Using structural equation modeling to analyze unemployment in districts
DOI:
https://doi.org/10.12775/EQUIL.2010.010Keywords:
structural equation model, SEM, unemployment in districts, latent variablesAbstract
The aim of this article is to analyze and discover reasons for district?s unemployment rate variety in Poland. According to theory and published findings the study concentrates on relationships between unemployment rate in region and economic although infrastructure and social factors. The study was performed using structural equation modelling (SEM) in which relationships between dependent and independent although latent and measurable variables can be include. As a latent variable in this research transport infrastructure was adopted. It was defined using urbanization rate, road and communication way length. The research demonstrated the existence of non-positive relationships between unemployment rate in district and urbanization rate. Low educational level and high percentage of people employed in agriculture increase unemployment level in districts. Good transport infrastructure has positive influence on number of vacancy and unemployment rate. Results of the research allow to analyze in detail the reasons for unemployment rate variety in various districts.
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References
Borowski P. (2004), Badanie bezrobocia metodą grupowania struktury na przykładzie woj. Lubelskiego, ?Wiadomości Statystyczne?, nr 2/2004,
Curran P.J., Bollen K.A., Paxton P., Kirby J., Chen F. (2002), The Noncentral Chi-square Distribution in Misspecified Structural Equation Models: Finite Sample Results from a Monte Carlo Simulation, ?Multivariate Behavioral Research? , Vol. 37, No. 1,
Kaplan D. (2000), Structural Equation Modeling: Foundations and Extensions, Sage Publications.
Loehlin J.C. (1987), Latent variable models: An introduction to factor, path, and structural analysis, Erlbaum,,
Matusik St.(2008), Kształtowanie się stopy bezrobocia w gminach woj. Małopolskiego, ?Wiadomości Statystyczne? nr 1/2008,
Pearl J. (200), Causality. Models, reasoning and inference, Cambrige,
Rozpędowska-Matraszek D. (2006), Prognozowanie bezrobocia według województw, ?Wiadomości Statystyczne?, nr 12,
Śleszyński P. (2007), Zmiany liczby bezrobotnych w gminach, ?Wiadomości Statystyczne?, nr 2/2007.
Tokarski T., (2005), Regionalne zróżnicowanie rynku pracy, ?Wiadomości Statystyczne?, nr 11/2005,