Seasonality and Markov switching in an unobserved component time series model |
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Authors: | Rob Luginbuhl Aart de Vos |
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Institution: | (1) Department of Econometrics, Vrije Universiteit, Amsterdam 1081 HV, The Netherlands (e-mail: eluginbuhl@feweb.vu.nl), NL |
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Abstract: | It is generally acknowledged that the growth rate of output, the seasonal pattern, and the business cycle are best estimated
simultaneously. To achieve this, we develop an unobserved component time series model for seasonally unadjusted US GDP. Our
model incorporates a Markov switching regime to produce periods of expansion and recession, both of which are characterized
by different underlying growth rates. Although both growth rates are time-varying, they are assumed to be cointegrated. The
analysis is Bayesian, which fully accounts for all sources of uncertainty. Comparison with results from a similar model for
seasonally adjusted data indicates that the seasonal adjustment of the data significantly alters several aspects of the full
model.
First Version Received: January 2001/Final Version Received: February 2002
Send offprint requests to: Rob Luginbuhl?Correspondence to: Rob Luginbuhl |
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Keywords: | : Business cycle Gibbs sampler Kalman filter Metropolis algorithm Simulation smoother |
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