Determinants of Industrial Sector Performance in India: An Empirical and Analytical Study

Abstract

This study investigates the long run and short run determinants of industrial sector growth in India using the Autoregressive Distributed Lag (ARDL) bounds testing approach. Annual time series data for the period of 1976 to 2024 have been employed to analyze the key macro-economic factors that influence industrial sector performance. The study first examines the stationary properties of the variables using the Augmented Dicky-Fuller (ADF) and Phillips-Perron unit root test. The results indicate that the variables are integrated at a mixed order, I(0) and I(1) and ARDL bounds test confirms the existence of a long-run cointegrating relationship among industrial output and its determinants. The findings shows that gross capital formation, exports of goods and services and inflation have positive and statistically significant impact on industrial sector growth in the long run while foreign direct investment and population are insignificant factors. The short run dynamics estimated through the Error Correction Model (ECM) indicate that the error correction term is negative and statistically significant. Diagnostic tests such as Breusch-Godfrey LM, Breusch-Pagan/Cook-Weisberg, White test for heteroscedasticity, Skewness/Kurtosis (joint), Jarque-Bera (JB) and Ramsey RESET have been performed which confirms the robustness of the results derived from ARDL estimation. Further, the finding of CUSUM and CUSUMSQ indicates that the estimated coefficients are structurally stable and no significant parameter instability occurred during the study period.