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Climatic effects on sugarcane productivity in India: a stochastic production function application

Ajay Kumar, Pritee Sharma and Sunil Ambrammal

International Journal of Economics and Business Research, 2015, vol. 10, issue 2, 179-203

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.

Keywords: sugarcane mean yield; yield variability; stochastic production function; C-D model; state-wise panel data; India; climatic effects; sugarcane productivity; climate; feasible GLS; generalised least squares; FGLS; rainfall; temperature. (search for similar items in EconPapers)
Date: 2015
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