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Spatial Convergence of Regions Revisited: A Spatial Maximum Likelihood Systems Approach

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  • Michael Paffermayr

Abstract

This paper suggests that one should account for the endogeneity of important explanatory variables and the persistence of technology shocks when analyzing spatial convergence among regions.Specifically, it is argued that a systems approach is called for that includes the average growth rate and the initial income level as the endogenous variables. For 212 European regions the estimation results reveal a substantial correlation between the disturbances of the equation explaining initial income per capita and that of its subsequent average growth rate. Moreover, the estimated speed of convergence is found substantially higher in a systems framework. This holds true for both spatial conditional and unconditional convergence.

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  • Michael Paffermayr, 2009. "Spatial Convergence of Regions Revisited: A Spatial Maximum Likelihood Systems Approach," Working Papers 2009-07, Faculty of Economics and Statistics, Universität Innsbruck.
    • Handle: RePEc:inn:wpaper:2009-07
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    More about this item

    Keywords

    Spatial beta-convergence; Spatial Solow model; Spatial systems maximum likelihood estimation; Europeanregions;
    All these keywords.

    JEL classification:

    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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