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Regional Convergence in Germany. A Geographically Weighted Regression Approach

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  • Hans-Friedrich Eckey

    ()

  • Reinhold Kosfeld

    ()

  • Matthias Turck

    ()

Abstract

Regional convergence of German labour markets represents a politically important question. Different studies have examined convergence processes in Germany. We derive equations to estimate the speed of convergence on the basis of an extended Solow model. The technique of geographically weighted regression permits a detailed analysis of convergence processes, which has not been conducted for Germany so far yet. It allows to estimate a separate speed of convergence for every region resulting from the local coefficients of the regression equations. The application of this technique to German labour market regions shows regions moving with a different speeds towards their steady states. The half-live times in the model of conditional convergence disperse less than the same coefficients in the absolute convergence model. Moreover, the speed of convergence is substantially slower in the manufacturing sector than in the service sector.

Suggested Citation

  • Hans-Friedrich Eckey & Reinhold Kosfeld & Matthias Turck, 2006. "Regional Convergence in Germany. A Geographically Weighted Regression Approach," ERSA conference papers ersa06p461, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa06p461
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    Cited by:

    1. Karsten Rusche, 2010. "Quality of life in the regions: an exploratory spatial data analysis for West German labor markets," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 30(1), pages 1-22, February.
    2. Franziska Lottmann, 2012. "Regional Unemployment in Germany: a spatial panel data analysis," ERSA conference papers ersa12p53, European Regional Science Association.
    3. Jesus Felipe & John McCombie, 2012. "Problems with Regional Production Functions and Estimates of Agglomeration Economies: A Caveat Emptor for Regional Scientists," Economics Working Paper Archive wp_725, Levy Economics Institute.
    4. Franziska Lottmann, 2012. "Explaining regional unemployment differences in Germany: a spatial panel data analysis," SFB 649 Discussion Papers SFB649DP2012-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Stephan Brunow & Georg Hirte, 2009. "The age pattern of human capital and regional productivity: A spatial econometric study on german regions," Papers in Regional Science, Wiley Blackwell, vol. 88(4), pages 799-823, November.
    6. Tolga Ülkü & Vahidin Jeleskovic & Jürgen Müller, 2014. "How scale and institutional setting explain the costs of small airports? -An application of spatial regression analysis," MAGKS Papers on Economics 201435, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    7. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland - Teil III: Konvergenz," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(15), pages 23-32, August.
    8. Brijesh C. Purohit, 2012. "Health Policy, Inequity and Convergence in India," Working Papers 2012-074, Madras School of Economics,Chennai,India.
    9. Benjamin Wirth, 2013. "Ranking German regions using interregional migration - What does internal migration tells us about regional well-being?," ERSA conference papers ersa13p1254, European Regional Science Association.
    10. Cem Ertur & Julie Le Gallo, 2008. "Regional Growth and Convergence: Heterogenous reaction versus interaction in spatial econometric approaches," Working Papers hal-00463274, HAL.
    11. Chiara Del Bo & Massimo Florio & Giancarlo Manzi, 2010. "Regional Infrastructure and Convergence: Growth Implications in a Spatial Framework," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 17(3), pages 475-493, September.
    12. Declan Curran, 2011. "British Regional Growth and Sectoral Trends - Global and Local Spatial Econometric Approaches," Post-Print hal-00687807, HAL.

    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy

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