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A uniform model selection test for semiparametric models

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  • Bravo, Francesco

Abstract

This paper proposes a new simple test for model selection between two possibly misspecified competing semiparametric models. An important feature of the test is that it controls uniformly its size regardless as to whether the competing models are nested, overlapping or non nested and can be applied to overidentified models with weakly dependent observations.

Suggested Citation

  • Bravo, Francesco, 2026. "A uniform model selection test for semiparametric models," Statistics & Probability Letters, Elsevier, vol. 232(C).
    • Handle: RePEc:eee:stapro:v:232:y:2026:i:c:s0167715226000222
    DOI: 10.1016/j.spl.2026.110658
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    References listed on IDEAS

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    1. Hansen, Lars Peter & Jagannathan, Ravi, 1997. "Assessing Specification Errors in Stochastic Discount Factor Models," Journal of Finance, American Finance Association, vol. 52(2), pages 557-590, June.
    2. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    3. Susanne M. Schennach & Daniel Wilhelm, 2017. "A Simple Parametric Model Selection Test," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1663-1674, October.
    4. Francesco Bravo & Ba M. Chu & David T. Jacho-Chávez, 2017. "Semiparametric estimation of moment condition models with weakly dependent data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(1), pages 108-136, January.
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