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Business Cycle Duration Dependence: A Parametric Approach

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Author Info
Sichel, Daniel E
Abstract

This paper reexamines duration dependence in U.S. business cycles using parametric hazard models. Positive duration dependence would indicate that expansions or contractions are more likely to end as they become "older." This paper provides statistically significant evidence of positive duration dependence for expansions before World War II and contractions after World War II. The evidence is stronger than in earlier research utilizing nonparametric techniques, because certain nonparametric techniques have low statistical power against the type of duration dependence found in this paper. Evidence is also presented suggesting that expansions became longer, on average, after World War II, while contractions became shorter. Copyright 1991 by MIT Press.

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Publisher Info
Article provided by MIT Press in its journal Review of Economics & Statistics.

Volume (Year): 73 (1991)
Issue (Month): 2 (May)
Pages: 254-60
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Handle: RePEc:tpr:restat:v:73:y:1991:i:2:p:254-60

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  1. Matteo Pelagatti, 2003. "Duration Dependent Markov-Switching Vector Autoregression: Properties, Bayesian Inference, Software and Application," Working Papers 20051101, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica, revised Nov 2005. [Downloadable!]
  2. Michael W. Klein, 1993. "Timing is All: Elections and the Duration of United States Business Cycles," NBER Working Papers 4383, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  3. Corrado Di Guilmi & Edoardo Gaffeo & Mauro Gallegati & Antonio Palestrini, 2004. "International evidence on business cycle magnitude dependence," Quantitative Finance Papers cond-mat/0401495, arXiv.org. [Downloadable!]
  4. Matteo M. Pelagatti, 2005. "Time Series Modeling with Duration Dependent Markov-Switching Vector Autoregressions: MCMC Inference, Software and Applications," Econometrics 0503008, EconWPA. [Downloadable!]
  5. 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!]
  6. Monica Billio & Roberto Casarin, 2008. "Identifying Business Cycle Turning Points with Sequential Monte Carlo Methods," Working Papers 0815, University of Brescia, Department of Economics. [Downloadable!]
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