Unveiling the interplay between climate variability and economic growth in India: an auto regressive distributed lag (ARDL) framework

AbstractThis study offers a comprehensive analysis of the impact of extreme weather events, intensified by climate change, on India’s real Gross National Product. Focusing on hydro-geological factors crucial for India’s Gross National Product, the Auto Regressive Distributed Lag model reveals significant insights. Notably, the study reveals a significant positive correlation between the lagged real GNP (GNP(−1)) and current real GNP, emphasizing the persistence of economic growth trends. Gross Fixed Capital Formation emerges as a key determinant, with a 0.50% increase in economic growth corresponding to a 1% rise in GFCF. Forest land and rainfall exhibited substantial positive associations, contributing to a noteworthy 1.674 and 0.099% with economic growth. Conversely, CO2 emissions, rising temperatures (both Maximum Temperature and Minimum Temperature) exerted a significant negative influence on real GNP, emphasizing the need for sustainable emission reduction strategies. ARDL Bounds Test, revealed existence of a long-run relationship between real GNP and the selected variables. An ECM-Long Run Test underscores the lasting impact, with a 32.4% adjustment towards long-run equilibrium. The study establishes a bi-directional causality between real Gross National Product and carbon dioxide emissions, emphasizing the interconnectedness of economic growth and emissions. This underscores the urgency for addressing climate change alongside sustainable economic development. The findings serve as a crucial guide for evidence-based policymaking, urging proactive strategies to navigate climate challenges and ensure a prosperous, sustainable future for India. The findings contribute to the existing literature, emphasizing the multifaceted nature of factors shaping India’s sustained economic development.