Income polarization in the Hungarian micro-regional system

Abstract

In this article, the authors introduce the geographical polarization of Hungarian wages. The primary focus was to show the managerial income differences from a lesser analyzed point of view. This part of the International Standard Classification of Occupations (ISCO) was selected based on the prior assumptions, according to which there are significant differences in their salaries, which is closely connected to the economic potential of a given geographic location.

The calculations were applied to show the differences along with two theoretical viewpoints. First of all, the NUTS4 breakdown is sufficiently detailed but not too fragmented; that is why it is possible to represent the regional disparities properly. On the other hand, the database was analyzed based on the ISCO. The four-digit data was aggregated to one digit to have a proper level of classification. The examination of each class separately served as a benchmark to identify the unique characteristics of managers.

A selected range of indicators most commonly used in the international literature was involved and ran on the Hungarian Wage Tariff Database of 2016. Based on the results, it can be concluded that managers have the highest average income and that at the same time, they have the largest standard deviation. However, those working in Agricultural and forestry occupations have larger-than-average differences (this is also supported by the Dua indicator, which is the largest – 1.351 for them), too. The differences between the richest and poorest regions for managers are 1.238 times, which can be considered moderate in regards to the other occupations. This is also supported by the Lorenz curve and the Gini index. The weighted relative standard deviation shows a similar inequality for managers and those working in Agricultural and forestry occupations (17.91 and 17.92 respectively), which are the largest in the examined database. Based on the logarithmic standard deviation, managers face the most extensive level of variance (0.0097).

Along with the selected indicators, it can be seen that the salary differences are the biggest in the case of the managers by NUTS4. With the highest average income, the differences are significant; however, it should be emphasized that similar polarization can be seen in the case of the Agricultural and forestry occupations. These figures are closely connected to territorial differences of GDP, which is supported by the graphic representation.