Bayesian Estimation and Model Selection in the Generalized Stochastic Unit Root Model

Abstract

We develop Bayesian techniques for estimation and model comparison in a novel Generalized Stochastic Unit Root (GSTUR) model. This allows us to investigate the presence of a deterministic time trend in economic series, while allowing the degree of persistence to change over time. In particular the model allows for shifts from stationarity I(0) to nonstationarity I(1) or vice versa. The empirical analysis demonstrates that the GSTUR model provides new insights on the properties of some macroeconomic time series such as stock market indices, inflation and exchange rates.