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Spatial Filtering and Eigenvector Stability: Space-Time Models for German Unemployment Data

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  • Roberto Patuelli

    ()
    (Institute for Economic Research (IRE), University of Lugano, Switzerland and The Rimini Centre for Economic Analysis, Italy)

  • Daniel A. Griffith

    (School of Economic, Political and Policy Sciences, University of Texas at Dallas, TX, USA)

  • Michael Tiefelsdorf

    (School of Economic, Political and Policy Sciences, University of Texas at Dallas, TX, USA)

  • Peter Nijkamp

    (Department of Spatial Economics, VU University Amsterdam, The Netherlands)

Abstract

Regions, independent of their geographic level of aggregation, are known to be interrelated partly due to their relative locations. Similar economic performance among regions can be attributed to proximity. Consequently, a proper understanding, and accounting, of spatial liaisons is needed in order to effectively forecast regional economic variables. Several spatial econometric techniques are available in the literature, which deal with the spatial autocorrelation (SAC) in geographically referenced data. The experiments carried out in this article are concerned with the analysis of the SAC observed for unemployment rates in 439 NUTS-3 German districts. The authors employ a semiparametric approach—spatial filtering—in order to uncover spatial patterns that are consistently significant over time. The authors first provide a brief overview of the spatial filtering method and illustrate the data set. Subsequently, they describe the empirical application carried out: that is, the spatial filtering analysis of regional unemployment rates in Germany. Furthermore, the authors exploit the resulting spatial filter as an explanatory variable in a panel modeling framework. Additional explanatory variables, such as average daily wages, are used in concurrence with the spatial filter. Their experiments show that the computed spatial filters account for most of the residual SAC in the data.

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Bibliographic Info

Article provided by in its journal International Regional Science Review.

Volume (Year): 34 (2011)
Issue (Month): 2 (April)
Pages: 253-280

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Handle: RePEc:sae:inrsre:v:34:y:2011:i:2:p:253-280

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Keywords: spatial filtering; eigenvectors; Germany; unemployment; GLMM;

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References

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  1. Maria Francesca Cracolici & Miranda Cuffaro & Peter Nijkamp, 2007. "Geographical Distribution of Unemployment: An Analysis of Provincial Differences in Italy," Tinbergen Institute Discussion Papers 07-065/3, Tinbergen Institute.
  2. Lopez-Bazo, Enrique & Del Barrio, Tomas & Artis, Manuel, 2002. "The regional distribution of spanish unemployment. A spatial analysis," ERSA conference papers ersa02p020, European Regional Science Association.
  3. Roberto Patuelli & Aura Reggiani & Peter Nijkamp & Uwe Blien, 2006. "New Neural Network Methods for Forecasting Regional Employment: an Analysis of German Labour Markets," Spatial Economic Analysis, Taylor & Francis Journals, Taylor & Francis Journals, vol. 1(1), pages 7-30.
  4. Simonetta Longhi & Peter Nijkamp, 2007. "Forecasting Regional Labor Market Developments under Spatial Autocorrelation," International Regional Science Review, , , vol. 30(2), pages 100-119, April.
  5. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, Blackwell, vol. 27(3), pages 247-267, November.
  6. 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.
  7. Reinhold Kosfeld & Christian Dreger, 2006. "Thresholds for employment and unemployment: A spatial analysis of German regional labour markets, 1992-2000," Papers in Regional Science, Wiley Blackwell, vol. 85(4), pages 523-542, November.
  8. Weinhold, Diana, 2002. "The Importance of Trade and Geography in the Pattern of Spatial Dependence of Growth Rates," Review of Development Economics, Wiley Blackwell, vol. 6(3), pages 369-82, October.
  9. Lambert, Dayton M. & Brown, Jason P. & Florax, Raymond J.G.M., 2010. "A two-step estimator for a spatial lag model of counts: Theory, small sample performance and an application," Regional Science and Urban Economics, Elsevier, vol. 40(4), pages 241-252, July.
  10. Olivier Jean Blanchard & Lawrence F. Katz, 1992. "Regional Evolutions," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 23(1), pages 1-76.
  11. Salima Bouayad-Agha & Lionel V�drine, 2010. "Estimation Strategies for a Spatial Dynamic Panel using GMM. A New Approach to the Convergence Issue of European Regions," Spatial Economic Analysis, Taylor & Francis Journals, Taylor & Francis Journals, vol. 5(2), pages 205-227.
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Cited by:
  1. Patuelli, Roberto & Schanne, Norbert & Griffith, Daniel A. & Nijkamp, Peter, 2011. "Persistence of regional unemployment : Application of a spatial filtering approach to local labour markets in Germany," IAB Discussion Paper 201103, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  2. Giuliano Guerra & Roberto Patuelli & Rico Maggi, 2010. "Ethnic Concentration, Cultural Identity and Immigrant Self-Employment in Switzerland," Working Paper Series, The Rimini Centre for Economic Analysis 11_10, The Rimini Centre for Economic Analysis, revised Aug 2011.
  3. Roberto Patuelli & Aura Reggiani & Peter Nijkamp & Norbert Schanne, 2009. "Neural Networks for Cross-Sectional Employment Forecasts: A Comparison of Model Specifications for Germany," Quaderni della facoltà di Scienze economiche dell'Università di Lugano, USI Università della Svizzera italiana 0903, USI Università della Svizzera italiana.
  4. Prodromídis, Pródromos-Ioánnis K., 2012. "Modeling male and female employment policy in Greece from local data," Economic Modelling, Elsevier, vol. 29(3), pages 823-839.
  5. Patuelli, R. & Schanne, N. & Griffith, D.A. & Nijkamp, P., 2010. "Persistent disparities in regional unemployment: Application of a spatial filtering approach to local labour markets in Germany," Serie Research Memoranda 0001, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

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