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• W2089867346 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." @default.
• W2089867346 created "2016-06-24" @default.
• W2089867346 creator A5086059595 @default.
• W2089867346 date "2011-06-01" @default.
• W2089867346 modified "2023-10-14" @default.
• W2089867346 title "A bootstrap-assisted spectral test of white noise under unknown dependence" @default.
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• W2089867346 doi "https://doi.org/10.1016/j.jeconom.2011.01.001" @default.
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