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...

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 gender earnings gap can be attributed either to the different distribution of males and females across jobs or to within job biases in favour of men. The latter is frequently called the wage structure effect, and it may be interpreted as wage discrimination against women. In this paper we...

We estimate heterogeneous wage structure effects for country-pairs within the EU by the Causal Forest algorithm, then identify groups of workers with the highest and lowest discrepancies in terms of wage differentials. We find that, in the East-West comparison, age is the most consistently...

It is well known that the size of the informal (black or grey) economy causes serious fiscal problems for Hungary. This study makes an attempt to quantify the budgetary and macroeconomic effects of different ways of widening the formal sector (whiteningʺ) with the help of a model. It turns out...