Understanding the Evolution of Gender Wage Gaps in Ukraine Ina Ganguli Harvard University Katherine Terrell PREM-Gender, University of Michigan World Bank Workshop on: “Women in the ECA Region” Jan. 24, 2008

Extensive Interest in Evolution of Gender Wage Gap in ECA Would the gap grow in transition from socialist to market-based economy? Arguments for and against Evidence is Mixed Brainerd (2000): grew in 2 FSU but fell in 4 CEEs and no change in 1 CEE Newell and Reilly (2001): no rise in 16 TEs in 1990s Orazem and Vodopivec (1995): Fell in Slovenia

Extensive Literature on Evolution of Gender Wage Gap in ECA However, changes in gender gaps are due to many different factors: Returns to labor o Changes in the level of discrimination (Joliffe, 2002 for Bulgaria; Joliffe and Campos, 2004 for Hungary) o Relative changes in returns to HC (Münich, Svejnar and Terrell, 2005; Liu et al., 2000) o Wage-setting policies (Blau and Kahn,1997 & 2003; DiNardo, Fortin, Lemieux, 1996)

Extensive Literature on Evolution of Gender Wage Gap in ECA Changes in gender gap due to various factors: Composition of the labor force Productive Characteristics (Hunt, 2002; Orazem and Vodopivec, 1995) Occupational segmentation (Jurajda, 2003 for CZ; Ogloblin, 1999 for Russia). Other transition factors, e.g. privatization (Brainerd, 2002; Liu et al., 2000; Munich, Svejnar and Terrell, 2005)

Our Research Questions 1. Size of gender gap across the wage distribution in 1986, 1991 and To what extent are changes in the gaps due to: a) Returns (Institutions) Minimum Wages Discrimination b) Composition of labor force 3. Differences in Private v. Public Sector composition and wage setting practices?

Our Contribution First micro-economic evidence on Ukraine’s gender gap during and after communism o Look at impact of wage-setting institutions - how does the MW affect the gender gap in Ukraine over time? o Previous transition studies focused on the average gap. We examine the gap across the distribution.

Ukraine’s Transition Independence in 1991 Gradual transition (1992) price liberalization; privatizn. Decline in GDP, hyperinflation, small change in emp. Min Wage (‘92) Entry into the EU 

Data: Ukrainian Longitudinal Monitoring Survey (ULMS) Carried out April-July, 2003 Retrospective questions of jobs in 1986, 1991 Three cross sections (1986, 1991 and 2003) full-time men and women; over 1,300 men and 1,400 women in each year. Data issues: Retrospective: Recall error and representativeness of 1986 & 1991 samples Selection: Use of FT workers and people with wage >0 Transition related: Inflation Wage arrears (12% among men and 9% among women) but “net contractual monthly salary”

Gender Gap

Public and Private Gaps, 2003 Larger mean gap in public sector; driven by difference at the top of the distribution Glass ceiling is most notable in Education, Health & Social Protection

Three Puzzles 1. Why did the gap in the lower end of the distribution fall from the communist period to the market period? 2. What explains the persistence of the gaps at the top end of the distribution (glass ceiling) from communism to markets? 3. Why is the a larger gap in the upper end of the distribution in the public sector than in the private sector in 2003?

Counterfactual Analysis, Using Machado and Mata (2004) Method Method Create counterfactual densities where women are given men’s characteristic (Xs) in one scenario and then women are given men’s rewards (  s) in another scenario. Summary of Static Findings Differences in pay structure (  s) are much more important than differences in characteristics (Xs) in explaining the gaps in every year -- explain more the 75% at each point in distribution

Counterfactual Analysis Over Time: Summary of Findings How did changes in the distribution of women’s Xs change the gaps? o No effect on mean. o Helps reduce gap in the bottom of the distribution o No change in the percentiles at the median and above Xs at the bottom weren’t as good in 1986, but Xs at the top were similar  explains puzzles #1 and #2. How did changes in women’s  s affect change in the gaps? o Increased mean gap o However, contributed to a reduction in gap at top and an increase at the bottom  does not help explain our puzzles.

Counterfactual Analysis, Over Time: Summary of Findings How did changes in the distribution of men’s Xs over time change the gaps? o Raised mean gap o  decline in men’s productive characteristics lead to widening of the gap at bottom 10% but not elsewhere in the distribution How did changes in men’s  s affect changes in the gaps? o Lowered the Gap  Men’s  s declined over time o Contributed to reducing gap in the bottom and increasing gap at the top o  Helps explain Puzzle #1 - narrowing of the gap at bottom

Kernel Density Estimates and Minimum Wages in 1986, 1991, 2003

Counterfactual Analysis, Public vs. Private: Summary of Findings In both sectors, gap is mainly due to difference in  s, more important in Private Sector: Private Sector: If women had men’s Bs, mean gap would have fallen to nearly zero and would have fallen more in the top half than in the bottom half distribution. Public Sector: If women had men’s  s, the mean gap would have also fallen and more in top half, but effect is smaller than in private sector. Differences in Xs small, but composition effect is different in each sector: If women would have had men’s Xs: Private Sector: mean gap would not have changed (but U shaped across distribn). Public Sector: mean gap would not have changed but would have grown at bottom and fallen slightly at top. Lower glass ceiling in public explained by women’s relatively worse characteristics

Another explanation for rise in floor… Importance of Min Wage for women

Conclusions on Evolution of Gender Wage Gap in Ukraine Mean gender gap declined from socially planned economy ( ) to market driven economy (0.34) Decline due to narrowing of gap at the bottom distribution, no change in gap at the top Change in structure of LF from public to private jobs put forces on reducing the gap at the top

Conclusions on Evolution of Gender Wage Gap in Ukraine Explanations: Decline at bottom due to: increase in MWs improvement of women’s characteristics (as those with poor characteristics left the L.F.) decline in men’s rewards Lack of change at top due to: No change in composition of men’s or women’s characteristics (although  s did change and contributed to widening)

Conclusions on Evolution of Gender Wage Gap in Ukraine In 2003, the public sector had wider mean gaps than private sector (0.40 v. 0.26) due to diff. at top, similar gaps at the bottom Explanation: Both sectors rely heavily on MW, especially for women; MW relatively high in that year Again, men get much higher rewards for their labor than women, especially in private Public sector, women at top of wage distribution have somewhat poorer characteristics than men (not in public)