Statistical analysis of the dynamic structure of china's economic sectors based on bayesian modeling

Hideo Noda, Koki Kyo

Research output: Contribution to journalArticle

2 Citations (Scopus)


This paper aims to develop an alternative production function-based approach for analyzing economic fluctuations at the sectoral level by applying Bayesian techniques. To estimate total factor productivity (TFP) and elasticities of output with respect to factors of production, we incorporate smoothness priors into statistical models based on sectoral production functions. In addition, we assume that TFP generally varies smoothly, but that in some situations there may be abrupt changes. Therefore, to avoid difficulties resulting from abrupt changes in TFP, a new method termed the random grouping method is introduced. Compared with the conventional production function approach, a main advantage of our proposed method is to make detailed analysis of complex movements of TFP possible by flexible modeling. To illustrate, we examine TFP trends in primary, secondary, and tertiary sectors of China's economy during 19782004. Estimation results suggest remarkable differences in TFP trends in the three sectors. For the period 2000-2004, the secondary and tertiary sectors have experienced stagnation in TFP growth, although to differing degrees.

Original languageEnglish
Pages (from-to)923-939
Number of pages17
Issue number3 B
Publication statusPublished - 1 May 2010


  • Bayesian modeling
  • Chinese economy
  • Random grouping method
  • Sectoral tfp
  • Smoothness priors

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