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Reproducing Business Cycle Features: How Important Is Nonlinearity Versus Multivariate Information?

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Author Info

  • James Morley

    (Washington University in St. Louis)

  • Jeremy Piger

    (University of Oregon)

  • Pao-Lin Tien

    ()
    (Department of Economics, Wesleyan University)

Abstract

In this paper, we consider the ability of time-series models to generate simulated data that display the same business cycle features found in U.S. real GDP. Our analysis of a range of popular time-series models allows us to investigate the extent to which multivariate information can account for the apparent univariate evidence of nonlinear dynamics in GDP. We find that certain nonlinear specifications yield an improvement over linear models in reproducing business cycle features, even when multivariate information inherent in the unemployment rate, inflation, interest rates, and the components of GDP is taken into account.

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File URL: http://repec.wesleyan.edu/pdf/ptien/2009003_tien.pdf
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Bibliographic Info

Paper provided by Wesleyan University, Department of Economics in its series Wesleyan Economics Working Papers with number 2009-003.

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Length: 33 pages
Date of creation: May 2009
Date of revision:
Handle: RePEc:wes:weswpa:2009-003

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References

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  1. Chang-Jin Kim & James Morley & Jeremy Piger, 2003. "Nonlinearity and the permanent effects of recessions," Working Papers 2002-014, Federal Reserve Bank of St. Louis.
  2. 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.
  3. Frédérick Demers & Ryan Macdonald, 2007. "The Canadian Business Cycle: A Comparison of Models," Working Papers 07-38, Bank of Canada.
  4. McQueen, Grant & Thorley, Steven, 1993. "Asymmetric business cycle turning points," Journal of Monetary Economics, Elsevier, vol. 31(3), pages 341-362, June.
  5. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-73, September.
  6. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
  7. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  8. Robert G. King & Charles I. Plosser & James H. Stock & Mark W. Watson, 1991. "Stochastic trends and economic fluctuations," Working Paper Series, Macroeconomic Issues 91-4, Federal Reserve Bank of Chicago.
  9. Jean Boivin & Marc P. Giannoni, 2003. "Has Monetary Policy Become More Effective?," NBER Working Papers 9459, National Bureau of Economic Research, Inc.
  10. Margaret McConnell & Gabriel Perez Quiros, 2000. "Output fluctuations in the United States: what has changed since the early 1980s?," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  11. James Morley & Jeremy Piger, 2012. "The Asymmetric Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 208-221, February.
  12. Hess, Gregory D & Iwata, Shigeru, 1997. "Measuring and Comparing Business-Cycle Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 432-44, October.
  13. Beatriz C. Galvao, Ana, 2002. "Can non-linear time series models generate US business cycle asymmetric shape?," Economics Letters, Elsevier, vol. 77(2), pages 187-194, October.
  14. Michael P. Clements & Hans-Martin Krolzig, 2004. "Can regime-switching models reproduce the business cycle features of US aggregate consumption, investment and output?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 9(1), pages 1-14.
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Blog mentions

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  1. Reproducing business cycle features: what for?
    by Economic Logician in Economic Logic on 2009-06-29 18:22:00

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