1. Heterogeneous reaction versus interaction in spatial econometric regional growth and convergence models
- Author
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Julie Le Gallo, Cem Ertur, Centre d'Economie et de Sociologie Rurales Appliquées à l'Agriculture et aux Espaces Ruraux (CESAER), Institut National de la Recherche Agronomique (INRA)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Laboratoire d'Économie d'Orleans (LEO), Université d'Orléans (UO)-Université de Tours-Centre National de la Recherche Scientifique (CNRS), Etablissement National d'Enseignement Supérieur Agronomique de Dijon (ENESAD)-Institut National de la Recherche Agronomique (INRA), Roberta Capello, Laboratoire d'Économie d'Orleans [FRE2014] (LEO), and Université d'Orléans (UO)-Université de Tours (UT)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
autocorrelation spatiale ,[SDV]Life Sciences [q-bio] ,Econometrics ,Economics ,Convergence (relationship) ,hétérogénéité spatiale - Abstract
In this chapter, we present the main econometric specifications capturing spatial heterogeneity, or models of absolute locations, and examine how these specifications can be extended to further allow for spatial autocorrelation models of heterogeneous reaction by emphasizing the complex links between spatial heterogeneity and spatial autocorrelation. We detail some of these issues in the growth and convergence context in this chapter by first presenting the specifications allowing for discrete heterogeneity, that is, when different parameters are estimated following spatial regimes including a focus on recent papers dealing with the endogenous detection of convergence in the presence of spatial autocorrelation. Then we present continuous spatial heterogeneity models: geographically weighted regressions and models allowing for both continuous spatial heterogeneity and spatial autocorrelation. We conclude with some research directions.
- Published
- 2019
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