EconPapers    
Economics at your fingertips  
 

Fast And Wild: Bootstrap Inference In Stata Using Boottest

David Roodman (), James MacKinnon (), Matthew Webb and Morten Nielsen ()

No 1406, Working Paper from Economics Department, Queen's University

Abstract: The wild bootstrap was originally developed for regression models with heteroskedasticity of unknown form. Over the past thirty years, it has been extended to models estimated by instrumental variables and maximum likelihood, and to ones where the error terms are (perhaps multi-way) clustered. Like bootstrap methods in general, the wild bootstrap is especiallyuseful when conventional inference methods are unreliable because large-sample assumptions do not hold. For example, there may be few clusters, few treated clusters, or weak instruments. The Stata package boottest can perform a wide variety of wild bootstrap tests, often at remarkable speed. It can also invert these tests to construct confidence sets. As a postestimation command, boottest works after linear estimation commands including regress, cnsreg, ivregress, ivreg2, areg, and reghdfe, as well as many estimation commands based on maximum likelihood. Although it is designed to perform the wild cluster bootstrap, boottest can also perform the ordinary (non-clustered) version. Wrappers offer classical Wald, score/LM, and Anderson-Rubin tests, optionally with (multi-way) clustering. We review the main ideasof the wild cluster bootstrap, offer tips for use, explain why it is particularly amenable to computational optimization, state the syntax of boottest, artest, scoretest, and waldtest, and present several empirical examples for illustration.

Keywords: artest; Anderson-Rubin test; Wald test; wild bootstrap; wild cluster bootstrap; score bootstrap; multi-way clustering; few treated clusters; boottest; waldtest (search for similar items in EconPapers)
JEL-codes: C15 C21 C23 C25 C36 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2018-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20) Track citations by RSS feed

Downloads: (external link)
https://www.econ.queensu.ca/sites/econ.queensu.ca/files/qed_wp_1406.pdf First version 2018 (application/pdf)

Related works:
Journal Article: Fast and wild: Bootstrap inference in Stata using boottest (2019) Downloads
Working Paper: Fast and Wild: Bootstrap Inference in Stata Using boottest (2018) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:qed:wpaper:1406

Access Statistics for this paper

More papers in Working Paper from Economics Department, Queen's University Contact information at EDIRC.
Bibliographic data for series maintained by Mark Babcock ().

 
Page updated 2020-07-01
Handle: RePEc:qed:wpaper:1406