This study measures the industrial performance of Indian states using secondary data. It uses value of gross output, gross value added, invested capital, number of factories, gross capital formation, total inputs, total persons engaged, and total emoluments of industries. Next, it examines the factors affecting the gross value added of industries, using state-wise panel data for the period 2003–2018. Linear, log-linear and non-linear regression models are considered to estimate the regression coefficients of total persons engaged, gross capital formation, total inputs, labor productivity, per person emoluments, capital intensity, and credit to industry by scheduled commercial banks, annual population growth, and literacy rate with the gross value added of industries. Among the Indian states, Gujarat, Maharashtra, Tamil Nadu and Karnataka make the greatest contributions to industrial development. Labor productivity, annual population growth, literacy rate, total person engaged, credit to industries by scheduled commercial banks, per person emoluments, and gross capital formation positively influence gross value added. Literacy rate, per person emoluments, capital intensity and total inputs display a hill-shaped association with gross value added. Labor productivity, annual population growth, credit to industries by scheduled commercial banks, total persons engaged, and gross capital formation display a linear association with the gross value added of industries in India.
Contribution/ Originality
This study makes a valuable contribution to the existing literature by examining the factors affecting industrial development in Indian states using a concrete empirical model. It provides practical policy implications to increase the industrial growth by strengthening labor productivity, capital intensity, financial support, capital formation and human skills across Indian sates.
Economics » Journal of Social Economics Research » Month: 12-2021 Issue: 2