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- W3180482846 abstract "Purpose: This study assesses the impact of climatic and geographical factors on the yield of potato, cotton, groundnut, sesame, linseed, sugarcane, rapeseed & mustard, and sunflower seeds using state-wise panel data in India during 1971-2013. Thereupon, it estimates the expected yield of aforesaid crops in different climate change scenarios.Methods: Cobb-Douglas production function model is used to estimate the regression coefficients of climatic and geographical factors with the yield of aforesaid crops. Results: The empirical result shows that maximum temperature, minimum temperature, rainfall, and precipitation have a significant impact on the yield of potato, groundnut, sesame, linseed, sugarcane, rapeseed & mustard, sunflower seeds. The projected results indicate that yield of sesame, linseed, rapeseed & mustard, potato, and cotton crops may decline by 0.16%, 0.83%, 5.65%, 14.68%, and 23.31% respectively due to one unit change in average maximum and minimum temperature, actual precipitation, and rainfall during crop seasons. Implications: The Agriculture department of the government should encourage farmers to implement crop-specific policies to mitigate the negative impact of climate change in agriculture. Limitations: Application of fertilizer, quality of seeds, cost of cultivation, farm management practices, irrigated area, demographic factors (e.g., population growth, urbanization, industrialization, etc.), and ecosystem services (e.g., water, soil fertility, and land) have a significant impact on the yield of cash crops. However, these variables were not included to predict the yield of cash crops in this study. Thus, this study acknowledged this limitation and existing researchers can incorporate these variables in further study." @default.
- W3180482846 created "2021-07-19" @default.
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- W3180482846 date "2021-06-21" @default.
- W3180482846 modified "2023-09-23" @default.
- W3180482846 title "Projected Productivity of Cash Crops in Different Climate Change Scenarios in India: Use of Marginal Impact Analysis Technique" @default.
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- W3180482846 doi "https://doi.org/10.38157/finance-economics-review.v3i1.281" @default.
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