Advanced Search
MyIDEAS: Login to save this paper or follow this series

Covariate selection and model averaging in semiparametric estimation of treatment effects

Contents:

Author Info

  • Toru Kitagawa

    ()
    (Institute for Fiscal Studies and University College London)

  • Chris Muris
Registered author(s):

    Abstract

    In the practice of program evaluation, choosing the covariates and the functional form of the propensity score is an important choice for estimating treatment effects. This paper proposes data-driven model selection and model averaging procedures that address this issue for the propensity score weighting estimation of the average treatment effects for treated (ATT). Building on the focussed information criterion (FIC), the proposed selection and averaging procedures aim to minimize the estimated mean squared error (MSE) of the ATT estimator in a local asymptotic framework. We formulate model averaging as a statistical decision problem in a limit experiment, and derive an averaging scheme that is Bayes optimal with respect to a given prior for the localisation parameters in the local asymptotic framework. In our Monte Carlo studies, the averaging estimator outperforms the post-covariate-selection estimator in terms of MSE, and shows a substantial reduction in MSE compared to conventional ATT estimators. We apply the procedures to evaluate the effect ot the labour market program described in LaLonde (1986).

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.cemmap.ac.uk/wps/cwp611313.pdf
    Download Restriction: no

    Bibliographic Info

    Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP61/13.

    as in new window
    Length:
    Date of creation: Dec 2013
    Date of revision:
    Handle: RePEc:ifs:cemmap:61/13

    Contact details of provider:
    Postal: The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE
    Phone: (+44) 020 7291 4800
    Fax: (+44) 020 7323 4780
    Email:
    Web page: http://cemmap.ifs.org.uk
    More information through EDIRC

    Order Information:
    Postal: The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE
    Email:

    Related research

    Keywords:

    This paper has been announced in the following NEP Reports:

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Gerda Claeskens & Raymond J. Carroll, 2007. "An asymptotic theory for model selection inference in general semiparametric problems," Biometrika, Biometrika Trust, vol. 94(2), pages 249-265.
    2. Magnus, Jan R. & Powell, Owen & Prüfer, Patricia, 2010. "A comparison of two model averaging techniques with an application to growth empirics," Journal of Econometrics, Elsevier, vol. 154(2), pages 139-153, February.
    3. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    4. repec:cup:cbooks:9780521496032 is not listed on IDEAS
    5. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Wiley Blackwell, vol. 65(2), pages 261-94, April.
    6. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-20, September.
    7. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2009. "Dealing with limited overlap in estimation of average treatment effects," Biometrika, Biometrika Trust, vol. 96(1), pages 187-199.
    8. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, 01.
    9. Wan, Alan T.K. & Zhang, Xinyu & Zou, Guohua, 2010. "Least squares model averaging by Mallows criterion," Journal of Econometrics, Elsevier, vol. 156(2), pages 277-283, June.
    10. Claeskens,Gerda & Hjort,Nils Lid, 2008. "Model Selection and Model Averaging," Cambridge Books, Cambridge University Press, number 9780521852258.
    11. Bryan S. Graham & Cristine Campos de Xavier Pinto & Daniel Egel, 2008. "Inverse Probability Tilting for Moment Condition Models with Missing Data," NBER Working Papers 13981, National Bureau of Economic Research, Inc.
    12. Bryan S. Graham & Cristine Campos de Xavier Pinto & Daniel Egel, 2011. "Efficient Estimation of Data Combination Models by the Method of Auxiliary-to-Study Tilting (AST)," NBER Working Papers 16928, National Bureau of Economic Research, Inc.
    13. Shakeeb Khan & Elie Tamer, 2010. "Irregular Identification, Support Conditions, and Inverse Weight Estimation," Econometrica, Econometric Society, vol. 78(6), pages 2021-2042, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:ifs:cemmap:61/13. 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: (Stephanie Seavers).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.