2019
DOI: 10.1002/pa.2040
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Assessing the impact of climate change on Indian agriculture: Evidence from major crop yields

Abstract: This study empirically examines the effect of climate change on the yields of primary food as well as non‐food crops in India. The present study uses annual time‐series data of seven major crops such as rice, wheat, pulses, rapeseeds and mustard, cotton, sugarcane, and groundnut for 58 years (1961–20 17) to assess the influence climatic variables namely rainfall, maximum, and minimum temperatures on crop yields. The empirical findings of the study indicate that a significant effect on major crop yields from ra… Show more

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Cited by 121 publications
(66 citation statements)
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References 45 publications
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“…The positive impact of minimum temperature on cotton yield may be unable offset the adverse effect of maximum temperature as reflected in estimated results. Present results of minimum and maximum temperature in mean yield function of cotton are contrary to some studies such as Padakandla (2016) and Guntukula (2020). The empirical outcomes of climatic factors in mean yield function of cotton are similar with Kumar et al (2015).…”
Section: Resultssupporting
confidence: 78%
“…The positive impact of minimum temperature on cotton yield may be unable offset the adverse effect of maximum temperature as reflected in estimated results. Present results of minimum and maximum temperature in mean yield function of cotton are contrary to some studies such as Padakandla (2016) and Guntukula (2020). The empirical outcomes of climatic factors in mean yield function of cotton are similar with Kumar et al (2015).…”
Section: Resultssupporting
confidence: 78%
“…This method is appropriate to measure the influence of climate change on crop productivity (Sarker et al, ). Following Lobell, Cahill, and Field () and Guntukula (), this study used three major climatic factors as explanatory variables, namely, minimum temperature, maximum temperature, and rainfall and maize yield as dependent variable. The following regression model is used. Yt=α+β1rainft+β2maxtempt+β3mintempt+β4areat+εt, …”
Section: Methodsmentioning
confidence: 99%
“…Although all major industries are susceptible to climate change, the agriculture sector is the one that has the highest vulnerability (Guntukula 2020). Many plants are sensitive to temperature changes; hence, global warming will have destructive effects on agricultural production (Appiah et al 2018).…”
Section: Introductionmentioning
confidence: 99%