Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors

Abstract

A positive Lyapunov exponent is one practical definition of chaos. We develop a formal test for chaos in a noisy system based on the consistent standard errors of the nonparametric Lyapunov exponent estimators. When our procedures are applied to international real output series, the hypothesis of the positive Lyapunov exponent is significantly rejected in many cases. One possible interpretation of this result is that the traditional exogenous models are better able to explain business cycle fluctuations than is the chaotic endogenous approach. However, our results are subject to a number of caveats, in particular our results could have been influenced by small sample bias, high noise level, incorrect filtering, and long memory of the data.

Keywords: Artificial neural networks, Business cycles, Local polynomial regression, Nonlinear dynamics, Nonlinear time series

JEL Classification: C14, E32