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Spatial Analysis Of Foreign Migration In Poland In 2012 Using Geographically Weighted Regression

100%
Lewandowska-Gwarda K.
Comparative Economic Research. Central and Eastern Europe
|
2014
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vol. 17
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issue 4
137-154
EN
Migration has a principal influence on countries’ population changes. Thus, the issues connected with the causes, effects and directions of people’s movements are a common topic of political and academic discussions. The aim of this paper is to analyse the spatial distribution of officially registered foreign migration in Poland in 2012. GIS tools are implemented for data visualization and statistical analysis. Geographically weighted regression (GWR) is used to estimate the impact of unemployment, wages and other socioeconomic variables on the foreign emigration and immigration measure. GWR provides spatially varying estimates of model parameters that can be presented on a map, giving a useful graphical representation of spatially varying relationships.
2
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Female unemployment and its determinants in Poland in 2016 from the spatial perspective

88%
Lewandowska-Gwarda K.
Oeconomia Copernicana
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2018
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vol. 9
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issue 2
183-204
EN
Research background: Through the cultural progress and socio-economic development in Poland women have obtained the same rights as men in the labour market. Nevertheless, they continuously face discrimination and the difficulty, resulting from their traditional role, in finding or maintaining employment. Purpose of the article: The main objective of this study was an analysis of female unemployment and its determinants in Poland in 2016 from the spatial perspective. The following research questions were also specified: Is female unemployment dependent on social factors (do they play the key role)? Are the factors determining the level of female unemployment spatially diversified? Is the GWR model an effective tool in analysis of female unemployment? Methods: The research applied GIS and spatial analysis methods including Geographically Weighted Regression, which enables the identification of the variability of regression coefficients in the geographical space. The analysis was carried out based on statistical data presenting the share of unemployed women in the working age population for 380 Polish districts (NUTS 4, LAU 1) in 2016. Findings & Value added: The research results showed that in the period 2003-2016 the female unemployment was getting lower, but it was still higher than men. It was also spatially diversified. Moreover, the determinants of female unemployment were diverse in the geographic space and did not have a significant impact on the variable in all spatial units. The existence of clusters of districts, characterised by similar interactions and its strength, was also confirmed. The results of this analysis proved that non-economic (social) factors largely affected the level of female unemployment in Poland in 2016. Using GWR enabled drawing detailed conclusions concerning the determinants of female unemployment in Poland, it proved to be an effective tool for the analysis of this phenomenon.
3
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Społeczno-ekonomiczne i przestrzenne uwarunkowania popytu na nowe samochody w Polsce

63%
Kudłak R., Kisiała W., Gadziński J., Dyba W., Kołsut B., Stryjakiewicz T.
Studia Regionalne i Lokalne
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2017
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issue 2(68)
119-139
PL
Celem artykułu jest identyfikacja oraz analiza przestrzennego zróżnicowania uwarunkowań społeczno-ekonomicznych kształtujących popyt na rynku samochodowym wśród klientów indywidualnych. W postępowaniu badawczym zmierzającym do realizacji założonego celu wykorzystano metody i modele ekonometrii przestrzennej. Zakresem przestrzennym objęto Polskę w układzie powiatów, a zakres czasowy wyznaczają lata 2010–2015. Wyniki badania dowiodły, że do pozacenowych czynników kształtujących popyt na nowe samochody w Polsce należy zaliczyć przede wszystkim poziom zamożności potencjalnych konsumentów. Uzupełniającą rolę odgrywały: sytuacja demograficzna, poziom rozwoju lokalnego oraz poziom zaspokojenia potrzeb motoryzacyjnych. Pogłębiona analiza w postaci geograficznie ważonej regresji (GWR) wykazała, że zidentyfikowane uwarunkowania wykazują zmienność przestrzenną, co może uzasadniać duże zróżnicowanie poziomu motoryzacji w Polsce.
EN
The article seeks to identify socio-economic conditions that affect the demand of individual consumers for cars and to analyze spatial differences in these conditions. To achieve this objective, econometric modelling is conducted. The analysis was conducted in all poviats in Poland and covered the years 2010-2015. The findings show that the demand for new cars is stimulated by incomes of potential consumers and by a net in-migration, while the level of unemployment together with prices of complementary goods (especially petrol prices) negatively affect the demand for cars. Moreover, geographically weighted regression shows that the identified conditions differ across the country, which may explain the noticeable differences in the level of motorization between poviats.
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