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ISPRS Int. J. Geo-Inf. 2018, 7(1), 17;

Geographically Weighted Regression in the Analysis of Unemployment in Poland

Faculty of Economics and Sociology, University of Lodz, 90-255 Lodz, Poland
Received: 4 September 2017 / Revised: 1 January 2018 / Accepted: 7 January 2018 / Published: 10 January 2018
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The main aim of this paper is an application of Geographically Weighted Regression (which enables the identification of the variability of regression coefficients in the geographical space) in the analysis of unemployment in Poland 2015. The study is conducted using 2015 statistical data for 380 districts (LAU 1) in Poland. The research results show that the determinants of unemployment are diverse in the geographic space and do not have a significant impact on unemployment rates in all spatial units (LAU 1). The existence of clusters of districts, characterised by the influence of the variables and a similar strength of interactions, is confirmed. Geographically Weighted Regression (GWR) proved to be an extremely effective instrument of spatial data analysis. The model had a considerably better fit with empirical data than the global model, and it enabled the drawing of detailed conclusions concerning the local determinants of unemployment in Poland. View Full-Text
Keywords: unemployment; spatial data analysis; GWR; Polish districts unemployment; spatial data analysis; GWR; Polish districts

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Lewandowska-Gwarda, K. Geographically Weighted Regression in the Analysis of Unemployment in Poland. ISPRS Int. J. Geo-Inf. 2018, 7, 17.

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