Publication Type
Journal Article
Version
publishedVersion
Publication Date
11-2024
Abstract
This paper addresses the problem of deriving heteroskedasticity and autocorrelation robust (HAR) inference for a scalar parameter of interest, under the assumption of a known upper bound on data persistence. Finite-sample optimal tests are derived within the Gaussian location model, revealing that robustness-efficiency tradeoffs are primarily determined by the maximal persistence. With a suitable adjustment to the critical value, the equal-weighted cosine (EWC) test emerges as nearly optimal, wherein the long-run variance is estimated through projections onto q type II cosines. This approach establishes a direct link between the choice of q and persistence assumptions, accompanied by adjustments to the conventional Student-t critical value. The findings are demonstrated through two empirical examples.
Keywords
heteroskedasticity, autocorrelation, robust inference, maximal persistence, equal-weighted cosine test, Gaussian location model, long-run variance, Student-t adjustment, statistical efficiency, empirical examples
Discipline
Econometrics | Statistics and Probability
Research Areas
Econometrics
Publication
Quantitative Economics
Volume
15
Issue
4
First Page
1107
Last Page
1149
ISSN
1759-7323
Identifier
10.3982/QE1762
Publisher
Econometric Society
Citation
DOU, Liyu.
Optimal HAR inference. (2024). Quantitative Economics. 15, (4), 1107-1149.
Available at: https://ink.library.smu.edu.sg/soe_research/2787
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://doi.org/10.3982/QE1762
