Markov Trends in Macroeconomic Time Series
Many macroeconomic time series are characterised by long periods of positive growth, expansion periods, and short periods of negative growth, recessions. A popular model to describe this phenomenon is the Markov trend, which is a stochastic segmented trend where the slope depends on the value of an unobserved two-state first-order Markov process. The two slopes of the Markov trend describe the growth rates in the two phases of the business cycle. This thesis deals with a Bayesian analysis of univariate and multivariate macroeconomic time series using Markov trend models. We consider Bayesian methods to analyse the presence of stochastic trends and the business cycle.
|Keywords||Markov processes, methods and techniques, time series|
|Promotor||Dijk, H.K. van (Herman)|
|Sponsor||Dijk, Prof. Dr. H.K. van (promotor)|
|Publisher||Thela Thesis, Amsterdam|
Paap, R.. (1997, November 27). Markov Trends in Macroeconomic Time Series. Thela Thesis, Amsterdam. Retrieved from http://hdl.handle.net/1765/2043
|dissert.zip Final Version , 1mb|