Dynamic Spatial Modelling of Regional Convergence Processes
AbstractEconometric analysis of convergence processes across countries or regions usually refers to a transition period between an arbitrary chosen starting year and a fictitious steady state. Panel unit root tests and panel cointegration techniques have proved to belong to powerful econometric tools if the conditions are met. When referring to economically defined regions, though, it is rather an exception than the rule that coherent time series are available. For this case we introduce a dynamic spatial modelling approach which is suitable to trace regional adjustment processes in space instead of time. It is shown how the spatial error-correction mechanism (SEC model) can be estimated depending on the spatial stationarity properties of the variables under investigation. The dynamic spatial modelling approach presented in this paper is applied to the issue of conditional income and productivity convergence across labour market regions in unified Germany. --
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Bibliographic InfoPaper provided by Hamburg Institute of International Economics (HWWA) in its series HWWA Discussion Papers with number 261.
Date of creation: 2004
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Web page: http://www.econstor.eu/handle/10419/20
More information through EDIRC
Regional convergence; dynamic spatial models; spatial unit roots; spatial error-correction;
Other versions of this item:
- Reinhold Kosfeld & Jorgen Lauridsen, 2004. "Dynamic spatial modelling of regional convergence processes," Empirical Economics, Springer, Springer, vol. 29(4), pages 705-722, December.
- R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
- R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
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