Energy consumption, CO2 emissions, and agricultural disaster efficiency evaluation of China based on the two-stage dynam
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RESEARCH ARTICLE
Energy consumption, CO2 emissions, and agricultural disaster efficiency evaluation of China based on the two-stage dynamic DEA method Fang-rong Ren 1
&
Ze Tian 2 & Hang-sheng Chen 2 & Yu-ting Shen 2
Received: 4 March 2020 / Accepted: 1 July 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract With a large agricultural sector, China is greatly affected by natural disasters caused by extreme weather events. Because the occurrence of natural disasters is closely related to the sharp increased consumption of energy and the massive emissions of carbon dioxide, this research examines relevant data from 2013 to 2017 in four major regions of China that cover 30 provincial administrative regions. Using the two-stage dynamic DEA model, we evaluate total efficiency value, two-stage efficiency value, and the efficiencies of energy consumption, CO2 emissions, and crop disaster areas, setting CO2 as the link between the production stage (first stage) and the crop damage stage (second stage). The research findings show that overall efficiency in China is generally low, whereby the total efficiencies of eastern and northeastern China are higher than those of central and western China. The efficiency value of the first stage (production stage) is greater than that of the second stage (crop damage stage), and the efficiency of most administrative regions’ second stage is below 0.3, which is the main reason for the country’s low overall efficiency. There is little difference between China’s CO2 and energy consumption efficiency scores, but the efficiency values of crop disaster areas fluctuate greatly. The efficiency scores of various indicators in the eastern region are generally higher and more balanced, and the total efficiency scores exhibit a decreasing trend from east to west. Therefore, it is necessary to implement the environmental policy of controlling energy consumption and early warning of natural disasters in the central and western regions, and promote the R&D industry and technological innovation of carbon dioxide emission reduction and disaster control in the economically developed eastern regions. Keywords CO2 emission . Agricultural disaster . Energy consumption . Two-stage dynamic DEA . Efficiency
Abbreviations CCR Charnes & Cooper & Rhodes BCC Banker & Charnes & Cooper Responsible editor: Eyup Dogan * Fang-rong Ren [email protected] Ze Tian [email protected] Hang-sheng Chen [email protected] Yu-ting Shen [email protected] 1
Business School, Hohai University, Nanjing 211100, China
2
Business School, Hohai University, Changzhou 213022, China
SBM DMU MPI ARDL VECM CPI St. dev. CNY AVE LMDI PDA DEA
Slacks-based measure Decision-making unit Malmquist productivity index Autoregressive distributed lag Vector error correction model Consumer Price Index Standard deviation China yuan Average Logarithmic mean Divisia index Production decomposition analysis Data envelopment analysis
Introduction With global climate change, coastal flooding, and inland droughts, the destruction
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