Eurostat estimated that in 2011 in the EU women earned on average 16.2% less than men. This rate (GPG – Gender Pay Gap) varies e.g. among EU countries, economic sectors. We can also observe that at the GPG rate affect age, education, job seniority of employees and size of enterprise among other. The wage differences between men and women are largely explained on the basis of human capital theory (see e.g. Haager 2000, Polachek 2004) and the discrimination theory (see e.g. Becker 1971). This phenomenon has a social dimension as well as economic importance (see discussion presented in Klasen 1999, Seguino 2000, Blecker and Seguino 2002, Löfström 2009, Sinha, Raju i Morrison 2007). Situation of women in the labor market is subject to European Union policy. Prevention of discrimination against women has been included in Strategy for equality between women and men 2010-2015.
The aim of the study was to estimate the impact of various factors on the level of the wages inequality between men and women. In the analysis there were used one equation econometric models.
Analysis was provided upon the European Union Structure of Earnings Survey (SES) data collected in 2006. There were used aggregated data, that Eurostat calls Metadata. SES is a survey conducted in accordance with the Council Regulation No. 530/1999 and the Commission Regulation No. 1916/2000 as amended by Commission Regulation No. 1738/2005. The SES for 2006 is the second of a series of four yearly. The SES is a survey providing information on relationships between the level of remuneration, individual characteristics of employees and their employer. Set of characteristics of employees included sex, age, occupation, job seniority, educational level, type of employment (full-time or part-time). Data on their employers are as follows: economic activity, size and location of the enterprise. The statistics of the SES refer to the enterprises with at least 10 employees.
Data on employment and wages are encompassed in the database that contain different characteristics, as presented in Figure 1.
Figure 1. Structure of SES database
To measure income inequality is often used GPG (Gender Pay Gap) indicator. GPG represents the difference between average gross hourly earnings of male paid employees (GHEM) and of female paid employees (GHEF) as a percentage of average gross hourly earnings of male paid employees.
GPG = (1 - GHEM/GHEF)×100 (1)
where (GHEM/GHEF)×100 = HE_FPCM is publicised by Eurostat.
In the analysis there were estimated one equation econometric models where dependent variable was GPG. In each model there were four types of independent variables: Activity, Wages, Fem and dummy variables.
Activity(i) – activity rate in the i-th country defined as labor force divided by population in working age in age group 20-64 (see strategy Europe 2020).
Wages(i,j) – wages rate calculated as:
Wages(i,j) = GHE(i,j)/GHE(i) (2)
Where GHE(i,j) – average hourly earnings of employees in i-th country and j-th group of employees, GHE(i) – average hourly earnings of employees in i-th country.
Fem (i,j) – feminization rate calculated as:
FEM(i,j) = EF(i,j)/( EF(i,j)+ EM(i,j)) (3)
Where EF(i,j) – number of employment women in i-th country and j-th group of employees, EM(i,j) – number of employment men in i-th country and j-th group of employees.
Dummy variables represent impact on the wage inequality such factors as: economic sector, level of education, type of employment contract, occupation, group of age, group of job seniority, size of enterprise.
The results indicated that both the feminization rate and activity of women are significantly associated with the GPG. Also such factors as economic sector, level of education, occupation, group of age differentiate wages between men and women.
References
Polachek S.W., How the Human Capital Model Explains Why the Gender Wage Gap Narrowed, IZA Bonn Discussion Paper No. 1102, April 2004.
Haager D.M., How do Investments in Human Capital Differentially Affect Gender Income? An Analysis of the Gender Wage Gap, The Park Place Economist, Vol. VIII, 2000.
Becker G.S., The Economics of Discrimination, 1971.
Klasen S.: Does Gender Inequality Reduce Growth and Development? Evidence from Cross-Country Regressions, World Bank Working Paper Series No. 7, 1999.
Morrison A., Raju D. Sinha N.: Gender Equality, Poverty and Economic Growth, Policy World Bank Policy Research Working Paper No. 4349, 2007.
*The project was funded by the National Science Centre, decision number DEC-2011/01/B/HS4/06346. |