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

Author

Listed:
  • 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.

Suggested Citation

  • 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.
    • Handle: RePEc:wes:weswpa:2009-003
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    File URL: http://repec.wesleyan.edu/pdf/ptien/2009003_tien.pdf
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    References listed on IDEAS

    as
    1. 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 655-673, September.
    2. Boldin Michael D., 1996. "A Check on the Robustness of Hamilton's Markov Switching Model Approach to the Economic Analysis of the Business Cycle," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(1), pages 1-14, April.
    3. Chang‐Jin Kim & James Morley & Jeremy Piger, 2005. "Nonlinearity and the permanent effects of recessions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 291-309.
    4. McQueen, Grant & Thorley, Steven, 1993. "Asymmetric business cycle turning points," Journal of Monetary Economics, Elsevier, vol. 31(3), pages 341-362, June.
    5. James Morley & Jeremy Piger, 2012. "The Asymmetric Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 208-221, February.
    6. 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 357-384, March.
    7. King, Robert G. & Plosser, Charles I. & Stock, James H. & Watson, Mark W., 1991. "Stochastic Trends and Economic Fluctuations," American Economic Review, American Economic Association, vol. 81(4), pages 819-840, September.
    8. Frédérick Demers & Ryan Macdonald, 2007. "The Canadian Business Cycle: A Comparison of Models," Staff Working Papers 07-38, Bank of Canada.
    9. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    10. 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.
    11. James Morley & Jeremy Piger, 2006. "The Importance of Nonlinearity in Reproducing Business Cycle Features," Contributions to Economic Analysis, in: Nonlinear Time Series Analysis of Business Cycles, pages 75-95, Emerald Group Publishing Limited.
    12. Margaret M. 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.
    13. Hess, Gregory D & Iwata, Shigeru, 1997. "Measuring and Comparing Business-Cycle Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 432-444, October.
    14. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    15. Friedman, Milton, 1993. "The "Plucking Model" of Business Fluctuations Revisited," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 171-177, April.
    16. Jean Boivin & Marc P. Giannoni, 2006. "Has Monetary Policy Become More Effective?," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 445-462, August.
    17. 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.
    18. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Reproducing business cycle features: what for?
      by Economic Logician in Economic Logic on 2009-06-29 23:22:00

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    Cited by:

    1. Frédérique BEC & Othman BOUABDALLAH & Laurent FERRARA, 2011. "The Possible Shapes of Recoveries in Markov-Switching Models," Working Papers 2011-02, Center for Research in Economics and Statistics.
    2. Bec, Frédérique & Bouabdallah, Othman & Ferrara, Laurent, 2015. "Comparing the shape of recoveries: France, the UK and the US," Economic Modelling, Elsevier, vol. 44(C), pages 327-334.

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    More about this item

    JEL classification:

    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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