Climatic Effects on Sugarcane Productivity in India: A Stochastic Production Function Application

Abstract

The present study estimates the influence of climatic and non-climatic factors on mean yield and yield variability of sugarcane crop in different weather seasons (e.g., rainy, winter and summer) in India. Sugarcane mean-yield for fourteen major sugarcane growing states from different agro-ecological zones are delimitated in panel data during 1971–2009. Regression coefficient for mean yield and yield variability production function (i.e. risk increasing or decreasing inputs) has been estimated through log-linear regression model with the help of Just and Pope (stochastic) production function specification. Empirical results based on feasible generalise least square (FGLS) estimations shows a significant effect of rainfall, maximum and minimum temperatures on sugarcane mean yield and yield variability. Whereas, average maximum temperature in summer and average minimum temperature in rainy season have a negative and statistically significant impact on sugarcane mean yield. Sugarcane mean yield positively gets affected with average maximum temperature during rainy and winter season.