IDEAS home Printed from https://ideas.repec.org/a/ect/emjrnl/v13y2010i3ps56-s79.html

Inference in limited dependent variable models robust to weak identification

Author

Listed:
  • Leandro M. Magnusson

Abstract

We propose tests for structural parameters in limited dependent variable models with endogenous explanatory variables. These tests are based upon the generalized minimum distance principle. They are of the correct size regardless of whether the structural parameters are identified and are especially appropriate for models whose moment conditions are non-linear in the parameters. Moreover, they are computationally simple, allowing them to be implemented using a large number of statistical software packages. We compare our tests to Wald tests in a simulation experiment and use them to analyse the female labour supply and the demand for cigarettes. Copyright (C) 2010 The Author(s). The Econometrics Journal (C) 2010 Royal Economic Society

Suggested Citation

  • Leandro M. Magnusson, 2010. "Inference in limited dependent variable models robust to weak identification," Econometrics Journal, Royal Economic Society, vol. 13(3), pages 56-79, October.
    • Handle: RePEc:ect:emjrnl:v:13:y:2010:i:3:p:s56-s79
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lanz, Bruno & Provins, Allan, 2017. "Using averting expenditures to estimate the demand for public goods: Combining objective and perceived quality," Resource and Energy Economics, Elsevier, vol. 47(C), pages 20-35.
    2. Frazier, David T. & Renault, Eric & Zhang, Lina & Zhao, Xueyan, 2025. "Weak identification in discrete choice models," Journal of Econometrics, Elsevier, vol. 248(C).
    3. Tetsuya Kaji, 2019. "Theory of Weak Identification in Semiparametric Models," Papers 1908.10478, arXiv.org, revised Aug 2020.
    4. Antonio Diez de Los Rios, 2015. "A New Linear Estimator for Gaussian Dynamic Term Structure Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 282-295, April.
    5. Jean-Marie Dufour & Joachim Wilde, 2018. "Weak identification in probit models with endogenous covariates," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(4), pages 611-631, October.
    6. Barber, Luke & Jetter, Michael & Krieger, Tim, 2024. "Foreshadowing Mars: Religiosity and pre-Enlightenment conflict in Europe," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302355, Verein für Socialpolitik / German Economic Association.
    7. Barber, Luke & Jetter, Michael & Krieger, Tim, 2023. "Foreshadowing Mars: Religiosity and Pre-enlightenment Warfare," IZA Discussion Papers 16586, IZA Network @ LISER.
    8. Cheng, Xu & Renault, Eric & Sangrey, Paul, 2025. "Identifying the volatility risk price through the leverage effect," Journal of Econometrics, Elsevier, vol. 248(C).
    9. David T. Frazier & Eric Renault & Lina Zhang & Xueyan Zhao, 2020. "Weak Identification in Discrete Choice Models," Papers 2011.06753, arXiv.org, revised Jan 2021.
    10. Chuhui Li & Donald S. Poskitt & Frank Windmeijer & Xueyan Zhao, 2022. "Binary outcomes, OLS, 2SLS and IV probit," Econometric Reviews, Taylor & Francis Journals, vol. 41(8), pages 859-876, September.
    11. Jetter, Michael & Walker, Jay K., 2022. "News coverage and mass shootings in the US," European Economic Review, Elsevier, vol. 148(C).
    12. Wendy Correa Martínez & Michael Jetter, 2016. "Isolating causality between gender and corruption: An IV approach," Documentos de Trabajo de Valor Público 14438, Universidad EAFIT.
    13. Jetter, Michael, 2017. "The effect of media attention on terrorism," Journal of Public Economics, Elsevier, vol. 153(C), pages 32-48.
    14. Frazier, David T. & Renault, Eric & Zhang, Lina & Zhao, Xueyan, 2021. "Weak Identification in Discrete Choice Models," The Warwick Economics Research Paper Series (TWERPS) 1336, University of Warwick, Department of Economics.
    15. Dakyung Seong, 2025. "Binary Response Model With Many Weak Instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(2), pages 214-230, March.
    16. M. Shahe Emran & Fenohasina Maret-Rakotondrazaka & Stephen C. Smith, 2014. "Education and Freedom of Choice: Evidence from Arranged Marriages in Vietnam," Journal of Development Studies, Taylor & Francis Journals, vol. 50(4), pages 481-501, April.
    17. Xu Cheng & Eric Renault & Paul Sangrey, 2024. "Identifying the Volatility Risk Price Through the Leverage Effect," PIER Working Paper Archive 24-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    18. Fiorini, Luciana C. & Jetter, Michael & Parmeter, Christopher F. & Parsons, Christopher, 2020. "The Effect of Community Size on Electoral Preferences: Evidence From Post-WWII Southern Germany," IZA Discussion Papers 13724, IZA Network @ LISER.
    19. Gregory Fletcher Cox, 2020. "Weak Identification with Bounds in a Class of Minimum Distance Models," Papers 2012.11222, arXiv.org, revised Oct 2025.
    20. repec:gii:ciesrp:cies_rp_36rev is not listed on IDEAS
    21. Aparicio, Juan P. & Jetter, Michael, 2020. "Captivating News in Colombia," IZA Discussion Papers 13834, IZA Network @ LISER.
    22. Aparicio, Juan P. & Jetter, Michael, 2022. "Captivating news: Media attention and FARC kidnappings," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 69-81.
    23. Cox, Gregory Fletcher, 2025. "Weak identification with bounds in a class of minimum distance models," Journal of Econometrics, Elsevier, vol. 252(PA).

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

    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:ect:emjrnl:v:13:y:2010:i:3:p:s56-s79. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley-Blackwell Digital Licensing or Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/resssea.html .

    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.