Lapenta, EliaIdRef and Lavergne, PascalIdRef (2024) Encompassing Tests for Nonparametric Regressions. Econometric Theory. pp. 1-30.

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Identification Number : 10.1017/S0266466624000100

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
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

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