Economics at your fingertips  

BOOTTEST: Stata module to provide fast execution of the wild bootstrap with null imposed

David Roodman ()

Statistical Software Components from Boston College Department of Economics

Abstract: boottest is a post-estimation command that offers fast execution of the wild bootstrap (Wu 1986) with null imposed, as recommended by Cameron, Gelbach, and Miller (2008) for estimates with clustered standard errors and few clusters. It also performs the “score bootstrap” (Kline and Santos 2012), which adapts the wild approach to Maximum Likelihood estimators. Two wrappers, waldtest and scoretest, give easy access to the classical Wald (1943) and Rao (1948) score/Lagrange multiplier tests. boottest works after regress, cnsreg, ivreg, ivregress, ivreg2 and most Stata ML-based estimation commands. boottest offers inference based on multi-way clustering after many Stata estimation commands that do not otherwise support it. When bootstrapping, it offers a choice of Rademacher, Mammen (1993), Webb (2014), and standard normal weights. boottest requires Stata version 11.2 or later and runs fastest in version 13 or later.

Language: Stata
Requires: Stata version 11.2
Keywords: wild bootstrap; Cameron; Gelbach; Miller; score bootstrap; Rao LM test; multi-way clustering (search for similar items in EconPapers)
Date: 2015-12-09, Revised 2017-09-13
Note: This module should be installed from within Stata by typing "ssc install boottest". Windows users should not attempt to download these files with a web browser.
References: Add references at CitEc
Citations Track citations by RSS feed

Downloads: (external link) program code (text/plain) program code (text/plain) help file (text/plain) program code (text/plain) program code (text/plain) program code (text/plain) Mata object library (application/x-stata)

Related works:
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:

Ordering information: This software item can be ordered from

Access Statistics for this software item

More software in Statistical Software Components from Boston College Department of Economics Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA. Contact information at EDIRC.
Series data maintained by Christopher F Baum ().

Page updated 2017-09-25
Handle: RePEc:boc:bocode:s458121