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Can regime-switching models reproduce the business cycle features of US aggregate consumption, investment and output?

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Author Info

  • Michael P. Clements

    (Department of Economics, University of Warwick, UK)

  • Hans-Martin Krolzig

    (Department of Economics, University of Oxford, UK)

Abstract

The ability of Markov-switching (MS) autoregressive models to replicate selected classical business cycle features found in US post-war consumption, investment and output is compared to that of linear models. Univariate MS models appear to offer more dynamically parsimonious representations, but generally are unable to reproduce features missed by linear models. In the multivariate models, some cointegration restrictions were found to have a crucial impact, and the ability of models that imposed cointegration to reproduce business cycle features was enhanced by Markov switching. Copyright © 2004 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/ijfe.231
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal International Journal of Finance & Economics.

Volume (Year): 9 (2004)
Issue (Month): 1 ()
Pages: 1-14

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Handle: RePEc:ijf:ijfiec:v:9:y:2004:i:1:p:1-14

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References

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  1. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
  2. Filardo, Andrew J. & Gordon, Stephen F., 1998. "Business cycle durations," Journal of Econometrics, Elsevier, vol. 85(1), pages 99-123, July.
  3. Acemoglu, Daron & Scott, Andrew, 1994. "Asymmetries in the Cyclical Behaviour of UK Labour Markets," Economic Journal, Royal Economic Society, vol. 104(427), pages 1303-23, November.
  4. Robert G. King & Charles I. Plosser, 1989. "Real business cycles and the test of the Adelmans," Proceedings, Federal Reserve Bank of San Francisco.
  5. Krolzig, Hans-Martin & Sensier, Marianne, 2000. "A Disaggregated Markov-Switching Model of the Business Cycle in UK Manufacturing," Manchester School, University of Manchester, vol. 68(4), pages 442-60, Special I.
  6. Timothy Cogley & James M. Nason, 1993. "Output dynamics in real business cycle models," Working Papers in Applied Economic Theory 93-10, Federal Reserve Bank of San Francisco.
  7. Canova, Fabio, 1993. "Detrending and Business Cycle Facts," CEPR Discussion Papers 782, C.E.P.R. Discussion Papers.
  8. Hamilton, James D., 1996. "Specification testing in Markov-switching time-series models," Journal of Econometrics, Elsevier, vol. 70(1), pages 127-157, January.
  9. Hans-Martin Krolzig & Michael P. Clements, 2002. "Can oil shocks explain asymmetries in the US Business Cycle?," Empirical Economics, Springer, vol. 27(2), pages 185-204.
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Cited by:
  1. James Morley & Jeremy M. Piger, 2005. "The importance of nonlinearity in reproducing business cycle features," Working Papers 2004-032, Federal Reserve Bank of St. Louis.
  2. James Morley & Jeremy Piger & Pao-Lin Tien, 2012. "Reproducing Business Cycle Features: Are Nonlinear Dynamics a Proxy for Multivariate Information?," Discussion Papers 2012-23, School of Economics, The University of New South Wales.
  3. David N. DeJong & Hariharan Dharmarajan & Roman Liesenfeld & Jean-Francois Richard, 2008. "Exploiting Non-Linearities in GDP Growth for Forecasting and Anticipating Regime Changes," Working Papers 367, University of Pittsburgh, Department of Economics, revised Sep 2008.
  4. James Morley & Jeremy Piger & Pao-Lin Tien, 2009. "Reproducing Business Cycle Features: How Important Is Nonlinearity Versus Multivariate Information?," Wesleyan Economics Working Papers 2009-003, Wesleyan University, Department of Economics.

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