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Sharma, Pritee
- Measuring the Influence of Weather Variables on Productivity of Food-Grain Crops in India:An Application of Just & Pope's Production Technique
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Authors
Affiliations
1 Entrepreneurship Development Institute of India, Ahmedabad, Gujarat-382428, IN
2 School of Humanities and Social Sciences, Indian Institute of Technology Indore, Madhya Pradesh, IN
3 Institute of Rural Management, Anand, Gujarat, IN
1 Entrepreneurship Development Institute of India, Ahmedabad, Gujarat-382428, IN
2 School of Humanities and Social Sciences, Indian Institute of Technology Indore, Madhya Pradesh, IN
3 Institute of Rural Management, Anand, Gujarat, IN
Source
AMBER – ABBS Management Business and Entrepreneurship Review, Vol 7, No 2 (2016), Pagination: 29-46Abstract
The present study investigates the impact of weather factors on mean yield and variability of food-grain crops during sowing, growing and harvesting time.
Design/Methodology/Approach: It used linear and log-linear regression models under stochastic production function technique. Mean yield and yield variability of wheat, chickpea, rice and maize crops are compiled as state-wise panel during 1971- 2012.
Major Findings: It shows that mean yield and yield variability of food-grain crops are climate sensitive, and climate change have a negative impact on yield of aforesaid crops. It ascertained that fluctuation in weather factors would increase food insecurity in India.
Research Limitations/Implications: Agriculture is a significant cause for climate change and environmental degradation, however the study avoid this fact. It assumes that all varieties of a crop similarly get affects due to climate change.
Practical Implications: It emphasized that Indian farmers need to adopt crop specific policies to mitigate the adverse effects of climate change. It provides conclusive policy recommendations to moderate the negative effects of climate change in agriculture.
Originality/Value: It estimate the influence of climatic factors on mean yield and yield variability of major food-grain crops at macro level. It also assesses the seasonal influence of weather factors on food-grain productivity.
Keywords
Climate Change, Non-Climatic Variables, Linear and Log-Linear Regression Model Mean Yield and Variability, Food-Grain Crops, India.Full Text
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