Impact of Climate Variability on Crop Productivity: Signal from Pooled OLS Regression

Abstract

The study investigates the impact of climatic variability on major crop productivity, including paddy, wheat, maize, and millet in Nuwakot district, Nepal, using pooled OLS regression on the data span from 1990 to 2023. Descriptive analysis reveals that paddy has the highest mean yield (3.18 t/ha), followed by wheat (2.43 t/ha), maize (2.28 t/ha), and millet (1.3t/ha) millet productivity is positively skewed, representing occasional high yields, while other crops show more consistent patterns. Climate factors reveal moderate rainfall variability (414.1 mm), consistently high humidity (80.2%) and relatively stable temperatures (max 30.96 0C, min 21.58 0C). OLS results shows that paddy productivity is significantly influenced by wheat yield (coef. = 0.966, p < 0.001) minimum temperature (coef. = 0.243, p = 0.017), while rainfall, humidity, and maximum temperature have weaker effects. Maize productivity is primarily affected by wheat productivity yields (coef. = 0.904, p < 0.001), while climatic factors showing no significant impact. millet shows low model fit (R2 = 0.40), indicating limited influence of the variables considered. Temperature appears to be the key climatic determinant for paddy, whereas maize and millet are less climate sensitive.