Eco-efficiency of grain production in China based on water footprints: A stochastic frontier approach

Abstract Eco-efficiency has consistently been of interest to researchers and policy makers. Many methods have been employed to calculate eco-efficiency, with the exception of the stochastic frontier approach, which is popular in efficiency and productivity analysis. Considering the strengths of the stochastic frontier approach and the features of grain production, an integrated WF-SFA method combining water footprint assessment and the stochastic frontier approach is proposed in this work. In the method, the green, blue and grey water footprints of grain production are calculated. Then, a translog stochastic frontier production function with actual grain output value as the only output and capital, labour and water footprints as the inputs is established. Next, eco-efficiency, which is defined as the ratio of the actual output to the potential output, can be assessed. This method is developed here to analyse the eco-efficiency of grain production and its determinants in China. The main empirical results are as follows. 1) The annual average grain production water footprint in China from 1997 to 2015 was 820.37 billion m 3 . 2) The eco-efficiencies were estimated to be within the range of 0.424–0.986, with an average value of 0.807. There is potential for China to increase the environmental and ecological sustainability with its grain production system. 3) The per capita GDP, per capita water supply, proportion of government expenditure on environmental protection and proportion of non-disaster areas positively influenced the grain production eco-efficiency. In addition, the calculated output elasticities of the blue and grey water footprints of recent years were negative. These findings can help China design relevant policies of agricultural sustainability focused on crop distribution, efficient irrigation water use and nutrient and pollutant management. This research provides a basic framework for the eco-efficiency evaluation of grain production with the stochastic frontier approach which can inform policy and strategic development.