The purpose of this paper is to perform an investigative analysis of the distribution of agricultural growth in China and the evolution of the decision mechanism.
The kernel density estimation method was used to investigate the distribution of agricultural growth in China using 1988‐2008 panel data of the 29 provinces on the mainland. A nonparametric income distribution approach was employed to decompose China's agricultural output growth into farmland accumulation, capital deepening, labor‐scale change, technical change, and efficiency change based on stochastic frontier function. A further investigation of the evolution of the decision mechanism for agricultural growth was then performed using counterfactual analysis.
The results of this analysis indicate that: from 1996, the distribution of agricultural output per worker evolved from a unimodal into a bimodal distribution; technical change is the primary impetus to distribution shift; and capital deepening and efficiency change play a dominant role in the deformation of the distribution of agricultural output per worker from a unimodal to a bimodal distribution.
The paper is an original work and its methodology makes a meaningful contribution to understanding China's agricultural growth. That is, the use of income distribution analysis method to analyze agricultural growth does not only allow a more in‐depth understanding of the gap between regional agricultural growth rates, but also makes up for the existing lack of convergence in agricultural growth in China.
