Bootstrapping likelihood-ratio-type tests based on convex M-estimation

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ID: 328219
2026
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Abstract
Abstract We consider likelihood-ratio-type statistics for testing restrictions on parameters built from a convex M-estimation criterion. In general, these statistics are not asymptotically pivotal. We propose a general simple nonparametric bootstrap procedure that yields asymptotically valid critical and p-values. The method modifies the bootstrap objective function to mimic what happens under the null hypothesis. A Monte-Carlo study illustrates that our method controls level well and is powerful.
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openalex_W7212136756 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Patrice Bertail, Pascal Lavergne
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Journal econometrics journal
Year 2026
DOI
10.1093/ectj/utag031
URL
https://doi.org/10.1093/ectj/utag031
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