Explaining production inefficiency in China's agriculture using data envelopment analysis and semi-parametric bootstrapping

In this paper we examine more closely the factors associated with production inefficiency in China's agriculture. The approach we take involves a two-stage process where output efficiency scores are first estimated using data envelopment analysis, and then in the second stage, variation in the resulting efficiency scores is explained using a truncated regression model with inference based on a semi-parametric bootstrap routine. Among the results we find that a heavy industrial presence is associated with reduced agricultural production efficiency and may be an indication that externalities from the industrial process, such as air and ground water pollution, affect agricultural production. We also find evidence that counties with a large percentage of the rural labor force engaged in agriculture tend to be less efficient, and suggests that nurturing and promoting growth of non-primary agriculture may lead to more efficient use of labor resources in agriculture.