A bootstrap-assisted spectral test of white noise under unknown dependence

Xiaofeng Shao

Journal of Econometrics, 2011, vol. 162, issue 2, 213-224

Abstract: To test for the white noise null hypothesis, we study the Cramér-von Mises test statistic that is based on the sample spectral distribution function. Since the critical values of the test statistic are difficult to obtain, we propose a blockwise wild bootstrap procedure to approximate its asymptotic null distribution. Using a Hilbert space approach, we establish the weak convergence of the difference between the sample spectral distribution function and the true spectral distribution function, as well as the consistency of bootstrap approximation under mild assumptions. Finite sample results from a simulation study and an empirical data analysis are also reported.

Keywords: Hypothesis; testing; Spectral; distribution; function; Time; series; White; noise; Wild; bootstrap (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (33)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:162:y:2011:i:2:p:213-224

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