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

Adaptive Experimental Design Using the Propensity Score

Contents:

Author Info

  • Jinyong Hahn

    ()
    (Department of Economics, UCLA)

  • Keisuke Hirano

    ()
    (University of Arizona)

  • Dean Karlan

    ()
    (Economic Growth Center, Yale University)

Abstract

Many social experiments are run in multiple waves, or are replications of earlier social experiments. In principle, the sampling design can be modified in later stages or replications to allow for more efficient estimation of causal effects. We consider the design of a two-stage experiment for estimating an average treatment effect, when covariate information is available for experimental subjects. We use data from the first stage to choose a conditional treatment assignment rule for units in the second stage of the experiment. This amounts to choosing the propensity score, the conditional probability of treatment given covariates. We propose to select the propensity score to minimize the asymptotic variance bound for estimating the average treatment effect. Our procedure can be implemented simply using standard statistical software and has attractive large-sample properties.

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.econ.yale.edu/growth_pdf/cdp969.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Economic Growth Center, Yale University in its series Working Papers with number 969.

as in new window
Length: 24 pages
Date of creation: Jan 2009
Date of revision:
Handle: RePEc:egc:wpaper:969

Contact details of provider:
Postal: PO Box 8269, New Haven CT 06520-8269
Phone: (203) 432-3610
Fax: (203) 432-3898
Web page: http://www.econ.yale.edu/
More information through EDIRC

Related research

Keywords: experimental design; propensity score; efficiency bound;

Other versions of this item:

Find related papers by JEL classification:

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. Duncan I. Simester & Peng Sun & John N. Tsitsiklis, 2006. "Dynamic Catalog Mailing Policies," Management Science, INFORMS, vol. 52(5), pages 683-696, May.
  2. Chamberlain, Gary, 1986. "Asymptotic efficiency in semi-parametric models with censoring," Journal of Econometrics, Elsevier, vol. 32(2), pages 189-218, July.
  3. Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
  4. Flores-Lagunes, Alfonso & Gonzalez, Arturo & Neumann, Todd C., 2005. "Learning but Not Earning? The Value of Job Corps Training for Hispanic Youths," IZA Discussion Papers 1638, Institute for the Study of Labor (IZA).
  5. Dean Karlan & John A. List, 2007. "Does Price Matter in Charitable Giving? Evidence from a Large-Scale Natural Field Experiment," American Economic Review, American Economic Association, vol. 97(5), pages 1774-1793, December.
  6. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
  7. Karlan, Dean S. & Zinman, Jonathan, 2007. "Credit Elasticities in Less-Developed Economies: Implications for Microfinance," CEPR Discussion Papers 6071, C.E.P.R. Discussion Papers.
  8. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc.
  9. Alfonso Flores-Lagunes & Arturo Gonzalez & Todd Neumann, 2010. "Learning But Not Earning? The Impact Of Job Corps Training On Hispanic Youth," Economic Inquiry, Western Economic Association International, vol. 48(3), pages 651-667, 07.
Full references (including those not matched with items on IDEAS)

Citations

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

Cited by:
  1. John A. List & Sally Sadoff & Mathis Wagner, 2009. "So you want to run an experiment, now what? Some Simple Rules of Thumb for Optimal Experimental Design," Carlo Alberto Notebooks 125, Collegio Carlo Alberto.
  2. Kyungchul Song, 2009. "Efficient Estimation of Average Treatment Effects under Treatment-Based Sampling," PIER Working Paper Archive 09-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  3. Fink, Günther & McConnell, Margaret & Vollmer, Sebastian, 2011. "Testing for Heterogeneous Treatment Effects in Experimental Data: False Discovery Risks and Correction Procedures," Hannover Economic Papers (HEP) dp-477, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  4. Timothy B. Armstrong & Shu Shen, 2013. "Inference on Optimal Treatment Assignments," Cowles Foundation Discussion Papers 1927, Cowles Foundation for Research in Economics, Yale University.
  5. Bhattacharya, Debopam & Dupas, Pascaline, 2012. "Inferring welfare maximizing treatment assignment under budget constraints," Journal of Econometrics, Elsevier, vol. 167(1), pages 168-196.
  6. Timothy B. Armstrong & Shu Shen, 2013. "Inference on Optimal Treatment Assignments," Cowles Foundation Discussion Papers 1927R, Cowles Foundation for Research in Economics, Yale University, revised Apr 2014.

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:egc:wpaper:969. 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: (Louise Danishevsky).

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.