Some Theory of Statistical Inference for Nonlinear Science

William Brock and Ehung G. Baek

The Review of Economic Studies, 1991, vol. 58, issue 4, 697-716

Abstract: This article shows how standard errors can be estimated for a measure of the number of excited degrees of freedom (the correlation dimension), and a measure of the rate of information creation (a proxy for the Kolmogorov entropy), and a measure of instability. These measures are motivated by nonlinear science and chaos theory. The main analytical method is central limit theory of U-statistics for mixing processes. The paper takes a step toward formal hypothesis testing in nonlinear science and chaos theory.

Date: 1991
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Persistent link: https://EconPapers.repec.org/RePEc:oup:restud:v:58:y:1991:i:4:p:697-716.

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