Assessing renewable energy, agriculture, and development impacts on CO2 emissions in Nepal

This study investigates the impact of renewable energy consumption (REC), agricultural GDP (AGDP), human development (HDI), and trade openness (TO) on CO₂ emissions in Nepal, utilizing the STIRPAT model. Using annual data from 1990 to 2021, we apply a battery of cointegration-consistent estimators including OLS, FMOLS, DOLS with one lead and lag (SIC-based), and CCR—to capture both short- and long-run elasticities. Robustness is confirmed using Johansen and Phillips–Ouliaris cointegration tests, KPSS stationarity checks, and sensitivity analysis with alternative lag lengths. Results show that REC has a large and statistically significant mitigating effect on emissions (elasticity ≈ − 7 to − 11%), while AGDP, HDI, and TO exert positive and significant long-run effects, indicating that growth and development remain carbon-intensive. Diagnostic tests (Breusch–Godfrey, White/Breusch–Pagan, RESET, CUSUM/CUSUMSQ) confirm the validity, stability, and correct specification of the models. Pairwise Granger causality results suggest unidirectional causality from CO₂ emissions to REC and HDI, supporting the presence of feedback effects between emissions and key socioeconomic drivers. An extended model including GDP per capita and its squared term validates the Environmental Kuznets Curve (EKC) hypothesis, with an estimated turning point around USD 1,300 per capita, implying Nepal is still in the upward-sloping segment of the curve. These findings underscore the importance of policies promoting renewable energy adoption, climate-smart agricultural practices, and sustainable trade integration. Quantitatively, a 10% rise in renewable energy share is associated with roughly an 11% reduction in per-capita CO₂ emissions, highlighting the strong leverage of clean energy expansion for achieving Nepal’s low-carbon growth trajectory. The study offers policy-relevant insights for Nepal and other developing economies pursuing low-carbon growth pathways.