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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)

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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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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
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Handle: RePEc:wes:weswpa:2009-003

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Find related papers by 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 and Testing

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  1. 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. [Downloadable!]
  2. 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.
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  3. Margaret M. McConnell & Gabriel Perez-Quiros, 2000. "Output Fluctuations in the United States: What Has Changed since the Early 1980's?," American Economic Review, American Economic Association, vol. 90(5), pages 1464-1476, December. [Downloadable!] (restricted)
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  4. 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. [Downloadable!] (restricted)
  5. 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, October. [Downloadable!] (restricted)
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  6. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March. [Downloadable!] (restricted)
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  7. 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. [Downloadable!] (restricted)
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  8. McQueen, Grant & Thorley, Steven, 1993. "Asymmetric business cycle turning points," Journal of Monetary Economics, Elsevier, vol. 31(3), pages 341-362, June. [Downloadable!] (restricted)
  9. 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. [Downloadable!] (restricted)
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