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Spatial Autocorrelation of the Gender Pay Gap Indicator Across the Macroregions of the European Union

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  • Matuszewska-Janica Aleksandra

    (Warsaw University of Life Sciences)

Abstract

Research background The unadjusted gender pay gap (GPG) is one of the indicators that measure progress towards SDG5. There is considerable variability in the values of this indicator among the individual countries and regions of the EU. However, due to the effects resulting from the neighbouring economies’ interactions, spatial autocorrelation (SA) should be taken into account when analysing these indicators, especially at the regional level. Purpose The main aim of the analysis is the identification of SA of the GPG across the EU countries and macroregions. Research methodology The analysis covers Eurostat data from the Structure of Earnings Survey. Global Moran’s I and Geary’s C, and local Moran’s I are used to examine SA. The results The results show that there is no SA of the GPG in EU countries, but for the macroregions level, are identified regions where this type of autocorrelation does exist. This means that for analysed phenomenon geographical proximity is only relevant in selected areas of the EU. These differences may be due to the uneven distribution of economic activities and related infrastructure, the education and skills of the labour force or population movements. This, in turn, leads directly to different wage levels and different levels of the GPG. Novelty Research on the GPG is dominated by approaches that do not take spatial relationships into account. This analysis complements the few studies to date that take into account the SA of the GPG regions across the EU.

Suggested Citation

  • Matuszewska-Janica Aleksandra, 2025. "Spatial Autocorrelation of the Gender Pay Gap Indicator Across the Macroregions of the European Union," Folia Oeconomica Stetinensia, Sciendo, vol. 25(1), pages 180-200.
  • Handle: RePEc:vrs:foeste:v:25:y:2025:i:1:p:180-200:n:1009
    DOI: 10.2478/foli-2025-0009
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    Keywords

    gender pay gap; SDG 5; European Union; regions; spatial autocorrelation;
    All these keywords.

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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