Reproducing Business Cycle Features: Are Nonlinear Dynamics a Proxy for Multivariate Information?

37 Pages Posted: 27 Mar 2012

See all articles by James Morley

James Morley

University of Sydney

Jeremy Piger

University of Oregon - Department of Economics

Pao-Lin Tien

affiliation not provided to SSRN

Date Written: March 23, 2012

Abstract

We consider the extent to which different time-series models can generate simulated data with the same business cycle features that are evident in U.S. real GDP. We focus our analysis on whether multivariate linear models can improve on the previously documented failure of univariate linear models to replicate certain key business cycle features. We find that a particular nonlinear Markov-switching specification with an explicit “bounceback” effect continues to outperform linear models, even when the models incorporate variables such as the unemployment rate, inflation, interest rates, and the components of GDP. These results are robust to simulated data generated either using Normal disturbances or bootstrapped disturbances, as well as to allowing for a one-time structural break in the variance of shocks to real GDP growth.

Keywords: Business cycle features, nonlinear dynamics, multivariate models

JEL Classification: E30, C52

Suggested Citation

Morley, James and Piger, Jeremy M. and Tien, Pao-Lin, Reproducing Business Cycle Features: Are Nonlinear Dynamics a Proxy for Multivariate Information? (March 23, 2012). UNSW Australian School of Business Research Paper No. 2012ECON23. Available at SSRN: https://ssrn.com/abstract=2028742 or http://dx.doi.org/10.2139/ssrn.2028742

James Morley (Contact Author)

University of Sydney ( email )

Rm 370 Merewether (H04)
Sydney, NSW 2006 2008
Australia

HOME PAGE: http://https://sites.google.com/site/jamescmorley/

Jeremy M. Piger

University of Oregon - Department of Economics ( email )

Eugene, OR 97403
United States

Pao-Lin Tien

affiliation not provided to SSRN

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