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

A positive Lyapunov exponent is one pratical definition of chaos. We develop a formal test for chaos in a noisy system based on the sign of the Lyapunov exponent. The test utilizes nonparametric regression techniques including local quadratic regression and neural networks. When our procedures are applied to international real output series, the Lyapunov exponent estimates are negative and the positivity hypothesis of the expononent 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.