The Importance of Nonlinearity in Reproducing Business Cycle Features

FRB St. Louis Working Paper No. 2004-032B

27 Pages Posted: 28 Jul 2005

See all articles by James Morley

James Morley

University of Sydney

Jeremy Piger

University of Oregon - Department of Economics

Date Written: May 2005

Abstract

This paper considers the ability of simulated data from linear and nonlinear time-series models to reproduce features in U.S. real GDP data related to business cycle phases. We focus our analysis on a number of linear ARIMA models and nonlinear Markov-switching models. To determine the timing of business cycle phases for the simulated data, we present a model-free algorithm that is more successful than previous methods at matching NBER dates and associated features in the postwar data. We find that both linear and Markov-switching models are able to reproduce business cycle features such as the average growth rate in recessions, the average length of recessions, and the total number of recessions. However, we find that Markov-switching models are better than linear models at reproducing the variability of growth rates in different business cycle phases. Furthermore, certain Markov-switching specifications are able to reproduce high-growth recoveries following recessions and a strong correlation between the severity of a recession and the strength of the subsequent recovery. Thus, we conclude that nonlinearity is important in reproducing business cycle features.

Keywords: business cycle, nonlinear, regime switching

JEL Classification: E32, E37

Suggested Citation

Morley, James and Piger, Jeremy M., The Importance of Nonlinearity in Reproducing Business Cycle Features (May 2005). FRB of St. Louis Working Paper No. 2004-032B. Available at SSRN: https://ssrn.com/abstract=761006 or http://dx.doi.org/10.2139/ssrn.761006

James Morley

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 (Contact Author)

University of Oregon - Department of Economics ( email )

Eugene, OR 97403
United States

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