Applications of the Fast Double Bootstrap

James MacKinnon ()

No 1023, Working Papers from Queen's University, Department of Economics

Abstract: The fast double bootstrap, or FDB, is a procedure for calculating bootstrap P values that is much more computationally efficient than the double bootstrap itself. In many cases, it can provide more accurate results than ordinary bootstrap tests. For the fast double bootstrap to be valid, the test statistic must be asymptotically independent of the random parts of the bootstrap data generating process. This paper presents simulation evidence on the performance of FDB tests in three cases of interest to econometricians. One of the cases involves both symmetric and equal-tail bootstrap tests, which, interestingly, can have quite different power properties. Another highlights the importance of imposing the null hypothesis on the bootstrap DGP.

Keywords: bootstrap test; serial correlation; ARCH errors; weak instruments; double bootstrap; fast double bootstrap; FDB (search for similar items in EconPapers)
JEL-codes: C12 C15 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: Written
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