http://hdl.handle.net/1765/2043
series: TI; Tinbergen Institute Research Series No. 171

Markov Trends in Macroeconomic Time Series

(Markov Trends in Macro economische Tijdreeksen)


Doctoral Thesis
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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.


Supervisor (promotor):

Prof. Dr. Dijk, H.K. van

The author wishes to thank:

Dijk, Prof. Dr. H.K. van (promotor)


Keywords


Automatically Extracted Terms
  • trend
  • model
  • markov
  • series
  • cointegration
  • markov trend
  • parameter
  • section
  • speci
  • cation
  • analysis
  • time series
  • markov trend model
  • factor
  • bayesian
  • distribution
  • speci cation
  • business cycle
  • unit roots
  • probability