Spatial Convergence of Regions Revisited: A Spatial Maximum Likelihood Systems Approach
AbstractThis 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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Bibliographic InfoPaper provided by Faculty of Economics and Statistics, University of Innsbruck in its series Working Papers with number 2009-07.
Date of creation: Mar 2009
Date of revision:
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More information through EDIRC
Spatial beta-convergence; Spatial Solow model; Spatial systems maximum likelihood estimation; Europeanregions;
Find related papers by 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, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-04-05 (All new papers)
- NEP-GEO-2009-04-05 (Economic Geography)
- NEP-URE-2009-04-05 (Urban & Real Estate Economics)
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