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FINITE-SAMPLE SIZE CONTROL OF IVX-BASED TESTS IN PREDICTIVE REGRESSIONS

Published online by Cambridge University Press:  10 August 2020

Mehdi Hosseinkouchack  and
Matei Demetrescu
Mehdi Hosseinkouchack*
Affiliation:
University of Mannheim
Matei Demetrescu
Affiliation:
Christian-Albrechts-University of Kiel
*
Address correspondence to Mehdi Hosseinkouchack, University of Mannheim, L7, 3-5, 68161 Mannheim, Germany; e-mail: [email protected].
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Abstract

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In predictive regressions with variables of unknown persistence, the use of extended IV (IVX) instruments leads to asymptotically valid inference. Under highly persistent regressors, the standard normal or chi-squared limiting distributions for the usual t and Wald statistics may, however, differ markedly from the actual finite-sample distributions which exhibit in particular noncentrality. Convergence to the limiting distributions is shown to occur at a rate depending on the choice of the IVX tuning parameters and can be very slow in practice. A characterization of the leading higher-order terms of the t statistic is provided for the simple regression case, which motivates finite-sample corrections. Monte Carlo simulations confirm the usefulness of the proposed methods.

Type
ARTICLES
Information
Econometric Theory , Volume 37 , Issue 4 , August 2021 , pp. 769 - 793
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2020. Published by Cambridge University Press

Footnotes

The authors would like to thank three anonymous referees, the Co-Editor (Giuseppe Cavaliere), as well as Karim Abadir and Uwe Hassler for very useful comments. Demetrescu gratefully acknowledges the support of the German Research Foundation (DFG) through the project DE 1617/4-2.

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