Transcript of Development and Reform Research Team University of Bologna The Gender Earnings Gap inside a Russian...
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- Development and Reform Research Team University of Bologna 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
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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
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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
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Motivation contt 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?
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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)
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Transition-specific background (contd) 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
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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)
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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)
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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)
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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, where firm, is 8 th 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%
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The firm (contd) 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.
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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 stavka and 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)
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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)
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Proportion of females in the firm
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Occupational distribution (%) Production workers Service staff
Engineers/ Technical staff Accounting staff ManagersN 1997
Males69.754.6819.700.115.761,772 Females48.85
5.0637.836.391.871,126 2002 Males69.895.6119.430.114.961,853
Females51.744.4636.045.532.231,121
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Earnings by gender, 1997 and 2002: All employees Workers
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Evolution of the GEG inside the firm
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OB decomposition, all employees
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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
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GEG at the quantiles: raw and adjusted gaps
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GEG at the quantiles: MM (2005) total gap and gap due to
coefficients 1997 2002
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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
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Potential explanations of the change in GEG: 1997-2002
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Change in GEG at the mean: JMP (1991)
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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)
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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
s? ___________________________________________________ 1 The actual
gap is the coefficient on the male dummy in the quantile
regressions without covariates.
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Change in GEG at the quantiles: MM (2005)
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Change in GEG at the quantiles: Women If the distribution of womens
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, womens 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 s 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 womens characteristics at the bottom (i.e. decrease
in discrimination) is an explanation of the larger fall of the GEG
at the bottom.
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Change in GEG at the quantiles: MM (2005)
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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 mens Xs were slightly better
in 1997 than in 2002, and worsening in mens 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 s, the gap
would have been larger everywhere. Mens s 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 s, however,
is higher at the top than at the bottom. It is increased rewards of
women at the bottom + a slight worsening in mens
characteristics
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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.
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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.
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Potential explanations of the existence of the GEG
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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 .
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Potential explanations of the GEG: bonuses NO, since the
decomposition and regression results for total compensation are
very similar to those of the GEG.
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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
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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
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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
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Distribution of workers by wage levels Auxilliary levels:
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Distribution of workers by wage levels Primary levels:
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Results for workers including levels at the means: Oaxaca-Blinder
decomposition
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Results for workers at the quantiles with and w/o levels No levels
With levels
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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).
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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)
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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)
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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