IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

Doing more when you're running LATE: Applying marginal treatment effect methods to examine treatment effect heterogeneity in experiments

Listed author(s):
  • Amanda Kowalski

I examine treatment effect heterogeneity within an experiment to inform external validity. The local average treatment effect (LATE) gives an average treatment effect for compliers. I bound and estimate average treatment effects for always takers and never takers by extending marginal treatment effect methods. I use these methods to separate selection from treatment effect heterogeneity, generalizing the comparison of OLS to LATE. Applying these methods to the Oregon Health Insurance Experiment, I find that the treatment effect of insurance on emergency room utilization decreases from always takers to compliers to never takers. Previous utilization explains a large share of the treatment effect heterogeneity. Extrapolations show that other expansions could increase or decrease utilization.

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://s3.amazonaws.com/fieldexperiments-papers2/papers/00560.pdf
Download Restriction: no

Paper provided by The Field Experiments Website in its series Artefactual Field Experiments with number 00560.

as
in new window

Length:
Date of creation: 2016
Handle: RePEc:feb:artefa:00560
Contact details of provider: Web page: http://www.fieldexperiments.com

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. Amanda Kowalski, 2016. "Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 107-117, January.
  2. James J. Heckman & Vytlacil, Edward J., 2007. "Econometric Evaluation of Social Programs, Part II: Using the Marginal Treatment Effect to Organize Alternative Econometric Estimators to Evaluate Social Programs, and to Forecast their Effects in New," Handbook of Econometrics,in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 71 Elsevier.
  3. Donald B. Rubin, 1977. "Assignment to Treatment Group on the Basis of a Covariate," Journal of Educational and Behavioral Statistics, , vol. 2(1), pages 1-26, March.
  4. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
  5. Liran Einav & Amy Finkelstein & Stephen P. Ryan & Paul Schrimpf & Mark R. Cullen, 2013. "Selection on Moral Hazard in Health Insurance," American Economic Review, American Economic Association, vol. 103(1), pages 178-219, February.
  6. Chernozhukov, Victor & Fernández-Val, Iván & Kowalski, Amanda E., 2015. "Quantile regression with censoring and endogeneity," Journal of Econometrics, Elsevier, vol. 186(1), pages 201-221.
  7. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, 05.
  8. Pedro Carneiro & James J. Heckman & Edward J. Vytlacil, 2011. "Estimating Marginal Returns to Education," American Economic Review, American Economic Association, vol. 101(6), pages 2754-2781, October.
  9. Marinho Bertanha & Guido W. Imbens, 2014. "External Validity in Fuzzy Regression Discontinuity Designs," NBER Working Papers 20773, National Bureau of Economic Research, Inc.
  10. Liran Einav & Amy Finkelstein & Mark R. Cullen, 2010. "Estimating Welfare in Insurance Markets Using Variation in Prices," The Quarterly Journal of Economics, Oxford University Press, vol. 125(3), pages 877-921.
  11. Lawrence F. Katz & Jeffrey R. Kling & Jeffrey B. Liebman, 2001. "Moving to Opportunity in Boston: Early Results of a Randomized Mobility Experiment," The Quarterly Journal of Economics, Oxford University Press, vol. 116(2), pages 607-654.
  12. Kolstad, Jonathan T. & Kowalski, Amanda E., 2012. "The impact of health care reform on hospital and preventive care: Evidence from Massachusetts," Journal of Public Economics, Elsevier, vol. 96(11), pages 909-929.
  13. Pierre-Andre Chiappori & Bernard Salanie, 2000. "Testing for Asymmetric Information in Insurance Markets," Journal of Political Economy, University of Chicago Press, vol. 108(1), pages 56-78, February.
  14. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 38(2), pages 112-134.
  15. Michael Anderson & Carlos Dobkin & Tal Gross, 2012. "The Effect of Health Insurance Coverage on the Use of Medical Services," American Economic Journal: Economic Policy, American Economic Association, vol. 4(1), pages 1-27, February.
  16. Sylvain Chassang & Gerard Padro I Miquel & Erik Snowberg, 2012. "Selective Trials: A Principal-Agent Approach to Randomized Controlled Experiments," American Economic Review, American Economic Association, vol. 102(4), pages 1279-1309, June.
  17. Amy Finkelstein & James Poterba, 2014. "Testing for Asymmetric Information Using “Unused Observables” in Insurance Markets: Evidence from the U.K. Annuity Market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 81(4), pages 709-734, December.
  18. Joshua D. Angrist, 2004. "Treatment effect heterogeneity in theory and practice," Economic Journal, Royal Economic Society, vol. 114(494), pages 52-83, March.
  19. Martin B. Hackmann & Jonathan T. Kolstad & Amanda E. Kowalski, 2015. "Adverse Selection and an Individual Mandate: When Theory Meets Practice," American Economic Review, American Economic Association, vol. 105(3), pages 1030-1066, March.
  20. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
  21. Miller, Sarah, 2012. "The effect of insurance on emergency room visits: An analysis of the 2006 Massachusetts health reform," Journal of Public Economics, Elsevier, vol. 96(11), pages 893-908.
  22. Martin Huber & Giovanni Mellace, 2010. "Sharp IV bounds on average treatment effects under endogeneity and noncompliance," University of St. Gallen Department of Economics working paper series 2010 2010-31, Department of Economics, University of St. Gallen.
Full references (including those not matched with items on IDEAS)

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

When requesting a correction, please mention this item's handle: RePEc:feb:artefa:00560. 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: (Joe Seidel)

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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.