Lavergne, Pascal and Bertail, Patrice (2020) Bootstrapping Quasi Likelihood Ratio Tests under Misspecification. TSE Working Paper, n. 20-1102, Toulouse

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Abstract

We consider quasi likelihood ratio (QLR) tests for restrictions on parameters under potential model misspecification. For convex M-estimation, including quantile regression, we propose a general and simple nonparametric bootstrap procedure that yields asymptotically valid critical values. The method modifies the bootstrap objective function to mimic what happens under the null hypothesis. When testing for an univariate restriction, we show how the test statistic can be made asymptotically pivotal. Our bootstrap can then provide asymptotic refinements as illustrated for a linear regression model. A Monte-Carlo study and an empirical application illustrate that double bootstrap of the QLR test controls level well and is powerful.

Item Type: Monograph (Working Paper)
Language: English
Date: May 2020
Place of Publication: Toulouse
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse 1 Capitole
Site: UT1
Date Deposited: 12 May 2020 12:43
Last Modified: 21 Jun 2021 12:49
OAI Identifier: oai:tse-fr.eu:124273
URI: https://publications.ut-capitole.fr/id/eprint/34956
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