Author(s)

Kai Cui, Wenshan Cui

Department of Statistical Science, Duke University, Durham, USA.
School of Science and Information, Qingdao Agricultural University, Qingdao, China.

The concept of cointegration is widely used in applied non-stationary time series analysis to describe the co-movement of data measured over time. In this paper, we proposed a Bayesian model for cointegration test and analysis, based on the dynamic latent factor framework. Efficient computational algorithms are also developed based on Markov Chain Monte Carlo (MCMC). Performance and efficiency of the the model and approaches are assessed by simulated and real data analysis.

Cointegration; Bayesian; Dynamic Factor; Non-Stationary; Root Structure; MCMC

K. Cui and W. Cui, "Bayesian Factorized Cointegration Analysis," Open Journal of Statistics, Vol. 2 No. 5, 2012, pp. 504-511. doi: 10.4236/ojs.2012.25065.