Journal
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
Volume 28, Issue 1, Pages 128-144Publisher
AMER STATISTICAL ASSOC
DOI: 10.1198/jbes.2009.07221
Keywords
Anderson-Rubin test; Confidence interval; Instrumental variables estimation; Pairs bootstrap; Residual bootstrap; Two-stage least squares; Weak instruments; Wild bootstrap
Funding
- Social Sciences and Humanities Research Council of Canada
- Economics, McGill University
- Fonds Quebecois de Recherche sur la Societe et la Culture
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We propose a wild bootstrap procedure for linear regression models estimated by instrumental variables. Like other bootstrap procedures that we proposed elsewhere, it uses efficient estimates of the reduced form equation(s). Unlike the earlier procedures, it takes account of possible heteroscedasticity of unknown form. We apply this procedure to t tests, including heteroscedasticity-robust t tests, and to the Anderson-Rubin test. We provide simulation evidence that it works far better than older methods, such as the pairs bootstrap. We also show how to obtain reliable confidence intervals by inverting bootstrap tests. An empirical example illustrates the utility of these procedures.
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