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Ordered Discrete-Choice Selection Models and Local Average Treatment Effect Assumptions: Equivalence, Nonequivalence, and Representation Results

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  • Edward Vytlacil

    (Stanford University)

Abstract

This note shows that the local average treatment effect (LATE) assumptions of Angrist and Imbens are weaker than imposing an ordered, discrete-choice selection model if one imposes the standard assumption of constant thresholds in the latter. However, the note extends results of Vytlacil to show that the LATE assumptions are equivalent to an ordered, discrete-choice selection model if one allows for random thresholds in the latter. A nonparametric representation result for ordered, discrete-choice models is produced as a by-product of these results. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Edward Vytlacil, 2006. "Ordered Discrete-Choice Selection Models and Local Average Treatment Effect Assumptions: Equivalence, Nonequivalence, and Representation Results," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 578-581, August.
    • Handle: RePEc:tpr:restat:v:88:y:2006:i:3:p:578-581
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    Cited by:

    1. Hoshino, Tadao & Yanagi, Takahide, 2023. "Treatment effect models with strategic interaction in treatment decisions," Journal of Econometrics, Elsevier, vol. 236(2).
    2. Christian Dippel & Robert Gold & Stephan Heblich & Rodrigo Pinto, 2017. "Instrumental Variables and Causal Mechanisms: Unpacking the Effect of Trade on Workers and Voters," CESifo Working Paper Series 6816, CESifo.
    3. Meghir, Costas & Rivkin, Steven, 2011. "Econometric Methods for Research in Education," Handbook of the Economics of Education, in: Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), Handbook of the Economics of Education, edition 1, volume 3, chapter 1, pages 1-87, Elsevier.
    4. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory, 2016. "Dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 191(2), pages 276-292.
    5. Sun, Zhenting, 2023. "Instrument validity for heterogeneous causal effects," Journal of Econometrics, Elsevier, vol. 237(2).
    6. Yu-Chang Chen & Haitian Xie, 2020. "Global Representation of the Conditional LATE Model: A Separability Result," Papers 2007.08106, arXiv.org, revised Mar 2022.
    7. Flavio Cunha & James J. Heckman & Salvador Navarro, 2007. "The Identification And Economic Content Of Ordered Choice Models With Stochastic Thresholds," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1273-1309, November.
    8. Yu‐Chang Chen & Haitian Xie, 2022. "Global Representation of the Conditional LATE Model: A Separability Result," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 789-798, August.
    9. Flavio Cunha & James J. Heckman & Salvador Navarro, 2007. "The Identification & Economic Content of Ordered Choice Models with Stochastic Thresholds," Working Papers 200726, Geary Institute, University College Dublin.

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