Regional income convergence in India: A Bayesian Spatial Durbin Model approach
AbstractA debate on the regional disparity is always an interesting topic. This study analysed the regional income disparity in India during 1980 – 2010, which contains pre, early and later reform periods. The study used per capita GSDP data from Central Statistical Organisation. First, the study reviewed various growth models and suggests that spatial durbin model of Fingleton and Lopez-Bazo(2006) is empirically useful. Second, this study estimated parameters of Bayesian Spatial Durbin Model and disscussed the convergence hypothesis in the light of LeSange and Fischer (2008) formulation. The study concludes that the later reform period has witnessed beta convergence due to feedback effect.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 44744.
Date of creation: 05 Mar 2013
Date of revision:
Convergence; Regional; Spatial Durbin Model and Bayesian;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-03-16 (All new papers)
- NEP-GEO-2013-03-16 (Economic Geography)
- NEP-URE-2013-03-16 (Urban & Real Estate Economics)
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