Assessment and Prediction of Grain Production Considering Climate Change and Air Pollution in China

Hengli Wang, Hong Liu and Rui Ma
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Hengli Wang: Institute of Big Data, Zhongnan University of Economics and Law, Wuhan 430073, China
Hong Liu: School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan 430073, China
Rui Ma: School of Statistics and Big Data, Henan University of Economics and Law, Zhengzhou 450000, China

Sustainability, 2022, vol. 14, issue 15, 1-22

Abstract: This study examines the spatial and temporal impacts of climate change on grain production in China. This is achieved by establishing a spatial error model consisting of four indicators: the climate, air pollution, economic behavior, and agricultural technology, covering 31 provinces in China from 2004 to 2020. These indicators are used to validate the spatial impacts of climate change on grain production. Air pollution data are used as instrumental variables to address the causality between climate and grain production. The regression results show that: First, climatic variables all have a non-linear “increasing then decreasing” effect on food production. Second, SO 2 , PM 10 , and PM 2.5 have a negative impact on grain production. Based on the model, changes in the climatic production potential of grain crops can be calculated, and the future spatial layout of climate production can also be predicted by using random forests. Studies have shown that the median value of China’s grain production potential is decreasing, and the low value is increasing.

Keywords: climate change; food production; climatic production potential; random forest; spatial error model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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