The analysis of spatial-temporal differences in unemployment rates in Poland by counties in the years 2019-2023

• Autorzy: Dagna Wleklińska

Identyfikatory

DOI

10.29119/1641-3466.2024.201.29

• Języki publikacji: EN

Abstrakty

EN

Purpose: The aim of the article is to identify the spatial differentiation of changes in the unemployment rate in the county system in Poland in the period 2019-2023. The subject of particular interest is the verification of the hypothesis about the existence of spatial dependencies in changes in the level of unemployment rates between counties considered to be neighboring in terms of a given criterion. Design/methodology/approach: The validity of using the methods and tools of spatial econometrics to describe unemployment as one of the most important negative socio-economic phenomena is confirmed by numerous empirical analyses, and in the face of dynamic economic and social changes, it does not lose its importance. The analysis used spatial and space-time econometric models. The spatial structure of dependencies between counties was quantified using the common border matrix. Findings: Research confirms the existence of spatial dependencies in the development of the unemployment rate registered in the counties in Poland. Practical implications: The practical implication of this study comes from the provision of evidence that when it comes to analyzing processes within specific areas, it is essential to account for the spatial relationships between objects, as these relationships significantly influence the outcomes and dynamics observed. Originality/value: The originality of the study comes from the tool used, which enables the analysis of processes through the prism of the structure of relationships between the objects they concern.

Słowa kluczowe

EN

registered unemployment rate; spatial models for time-series and cross-sectional data; spatial interaction; pandemic

PL

zarejestrowana stopa bezrobocia; modele przestrzenne dla szeregów czasowych i danych przekrojowych; interakcja przestrzenna; pandemia

• Wydawca: Wydawnictwo Politechniki Śląskiej
• Czasopismo: Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
• Rocznik: 2024
• Tom: z. 201
• Strony: 379--390
• Opis fizyczny: Bibliogr. 12 poz.

Twórcy

autor

Dagna Wleklińska

• Kazimierz Wielki University in Toruń

• https://orcid.org/0000-0002-8198-1669

Bibliografia

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• 2. Cliff, A.D., Ord, J.K. (1981). Spatial Processes: Models & Applications. London: Pion.
• 3. Cracolini, M.F., Cuffaro, M., Nijkamp, P. (2008). The spatial analysis on Italian unemployment differences. Statistical Methods and Applications, Vol. 18, pp. 275-291, doi: 10.1007/s 10260-007-0087-z
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• 8. Muller-Frączek, A., Pietrzak, M.B. (2012). Analiza stopy bezrobocia w Polsce w ujęciu przestrzenno-czasowym. Oeconomia Copernicana, No. 2, pp. 43-55, doi: 10.12775/OeC.2012.008
• 9. Okun, A. (1962). Potential GNP: its Measurement and Significance. Proceedings of the Business and Economics Section. American Statistical Association, pp. 98-103, doi: 10.12691/ijefm-7-1-4
• 10. Pareira, S., Turkman, F., Correia, L. (2017). Spatio-temporal analysis of regional unemployment rates: A comparison of model-based approaches. Statistical Journal, 16(4), doi: 10.48550/arXiv.1704.05767
• 11. Schabenberger, O., Gotway, C.A. (2005). Statistical Methods for Spatial Data Analysis. London/New York: Champion & Hall/CRC, Boca Raton.
• 12. Suchecki, B. (2010). Ekonometria Przestrzenna. Metody i Modele Analizy Danych Przestrzennych. Warsaw: C.H. Beck.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).