Abstract:

There are various models of the distribution of earnings which constitute the most important share of income of individuals. One of the most considerable of these models is the regression modeling developed by Jacob Mincer, in which labor earnings are investigated by employing human capital theory. The aim of the study is to measure the earnings inequality between genders in Turkey by expanding the basic Mincer earnings model. To this end, the cross-sectional data set of the Survey of Income and Living Conditions (SILC) published by the Turkish Statistical Institute (TurkStat) for the years 2007 and 2017 was used in the study. The gender variable was appended to the basic Mincer earnings equation and the analysis was performed with the generalized ordinal logit model. In the next step of the analysis, the Blinder-Oaxaca decomposition method was employed for the estimation and dimension of the difference in gender earnings. The findings revealed that while the effect of education on earnings is decreasing, but experience exhibited a concave structure and its effect on earnings is increased. The probability of men being in the high-earning group is decreased between genders, but it was concluded that women are still in the disadvantaged group according to the Blinder-Oaxaca Decomposition analysis.

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