Growth decomposition of the Indian states using panel data techniques

被引:0
|
作者
Ghosh, Taniya [1 ]
Kaustubh [2 ]
机构
[1] Indira Gandhi Inst Dev Res IGIDR, Gen AK Vaidya Marg, Film City Rd, Mumbai 400065, India
[2] Dept Econ & Policy Res, Reserve Bank India, Mumbai, India
关键词
Beta-convergence; common factor models; cross-sectional dependence; principal component analysis; production function;
D O I
10.1080/00036846.2023.2212974
中图分类号
F [经济];
学科分类号
02 ;
摘要
The study investigates the causes of rising economic inequality among Indian states between 2000 and 2017. To identify the components of output growth that are driving rising regional inequality in the Solow Model framework, we first create state-level data on capital stock and labour force, which are not published in India's national accounts. While we find beta divergence in per capita state domestic product (SDP) between states, there is no evidence of beta divergence in capital stock accumulation. Therefore, differences in TFP growth, rather than capital stock accumulation, may be one of the factors contributing to India's rising regional inequality. Furthermore, a productivity index for Indian states was created using the physical and social infrastructure, health, education, digital connectivity, and energy access to help explain the differences in states' TFP. When common factor models were used to account for the high cross-sectional dependence between state growth rates, the influence of capital accumulation and productivity index on state growth was significantly reduced. Hence, the Indian economy's common growth factor emerges as a major driver of the SDPs, with higher per capita SDP states benefiting more from overall growth than the lower per capita SDP states, resulting in growing regional disparities.
引用
收藏
页码:4664 / 4684
页数:21
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