Bayesian Analysis of an Unobserved-Component Time Series Model of GDP with Markov-Switching and Time-Varying Growths
AbstractWe propose an unobserved-component time series model of gross domestic product that includes Markov switching as an unobserved component. In addition to a trend component, the model has two time-varying drift components. One drift represents the expected rate of growth during recession; the other drift represents the expected rate during expansion. Estimates indicate a substantial decline in the latter annual rate for the United States from 6.4% in 1950 to 3.6% by 1990. We have employed weak priors based on prewar data. The estimation makes use of the Gibbs sampler and the Metropolis algorithm.
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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 17 (1999)
Issue (Month): 4 (October)
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