boottest: Fast wild cluster bootstrap inference

In s3alfisc/wildboottestjlr: Fast Wild Cluster Bootstrap Inference in R via WildBootTests.jl and JuliaConnectoR

Fast wild cluster bootstrap inference

Description

boottest is a S3 method that allows for fast wild cluster bootstrap inference for objects of class lm, fixest, felm and ivreg by implementing the fast wild bootstrap algorithm developed in Roodman et al., 2019.

Usage

boottest(object, ...)

Arguments

object	An object of type lm, fixest, felm or ivreg
...	other arguments

Value

An object of class boottest.

References

Roodman et al., 2019, "Fast and wild: Bootstrap inference in STATA using boottest", The STATA Journal. (https://journals.sagepub.com/doi/full/10.1177/1536867X19830877)

Cameron, A. Colin, Jonah B. Gelbach, and Douglas L. Miller. "Bootstrap-based improvements for inference with clustered errors." The Review of Economics and Statistics 90.3 (2008): 414-427.

MacKinnon, James G., and Matthew D. Webb. "The wild bootstrap for few (treated) clusters." The Econometrics Journal 21.2 (2018): 114-135.

MacKinnon, James. "Wild cluster bootstrap confidence intervals." L'Actualite economique 91.1-2 (2015): 11-33.

Webb, Matthew D. Reworking wild bootstrap based inference for clustered errors. No. 1315. Queen's Economics Department Working Paper, 2013.

See Also

wildboottestjlr::boottest.lm, wildboottestjlr::boottest.fixest, wildboottestjlr::boottest.felm or wildboottestjlr::boottest.ivreg

s3alfisc/wildboottestjlr documentation built on June 16, 2022, 7:40 a.m.