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The Economics of Exclusion Restrictions in IV Models

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  • Damon Jones

Abstract

We explore a key underlying assumption, the exclusion restriction, commonly used in interpreting IV estimates in the presence of heterogenous treatment effects as a local average treatment effect (LATE). We show through a series of simple examples that in some commonly featured cases that this assumption is likely to be violated among inframarginal agents, i.e. the always- and never-takers. This violation of the exclusion restriction will generally confound the LATE interpretation of the associated IV results. We discuss potential adjustments to IV estimates in the presence of this bias.

Suggested Citation

  • Damon Jones, 2015. "The Economics of Exclusion Restrictions in IV Models," NBER Working Papers 21391, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:21391
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    References listed on IDEAS

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    1. Susan M. Dynarski, 2003. "Does Aid Matter? Measuring the Effect of Student Aid on College Attendance and Completion," American Economic Review, American Economic Association, vol. 93(1), pages 279-288, March.
    2. Rothstein, Jesse & Rouse, Cecilia Elena, 2011. "Constrained after college: Student loans and early-career occupational choices," Journal of Public Economics, Elsevier, vol. 95(1-2), pages 149-163, February.
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    4. James Heckman, 1997. "Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations," Journal of Human Resources, University of Wisconsin Press, vol. 32(3), pages 441-462.
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    Cited by:

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    3. Benjamin G. Hyman, 2022. "Can Displaced Labor Be Retrained? Evidence from Quasi-Random Assignment to Trade Adjustment Assistance," Working Papers 22-05, Center for Economic Studies, U.S. Census Bureau.
    4. Trevon D. Logan, 2018. "Do Black Politicians Matter?," NBER Working Papers 24190, National Bureau of Economic Research, Inc.
    5. 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.
    6. 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.
    7. Marin Drlje & Stepan Jurajda, 2021. "LATE Estimators under Costly Non-compliance in Student-College Matching Markets," CERGE-EI Working Papers wp686, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    8. James Berry & Greg Fischer & Raymond Guiteras, 2020. "Eliciting and Utilizing Willingness to Pay: Evidence from Field Trials in Northern Ghana," Journal of Political Economy, University of Chicago Press, vol. 128(4), pages 1436-1473.
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    11. Hans (J.L.W.) van Kippersluis & Niels (C.A.) Rietveld, 2017. "Beyond Plausibly Exogenous," Tinbergen Institute Discussion Papers 17-096/V, Tinbergen Institute.
    12. Contreras, Ivette, 2023. "Following your lead: Migration networks and immigrants' education decisions," World Development, Elsevier, vol. 170(C).

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    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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