in GEG: 1997-2002

24. Change in GEG at the mean: JMP (1991)

25. Change in GEG at the mean: JMP (1991) • About 29 percent of the decrease can be explained by changes in observed characteristics and prices • Changes in observed characteristics about four times as important as changes in observed prices • About 6 points of the reduction of the gap is because women improve their position in the male residual earnings distribution • About 8 points are due to a narrowing of this distribution • The joint contribution of gender-specific effect has the most weight (contrary to the early years of transition, see Brainerd, 2000)

26. Change in GEG at the quantiles: MM (2005) • Raw gap fell more at the bottom than at the top. • Is that due to changes in Xs or changes in βs? ___________________________________________________ 1 The actual gap is the coefficient on the male dummy in the quantile regressions without covariates.

27. Change in GEG at the quantiles: MM (2005)

28. Change in GEG at the quantiles: Women • If the distribution of women’s Xs had not changed from 1997, the gap would have decreased at the bottom, but would have stayed almost the same throughout the rest of the distribution (row 6). • Thus, women’s characteristics were better in 1997 at the bottom, but not in the rest of the distribution. That does not help to explain the larger fall at the bottom. • If women in 2002 had the returns to their characteristics as in 1997, the gap would have been even negative at the top (benefiting women over men) and would have risen a lot at the bottom. • Changes in βs contributed to the large reduction in the gap at the bottom and an increase at the top. Thus, a large increase in the prices of women’s characteristics at the bottom (i.e. decrease in “discrimination”) is an explanation of the larger fall of the GEG at the bottom.

29. Change in GEG at the quantiles: MM (2005)

30. Change in GEG at the quantiles: Men • If men in 2002 had characteristics of 1997, the gap would have been slightly larger at the bottom 10th percentile and almost the same in the rest of the distribution. • Thus, at the very bottom men’s Xs were slightly better in 1997 than in 2002, and worsening in men’s Xs contributed to the fall in the gap there (however, to a small extent). The best from the bottom have moved away. • If men in 2002 had 1997 βs, the gap would have been larger everywhere. Men’s βs in 1997 were better than in 2002 and decline in rewards for men contributed to reducing the gap throughout the whole distribution. The reduction in βs, however, is higher at the top than at the bottom. ⇓ It is increased rewards of women at the bottom + a slight worsening in men’s characteristics

31. What have we learned so far? • There exist a GEG inside a Russian firm, which is the largest for production workers and is absent for managers • The gap is largerly unexplained by productivity characteristics at the mean and at the quantiles • The gap declines from 1997 to 2002, and the “glass ceiling” effect emerges • Potential explanations of the decline: change in prices and composition effect • It is not the less-skilled women who separate (Hunt, 2002) • The “quality” of new hirees is slightly worse for both genders, average “quality” of female employees does not improve over time nor is changing composition of males at lower end driven by hirings • 1/3 of the fall of GEG at the mean is explained by changes in observed characteristics and prices.

32. What have we learned so far? • The decline of GEG is largely due to a decline in the lowest part of the distribution. • The reasons: • men with better characteristics leave the bottom of the wage distribution, which also improves relative position of women in residual male wage distribution; • decreased rewards for men; • mainly: the rewards to characteristics for women improve disproportionately at the bottom of the distribution.

33. Potential explanations of the existence of the GEG

34. Potential reasons behind • The GEG declines from 36% to 17% between 1997 and 2002, however is still present • Potential reasons: • Bonuses • Arrears • Trade-off between job security and wages • Discrimination • Segregation • ….

35. Potential explanations of the GEG: bonuses • NO, since the decomposition and regression results for total compensation are very similar to those of the GEG.

36. Potential explanations of the GEG: wage arrears • Existed only in 1998 in this firm • W.a.’s in 1998 are very small and lowest for workers (0.05 months of 1997 wages vs. around 2 months in Russia, see e.g. Lehmann and Wadsworth, 2007); • Dohmen, Lehmann and Schaffer (2008): in this firm no gender difference in incidence of w.a.’s for all employees; • Decomposition results for employees with wages paid in full are very similar. ⇓ NO

37. Potential explanations of the GEG : trade-off between secure jobs and wages • In the firm, the majority of separations are quits (79% among all separations) • After having controlled for productivity characteristics and occupations, females have on average 3 p.p. higher probability to quit than males • They have also 1 p.p. higher probability to be laid-off ⇓ NO, but it is not a direct test of self-selection

38. Potential explanations of the GEG : segregation • Production workers have the highest GEG that contributes most to the overall gap • Production workers have jobs that are linked to levels - 8 for “primary workers” and 6 for “auxiliary workers”: so far for 2002 only • Controlling for such hierarchical levels is a descriptive exercise because of the endogeneity of these levels • Ransom and Oaxaca (2005): “But this makes the male/female wage difference that we observe all the more startling: among these workers , although wages were set by a collective bargaining that was, ostensibly, gender neutral, a large wage differential arose because women were placed in jobs different from those assigned to similar men”

39. Distribution of workers by wage levels • Auxilliary levels:

40. Distribution of workers by wage levels • Primary levels:

41. Results for workers including levels at the means: Oaxaca-Blinder decomposition

42. Results for workers at the quantiles with and w/o levels No levels With levels

43. Segregation • There exist virtually no GEG within the job levels for production workers • Controlling for these levels leads to disappearance of the gap • These levels explain the whole wage differential • This (descriptive) exercise points out that, in spite of a seemingly gender-neutral wage policy of the top management, large earnings differentials arises because overwhelming numbers of women are placed in low-paid job levels • However, gender difference in occupational distribution may reflect promotion discrimination or unequal occupational access. If it does, then it cannot be used to “explain” the GWG • The results with no levels in the regressions can be viewed as an “upper bound” for the extent of “discrimination”, and the results with levels - as a “lower bound” (Arulampalam et al., 2006).

44. Segregation or unequal job assignments ? • Probit regression results show that females have 84 p.p. lower probability to be in the primary levels (even those with university education) • Fairlie (2003) decomposition shows that only 11% of this job assignment can be explained by the observed characteristics • Gender differences in promotion rates and in entry-level jobs (to be completed…)

45. What have we found • There exists an intra-firm GEG that declines over 1997-2002, which is driven by the GEG for production workers • Increased rewards for women at the lower end of the distribution (and outflow of men with better characteristics at the bottom) seem to be a reason behind the decline • Bonuses, wage arrears or wages-secure jobs tradeoff do not seem to be reasons behind the existence of the GEG • For production workers the gap is almost completely explained when workers’ levels are included into the regressions • Job levels explain about 45-59% of all the variation in wages (R2 from the respective regressions)

46. Conclusions and future research • Composition effect and increase in rewards for women at the bottom of the wage distribution (decrease in discrimination?) are the reasons behind the decrease in GEG • Consistent with the increasing competition that firm faces as well as with the reduction on childcare facilities in the second half of 1990s • The potential explanation of the existence of the GEG seems to be existence of segregation in the internal labor market in Russia • However, the lower job assignment of women could only to a small degree be explained by individual productivity characteristics and deserves further explorations • Current research agenda: lower entry-level jobs vs. lower promotion opportunities