Regional income convergence in India: A Bayesian Spatial Durbin Model approach

Soundararajan, Pushparaj (2013): Regional income convergence in India: A Bayesian Spatial Durbin Model approach.

Abstract

A 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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Convergence, Regional, Spatial Durbin Model and Bayesian
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R12 - Size and Spatial Distributions of Regional Economic Activity

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