Robust heteroskedasticity-robust tests

C-Tier
Journal: Economics Letters
Year: 2017
Volume: 159
Issue: C
Pages: 28-32

Score contribution per author:

1.005 = (α=2.01 / 1 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Hausman and Palmer (2012) suggest using the Edgeworth corrected critical values of Rothenberg (1988) along with a pairs bootstrap covariance matrix estimator in order to obtain second order correct heteroskedasticity-robust inferences. According to their simulations, this test has size comparable to and power greater than a wild bootstrap test. In this note, I show that this does not hold in general. Using a more extensive set of simulations reveals that the wild bootstrap test is much more robust to the underlying data generating process.

Technical Details

RePEc Handle
repec:eee:ecolet:v:159:y:2017:i:c:p:28-32
Journal Field
General
Author Count
1
Added to Database
2026-01-29