On the Number of Bootstrap Repetitions for Bootstrap Standard Errors, Confidence Intervals, and Tests

Donald Andrews () and Moshe Buchinsky

No 1141R, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: This paper considers the problem of choosing the number of bootstrap repetitions B for bootstrap standard errors, confidence intervals, and tests. For each of these problems, the paper provides a three-step method for choosing B to achieve a desired level of accuracy. Accuracy is measured by the percentage deviation of the bootstrap standard error estimate, confidence interval endpoint(s), test's critical value, or test's p-value based on B bootstrap simulations from the corresponding ideal bootstrap quantities for which B = infinity. Monte Carlo simulations show that the proposed methods work quite well. The results apply quite generally to parametric, semiparametric, and nonparametric models with independent and dependent data. The results apply to the standard nonparametric iid bootstrap, moving block bootstraps for time series data, parametric and semiparametric bootstraps, and bootstraps for regression models based on bootstrapping residuals.

Keywords: Bootstrap; bootstrap repetitions; coefficient of excess kurtosis; confidence interval; density estimation; hypothesis test; p-value; quantile; simulation; standard error estimate (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 C15 (search for similar items in EconPapers)
Pages: 52 pages
Date: 1997-08
Note: CFP 1069.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Published in Econometric Theory (2002), 18: 962-984

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