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Spatial And Spatiotemporal Models Of Unemployment Rate In Poland

Author

Listed:
  • Iwona Müller-Fraczek

    (Nicolaus Copernicus University)

  • Michal Bernard Pietrzak

    (Nicolaus Copernicus University)

Abstract

The article show interest in modelling of economic processes which are characterized by spatial dependence. An unemployment rate indicating a level of socio-economic development of regions constitutes one of such processes. The correct quantitative description of this process, as one of more important negative socio-economic phenomena, is an important task of econometrics, in particular, of spatial econometrics. The purpose of the article is to provide a spatial analysis of the unemployment rate registered at the end of each year in Polish poviats. The research covers the period of 2004-2009. Two approaches to modelling are used - spatial and spatiotemporal. The neighbourhood matrix based on the common border of poviats is applied to reflect the strength and direction of spatial relations. There are used two exogenous variables: investments and entities of the economy recorded, both per capita. In the spatial as well as in the spatiotemporal approach the main tendencies of the change of the unemployment rate are described with a spatial linear trend. All of the received models have good economic and statistic properties and they could be used for further analysis.

Suggested Citation

  • Iwona Müller-Fraczek & Michal Bernard Pietrzak, 2012. "Spatial And Spatiotemporal Models Of Unemployment Rate In Poland," Oeconomia Copernicana, Institute of Economic Research, vol. 3(2), pages 43-55, June.
  • Handle: RePEc:pes:ieroec:v:3:y:2012:i:2:p:43-55
    DOI: 10.12775/OeC.2012.008
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    More about this item

    Keywords

    spatial econometrics; unemployment rate; spatial model; spatiotemporal model;
    All these keywords.

    JEL classification:

    • J08 - Labor and Demographic Economics - - General - - - Labor Economics Policies
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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