we study the size and evolution of the gender wage gap in Poland. We employ two different methods a parametric Oaxaca-Blinder decomposition and the non-parametric Nopo decomoposition. We show that since transition the adjusted gender wage gap in Poland was always larger than the raw gap.

1. The Gender Wage Gap in Poland: Measurement,
Decompositions and Interpretation
Karolina Goraus
Warsaw University
Faculty of Economic Sciences

2. 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

3. 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

4. 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

5. 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)

6. „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

7. 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

8. 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

9. 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

10. 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

11. Decompositions for first quarter of 1995 - Oaxaca
Wage equation for males

12. Decompositions for first quarter of 1995 - Oaxaca
Wage equation for females

13. 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

14. Decompositions for first quarter of 1995 - Nopo
- wage gap of 0.28
- unexplained component of 0.32

15. 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

16. Decompositions for last quarter of 2009 - Nopo
- wage gap of 0.23
- unexplained component of 0.28

17. 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

18. Analysis of all quarters from 1995 to 2009
95-0395-0695-0995-1296-0396-0696-0996-1297-0397-0697-0997-1298-0398-0698-0998-1299-0399-0699-0999-1200-0300-0600-0900-1201-0301-0601-0901-1202-0302-0602-0902-1203-0303-0603-0903-1204-0304-0604-0904-1205-0305-0605-0905-1206-0306-0606-0906-1207-0307-0607-0907-1208-0308-0608-0908-1209-0309-0609-0909-12
0
0,05
0,1
0,15
0,2
0,25
0,3
Raw difference as % of females' wage

19. Analysis of all quarters from 1995 to 2009
95-0395-0695-0995-1296-0396-0696-0996-1297-0397-0697-0997-1298-0398-0698-0998-1299-0399-0699-0999-1200-0300-0600-0900-1201-0301-0601-0901-1202-0302-0602-0902-1203-0303-0603-0903-1204-0304-0604-0904-1205-0305-0605-0905-1206-0306-0606-0906-1207-0307-0607-0907-1208-0308-0608-0908-1209-0309-0609-0909-12
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

20. Analysis of all quarters from 1995 to 2009
95-0395-0695-0995-1296-0396-0696-0996-1297-0397-0697-0997-1298-0398-0698-0998-1299-0399-0699-0999-1200-0300-0600-0900-1201-0301-0601-0901-1202-0302-0602-0902-1203-0303-0603-0903-1204-0304-0604-0904-1205-0305-0605-0905-1206-0306-0606-0906-1207-0307-0607-0907-1208-0308-0608-0908-1209-0309-0609-0909-12
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

21. 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

22. Thank you for your attention:]