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How large is the farm income loss due to climate change? Evidence from India

Author

Listed:
  • Rajesh Kalli
  • Pradyot Ranjan Jena

Abstract

Purpose - Climate change is the most concerned issue in the global economy; increase in climate variability and uncertain climate events have caused distress in agriculture sector. The study estimates economic effect of climate change on agriculture income for the Indian state of Karnataka. The study reports the difference of result from past studies, where estimates from present study indicate higher negative impact of rise in temperature. Design/methodology/approach - Fixed effect panel regression method was used to examine change in agriculture revenue to climate response. Climate variables were classified based on the crop calendar to capture the damage caused by climate change. The authors use fine scale climate data set constructed at regional context for 20 districts and time period of 21 years (1992–2012). Findings - The result showed that with 1-degree rise in average maximum temperature, the revenue declined by 17–21%. The prediction behavior of the different models was evaluated using out-of-sample forecast approach by training and testing historical data set. Originality/value - The study adopts recent data sets on agriculture and the updated climate variables to estimate the climate change impact on agriculture. The study yields the better results when compared to previous traditional models applied in literature in Indian context. The study further evaluates the prediction behavior and robustness of the estimated models using out-of-sample forecast method.

Suggested Citation

  • Rajesh Kalli & Pradyot Ranjan Jena, 2022. "How large is the farm income loss due to climate change? Evidence from India," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 14(2), pages 331-348, January.
  • Handle: RePEc:eme:caerpp:caer-11-2020-0275
    DOI: 10.1108/CAER-11-2020-0275
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    Cited by:

    1. Pradyot Ranjan Jena & Babita Majhi & Rajesh Kalli & Ritanjali Majhi, 2023. "Prediction of crop yield using climate variables in the south-western province of India: a functional artificial neural network modeling (FLANN) approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(10), pages 11033-11056, October.

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