IDEAS home Printed from https://ideas.repec.org/p/sin/wpaper/12-a017.html
   My bibliography  Save this paper

Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT

Author

Listed:

Abstract

We propose inverse probability weighted estimators for the local average treatment effect (LATE) and the local average treatment effect for the treated (LATT) under instrumental variable assumptions with covariates. We show that these estimators are asymptotically normal and effcient. When the (binary) instrument satisfies one-sided non-compliance, we propose a Durbin- Wu-Hausman-type test of whether treatment assignment is unconfounded conditional on some observables. The test is based on the fact that under one-sided non-compliance LATT coincides with the average treatment effect for the treated (ATT). We conduct Monte Carlo simulations to demonstrate, among other things, that part of the theoretical effciency gain afforded by unconfoundedness in estimating ATT survives pre-testing. We illustrate the implementation of the test on data from training programs administered under the Job Training Partnership Act in the U.S.

Suggested Citation

  • Stephen G. Donald & Yu-Chin Hsu & Robert P. Lieli, 2012. "Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT," IEAS Working Paper : academic research 12-A017, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Jan 2014.
  • Handle: RePEc:sin:wpaper:12-a017
    as

    Download full text from publisher

    File URL: http://www.econ.sinica.edu.tw/UpFiles/2013092817175327692/Seminar_PDF2013093010102890633/12-A017(all)4.pdf
    Download Restriction: no

    Citations

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


    Cited by:

    1. Huber, Martin, 2013. "A simple test for the ignorability of non-compliance in experiments," Economics Letters, Elsevier, vol. 120(3), pages 389-391.
    2. Marianna Endresz & Peter Harasztosi & Robert P. Lieli, 2015. "The Impact of the Magyar Nemzeti Bank's Funding for Growth Scheme on Firm Level Investment," MNB Working Papers 2015/2, Magyar Nemzeti Bank (Central Bank of Hungary).
    3. Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2015. "Estimating Conditional Average Treatment Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 485-505, October.
    4. de Luna, Xavier & Johansson, Per, 2012. "Testing for nonparametric identification of causal effects in the presence of a quasi-instrument," Working Paper Series 2012:14, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    5. Donald, Stephen G. & Hsu, Yu-Chin & Lieli, Robert P., 2014. "Inverse probability weighted estimation of local average treatment effects: A higher order MSE expansion," Statistics & Probability Letters, Elsevier, vol. 95(C), pages 132-138.

    More about this item

    Keywords

    local average treatment effect; instrumental variables; unconfoundedness; inverse probability weighted estimation; nonparametric estimation;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:sin:wpaper:12-a017. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (HsiaoyunLiu). General contact details of provider: http://edirc.repec.org/data/sinictw.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.