Climate change and its effects on maize yield in Nepal: An empirical analysis using the ARDL model

Abstract

This study analyzes the impact of climate change on maize yield in Nepal’s Gulmi (hilly) and Rupandehi (Terai) districts using climatic data from 1981 to 2023 on rainfall, relative humidity, maximum temperature, and minimum temperature applying the Autoregressive Distributed Lag (ARDL) model. The findings obtained ARDL model shows that rainfall positively influences yield in both regions. Relative humidity has a positive long-term effect in Gulmi but a negative impact in Rupandehi. Maximum temperature increases yield in Gulmi but significantly reduces it in Rupandehi, indicating regional sensitivity. Minimum temperature negatively affects Gulmi yields but has a negligible positive effect in Rupandehi. The ARDL models demonstrate strong explanatory power, with adjusted R² values of 0.86 (Gulmi) and 0.80 (Rupandehi), confirming a significant long-term relationship between climate variables and yield. Error correction terms suggest that 28% (Gulmi) and 30% (Rupandehi) of short-term yield deviations adjust back to long-run equilibrium annually. These results highlight the importance of localized climate adaptation strategies in agriculture. © 2025, Association of Agrometeorologists. All rights reserved.