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Multibenchmark reality checks

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dc.contributor.authorArbués, Ignacio
dc.contributor.authorMatilla García, Mariano
dc.date.accessioned2024-12-02T11:05:10Z
dc.date.available2024-12-02T11:05:10Z
dc.date.issued2024-11
dc.descriptionEste es el manuscrito aceptado del artículo. La versión registrada fue publicada por primera vez en Economic Modelling, (2024)140, 106848, está disponible en línea en el sitio web del editor; https://doi.org/10.1016/j.econmod.2024.106848 This is the accepted manuscript of the article. The copyrighted version was first published in Economic Modeling, (2024)140, 106848, and is available online at the publisher's website; https://doi.org/10.1016/j.econmod.2024.106848
dc.description.abstractEmpirical economic modelers often have to choose between two classes of models, with each class containing multiple models. In many cases, this decision is based on the predictive ability of the considered models. This entails that multiple testing and/or p-hacking pose known risks. This study presents a new statistical approach for comparing all model in a single test, serving as a multi-benchmark reality check test. The behavior of the test is studied asymptotically and in small finite samples. We show how the new approach works by analyzing whether one family of linear bivariate models outperforms a univariate family in predicting commodity prices. This paper raises new questions for future research. From an empirical viewpoint, we present several open questions in economic modeling that can be tested with multi-benchmark tests. Meanwhile, from a theoretical viewpoint, further studies can investigate whether a more general method for approximating or simulating the test distribution can be developed.en
dc.description.versionversión final
dc.identifier.citationArbués, I., & Matilla-García, M. (2024). Multibenchmark reality checks. Economic Modelling, 140, 106848. https://doi.org/10.1016/j.econmod.2024.106848
dc.identifier.doihttps://doi.org/10.1016/j.econmod.2024.106848
dc.identifier.issn0264-9993
dc.identifier.urihttps://hdl.handle.net/20.500.14468/24626
dc.journal.titleEconomic Modelling
dc.journal.volume140
dc.language.isoen
dc.publisherElsevier
dc.relation.centerFacultades y escuelas::Facultad de Ciencias Económicas y Empresariales
dc.relation.departmentEconomía Aplicada y Estadística
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject53 Ciencias Económicas
dc.subject.keywordsGranger causalityen
dc.subject.keywordsout-of-sample forecasten
dc.subject.keywordsmodel selectionen
dc.subject.keywordsbootstrapen
dc.titleMultibenchmark reality checksen
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
relation.isAuthorOfPublication7ad4a531-f3a5-451d-a646-48a1cd0ad86e
relation.isAuthorOfPublication.latestForDiscovery7ad4a531-f3a5-451d-a646-48a1cd0ad86e
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