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

Author

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  • Ajay Kumar
  • Pritee Sharma
  • Sunil Kumar Ambrammal
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.

Suggested Citation

  • Ajay Kumar & Pritee Sharma & Sunil Kumar Ambrammal, 2015. "Climatic effects on sugarcane productivity in India: a stochastic production function application," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 10(2), pages 179-203.
    • Handle: RePEc:ids:ijecbr:v:10:y:2015:i:2:p:179-203
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    Citations

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    Cited by:

    1. Saumya Verma & Shreekant Gupta & Partha Sen, 2020. "Does climate change make foodgrain yields more unpredictable? Evidence from India," Working papers 305, Centre for Development Economics, Delhi School of Economics.
    2. Singh, Ajay Kumar & Ashraf, Shah Nawaz & Sharma, Sandeep Kumar, 2023. "Farmer’s Perception on Climatic Factors and Social-economic Characteristics in the Agricultural Sector of Gujarat," Research on World Agricultural Economy, Nan Yang Academy of Sciences Pte Ltd (NASS), vol. 4(1), March.
    3. Sanjeev Kumar & Ajay K. Singh, 2023. "Modeling the effects of climate change on agricultural productivity: evidence from Himachal Pradesh, India," Asia-Pacific Journal of Regional Science, Springer, vol. 7(2), pages 521-548, June.
    4. Jyoti, Bhim & Singh, Ajay Kumar, 2020. "Projected Sugarcane Yield in Different Climate Change Scenarios in Indian States: A State-Wise Panel Data Exploration," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 8(4), October.
    5. Ajay, Kumar Singh & Kumar, Sanjeev & Ashraf, Shah Nawaz & Jyoti, Bhim, 2022. "Implications of Farmer’s Adaptation Strategies to Climate Change in Agricultural Sector of Gujarat: Experience from Farm Level Data," Research on World Agricultural Economy, Nan Yang Academy of Sciences Pte Ltd (NASS), vol. 3(1), March.
    6. Abbas Ali, Chandio & Yuansheg, Jiang & Asad, Amin & Waqar, Akram & Ilhan, Ozturk & Avik, Sinha & Fayyaz, Ahmad, 2021. "Modeling the impact of climatic and non-climatic factors on cereal production: evidence from Indian agricultural sector," MPRA Paper 110065, University Library of Munich, Germany, revised 2021.

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