Journal of Earth Science & Climatic Change
Open Access

Abstract

T his paper explores the impact of climate variability on aggregate land productivity of major food grain and non-food grain crops of the country using secondary data with panel set for time period, 1985-2009. Secondary data for similar period was taken from various sources; and linear interpolation and graphical projection methods were used to identify the missing values in the available time series data. Value of production of fifteen crops was calculated by farm harvest price (at constant price 1993- 94); and these fifteen crops were taken from thirteen major agriculturist intensive states of the nation. Cobb-Douglas production function model was incorporated. Per unit land productivity (in monetary term) as dependent variables was regressed with thirteen different socio-economic and climatic factors. To identify the cross sectional independence, Pesaran's test was used. For group-wise heteroskedasticity, Wald test is applied in regression model. To address the presence the autocorrelation, Wooldridge test is incorporated. To remove the presence of serial correlation, heteroskedasticity and cross sectional autocorrelation; the linear regression, heteroskedastic panels corrected standard errors estimation model was used. This paper provides the empirical evidence that climate variability negatively affect the aggregate value of production; it means that climate variability negatively affect the land value in India. On the other hand, government expenditure on agricultural and allied sector; rural development; irrigation and flood control is an important factor that may mitigate the adverse effect of climate variability and increase the land productivity. This paper suggests a policy and future research gap.

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