Explaining Production Inefficiency in China’s Agriculture using Data Envelope 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 envelope analysis (DEA), and then in the second stage, variation in the resulting efficiency scores are explained using a truncated regression model with inference based on a semi-parametric bootstrap routine. Among the results we find a heavy industrial presence is associated with reduced agricultural production efficiency and may be an indication that externalities from the industrial process, like 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, which suggests that policies to facilitate the removal of labor from agriculture, but not necessarily from the rural areas, would bring about enhanced agricultural efficiency and calls into question policies that promote wholesale migration from rural areas. Sensitivity analysis indicates results are robust to influential observations and outliers