Testing many restrictions under heteroskedasticity

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985998%3A_____%2F23%3A00582611" target="_blank" >RIV/67985998:_____/23:00582611 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11640/23:00574156

Result on the web

<a href="https://doi.org/10.1016/j.jeconom.2023.03.011" target="_blank" >https://doi.org/10.1016/j.jeconom.2023.03.011</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jeconom.2023.03.011" target="_blank" >10.1016/j.jeconom.2023.03.011</a>

Result language

angličtina

Original language name

Testing many restrictions under heteroskedasticity

Original language description

We propose a hypothesis test that allows for many tested restrictions in a heteroskedastic linear regression model. The test compares the conventional F statistic to a critical value that corrects for many restrictions and conditional heteroskedasticity. This correction uses leave-one-out estimation to correctly center the critical value and leave-three-out estimation to appropriately scale it. The large sample properties of the test are established in an asymptotic framework where the number of tested restrictions may be fixed or may grow with the sample size, and can even be proportional to the number of observations. We show that the test is asymptotically valid and has non-trivial asymptotic power against the same local alternatives as the exact F test when the latter is valid. Simulations corroborate these theoretical findings and suggest excellent size control in moderately small samples, even under strong heteroskedasticity.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

50202 - Applied Economics, Econometrics

Project

<a href="/en/project/GA20-28055S" target="_blank" >GA20-28055S: ECONOMETRICS WITH OVERPARAMETERIZATION AND WEAK IDENTIFICATION</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Econometrics

ISSN

0304-4076

e-ISSN

1872-6895

Volume of the periodical

236

Issue of the periodical within the volume

1

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

19

Pages from-to

105473

UT code for WoS article

001032935200001

EID of the result in the Scopus database

2-s2.0-85163996332