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The importance of spatial autocorrelation for regional employment growth in Germany

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Abstract

In analyzing the disparities in regional employment growth in Germany, in the recent empirical literature the so called shift-share-regression models are frequently applied. However, these models usually neglect spatial interdependencies, even though such interdependencies are likely to occur on a regional level. Therefore, this paper focuses on the importance of spatial dependencies using spatial autocorrelation in order to analyze regional employment growth. Spatial dependency in the form of spatial lag, spatial error, and cross regressive models are compared. The results indicate that the exogenous variables’ spatial lag sufficiently explains the spatial autocorrelation of regional employment growth. Copyright Springer-Verlag 2012

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  • Ulrich Zierahn, 2012. "The importance of spatial autocorrelation for regional employment growth in Germany," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 32(1), pages 19-43, March.
    • Handle: RePEc:spr:jahrfr:v:32:y:2012:i:1:p:19-43
    DOI: 10.1007/s10037-011-0062-x
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    Cited by:

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    2. Uwe Blien & Lutz Eigenhueller & Markus Promberger & Norbert Schanne, 2013. "The Shift-Share Regression: An Application to Regional Employ-ment Development," ERSA conference papers ersa13p614, European Regional Science Association.
    3. Pietro Pizzuto, 2020. "The role of regional competitiveness in shaping the heterogeneous impact of the Great Recession," Regional Science Policy & Practice, Wiley Blackwell, vol. 12(2), pages 267-290, April.
    4. Oberst, Christian & Oelgemöller, Jens, 2013. "Economic Growth and Regional Labor Market Development in German Regions: Okun’s Law in a Spatial Context," FCN Working Papers 5/2013, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).

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    More about this item

    Keywords

    Spatial interdependency; Spatial autocorrelation; Shift-share-regression; Regional employment growth; C21; E24; R11; R23;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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