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This study explores the dynamic relationships among key macroeconomic variables influencing inflation in India from 1981 to 2021. Utilizing a comprehensive empirical approach, the research employs the Autoregressive Distributive Lag (ARDL) model to analyse both short-term and long-term effects of variables such as money supply (M3), GDP growth rate, international oil prices, exchange rates, current account balance, and lending interest rates on inflation. The methodology includes stationarity tests to ensure the robustness of the time series data, followed by cointegration tests to confirm the long-run relationships among the variables. Additionally, the Quantile ARDL model examines these variables’ impact across different inflation distribution quantiles, providing a more nuanced understanding of their effects. The findings highlight significant positive and negative relationships between these variables and inflation, depending on their lag periods. Notably, the results reveal that money supply and international oil prices play critical roles in shaping inflationary trends, with both direct and lagged effects. The study also identifies that GDP growth generally negatively influences inflation, suggesting that higher economic growth may not necessarily lead to inflationary pressures in the Indian context. The mixed effects of exchange rates on inflation further underscore the complexity of managing inflation in a volatile global environment. This research provides valuable insights for policymakers, emphasizing the need for a balanced approach that includes flexible monetary policy, effective exchange rate management, and strategies to reduce dependency on imported goods to mitigate external shocks. These findings offer a comprehensive understanding of the determinants of inflation in India, contributing to formulating evidence-based policies for economic stability and growth.
Das et al. (Thu,) studied this question.