Higher-Order Improvements of a Computationally Attractive-Step Bootstrap for Extremum Estimators

Donald Andrews ()

No 1230R, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: This paper establishes the higher-order equivalence of the k-step bootstrap, introduced recently by Davidson and MacKinnon (1999a), and the standard bootstrap. The k-step bootstrap is a very attractive alternative computationally to the standard bootstrap for statistics based on nonlinear extremum estimators, such as generalized method of moment and maximum likelihood estimators. The paper also extends results of Hall and Horowitz (1996) to provide new results regarding the higher-order improvements of the standard bootstrap and the k-step bootstrap for extremum estimators (compared to procedures based on first-order asymptotics). The results of the paper apply to Newton-Raphson (NR), default NR, line-search NR, and Gauss-Newton k-step bootstrap procedures. The results apply to the nonparametric iid bootstrap, non-overlapping and overlapping block bootstraps, and restricted and unrestricted parametric bootstraps. The results cover symmetric and equal-tailed two-sided t tests and confidence intervals, one-sided t tests and confidence intervals, Wald tests and confidence regions, and J tests of over-identifying restrictions.

Keywords: Asymptotics; block bootstrap; Edgeworth expansion; extremum estimator; Gauss-Newton; generalized method of moments estimator; k-step bootstrap; maximum likelihood estimator; Newton-Raphson; parametric bootstrap; t statistic; test of over-identifying (search for similar items in EconPapers)
JEL-codes: C12 C13 C15 (search for similar items in EconPapers)
Pages: 66 pages
Date: 1999-07, Revised 2001-01
Note: CFP 1031.
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published in Econometrica (January 2002), 70(1): 70(1): 119-162

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Related works:
Journal Article: Higher-Order Improvements of a Computationally Attractive "k"-Step Bootstrap for Extremum Estimators (2002)
Working Paper: Higher-Order Improvements of a Computationally Attractive-Step Bootstrap for Extremum Estimators (1999)
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