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Robustness of the Encouragement Design in a Two-Treatment Randomized Control Trial

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  • Behaghel, Luc

    (Paris School of Economics)

  • Crépon, Bruno

    (CREST)

  • Gurgand, Marc

    (Paris School of Economics)

Abstract

In this paper we discuss how the "encouragement design" used in randomized controlled trials can be extended to a setting with two treatments and one control group. Conditions to interpret the Two-Stage Least Squares (TSLS) estimates causally are stronger than in the case with only one treatment and one control group. A first case where a causal interpretation holds is when only those assigned to one of the two treatments can effectively enter the corresponding program. A second case is when there are always takers. In that second case, entry rates into a given program should be the same among those assigned to the control group and those assigned to the other program; this restriction can be tested from the data. In cases where the restriction is rejected, we derive bounds to the Local Average Treatment Effect (LATE) based on weaker monotonicity conditions. We illustrate the results using data from a large randomized experiment where job seekers at risk of long term unemployment can receive a reinforced counseling scheme offered either by the public or the private sector, or remain on a standard track.

Suggested Citation

  • Behaghel, Luc & Crépon, Bruno & Gurgand, Marc, 2013. "Robustness of the Encouragement Design in a Two-Treatment Randomized Control Trial," IZA Discussion Papers 7447, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp7447
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    References listed on IDEAS

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    1. Luc Behaghel & Bruno Cr?pon & Marc Gurgand, 2014. "Private and Public Provision of Counseling to Job Seekers: Evidence from a Large Controlled Experiment," American Economic Journal: Applied Economics, American Economic Association, vol. 6(4), pages 142-174, October.
    2. David S. Lee, 2009. "Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(3), pages 1071-1102.
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    Cited by:

    1. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    2. Atila Abdulkadiroğlu & Joshua D. Angrist & Yusuke Narita & Parag A. Pathak, 2017. "Research Design Meets Market Design: Using Centralized Assignment for Impact Evaluation," Econometrica, Econometric Society, vol. 85, pages 1373-1432, September.
    3. Patrick Kline & Christopher R. Walters, 2016. "Evaluating Public Programs with Close Substitutes: The Case of HeadStart," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1795-1848.
    4. Lars Kirkebøen & Edwin Leuven & Magne Mogstad, 2014. "Field of Study, Earnings, and Self-Selection," NBER Working Papers 20816, National Bureau of Economic Research, Inc.
    5. Bhuller, Manudeep & Sigstad, Henrik, 2024. "2SLS with multiple treatments," Journal of Econometrics, Elsevier, vol. 242(1).
    6. Gordon B. Dahl & Dan-Olof Rooth & Anders Stenberg, 2020. "Long-Run Returns to Field Study in Secondary School," CESifo Working Paper Series 8462, CESifo.
    7. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    8. Gordon Dahl & Dan-Olof Rooth & Anders Stenberg, 2020. "High School Majors, Comparative (Dis)Advantage, and Future Earnings," NBER Working Papers 27524, National Bureau of Economic Research, Inc.
    9. Mogstad, Magne & Torgovitsky, Alexander, 2024. "Instrumental variables with unobserved heterogeneity in treatment effects," Handbook of Labor Economics,, Elsevier.
    10. Humlum, Anders & Munch, Jakob R. & Rasmussen, Mette, 2023. "What Works for the Unemployed? Evidence from Quasi-Random Caseworker Assignments," IZA Discussion Papers 16033, Institute of Labor Economics (IZA).
    11. Paul Goldsmith-Pinkham & Peter Hull & Michal Kolesár, 2024. "Contamination Bias in Linear Regressions," American Economic Review, American Economic Association, vol. 114(12), pages 4015-4051, December.
    12. Nibbering, Didier & Oosterveen, Matthijs & Silva, Pedro Luís, 2022. "Clustered Local Average Treatment Effects: Fields of Study and Academic Student Progress," IZA Discussion Papers 15159, Institute of Labor Economics (IZA).
    13. Paul Goldsmith-Pinkham & Peter Hull & Michal Kolesár, 2021. "On Estimating Multiple Treatment Effects with Regression," Working Papers 2021-41, Princeton University. Economics Department..

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    More about this item

    Keywords

    randomized evaluation; local average treatment effect; bounds;
    All these keywords.

    JEL classification:

    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy
    • H44 - Public Economics - - Publicly Provided Goods - - - Publicly Provided Goods: Mixed Markets

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