This document compares different methods for analyzing the gender wage gap in Poland using data from the Polish Labour Force Survey of 2012. It finds that the adjusted gender wage gap is 20% according to the methods analyzed, which is twice as large as the raw gap, indicating evidence of a glass ceiling. The different methods produced generally similar results on average but with large variations. After correcting for selection bias and common support, the differences between methods increased.

1. Gender wage gap in Poland
Gender wage gap in Poland
A comparative analysis of available methods
Lucas Augusto van der Velde
PhD Candidate
Research Assistant in GRApE
Faculty of economic sciences
University of Warsaw
May 31, 2014

2. Gender wage gap in Poland
Table of contents
1 Introduction
2 Methods & Specications
3 Data
4 Results
5 Conclusions

3. Gender wage gap in Poland
Introduction
Introduction
Motivation
Our work

4. Gender wage gap in Poland
Introduction
Introduction
Motivation
Our work
Goal: Provide a guide for the practitioner

5. Gender wage gap in Poland
Introduction
Introduction
Motivation
Our work
Goal: Provide a guide for the practitioner
How: Compare the gender wage gap in dierent methods and specications

6. Gender wage gap in Poland
Introduction
Introduction
Motivation
Our work
Goal: Provide a guide for the practitioner
How: Compare the gender wage gap in dierent methods and specications
Data: Polish LFS 2012

7. Gender wage gap in Poland
Methods Specications
Methods under analysis
Linear regressions
Oaxaca Blinder decompositions (5)
John, Murphy and Pierce
Di Nardo, Fortin and Lemieux
Machado Mata
Nopo
Firpo, Fortin and Lemieux

8. Gender wage gap in Poland
Methods Specications
Summary
How should the perfect decomposition method look like?
Characteristics OB JMP DFL MM Nopo FFL

9. Gender wage gap in Poland
Methods Specications
Summary
How should the perfect decomposition method look like?
Characteristics OB JMP DFL MM Nopo FFL
Selection Bias OK OK OK

10. Gender wage gap in Poland
Methods Specications
Summary
How should the perfect decomposition method look like?
Characteristics OB JMP DFL MM Nopo FFL
Selection Bias OK OK OK
Dimensionality Curse OK OK OK OK OK

11. Gender wage gap in Poland
Methods Specications
Summary
How should the perfect decomposition method look like?
Characteristics OB JMP DFL MM Nopo FFL
Selection Bias OK OK OK
Dimensionality Curse OK OK OK OK OK
Detailed decomposition OK OK OK

12. Gender wage gap in Poland
Methods Specications
Summary
How should the perfect decomposition method look like?
Characteristics OB JMP DFL MM Nopo FFL
Selection Bias OK OK OK
Dimensionality Curse OK OK OK OK OK
Detailed decomposition OK OK OK
Quantile decomposition OK OK OK OK

13. Gender wage gap in Poland
Methods Specications
Summary
How should the perfect decomposition method look like?
Characteristics OB JMP DFL MM Nopo FFL
Selection Bias OK OK OK
Dimensionality Curse OK OK OK OK OK
Detailed decomposition OK OK OK
Quantile decomposition OK OK OK OK
Common Support OK

14. Gender wage gap in Poland
Methods Specications
Summary
How should the perfect decomposition method look like?
Characteristics OB JMP DFL MM Nopo FFL
Selection Bias OK OK OK
Dimensionality Curse OK OK OK OK OK
Detailed decomposition OK OK OK
Quantile decomposition OK OK OK OK
Common Support OK
Functional Form OK OK

15. Gender wage gap in Poland
Methods Specications
Summary
How should the perfect decomposition method look like?
Characteristics OB JMP DFL MM Nopo FFL
Selection Bias OK OK OK
Dimensionality Curse OK OK OK OK OK
Detailed decomposition OK OK OK
Quantile decomposition OK OK OK OK
Common Support OK
Functional Form OK OK
Compare across time OK OK OK

16. Gender wage gap in Poland
Methods Specications
What we expect with respect to...
The selection bias: the adjusted gap increases when women experience
more selection than men
The addition of new variables increases the adj. gap when variation within
is larger than between
The common support: the adj. gap increases when the non-matched
women are better endowed than men.

17. Gender wage gap in Poland
Methods Specications
What we expect with respect to...
The selection bias: the adjusted gap increases when women experience
more selection than men
The addition of new variables increases the adj. gap when variation
within is larger than between
The common support: the adj. gap increases when the non-matched
women are better endowed than men.

18. Gender wage gap in Poland
Methods Specications
What we expect with respect to...
The selection bias: the adjusted gap increases when women experience
more selection than men
The addition of new variables increases the adj. gap when variation within
is larger than between
The common support: the adj. gap increases when the non-matched
women are better endowed than men.

19. Gender wage gap in Poland
Data
The Sample
Polish Labour Force Survey (2012)
Male Female C-Support
Hourly wage 11.91 11.00 0.12
Age 40.64 41.29 0.04
Experience 19.15 17.89 0.07
Agriculture 0.41 0.21 0.32
Construction 0.15 0.01 0.39
Industry 0.35 0.43 0.12
Services 0.08 0.35 0.49
Secondary 0.75 0.62 0.20
Tertiary 0.16 0.33 0.28
Social sciences 0.07 0.28 0.40
Medicine 0.01 0.08 0.26
Engeneering 0.59 0.18 0.65
Teaching 0.01 0.03 0.11

20. Gender wage gap in Poland
Data
Dierent specications
Basic: Age, experience, education levels, married, kids, rural, cities,
Mazowieckie
Industry: Industry dummies for agriculture (reference), manufacture,
construction and services.
Industry plus: Industry + rm size and ownership type
Occupations: 9 occupational dummies (ISCO-1 codes)
Tenure: Basic + tenure
Education: 9 educational eld dummies

21. Gender wage gap in Poland
Results
Comparison across methods

22. Gender wage gap in Poland
Results
Comparison across specications

23. Gender wage gap in Poland
Results
Comparison of the methods

24. Gender wage gap in Poland
Conclusions
Conclusions
With respect to the gap
The adjusted gap is 20% of female gap - two times the size of the raw gap.
There is evidence of a glass ceiling in Poland
We did not nd evidence of segregation on industries nor on eld of study
Comparison of methods
On average similar results, but great variations between methods.
After correcting for the selection bias and the common support the
dierences were greater

25. Gender wage gap in Poland
Conclusions
Questions or suggestions?

26. Gender wage gap in Poland
Conclusions
Questions or suggestions?
Thank you for your attention

27. Gender wage gap in Poland
Conclusions
References
Blinder, A. (1973): Wage Discrimination: Reduced Form and Structural
Estimates, Journal of Human Resources, 8, 436-455.
DiNardo, J. , N. Fortín, and T. Lemieux, 1996 Labor market institutions and the
distribution of wages, 1973-1992: a Semi-parametric approach Econometrica,
Vol. 64, No.5, 1001 -1044.
Firpo, S., Fortín, N., and Lemieux, T. 2009 Unconditional Quantile regressions,
Econometrica, Vol. 77, No. 3, 953-973
Fortín, N., T. Lemieux and S. Firpo, 2010 Decomposition methods in
Economics NBER Working paper 16045
Juhn, C., K. M. Murphy, and B. Pierce (1993): Wage Inequality and the Rise in
Returns to Skill, Journal of Political Economy, 101, 410-442.
Machado, J. A. F., and J. Mata (2005): Counterfactual Decomposition of
Changes in Wage Distributions using Quantile Regression, Journal of Applied
Econometrics, 20, 445-465.
Nopo, H(2008) Matching as a Tool to Decompose Wage Gaps, The review of
Economics and Statistics, May 2008, vol. 90, No. 2, Pages 290 299.