Bayesian analysis of the dynamic structure in China’s economic growth

To analyze the dynamic structure in China’s economic growth during the period 1952–1998, we introduce a model of the aggregate production function for the Chinese economy that considers total factor productivity (TFP) and output elasticities as time‐varying parameters. Specifically, this paper is concerned with the relationship between the rate of economic growth in China and the trend in TFP. Here, we consider the time‐varying parameters as random variables and introduce smoothness priors to construct a set of Bayesian linear models for parameter estimation. The results of the estimation are in agreement with the movements in China’s social economy, thus illustrating the validity of the proposed methods.