Sieve bootstrap t-tests on long-run average parameters

Fuertes, A. (2008). Sieve bootstrap t-tests on long-run average parameters. Computational Statistics & Data Analysis, 52(7), pp. 3354-3370. doi: 10.1016/j.csda.2007.11.014

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Panel estimators can provide consistent measures of a long-run average parameter even if the individual regressions are spurious. However, the t-test on this parameter is fraught with problems because the limit distribution of the test statistic is non-standard and rather complicated, particularly in panels with mixed (non-)stationary errors. A sieve bootstrap framework is suggested to approximate the distribution of the t-statistic. An extensive Monte Carlo study demonstrates that the bootstrap is quite useful in this context.

Item Type: Article
Additional Information: NOTICE: this is the author’s version of a work that was accepted for publication in Computational Statistics & Data Analysis. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computational Statistics & Data Analysis, Volume 52, Issue 7, 15 March 2008,
Subjects: H Social Sciences > HG Finance
Divisions: Cass Business School > Faculty of Finance
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