IDEAS home Printed from https://ideas.repec.org/p/boc/dsug12/11.html
   My bibliography  Save this paper

leebounds: Lee’s treatment effect bounds for samples with nonrandom sample selection

Author

Listed:
  • Harald Tauchmann

    (RWI)

Abstract

Even if assignment of treatment is purely exogenous, estimating treatment effects may suffer from severe bias if the available sample is subject to nonrandom sample selection/attrition. Lee (Review of Economic Studies, 2009) addresses this issue by proposing an estimator for treatment effect bounds in the presence of nonrandom sample selection. In this approach, the lower and upper bound, respectively, correspond to extreme assumptions about the missing information that are consistent with the observed data. As opposed to conventional parametric approaches to correcting for sample selection bias, such as the classical heckit estimator, Lee bounds rest on very few assumptions, namely, random assignment of treatment and monotonicity. The latter means that treatment affects selection for any individual in the same direction. I introduce the new Stata command leebounds, which implements Lee’s bounds estimator in Stata. The command allows for several options, such as tightening bounds by the use of covariates, confidence intervals for the treatment effect, and statistical inference based on a weighted bootstrap. The command is applied to data gathered from a randomized trial of the effect of financial incentives on weight-loss among obese individuals.

Suggested Citation

  • Harald Tauchmann, 2012. "leebounds: Lee’s treatment effect bounds for samples with nonrandom sample selection," German Stata Users' Group Meetings 2012 11, Stata Users Group.
  • Handle: RePEc:boc:dsug12:11
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/dsug2012/desug12_tauchmann.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters,in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492 National Bureau of Economic Research, Inc.
    2. Ahn, Hyungtaik & Powell, James L., 1993. "Semiparametric estimation of censored selection models with a nonparametric selection mechanism," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 3-29, July.
    3. Augurzky, Boris & Bauer, Thomas K. & Reichert, Arndt R. & Schmidt, Christoph M. & Tauchmann, Harald, 2012. "Does Money Burn Fat? Evidence from a Randomized Experiment," IZA Discussion Papers 6888, Institute for the Study of Labor (IZA).
    4. David S. Lee, 2009. "Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects," Review of Economic Studies, Oxford University Press, vol. 76(3), pages 1071-1102.
    Full references (including those not matched with items on IDEAS)

    More about this item

    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:boc:dsug12:11. 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: (Christopher F Baum). General contact details of provider: http://edirc.repec.org/data/stataea.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.

    If CitEc recognized a 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.

    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.