Autokorelacja przestrzenna współczynnika dzietności w Polsce
Spatial autocorrelation of the total fertility rate in Poland

Summary/Abstract: The total fertility rate (TFR) in Poland has remained below the replacement level for many years, posing a significant challenge in the context of population ageing. The analysis of the spatial autocorrelation of fertility is crucial for examining regional disparities, as it allows the identification of clusters of geographical units with similar fertility levels as well as areas that are heterogeneous in this respect. The aim of this article is to statistically identify geographical dependencies in fertility rates across powiats. The study covers the period between 2002 and 2023. The data were obtained from the Local Data Bank of Statistics Poland, and the analysis used measures and tests of Moran's global and local autocorrelation. The results indicate both temporal and spatial variation in TFR values across powiats and, more broadly, across voivodships. In each analysed year, a statistically significant positive global spatial autocorrelation was observed. In the final years of the study, the values of the global statistic attested to the intensification of the geographical dependence. On the basis of local indicators of spatial autocorrelation, clusters of positive spatial association were identified, namely High-High (HH) clusters (powiats with a relatively high TFR neigbouring powiats with a similarly high TFR), and Low-Low (LL) clusters (powiats with a relatively low TFR neighbouring powiats with a similarly low TFR). For the year 2023, nine such clusters of powiats were identified (in breakdown by voivodships they belonged in). The HH clusters were located in Mazowieckie, Wielkopolskie, Małopolskie, Pomorskie and Łódzkie voivodships, while the LL ones in Warmińsko-Mazurskie, Dolnośląskie, Śląskie and Lubelskie voivodships. Local spatial autocorrelation also singled out spatial outliers, i.e. powiats with a substantially different TFR than the neighbouring ones. The geographical clustering patterns indicate that fertility levels are regionally varied.

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