Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5097554 | Journal of Econometrics | 2006 | 38 Pages |
Abstract
A nonparametric, residual-based stationary bootstrap procedure is proposed for unit root testing in a time series. The procedure generates a pseudoseries which mimics the original, but ensures the presence of a unit root. Unlike many others in the literature, the proposed test is valid for a wide class of weakly dependent processes and is not based on parametric assumptions on the data-generating process. Large sample theory is developed and asymptotic validity is shown via a bootstrap functional central limit theorem. The case of a least squares statistic is discussed in detail, including simulations to investigate the procedure's finite sample performance.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Cameron Parker, Efstathios Paparoditis, Dimitris N. Politis,