Resources Science ›› 2019, Vol. 41 ›› Issue (5): 884-896.doi: 10.18402/resci.2019.05.06

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Change in agricultural green productivity in China considering the cost of carbon emissions

Jintao ZHAN1,2(), Yujiao XU1, Jihong GE1,2()   

  1. 1. College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China
    2. Research Center for China Food Security, Nanjing Agricultural University, Nanjing 210095, China
  • Received:2018-04-11 Revised:2018-08-31 Online:2019-05-25 Published:2019-05-25


Green development will become the key component of China’s future agricultural growth. Measuring green productivity of agriculture is conducive to identifying its current development stage. By introducing carbon emissions trading theory and taking agricultural green GDP considering carbon emission cost as output, nitrogen and phosphorus losses as an input factor, and using parameter stochastic frontier analysis (SFA) model, this study calculated and analyzed the provincial-level green total factor productivity (GTFP) change index of China’s agricultural sector from 2000 to 2015, then compared it with the traditional total factor productivity (TFP). The results show that the average annual decline of China’s agricultural GTFP was 0.14% during the study period, mainly due to the “retrogression” of environmental technologies before 2008/2009. The temporal trend fluctuated and the spatial distribution varied between regions. In addition, the index of TFP in agriculture was superior to GTFP’s, with an average annual increase of 0.02%,mainly due to technological progress, but the average traditional technology efficiency is declining. The key to improving the green productivity of agriculture in China in the future is to shift the focus of research and development investment away from overemphasizing output, strengthen the research and development of agricultural environmental technologies, and improve the technical efficiency of the traditional input factors.

Key words: agricultural green productivity, cost of carbon emissions, nitrogen loss, phosphorus loss, stochastic frontier analysis, China