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A Simple Parametric Model Selection Test

Schennach, SM; Wilhelm, D; (2017) A Simple Parametric Model Selection Test. Journal of the American Statistical Association , 112 (520) pp. 1663-1674. 10.1080/01621459.2016.1224716. Green open access

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We propose a simple model selection test for choosing among two parametric likelihoods which can be applied in the most general setting without any assumptions on the relation between the candidate models and the true distribution. That is, both, one or neither is allowed to be correctly specified or misspecified, they may be nested, non-nested, strictly non-nested or overlapping. Unlike in previous testing approaches, no pre-testing is needed, since in each case, the same test statistic together with a standard normal critical value can be used. The new procedure controls asymptotic size uniformly over a large class of data generating processes. We demonstrate its finite sample properties in a Monte Carlo experiment and its practical relevance in an empirical application comparing Keynesian versus new classical macroeconomic models.

Type: Article
Title: A Simple Parametric Model Selection Test
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/01621459.2016.1224716
Publisher version: http://dx.doi.org/10.1080/01621459.2016.1224716
Language: English
Additional information: Copyright © Susanne M. Schennach and DanielWilhelm. Published with License by Taylor & Francis This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: uniform size control, one-step test, sample-splitting, Vuong test
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics
URI: https://discovery.ucl.ac.uk/id/eprint/1553910
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