This paper reports the results of a Blinder-Oaxaca style decomposition analysis on Hungarian matched employer-employee data to study the gender pay-gap. We carry out the decomposition by Random Forest regressions. The raw gap in our horizon (2008-2016) is increasing, but we find that the wage...

This paper reports the results of a Blinder-Oaxaca style decomposition analysis on Hungarian matched employer-employee data to study the gender pay-gap. We carry out the decomposition by Random Forest regressions. The raw gap in our horizon (2008-2016) is increasing, but we find that the wage...

The Blinder-Oaxaca decomposition was developed in order to detect and characterize discriminatory treatment, and one of its most frequent use has been the study of wage discrimination. It recognizes that the mere difference between the average wages of two groups may not mean discrimination (in...

We estimate the gender pay gap with the traditional OLS based Blinder-Oaxaca decomposition, and with an extension using Random Forest (RF) regressions on Hungarian data for the years 2008-2016. Random Forests perform better as predictors out-of-sample and yield consistently lower estimates for...

The Blinder-Oaxaca decomposition was developed in order to detect and characterize discriminatory treatment, and one of its most frequent use has been the study of wage discrimination. It recognizes that the mere difference between the average wages of two groups may not mean discrimination (in...

We estimate the gender pay gap with the traditional OLS based Blinder-Oaxaca decomposition, and with an extension using Random Forest (RF) regressions on Hungarian data for the years 2008-2016. Random Forests perform better as predictors out-of-sample and yield consistently lower estimates for...