Lapenta, Elia and Lavergne, Pascal
(2024)
Encompassing Tests for Nonparametric Regressions.
Econometric Theory.
pp. 1-30.
This is the latest version of this item.
Abstract
We set up a formal framework to characterize encompassing of nonparametric models through the distance. We contrast it to previous literature on the comparison of nonparametric regression models. We then develop testing procedures for the encompassing hypothesis that are fully nonparametric. Our test statistics depend on kernel regression, raising the issue of bandwidth’s choice. We investigate two alternative approaches to obtain a “small bias property” for our test statistics. We show the validity of a wild bootstrap method. We empirically study the use of a data-driven bandwidth and illustrate the attractive features of our tests for small and moderate samples.
Item Type: | Article |
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Language: | English |
Date: | 2024 |
Refereed: | Yes |
Place of Publication: | Cambridge |
Subjects: | B- ECONOMIE ET FINANCE |
Divisions: | TSE-R (Toulouse) |
Site: | UT1 |
Date Deposited: | 12 Feb 2025 10:53 |
Last Modified: | 12 Feb 2025 10:55 |
OAI Identifier: | oai:tse-fr.eu:130305 |
URI: | https://publications.ut-capitole.fr/id/eprint/50405 |
Available Versions of this Item
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Encompassing Tests for Nonparametric Regressions. (deposited 05 May 2022 11:13)
- Encompassing Tests for Nonparametric Regressions. (deposited 12 Feb 2025 10:53) [Currently Displayed]