gender wage gap in poland
TRANSCRIPT
The Gender Wage Gap in Poland: Measurement,
Decompositions and Interpretation
Karolina Goraus
Warsaw University
Faculty of Economic Sciences
Outline
Introduction
Data and research methods
Measurment of raw gender wage gap
Oaxaca-Blinder and Nopo decompositions
Analysis of each quarter in the period 1995-2009
Conclusions
Aim of the study
Measure and decompose gender wage gap in Poland with the usage of different methods
Among others, apply the technique of decomposition developed by Nopo(2008), that, to the best of my knowledge, has not yet been used for the Polish data
Apply chosen methods to analyse relatively long period of time
Assess the importance of the component of the gender wage gap in Poland that might possibly represent discrimination
Motivation
Gender wage gap relevant in assessment of the relative position of females
Question if economic position of females in Poland has improved along with the positive economic performance of the country remains open
Poland had a delay in having its scientists or politicians concentrated on gender wage gap issue
Data and research methods
Data: Survey of Economic Activity of the Population, quarterly data from 1995 to 2009
Research methods:
- „standard” way of measuring gender wage gap
- Oaxaca-Blinder decomposition
- technique of decomposition developed by Nopo (2008)
„Standard” way of measuring gender wage gap
Calculation of the difference in the average wages of females and males in the population
Expressed as percentage of average females' or males' wage
Additionally I assess the statistical significance of this difference with two-group mean-comparison test
Oaxaca-Blinder decomposition
Very famous tool to decompose wage gaps between two groups in the society
Two components of gender wage gap:
- first one attributable to difference in characteristics
- second one to difference in rewards that these characteristics have for females and males
Wage equations
Decomposition of Nopo
Oaxaca-Blinder fails to recognise gender differences in the supports
Decomposition into four components attributed to:
(DM) differences between two groups of males – those whose characteristics can be matched to female characteristics and those who cannot
(DX) differences in the distribution of characteristics of males and females over the common support
(D0) unexplained part
(DF) differences in characteristics between two groups of females, those who have characteristics that can be matched to male characteristics and those who cannot
Measuring raw gender wage gap
Period: first quarter of 1995
Significant difference in wages, that can be expressed as 29% of the average female's wage, or 22% of the average male's wage
Measuring raw gender wage gap
Period: last quarter of 2009
Significant difference which equals 22.8% of the average female's wage in this period, or 18.6% of the average male's wage
Decompositions for first quarter of 1995 - Oaxaca
Wage equation for males
Decompositions for first quarter of 1995 - Oaxaca
Wage equation for females
Decompositions for first quarter of 1995 - Oaxaca
- mean of the log wages is 5.99 for males and 5.77 for females
- wage gap of 0.23
- unexplained component of 0.3
Decompositions for first quarter of 1995 - Nopo
- wage gap of 0.28
- unexplained component of 0.32
Decompositions for last quarter of 2009 - Oaxaca
- mean of the log wages is 7.38 for males and 7.17 for females
- wage gap of 0.21
- unexplained component of 0.31
Decompositions for last quarter of 2009 - Nopo
- wage gap of 0.23
- unexplained component of 0.28
Summary of the findings
- raw gap expressed as percentage of females wage has decreased by around 6%
- although raw gender wage gap is decreasing the unexplained component that is possibly caused by discrimination stays at rather stable level
Analysis of all quarters from 1995 to 2009
95
-03
95
-06
95
-09
95
-12
96
-03
96
-06
96
-09
96
-12
97
-03
97
-06
97
-09
97
-12
98
-03
98
-06
98
-09
98
-12
99
-03
99
-06
99
-09
99
-12
00
-03
00
-06
00
-09
00
-12
01
-03
01
-06
01
-09
01
-12
02
-03
02
-06
02
-09
02
-12
03
-03
03
-06
03
-09
03
-12
04
-03
04
-06
04
-09
04
-12
05
-03
05
-06
05
-09
05
-12
06
-03
06
-06
06
-09
06
-12
07
-03
07
-06
07
-09
07
-12
08
-03
08
-06
08
-09
08
-12
09
-03
09
-06
09
-09
09
-12
0
0,05
0,1
0,15
0,2
0,25
0,3
Raw difference as % of females' wage
Analysis of all quarters from 1995 to 2009
95
-03
95
-06
95
-09
95
-12
96
-03
96
-06
96
-09
96
-12
97
-03
97
-06
97
-09
97
-12
98
-03
98
-06
98
-09
98
-12
99
-03
99
-06
99
-09
99
-12
00
-03
00
-06
00
-09
00
-12
01
-03
01
-06
01
-09
01
-12
02
-03
02
-06
02
-09
02
-12
03
-03
03
-06
03
-09
03
-12
04
-03
04
-06
04
-09
04
-12
05
-03
05
-06
05
-09
05
-12
06
-03
06
-06
06
-09
06
-12
07
-03
07
-06
07
-09
07
-12
08
-03
08
-06
08
-09
08
-12
09
-03
09
-06
09
-09
09
-12
0
0,2
0,4
0,6
0,8
1
1,2
1,4
1,6
1,8
2
Oaxaca - Discrimination as % of raw wage gap
Analysis of all quarters from 1995 to 2009
95
-03
95
-06
95
-09
95
-12
96
-03
96
-06
96
-09
96
-12
97
-03
97
-06
97
-09
97
-12
98
-03
98
-06
98
-09
98
-12
99
-03
99
-06
99
-09
99
-12
00
-03
00
-06
00
-09
00
-12
01
-03
01
-06
01
-09
01
-12
02
-03
02
-06
02
-09
02
-12
03
-03
03
-06
03
-09
03
-12
04
-03
04
-06
04
-09
04
-12
05
-03
05
-06
05
-09
05
-12
06
-03
06
-06
06
-09
06
-12
07
-03
07
-06
07
-09
07
-12
08
-03
08
-06
08
-09
08
-12
09
-03
09
-06
09
-09
09
-12
0,000000
0,200000
0,400000
0,600000
0,800000
1,000000
1,200000
1,400000
1,600000
1,800000
2,000000
Nopo – Discrimination as % of raw wage gap
Conclusions
(1) Raw gender wage gap in Poland expressed as percentage of females' average wage has decreased by around 6% between first quarter of 1995 and last quarter of 2009, and at the end of the analysed period was on the level of 23%
(2) Component of Oaxaca-Blinder decomposition that can be possibly caused by the discrimination, expressed as the percentage of the raw wage gap has slightly increased over the analysed period, as did the respective component of the Nopo decomposition, expressed in the same way
(3) The raw gender wage gap decreased over time mostly because females have even more “valuable” characteristics, but the adjusted gender wage gap that is most probably due to discrimination stays almost unchanged
Thank you for your attention:]