IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i3p478-d740642.html
   My bibliography  Save this article

Selection Criteria for Overlapping Binary Models—A Simulation Study

Author

Listed:
  • Teresa Aparicio

    (Department of Economic Analysis, University of Zaragoza, Gran Vía, 2, 50005 Zaragoza, Spain)

  • Inmaculada Villanúa

    (Department of Economic Analysis, University of Zaragoza, Gran Vía, 2, 50005 Zaragoza, Spain)

Abstract

This paper deals with the problem of choosing the optimum criterion for selecting the best model out of a set of overlapping binary models. The criteria we studied were the well-known AIC and SBIC, and a third one called C 2 . Special attention was paid to the setting where neither of the competing models was correctly specified. This situation has not been studied very much but it is the most common case in empirical works. The theoretical study we carried out allowed us to conclude that, in general terms, all criteria perform well. A Monte Carlo exercise corroborated those results.

Suggested Citation

  • Teresa Aparicio & Inmaculada Villanúa, 2022. "Selection Criteria for Overlapping Binary Models—A Simulation Study," Mathematics, MDPI, vol. 10(3), pages 1-15, February.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:3:p:478-:d:740642
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/3/478/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/3/478/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hashem Pesaran, M. & Pesaran, Bahram, 1993. "A simulation approach to the problem of computing Cox's statistic for testing nonnested models," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 377-392.
    2. J. M. C. Santos Silva, 2001. "A score test for non-nested hypotheses with applications to discrete data models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 577-597.
    3. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    4. Reem Aljarallah & Samer A Kharroubi, 2021. "Use of Bayesian Markov Chain Monte Carlo Methods to Model Kuwait Medical Genetic Center Data: An Application to Down Syndrome and Mental Retardation," Mathematics, MDPI, vol. 9(3), pages 1-11, January.
    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. M. T. Aparicio & I. Villan�a, 2012. "Selection criteria for overlapping binary Models," Documentos de Trabajo dt2012-01, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
    2. Silva João M. C. Santos & Tenreyro Silvana & Windmeijer Frank, 2015. "Testing Competing Models for Non-negative Data with Many Zeros," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 1-18, January.
    3. McAleer, Michael, 1995. "The significance of testing empirical non-nested models," Journal of Econometrics, Elsevier, vol. 67(1), pages 149-171, May.
    4. J. M. C. Santos Silva, 2001. "A score test for non-nested hypotheses with applications to discrete data models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 577-597.
    5. William Greene, 2007. "Discrete Choice Modeling," Working Papers 07-6, New York University, Leonard N. Stern School of Business, Department of Economics.
    6. Isabel Mendes & Isabel Proença, 2009. "Measuring the Social Recreation Per-Day Net Benefit of Wildlife Amenities of a National Park: A Count-Data Travel Cost Approach," Working Papers Department of Economics 2009/35, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    7. Genius, Margarita & Strazzera, Elisabetta, 2002. "A note about model selection and tests for non-nested contingent valuation models," Economics Letters, Elsevier, vol. 74(3), pages 363-370, February.
    8. Heinz König & Michael Lechner, 1994. "Some Recent Developments in Microeconometrics - A Survey," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 130(III), pages 299-331, September.
    9. Franses Philip Hans & Paap Richard, 2013. "Common large innovations across nonlinear time series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 251-263, May.
    10. 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.
    11. M. Genius & E. Strazzera, 2000. "Evaluation of likelihood based tests for non-nested dichotomus choice contingent valuation models," Working Paper CRENoS 200012, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    12. Christophe Bontemps & Grayham E. Mizon, 2008. "Encompassing: Concepts and Implementation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 721-750, December.
    13. Godwin Nwaobi, 2001. "A Vector Error Correction And Nonnested Modelling Of Money Demand Function In Nigeria," Econometrics 0111004, University Library of Munich, Germany.
    14. Isabel Proenca & Isabel Menes, 2000. "Measuring the Average Per Day Net Benefit of Non-consumptive Wildlife - Associated Recreation For a National Park: a Count-Data Travel Cost Approach," Regional and Urban Modeling 283600078, EcoMod.
    15. Fabrice Gilles & Sabina Issehnane & Florent Sari, 2022. "Using short-term jobs as a way to find a regular job. What kind of role for local context?," TEPP Working Paper 2022-07, TEPP.
    16. repec:hal:spmain:info:hdl:2441/dambferfb7dfprc9m052g20qh is not listed on IDEAS
    17. Paulo M. D. C. Parente & Richard J. Smith, 2021. "Quasi‐maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 377-405, July.
    18. Cornelia Lawson, 2013. "Academic Inventions Outside the University: Investigating Patent Ownership in the UK," Industry and Innovation, Taylor & Francis Journals, vol. 20(5), pages 385-398, July.
    19. Vipin Arora & Shuping Shi, 2016. "Nonlinearities and tests of asset price bubbles," Empirical Economics, Springer, vol. 50(4), pages 1421-1433, June.
    20. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    21. Da Fonseca José & Grasselli Martino & Ielpo Florian, 2014. "Estimating the Wishart Affine Stochastic Correlation Model using the empirical characteristic function," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 1-37, May.

    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:gam:jmathe:v:10:y:2022:i:3:p:478-:d:740642. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.