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Regional Unemployment in Germany: a spatial panel data analysis

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  • Franziska Lottmann

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    Abstract

    This empirical paper wants to analyze determinants for regional differences in German unemployment rates using a spatial panel model. The analysis of regional differences is of particular interest in the German case due to its specific history. Twenty-two years after German reunification, there are still structural differences between both parts affecting economic activity. We identify the driving factors in the whole of Germany as well as in East and West Germany separately. To our best knowledge, this study is the first contribution investigating regional unemployment in the reunified Germany. We provide evidence of spatial dependence in regional unemployment data. Taking into account theoretical contributions to this literature, we exploit 24 possible explanatory variables on 412 German districts for the period from 1999 until 2007. To select the relevant variables for our model, we apply a two-step model selection procedure. Firstly, we divide our variables into three groups according to theoretical importance. Secondly, we regress regional unemployment rates on different combinations of variables where the essential variables are always contained. As unemployment data also exhibit temporal dependence, we specify both a static and a dynamic spatial panel model. The spatial econometric literature provides various types of spatial models. To decide which type of spatial model is appropriate in our context, we apply the specification test by Debarsy and Ertur (2010, Reg. Sci. Urban Econ.). The static model specification is estimated using the quasi-maximum likelihood estimator proposed in Lee and Yu (2010, J. Econometrics) and the dynamic model is estimated using the quasi-maximum likelihood estimator proposed by Lee and Yu (2010, Econometric Theory). To incorporate the spatial information into the model, we construct different spatial weights matrices. On the one hand, we use the binary contiguity matrix and, on the other, we apply a distance-based spatial weights matrix as well as the matrix proposed in Molho (1995, J. Reg. Sci.). We extend the existing literature by the following two aspects: Firstly, we apply both a static and a dynamic spatial panel model. Hence, we exploit the panel dimension of our data and, in addition to that, we account for both spatial and temporal dependence in the data. Our results show that the spatial dynamic panel model fits the data in the best way. Secondly, we provide evidence for regional unemployment in Germany being of disequilibrium nature. This finding justifies political interventions on regional labor markets. JEL: C23, R12, R23 Keywords: regional unemployment, spatial dependence, spatial panel models, Germany

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    Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa12p53.

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    Date of creation: Oct 2012
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    Handle: RePEc:wiw:wiwrsa:ersa12p53

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    1. Christian Bayer & Falko Jü�en, 2007. "Convergence in West German Regional Unemployment Rates," German Economic Review, Verein für Socialpolitik, Verein für Socialpolitik, vol. 8, pages 510-535, November.
    2. Jimeno, Juan F. & Bentolila, Samuel, 1998. "Regional unemployment persistence (Spain, 1976-1994)," Labour Economics, Elsevier, Elsevier, vol. 5(1), pages 25-51, March.
    3. Badi H. Baltagi & Seuck Heun Song & Won Koh, 2002. "Testing Panel Data Regression Models with Spatial Error Correlation," 10th International Conference on Panel Data, Berlin, July 5-6, 2002, International Conferences on Panel Data B6-4, International Conferences on Panel Data.
    4. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, Elsevier, vol. 115(1), pages 53-74, July.
    5. Maddala, G S & Wu, Shaowen, 1999. " A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, Department of Economics, University of Oxford, vol. 61(0), pages 631-52, Special I.
    6. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, Elsevier, vol. 146(1), pages 118-134, September.
    7. J. Paul Elhorst, 2003. "The Mystery of Regional Unemployment Differentials: Theoretical and Empirical Explanations," Journal of Economic Surveys, Wiley Blackwell, Wiley Blackwell, vol. 17(5), pages 709-748, December.
    8. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, Elsevier, vol. 20(2), pages 249-272, April.
    9. Marston, Stephen T, 1985. "Two Views of the Geographic Distribution of Unemployment," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 100(1), pages 57-79, February.
    10. Mark Partridge & Dan Rickman, 1997. "The Dispersion of US State Unemployment Rates: The Role of Market and Non-market Equilibrium Factors," Regional Studies, Taylor & Francis Journals, Taylor & Francis Journals, vol. 31(6), pages 593-606.
    11. Debarsy, Nicolas & Ertur, Cem, 2010. "Testing for spatial autocorrelation in a fixed effects panel data model," Regional Science and Urban Economics, Elsevier, Elsevier, vol. 40(6), pages 453-470, November.
    12. Ron Martin, 1997. "Regional Unemployment Disparities and their Dynamics," Regional Studies, Taylor & Francis Journals, Taylor & Francis Journals, vol. 31(3), pages 237-252.
    13. Decressin, Jörg & Fatás, Antonio, 1994. "Regional Labour Market Dynamics in Europe," CEPR Discussion Papers, C.E.P.R. Discussion Papers 1085, C.E.P.R. Discussion Papers.
    14. Badi H. Baltagi & Long Liu, 2008. "Testing for Random Effects and Spatial Lag Dependence in Panel Data Models," Center for Policy Research Working Papers, Center for Policy Research, Maxwell School, Syracuse University 102, Center for Policy Research, Maxwell School, Syracuse University.
    15. Aragon, Y. & Haughton, D. & Haughton, J. & Leconte, E. & Malin, E. & Ruiz-Gazen, A. & Thomas-Agnan. C., 1999. "Explaining the Pattern of Regional Unemployment: the Case of the Midi-Pyrenees Region," Papers, Toulouse - GREMAQ 99.519, Toulouse - GREMAQ.
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