Econometrica

Journal Of The Econometric Society

An International Society for the Advancement of Economic
Theory in its Relation to Statistics and Mathematics

Edited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262

Econometrica: Jul, 2015, Volume 83, Issue 4

Power Enhancement in High‐Dimensional Cross‐Sectional Tests

https://doi.org/10.3982/ECTA12749
p. 1497-1541

J. Fan, Y. Liao, and J. Yao

We propose a novel technique to boost the power of testing a high‐dimensional vector H : θ =0 against sparse alternatives where the null hypothesis is violated by only a few components. Existing tests based on quadratic forms such as the Wald statistic often suffer from low powers due to the accumulation of errors in estimating high‐dimensional parameters. More powerful tests for sparse alternatives such as thresholding and extreme value tests, on the other hand, require either stringent conditions or bootstrap to derive the null distribution and often suffer from size distortions due to the slow convergence. Based on a screening technique, we introduce a “power enhancement component,” which is zero under the null hypothesis with high probability, but diverges quickly under sparse alternatives. The proposed test statistic combines the power enhancement component with an asymptotically pivotal statistic, and strengthens the power under sparse alternatives. The null distribution does not require stringent regularity conditions, and is completely determined by that of the pivotal statistic. The proposed methods are then applied to testing the factor pricing models and validating the cross‐sectional independence in panel data models.


Log In To View Full Content

Supplemental Material

Supplement to “Power Enhancement in High‐Dimensional Cross‐Sectional Tests”

This supplementary material contains additional proofs of the main paper.

Supplement to "Power Enhancement in High-Dimensional Cross-Sectional Tests"

This zip file contains the replication files for the manuscript.

Journal News

View