IDEAS home Printed from https://ideas.repec.org/a/taf/jnlasa/v112y2017i520p1663-1674.html
   My bibliography  Save this article

A Simple Parametric Model Selection Test

Author

Listed:
  • Susanne M. Schennach
  • Daniel Wilhelm

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 specified or misspecified, they may be nested, nonnested, strictly nonnested, or overlapping. Unlike in previous testing approaches, no pretesting 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. Supplementary materials for this article are available online.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:jnlasa:v:112:y:2017:i:520:p:1663-1674
    DOI: 10.1080/01621459.2016.1224716
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01621459.2016.1224716
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/01621459.2016.1224716?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
    3. Sin, Chor-Yiu & White, Halbert, 1996. "Information criteria for selecting possibly misspecified parametric models," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 207-225.
    4. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    5. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    6. Barro, Robert J, 1977. "Unanticipated Money Growth and Unemployment in the United States," American Economic Review, American Economic Association, vol. 67(2), pages 101-115, March.
    7. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    8. Leeb, Hannes & Pötscher, Benedikt M., 2005. "Model Selection And Inference: Facts And Fiction," Econometric Theory, Cambridge University Press, vol. 21(1), pages 21-59, February.
    9. Ramalho, Joaquim J. S. & Smith, Richard J., 2002. "Generalized empirical likelihood non-nested tests," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 99-125, March.
    10. Fan, Yanqin & Li, Qi, 1996. "Consistent Model Specification Tests: Omitted Variables and Semiparametric Functional Forms," Econometrica, Econometric Society, vol. 64(4), pages 865-890, July.
    11. Tauchen, George, 1985. "Diagnostic testing and evaluation of maximum likelihood models," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 415-443.
    12. Pesaran, M H, 1982. "A Critique of the Proposed Tests of the Natural Rate-Rational Expectations Hypothesis," Economic Journal, Royal Economic Society, vol. 92(367), pages 529-554, September.
    13. Sargent, Thomas J & Wallace, Neil, 1975. ""Rational" Expectations, the Optimal Monetary Instrument, and the Optimal Money Supply Rule," Journal of Political Economy, University of Chicago Press, vol. 83(2), pages 241-254, April.
    14. Mizon, Grayham E & Richard, Jean-Francois, 1986. "The Encompassing Principle and Its Application to Testing Non-nested Hypotheses," Econometrica, Econometric Society, vol. 54(3), pages 657-678, May.
    15. Small, David H, 1979. "Unanticipated Money Growth and Unemployment in the United States: Comment," American Economic Review, American Economic Association, vol. 69(5), pages 996-1003, December.
    16. Joseph P. Romano & Azeem M. Shaikh & Michael Wolf, 2010. "Hypothesis Testing in Econometrics," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 75-104, September.
    17. Andrew Chesher & Richard J. Smith, 1997. "Likelihood Ratio Specification Tests," Econometrica, Econometric Society, vol. 65(3), pages 627-646, May.
    18. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    19. Kamran Dadkhah, 2009. "The Evolution of Macroeconomic Theory and Policy," Springer Books, Springer, number 978-3-540-77008-4, January.
    20. Nishii, R., 1988. "Maximum likelihood principle and model selection when the true model is unspecified," Journal of Multivariate Analysis, Elsevier, vol. 27(2), pages 392-403, November.
    21. Smith, Richard J, 1992. "Non-nested.Tests for Competing Models Estimated by Generalized Method of Moments," Econometrica, Econometric Society, vol. 60(4), pages 973-980, July.
    22. Hong, Han & Preston, Bruce & Shum, Matthew, 2003. "Generalized Empirical Likelihood–Based Model Selection Criteria For Moment Condition Models," Econometric Theory, Cambridge University Press, vol. 19(6), pages 923-943, December.
    23. Inoue, Atsushi & Kilian, Lutz, 2006. "On the selection of forecasting models," Journal of Econometrics, Elsevier, vol. 130(2), pages 273-306, February.
    24. Whang, Yoon-Jae & Andrews, Donald W. K., 1993. "Tests of specification for parametric and semiparametric models," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 277-318.
    25. Joseph P. Romano, 2004. "On Non‐parametric Testing, the Uniform Behaviour of the t‐test, and Related Problems," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(4), pages 567-584, December.
    26. Leamer, Edward E., 1983. "Model choice and specification analysis," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 5, pages 285-330, Elsevier.
    27. Yu-Chin Hsu & Xiaoxia Shi, 2013. "Model Selection Tests for Conditional Moment Inequality Models," IEAS Working Paper : academic research 13-A004, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    28. Andrews, Donald W. K. & Lu, Biao, 2001. "Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models," Journal of Econometrics, Elsevier, vol. 101(1), pages 123-164, March.
    29. Douglas Rivers & Quang Vuong, 2002. "Model selection tests for nonlinear dynamic models," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 1-39, June.
    30. Yatchew, Adonis John, 1992. "Nonparametric Regression Tests Based on Least Squares," Econometric Theory, Cambridge University Press, vol. 8(4), pages 435-451, December.
    31. Sawa, Takamitsu, 1978. "Information Criteria for Discriminating among Alternative Regression Models," Econometrica, Econometric Society, vol. 46(6), pages 1273-1291, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Otsu, Taisuke & Whang, Yoon-Jae, 2011. "Testing For Nonnested Conditional Moment Restrictions Via Conditional Empirical Likelihood," Econometric Theory, Cambridge University Press, vol. 27(1), pages 114-153, February.
    2. Chen, Xiaohong & Hong, Han & Shum, Matthew, 2007. "Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models," Journal of Econometrics, Elsevier, vol. 141(1), pages 109-140, November.
    3. Marmer, Vadim & Otsu, Taisuke, 2012. "Optimal comparison of misspecified moment restriction models under a chosen measure of fit," Journal of Econometrics, Elsevier, vol. 170(2), pages 538-550.
    4. Susanne M. Schennach, 2007. "Point estimation with exponentially tilted empirical likelihood," Papers 0708.1874, arXiv.org.
    5. Gourieroux, C. & Monfort, A., 2021. "Model risk management: Valuation and governance of pseudo-models," Econometrics and Statistics, Elsevier, vol. 17(C), pages 1-22.
    6. Zhipeng Liao & Xiaoxia Shi, 2020. "A nondegenerate Vuong test and post selection confidence intervals for semi/nonparametric models," Quantitative Economics, Econometric Society, vol. 11(3), pages 983-1017, July.
    7. Escanciano, Juan Carlos & Song, Kyungchul, 2010. "Testing single-index restrictions with a focus on average derivatives," Journal of Econometrics, Elsevier, vol. 156(2), pages 377-391, June.
    8. Komunjer, Ivana & Ragusa, Giuseppe, 2016. "Existence And Characterization Of Conditional Density Projections," Econometric Theory, Cambridge University Press, vol. 32(4), pages 947-987, August.
    9. Li, Tong, 2009. "Simulation based selection of competing structural econometric models," Journal of Econometrics, Elsevier, vol. 148(2), pages 114-123, February.
    10. Lee, Seojeong, 2014. "Asymptotic refinements of a misspecification-robust bootstrap for generalized method of moments estimators," Journal of Econometrics, Elsevier, vol. 178(P3), pages 398-413.
    11. Paulo Parente & Richard Smith, 2012. "Exogeneity in semiparametric moment condition models," CeMMAP working papers 30/12, Institute for Fiscal Studies.
    12. Shi, Xiaoxia, 2015. "Model selection tests for moment inequality models," Journal of Econometrics, Elsevier, vol. 187(1), pages 1-17.
    13. Arie Preminger & David Wettstein, 2005. "Using the Penalized Likelihood Method for Model Selection with Nuisance Parameters Present only under the Alternative: An Application to Switching Regression Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(5), pages 715-741, September.
    14. Parente, Paulo M.D.C. & Smith, Richard J., 2017. "Tests of additional conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 200(1), pages 1-16.
    15. James Davidson & Andreea G. Halunga, 2013. "Consistent Model Specification Testing," Discussion Papers 1312, University of Exeter, Department of Economics.
    16. Matthew Backus & Christopher Conlon & Michael Sinkinson, 2021. "Common Ownership and Competition in the Ready-to-Eat Cereal Industry," NBER Working Papers 28350, National Bureau of Economic Research, Inc.
    17. Li, Yong & Yu, Jun & Zeng, Tao, 2018. "Specification tests based on MCMC output," Journal of Econometrics, Elsevier, vol. 207(1), pages 237-260.
    18. Hahn, Jinyong & Newey, Whitney K. & Smith, Richard J., 2014. "Neglected heterogeneity in moment condition models," Journal of Econometrics, Elsevier, vol. 178(P1), pages 86-100.
    19. Otsu, Taisuke & Seo, Myung Hwan & Whang, Yoon-Jae, 2012. "Testing for non-nested conditional moment restrictions using unconditional empirical likelihood," Journal of Econometrics, Elsevier, vol. 167(2), pages 370-382.
    20. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:jnlasa:v:112:y:2017:i:520:p:1663-1674. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UASA20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.