waldtest: Arbitrary Linear Hypothesis Testing for Regression Models via...

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

Arbitrary Linear Hypothesis Testing for Regression Models via Wald-Tests

Description

waldtest is a S3 method that allows for arbitrary linear hypothesis testing for objects of class lm, fixest, felm and ivreg

Usage

waldtest(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

waldtest.lm, waldtest.fixest, waldttest.felm or waldttest.ivreg

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