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A simple parametric model selection test

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  • Susanne M. Schennach

    () (Institute for Fiscal Studies and Brown University)

  • Daniel Wilhelm

    () (Institute for Fiscal Studies and cemmap and UCL)

Abstract

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 speci ed or misspeci ed, 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.

Suggested Citation

  • Susanne M. Schennach & Daniel Wilhelm, 2016. "A simple parametric model selection test," CeMMAP working papers CWP30/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:30/16
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    References listed on IDEAS

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    Cited by:

    1. Breitmoser, Yves, 2017. "Discrete Choice with Presentation Effects," Rationality and Competition Discussion Paper Series 35, CRC TRR 190 Rationality and Competition.
    2. Breitmoser, Yves, 2016. "Stochastic choice, systematic mistakes and preference estimation," MPRA Paper 72779, University Library of Munich, Germany.
    3. Breitmoser, Yves & Vorjohann, Pauline, 2018. "Welfare-Based Altruism," Rationality and Competition Discussion Paper Series 89, CRC TRR 190 Rationality and Competition.
    4. Xiaoxia Shi, 2015. "A nondegenerate Vuong test," Quantitative Economics, Econometric Society, vol. 6(1), pages 85-121, March.

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    Keywords

    Parametric Model Selection Test;

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