A0190
Title: A frequency domain wild bootstrap for dependent data (virtual presentation)
Authors: Rami Chehab - University of Exeter (United Kingdom) [presenting]
Abstract: A resampling method for stationary dependent time series is proposed which based on Rademacher wild bootstrap draws from the Fourier transform of the data. The main distinguishing feature of our method is that the bootstrap draws share their periodogram identically with the sample, implying good properties under dependence of arbitrary form. A drawback of the basic procedure, that the bootstrap distribution of the mean is degenerate, is overcome by a simple Gaussian augmentation. Monte Carlo evidence indicates a favourable comparison with alternative methods in tests of significance and of location in a regression model with autocorrelated shocks, and also of unit roots.
