Local versus Global Convergence in Europe: A Bayesian Spatial Econometric Approach
AbstractNumerous studies have pointed to the econometric problems introduced by heterogeneity in cross-sectional data samples used to explore convergence suggested by neo-classical growth models. We introduce a local concept of convergence along with a Bayesian locally linear spatial estimation method to address these problems. The method allows global and local beta-convergence to be viewed in a continuous fashion. Inference regarding global convergence can be treated as a mixture distribution arising from local beta-convergence estimates from each region in the sample. Taking this approach eliminates the need to specify sub-samples and regimes as well as parameter variation schemes that have been used to model heterogeneity. We illustrate the method using a sample of 138 European regions.
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Bibliographic InfoArticle provided by Southern Regional Science Association in its journal Review of Regional Studies.
Volume (Year): 37 (2007)
Issue (Month): 1 ()
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- R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
- R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
- R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
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