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Stochastic Trends, Deterministic Trends and Business Cycle Turning Points

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Author Info
GORDON, Stephen ()

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Abstract

This study examines the relationship between specifications for long-run output patterns and specifications for business cycle dynamics. In an application to US GDP, it is found that inferences about the nature of the trend in output are not robust to changes in the specification for short-run fluctuations. Similarly, the choice of which model best describes the transitory movements in output depends on the way in which the trend is specified. The empirical analysis makes use of Bayesian methods to compare non-nested models for US GDP. Inspection of the predictive likelihoods for the individual data points suggests that the information contained in the data is largely limited to the observations associated with business cycle turning points.

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File URL: http://www.ecn.ulaval.ca/w3/recherche/cahiers/1995/9503.ps
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Paper provided by Université Laval - Département d'économique in its series Cahiers de recherche with number 9503.

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Date of creation: 1995
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Handle: RePEc:lvl:laeccr:9503

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  1. E. Andersson & D. Bock & M. Frisén, 2006. "Some statistical aspects of methods for detection of turning points in business cycles," Journal of Applied Statistics, Taylor and Francis Journals, vol. 33(3), pages 257-278, April. [Downloadable!] (restricted)
  2. Koskinen, Lasse & Öller, Lars-Erik, 2001. "A Classifying Procedure for Signaling Turning Points," Working Paper Series in Economics and Finance 427, Stockholm School of Economics. [Downloadable!]
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  3. Clements, M.P. & Krolzig, H-M., 1999. "Business Cycle Asymmetries: Characterisationand Testing Based on Markov-Switching Autoregression," The Warwick Economics Research Paper Series (TWERPS) 522, University of Warwick, Department of Economics. [Downloadable!]
  4. John M Maheu & Thomas H McCurdy, 2007. "Modeling foreign exchange rates with jumps," Working Papers tecipa-279, University of Toronto, Department of Economics. [Downloadable!]
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