Spatial Autocorrelation Methods in Identifying Migration Patterns: Case Study of Slovakia

Abstract The collapse of the socialist regime led to significant changes in migration patterns, garnering considerable attention in geographical research. However, despite the increased interest, many studies on internal migration lack a detailed analysis of its spatial aspects. Spatial autocorrelation methods can reveal spatial patterns, but so far they have not been applied in the detailed research of internal migration in post-socialist countries. The aim of this study is to explore the spatial patterns of internal migration with regard to intra-regional and inter-regional migration processes using selected indicators of spatial autocorrelation (Global Moran’s I, Anselin local Moran’s I and Getis-Ord Gi* statistic) with Slovakia as a case study. A partial goal is to evaluate the benefits of applying these methods in the assessment of internal migration. Local indicators of spatial autocorrelation demonstrated significant differentiation of both intra-regional and inter-regional migration processes. The dominant intra-regional process is the decentralization of the population, which is very intensive in the regions of the largest towns and cities. Inter-regional migration displays spatial polarisation, emphasizing the importance of the location of key economic centres. The methodology employed in this study clearly displays the clusters of municipalities with above-average and below-average values. This approach enables the identification and cartographic interpretation of specific municipalities where migration contributes the most to the spatial redistribution of the population. The study serves as a valuable framework for similar analyses, emphasizing the broader applicability of spatial autocorrelation methods in studying migration patterns.