Asian Journal of Economics, Business and Accounting

The primary aim of this study is to investigate the long-term relationships among various variables, with economic growth serving as the dependent variable and factors such as exports, export instability, and foreign exchange (forex) serving as independent variables. Specifically, the research aims to explore the potential impact of emerging technologies, such as artificial intelligence (AI), on India's export performance from 2001 to 2021. Employing the Autoregressive Distributed Lag (ARDL) model and Granger causality analysis, the study examines the causal relationships between these variables. Data from reputable sources, such as the Reserve Bank of India's Handbook of Statistics on the Indian Economy and the World Integrated Trade Solution (WITS) database, are utilized. Various statistical tests are conducted, including Autocorrelation, Heteroskedasticity, and Normality tests. The study's key finding reveals a statistically significant effect of the Error Correction Term (ECT) with a p-value of 0.00, indicating a 33 percent adjustment rate. Granger Causality tests indicate bidirectional causality between exports and GDP, as well as a unidirectional relationship from export instability to economic growth, suggesting that export instability has a positive influence on economic growth. However, economic growth does not appear to have a causal effect on export instability, but a significant association is found between foreign currency reserves and GDP, underscoring the complex dynamics of economic variables within the Indian context.