Asian Journal of Economics, Business and Accounting

Regional industrial growth depends partly on the efficiency with which labour and capital are used in the production process. This study examines the factors associated with labour productivity in the industrial sector across 21 Indian states. Using secondary data from published sources, including the Annual Survey of Industries, Statistical Abstracts of various states and state-level Human Development Index estimates, the study applies correlation analysis, simple linear regression and multiple regression. Five-year averages for 2019–20 to 2023–24 are used for the selected indicators, except for the Human Development Index because of its irregular availability. Labour productivity is measured as net value added per person engaged, while the explanatory variables include the Human Development Index, capital intensity, average industrial wage and per capita public development expenditure. The results show that capital intensity and average industrial wages have positive and statistically significant relationships with industrial labour productivity. In contrast, the Human Development Index and per capita public development expenditure do not show statistically significant direct effects in the present cross-sectional model. The multiple regression results indicate that capital intensity and average wages together explain 64.59% of the variation in labour productivity. The findings suggest that policies supporting technological upgrading, productive capital access and fair wage structures may contribute to industrial productivity improvement.