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

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.