Decomposing the Drivers of CO2 Emissions in India: A Dual Adjustment Approach

Understanding how economic growth (GDP), livestock production (LPI), agriculture, forestry and fishing (AFF), renewable energy consumption (REN), and urbanization (URB) influence carbon emissions is essential for designing effective climate policies in rapidly developing economies such as India. This study examines the long-run and short-run effects of these factors on CO2 emissions in India during 1990–2024 using the Dual Adjustment Approach (DAA) and the Autoregressive Distributed Lag (ARDL) model. The DAA framework decomposes variables into permanent (trend) and transitory (cyclical) components, allowing a simultaneous assessment of long-run equilibrium and short-run dynamics. Both DAA and ARDL models indicate that GDP and LPI increase CO2 emissions in the long run, while REN reduces them. AFF exerts a weak effect on emissions compared with the other determinants. URB is associated with lower long-run emissions, supporting the urban efficiency hypothesis, but this depends on sustained infrastructure investment and policy support, rather than automatic results of current urbanization levels. The transitory component analysis shows that short-run fluctuations in GDP increase emissions, while the effects of the remaining variables are driven by long-run structural changes. The findings highlight the importance of expanding renewable energy deployment, improving environmental efficiency in agricultural and livestock production systems, and promoting sustainable urban development to reduce carbon emissions in the case of India.