Lazarus, Eben;
Lewis, Daniel J;
Stock, James H;
(2021)
The Size‐Power Tradeoff in HAR Inference.
Econometrica
, 89
(5)
pp. 2497-2516.
10.3982/ecta15404.
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Abstract
Heteroskedasticity‐ and autocorrelation‐robust (HAR) inference in time series regression typically involves kernel estimation of the long‐run variance. Conventional wisdom holds that, for a given kernel, the choice of truncation parameter trades off a test's null rejection rate and power, and that this tradeoff differs across kernels. We formalize this intuition: using higher‐order expansions, we provide a unified size‐power frontier for both kernel and weighted orthonormal series tests using nonstandard “fixed‐ b” critical values. We also provide a frontier for the subset of these tests for which the fixed‐ b distribution is t or F. These frontiers are respectively achieved by the QS kernel and equal‐weighted periodogram. The frontiers have simple closed‐form expressions, which show that the price paid for restricting attention to tests with t and F critical values is small. The frontiers are derived for the Gaussian multivariate location model, but simulations suggest the qualitative findings extend to stochastic regressors.
Type: | Article |
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Title: | The Size‐Power Tradeoff in HAR Inference |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.3982/ecta15404 |
Publisher version: | https://doi.org/10.3982/ECTA15404 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Heteroskedasticity- and autocorrelation-robust estimation, HAR, longrun variance estimator. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics |
URI: | https://discovery.ucl.ac.uk/id/eprint/10160483 |
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