A test for independence based on the correlation dimension

W. A. Broock, Jose Scheinkman (), W. D. Dechert and B. LeBaron

Econometric Reviews, 1996, vol. 15, issue 3, pages 197-235

Abstract: This paper presents a test of independence that can be applied to the estimated residuals of any time series model that can be transformed into a model driven by independent and identically distributed errors. The first order asymptotic distribution of the test statistic is independent of estimation error provided that the parameters of the model under test can be estimated [image omitted] -consistently. Because of this, our method can be used as a model selection tool and as a specification test. Widely used software1 written by Dechert and LeBaron can be used to implement the test. Also, this software is fast enough that the null distribution of our test statistic can be estimated with bootstrap methods. Our method can be viewed as a nonlinear analog of the Box-Pierce Q statistic used in ARIMA analysis.

Keywords: Nonlinear Time Series; Specification Tests; Correlation Dimension; Chaos (search for similar items in EconPapers)
Date: 1996
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Working Paper: A Test for Independence Based on the Correlation Dimension (1995)
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