GDP, FDI, and Manufacturing Dynamics in India: A VECM Approach (1970-2024)

Abstract

India's rapid economic transformation over the past five decades has generated considerable scholarly interest in the drivers of its growth trajectory, yet the dynamic interrelationships among key macroeconomic variables remain insufficiently understood. This study investigates the long-run equilibrium and causal relationships among GDP per capita, foreign direct investment (FDI), exports, and manufacturing value added in India over the period 1970–2024. Employing the Vector Error Correction Model (VECM) on secondary time-series data sourced from the World Bank Indicators, the study first confirms variable stationarity through unit root testing and selects an optimal lag length of five periods. Granger causality tests reveal that exports do not exert significant causal influence on the remaining variables and are therefore excluded from the final model. Therefore, The final Granger causality results demonstrate bidirectional causality between GDP per capita and FDI, alongside unidirectional causality running from manufacturing value added to both GDP per capita and FDI. The Johansen cointegration test identifies cointegrating equations among GDP per capita, FDI, and manufacturing value added, confirming the presence of a long-run equilibrium relationship.  The long-run cointegrating equation reveals that manufacturing value added exerts a negative and statistically significant effect on GDP per capita, while FDI is not statistically significant. The error correction term is significant only in the manufacturing equation, indicating that adjustment toward long-run equilibrium occurs through the manufacturing sector at a slow speed. Short-run dynamics are limited, with variables primarily influenced by their own lagged values. These findings challenge the strong version of FDI-led growth hypothesis in the Indian context and underscore the central role of manufacturing performance in the long-run adjustment process.