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Inference with Imperfect Randomization: The Case of the Perry Preschool Program

Author

Listed:
  • Rodrigo Pinto

    (University of Chicago)

  • Azeem Shaikh

    (University of Chicago)

  • Adam Yavitz

    (University of Chicago)

  • James Heckman

    (University of Chicago)

Abstract

This paper considers the problem of inference about the effect of a program on multiple outcomes when assignment of treatment status is imperfectly randomized. Here, by imperfect randomization we mean that treatment status may have been reassigned after the initial randomization on the basis of observed or unobserved characteristics. We develop our methodology in the context of the High/Scope Perry Preschool program. We find significant effects of the program on a number of different outcomes of interest, including outcomes related to criminal activity for males, even after accounting for the imperfectness of the randomization and the multiplicity of hypotheses. On the other hand, effects of the program on other outcomes of interest, including outcomes related to criminal behavior for females, are no longer significant after more careful scrutiny.

Suggested Citation

  • Rodrigo Pinto & Azeem Shaikh & Adam Yavitz & James Heckman, 2010. "Inference with Imperfect Randomization: The Case of the Perry Preschool Program," 2010 Meeting Papers 1336, Society for Economic Dynamics.
    • Handle: RePEc:red:sed010:1336
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    Citations

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    Cited by:

    1. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2018. "Inference Under Covariate-Adaptive Randomization," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(524), pages 1784-1796, October.
    2. Aviva Aron-Dine & Liran Einav & Amy Finkelstein, 2013. "The RAND Health Insurance Experiment, Three Decades Later," Journal of Economic Perspectives, American Economic Association, vol. 27(1), pages 197-222, Winter.
    3. John A. List & Azeem M. Shaikh & Yang Xu, 2019. "Multiple hypothesis testing in experimental economics," Experimental Economics, Springer;Economic Science Association, vol. 22(4), pages 773-793, December.
    4. Daniela Del Boca & Christopher Flinn & Matthew Wiswall, 2016. "Transfers to Households with Children and Child Development," Economic Journal, Royal Economic Society, vol. 126(596), pages 136-183, October.
    5. James J. Heckman & Ganesh Karapakula, 2019. "The Perry Preschoolers at Late Midlife: A Study in Design-Specific Inference," Working Papers 2019-034, Human Capital and Economic Opportunity Working Group.
    6. Laurent Davezies & Guillaume Hollard & Pedro Vergara Merino, 2024. "Revisiting Randomization with the Cube Method," Papers 2407.13613, arXiv.org, revised Jul 2025.
    7. Arouna, Aminou & Michler, Jeffrey D. & Lokossou, Jourdain C., 2021. "Contract farming and rural transformation: Evidence from a field experiment in Benin," Journal of Development Economics, Elsevier, vol. 151(C).
    8. James J Heckman & Ganesh Karapakula, 2021. "Using a satisficing model of experimenter decision-making to guide finite-sample inference for compromised experiments," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 1-39.
    9. John A. List & Azeem M. Shaikh & Atom Vayalinkal, 2023. "Multiple testing with covariate adjustment in experimental economics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 920-939, September.
    10. Sneha Elango & Jorge Luis García & James J. Heckman & Andrés Hojman, 2015. "Early Childhood Education," NBER Chapters, in: Economics of Means-Tested Transfer Programs in the United States, Volume 2, pages 235-297, National Bureau of Economic Research, Inc.
    11. Jeffrey D. Michler & Anna Josephson, 2022. "Recent developments in inference: practicalities for applied economics," Chapters, in: A Modern Guide to Food Economics, chapter 11, pages 235-268, Edward Elgar Publishing.
    12. Yuehao Bai & Joseph P. Romano & Azeem M. Shaikh, 2022. "Inference in Experiments With Matched Pairs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(540), pages 1726-1737, October.
    13. Zhao, Anqi & Ding, Peng, 2021. "Covariate-adjusted Fisher randomization tests for the average treatment effect," Journal of Econometrics, Elsevier, vol. 225(2), pages 278-294.
    14. Asoni, Andrea, 2011. "Intelligence, Self-confidence and Entrepreneurship," Working Paper Series 887, Research Institute of Industrial Economics.
    15. Fougère, Denis & Filatriau, Olivier & Tô, Maxime, 2013. "Will Sooner Be Better? The Impact of Early Preschool Enrollment on Cognitive and Noncognitive Achievement of Children," CEPR Discussion Papers 9480, C.E.P.R. Discussion Papers.

    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

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