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Duration Dependence In The Us Business Cycle


  • Allan P. Layton
  • Daniel R. Smith


Durland and McCurdy (1994) investigated the issue of duration dependence in US business cycle phases using a Markov regime switching approach, introduced by Hamilton (1989) and extended to the case of variable transition parameters by Filardo (1994). In Durland and McCurdy’s model duration alone was used as an explanatory of the transition probabilities. They found that recessions were duration dependent whilst expansions were not. In this paper, we explicitly incorporate the widely-accepted US business cycle phase change dates as determined by the NBER, and use a state-dependent multinomial Logit (and Probit) modelling framework. The model incorporates both duration and movements in two leading indexes - one designed to have a short lead (SLI) and the other designed to have a longer lead (LLI) - as potential explanators. We find that doing so suggests that current duration is not only a significant determinant of transition out of recessions, but that there is some evidence that it is also weakly significant in the case of expansions. Furthermore, we find that SLI has more informational content for the termination of recessions whilst LLI does so for expansions.

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  • Allan P. Layton & Daniel R. Smith, 2003. "Duration Dependence In The Us Business Cycle," School of Economics and Finance Discussion Papers and Working Papers Series 152, School of Economics and Finance, Queensland University of Technology.
  • Handle: RePEc:qut:dpaper:152

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    1. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
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    6. Thompson, Patrick A & Noordewier, Thomas, 1992. "Estimating the Effects of Consumer Incentive Programs on Domestic Automobile Sales," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 409-417, October.
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