TY - JOUR
AU - Kang, Wensheng
AB - This paper utilises Bayesian approach to extract latent common trends and cycles of non-stationary panel data. I develop a Markov Chain Monte Carlo (MCMC) algorithm to explore the highly dimensional posterior distribution of the panel model. Numerical simulation shows that the Bayesian approach based on this algorithm is effective at both estimating the elements of regression coefficients and error variance matrix and extracting latent components. To illustrate the potential of the approach, the study applies the method to investigate quarterly metropolitan housing prices and daily dot-com stock prices. The empirical results show the stronger the long-run growth the higher the cyclical volatility.
TI - Trends and cycles in non-stationary panel models
JO - International Journal of Mathematical Modelling and Numerical Optimisation
DO - 10.1504/IJMMNO.2014.059939
DA - 2014-01-01
UR - https://www.deepdyve.com/lp/inderscience-publishers/trends-and-cycles-in-non-stationary-panel-models-v5wanlx5uS
SP - 108
EP - 130
VL - 5
IS - 1
DP - DeepDyve
ER -