Spatial Analysis of Regional Divergence in India: Income and Economic Structure Perspectives

Two research methods–exploratory spatial data analysis and structural divergence analysis–are used to provide empirical support for the fact that GSDP per capita in 30 States in India continue to diverge in the post-reform period 1993–2004. First, exploratory spatial data analysis reveals the evidence of spatial clustering, such that rich forward States are located near other forward States (High-High Clusters), while backward States are located near other backward States (Low-Low Clusters). The local indicators of spatial autocorrelation suggest that the spatial dependence of GSDP per capita in 30 States in India is dominated by Low-Low clusters throughout the period. Second, structural divergence analysis reveals that the sector’s contribution to the aggregate divergence is led by industry (60.26%), and followed by services (54.34%), while agriculture plays a role of buffer and offsets the rate of aggregate divergence (−11.81%). The positive spatial autocorrelation of income from services and industry persists, but negative spatial autocorrelation of income from agriculture is observed throughout the period 1993–2004. Therefore, the similarity of High-High (South of India) and Low-Low (BIMARU States) clusters location for economy-wise and sector-wise analysis highlights that the aggregate divergence in India is caused by structural divergence.