Agriculture, industry, and economic growth as determinants of carbon emissions in climate hotspots: evidence from dynamic causal analysis
摘要
The present research explores the association between CO2 emission, agricultural land use, agricultural value addition, industrial value addition, and GDP in the recently emerging industrialized countries of China, India, and Pakistan. The area has faced the devastating impact of climate change and is a hotspot for GHG emissions nowadays. The study deployed panel data from the year 1990 to 2022, employing generalized impulse response, pairwise Granger causality test, and impulse response and variance decomposition analysis to analyze GHG emission due to value addition in agriculture and industry. GDP has a statistically significant negative impact on CO2 emissions in the long run. This could indicate that economic growth reduces emissions, possibly due to energy efficiency improvements or a transition to cleaner industries. The industrial sector's value-added has a strong and statistically significant positive effect on emissions. This suggests that industrial activities contribute significantly to CO2 emissions. Results of generalized impulse response, pairwise Granger causality test, and impulse response and variance decomposition analysis were also presented to investigate the effects of shocks on adjustment trajectories of variables. The long-run regression results show a positive and insignificant link between carbon emission and land under cereal crops and agricultural production. A positive and significant relationship prevails between carbon emission and industrial production. Policymakers must initiate industrial policies, projects, and planning in meaningful ways to control carbon emissions and promote geo-sustainability. Consequently, the region should endorse environmentally friendly programs for sustainable industrial patterns and avoid environmental degradation through carbon emissions.