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The spatial differentiation of salaries is the subject of many scientific studies, both theoretical and empirical. One of the factors determining remuneration in Poland is the structure and type of business activity, specific for a given region and depending on its poviats (counties) in terms of the level of the average gross monthly salary by means of spatial autocorrelation statistical methods. The analysed statistical data for 2010–2019 come from the Local Data Bank (Bank Danych Lokalnych – BDL) of Statistics Poland. Global and local measures were used in the analysis. The calculation of the global parameters of spatial autocorrelation was based on the I Moran and C Geary statistics, while the Ii Moran statistic, which belongs to local spatial indicators from the LISA group (Local Indicators of Spatial Association), was used to identify the local autocorrelation. The statistical significance of the global statistics was verified by means of a randomisation approach based on theoretical moments.The I Moran and C Geary global statistics indicated a significant (very weak or weak) and positive spatial autocorrelation between poviats in terms of the level of average gross monthly salaries in 2010–2019, which shows the existence of spatial poviat structures of similar values, i.e. clusters with high or low values of average salaries. The increase in I Moran’s statistics and the growth of the C Geary in the analysed period indicate a decrease in the differentiation of average monthly salaries between poviats, thus signifying an increase in the dependence of spatial autocorrelation. The analysis of the results of the obtained local statistics allowed the determination of clusters of similar poviats in Poland, e.g. Mazowiecki, Pomorski and Śląski. Furthermore, the results of the analysis indicated the presence of outlier poviats.

The use of spatial statistics in the analysis of salaries at poviat level in Poland