IDEAS home Printed from https://ideas.repec.org/a/adr/anecst/y2017i128p151-202.html
   My bibliography  Save this article

A Specification Test for Nonparametric Instrumental Variable Regression

Author

Listed:
  • Patrick GAGLIARDINI
  • Olivier SCAILLET

Abstract

We consider testing for correct specification of a nonparametric instrumental variable regression. First we study the notion of correct specification, misspecification and overidentification in this ill-posed inverse problem setting. Second we study a test statistic based on the empirical minimum distance criterion corresponding to the conditional moment restriction evaluated with a Tikhonov Regularized estimator of the functional parameter. The test statistic admits an asymptotic normal distribution under the null hypothesis, and the test is consistent under global alternatives. A bootstrap procedure is available to get simulation based critical values. Finally, we explore the finite sample behavior with Monte Carlo experiments, and provide an empirical illustration for an estimated Engel curve.

Suggested Citation

  • Patrick GAGLIARDINI & Olivier SCAILLET, 2017. "A Specification Test for Nonparametric Instrumental Variable Regression," Annals of Economics and Statistics, GENES, issue 128, pages 151-202.
  • Handle: RePEc:adr:anecst:y:2017:i:128:p:151-202
    DOI: 10.15609/annaeconstat2009.128.0151
    as

    Download full text from publisher

    File URL: http://www.jstor.org/stable/10.15609/annaeconstat2009.128.0151
    Download Restriction: no

    File URL: https://libkey.io/10.15609/annaeconstat2009.128.0151?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
    ---><---

    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. Gagliardini, Patrick & Scaillet, Olivier, 2012. "Tikhonov regularization for nonparametric instrumental variable estimators," Journal of Econometrics, Elsevier, vol. 167(1), pages 61-75.
    2. Breunig, Christoph, 2012. "Goodness-of-fit tests based on series estimators in nonparametric instrumental regression," Working Papers 12-13, University of Mannheim, Department of Economics.
    3. Christoph Breunig, 2019. "Goodness-of-Fit Tests based on Series Estimators in Nonparametric Instrumental Regression," Papers 1909.10133, arXiv.org.
    4. Shaw Philip & Cohen Michael Andrew & Chen Tao, 2016. "Nonparametric Instrumental Variable Estimation in Practice," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 153-177, January.
    5. Breunig, Christoph, 2015. "Goodness-of-fit tests based on series estimators in nonparametric instrumental regression," Journal of Econometrics, Elsevier, vol. 184(2), pages 328-346.
    6. Christoph Breunig, 2019. "Specification Testing in Nonparametric Instrumental Quantile Regression," Papers 1909.10129, arXiv.org.
    7. Christoph Breunig, 2016. "Specification Testing in Nonparametric Instrumental Quantile Regression," SFB 649 Discussion Papers SFB649DP2016-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    More about this item

    Keywords

    Specification Test; Nonparametric Regression; Instrumental Variables; Minimum Distance; Tikhonov Regularization; Ill-posed Inverse Problems; Generalized Method of Moments; Bootstrap; Engel Curve.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

    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:adr:anecst:y:2017:i:128:p:151-202. 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: Secretariat General or Laurent Linnemer (email available below). General contact details of provider: https://edirc.repec.org/data/ensaefr.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.