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A time-varying threshold STAR model of unemployment and the natural rate

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  • Michael J. Dueker
  • Michael T. Owyang
  • Martin Sola

Abstract

Smooth-transition autoregressive (STAR) models have proven to be worthy competitors of Markov-switching models of regime shifts, but the assumption of a time-invariant threshold level does not seem realistic and it holds back this class of models from reaching their potential usefulness. Indeed, an estimate of a time-varying threshold level of unemployment, for example, might serve as a meaningful estimate of the natural rate of unemployment. More precisely, within a STAR framework, one might call the time-varying threshold the “tipping level” rate of unemployment, at which the mean and dynamics of the unemployment rate shift. In addition, once the threshold level is allowed to be time-varying, one can add an error-correction term—between the lagged level of unemployment and the lagged threshold level—to the autoregressive terms in the STAR model. In this way, the time-varying latent threshold level serves dual roles: as a demarcation between regimes and as part of an error-correction term.free rate puzzles, and the occurrence of trading break-downs.

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Bibliographic Info

Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2010-029.

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Date of creation: 2010
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Handle: RePEc:fip:fedlwp:2010-029

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Keywords: Time-series analysis ; Capital assets pricing model ; Unemployment;

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  1. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
  2. Tara M. Sinclair, 2009. "The Relationships between Permanent and Transitory Movements in U.S. Output and the Unemployment Rate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 529-542, 03.
  3. Skalin, Joakim & Ter svirta, Timo, 2002. "Modeling Asymmetries And Moving Equilibria In Unemployment Rates," Macroeconomic Dynamics, Cambridge University Press, vol. 6(02), pages 202-241, April.
  4. Michael J. Dueker & Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2010. "State-Dependent Threshold STAR Models," UFAE and IAE Working Papers 818.10, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
  5. Deschamps, Philippe J., 2007. "Comparing smooth transition and Markov switching autoregressive models of US Unemployment," DQE Working Papers 7, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised 04 Jun 2008.
  6. Marcelle Chauvet & Chinhui Juhn & Simon Potter, 2001. "Markov switching in disaggregate unemployment rates," Staff Reports 132, Federal Reserve Bank of New York.
  7. Michael T. Owyang, 2001. "Persistence, excess volatility, and volatility clusters in inflation," Review, Federal Reserve Bank of St. Louis, issue Nov., pages 41-52.
  8. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August.
  9. Basistha, Arabinda & Nelson, Charles R., 2007. "New measures of the output gap based on the forward-looking new Keynesian Phillips curve," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 498-511, March.
  10. Clark, Peter K., 1989. "Trend reversion in real output and unemployment," Journal of Econometrics, Elsevier, vol. 40(1), pages 15-32, January.
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