Does Temperature and Rainfall Asymmetrically affect Wheat Production in Nepal? Using NARDL Model Approach

Abstract

Wheat production in Nepal is highly sensitive to climatic variability, particularly temperature and rainfall. This study examines the asymmetric impacts of these climatic factors on wheat yields using the Nonlinear Autoregressive Distributed Lag (NARDL) model. A quantitative research design was employed, analyzing time-series data from 1990 to 2022. The NARDL model was used to capture both short- and long-term asymmetric effects of temperature and rainfall on wheat yield. Diagnostic and stability tests ensured the robustness of the model. The findings reveal that positive temperature changes significantly reduce wheat yields in the short term (coefficient: -2483.80, p < 0.01), followed by a compensatory positive effect in subsequent periods (coefficient: 2935.31, p < 0.01). Negative temperature changes and rainfall variability, both positive and negative, were statistically insignificant in their impacts. The model’s R-squared value of 0.972 highlights its strong explanatory power. The results underscore the critical role of temperature in influencing wheat productivity, with rainfall’s limited impact suggesting effective water management practices. These findings align with global studies on climate resilience but highlight unique adaptation mechanisms in Nepal. This study emphasizes the need for heat-tolerant wheat varieties and enhanced irrigation systems to mitigate climatic stressors. The use of the NARDL model offers novel insights into the asymmetric dynamics of climatic factors, advancing methodologies in climate-agriculture research.