IDEAS home Printed from https://ideas.repec.org/a/taf/jnlbes/v31y2013i4p534-545.html
   My bibliography  Save this article

Partial Identification of Local Average Treatment Effects With an Invalid Instrument

Author

Listed:
  • Carlos A. Flores
  • Alfonso Flores-Lagunes

Abstract

We derive nonparametric bounds for local average treatment effects (LATE) without imposing the exclusion restriction assumption or requiring an outcome with bounded support. Instead, we employ assumptions requiring weak monotonicity of mean potential and counterfactual outcomes within or across subpopulations defined by the values of the potential treatment status under each value of the instrument. The key element in our derivation is a result relating LATE to a causal mediation effect, which allows us to exploit partial identification results from the causal mediation analysis literature. The bounds are employed to analyze the effect of attaining a GED, high school, or vocational degree on future labor market outcomes using randomization into a training program as an invalid instrument. The resulting bounds are informative, indicating that the local effect when assigned to training for those whose degree attainment is affected by the instrument is at most 12.7 percentage points on employment and $64.4 on weekly earnings.

Suggested Citation

  • Carlos A. Flores & Alfonso Flores-Lagunes, 2013. "Partial Identification of Local Average Treatment Effects With an Invalid Instrument," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(4), pages 534-545, October.
  • Handle: RePEc:taf:jnlbes:v:31:y:2013:i:4:p:534-545
    DOI: 10.1080/07350015.2013.822760
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07350015.2013.822760
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/07350015.2013.822760?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Peter Z. Schochet & John Burghardt & Steven Glazerman, 2001. "National Job Corps Study: The Impacts of Job Corps on Participants' Employment and Related Outcomes," Mathematica Policy Research Reports db6c4204b8e1408bb0c6289ec, Mathematica Policy Research.
    2. repec:mpr:mprres:2951 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Burt S. Barnow & Jeffrey Smith, 2015. "Employment and Training Programs," NBER Chapters, in: Economics of Means-Tested Transfer Programs in the United States, Volume 2, pages 127-234, National Bureau of Economic Research, Inc.
    2. Peter Z. Schochet & Ronald D'Amico & Jillian Berk & Sarah Dolfin & Nathan Wozny, "undated". "Estimated Impacts for Participants in the Trade Adjustment Assistance (TAA) Program Under the 2002 Amendments," Mathematica Policy Research Reports 582d8723f6884d4eb7a3f95a4, Mathematica Policy Research.
    3. German Blanco & Carlos A. Flores & Alfonso Flores-Lagunes, 2013. "Bounds on Average and Quantile Treatment Effects of Job Corps Training on Wages," Journal of Human Resources, University of Wisconsin Press, vol. 48(3), pages 659-701.
    4. Ronald D'Amico & Peter Z. Schochet, "undated". "The Evaluation of the Trade Adjustment Assistance Program: A Synthesis of Major Findings," Mathematica Policy Research Reports c6b34445ad854f5d8178f580f, Mathematica Policy Research.
    5. Martin Huber & Yu‐Chin Hsu & Ying‐Ying Lee & Layal Lettry, 2020. "Direct and indirect effects of continuous treatments based on generalized propensity score weighting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 814-840, November.
    6. Markus Frölich & Martin Huber, 2017. "Direct and indirect treatment effects–causal chains and mediation analysis with instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1645-1666, November.
    7. Christy A. Visher & Laura Winterfield & Mark B. Coggeshall, 2006. "Systematic Review of Non‐Custodial Employment Programs: Impact on Recidivism Rates of Ex‐Offenders," Campbell Systematic Reviews, John Wiley & Sons, vol. 2(1), pages 1-28.
    8. Flores, Carlos A. & Flores-Lagunes, Alfonso, 2009. "Identification and Estimation of Causal Mechanisms and Net Effects of a Treatment under Unconfoundedness," IZA Discussion Papers 4237, Institute of Labor Economics (IZA).
    9. Hugo Bodory & Martin Huber & Lukáš Lafférs, 2022. "Evaluating (weighted) dynamic treatment effects by double machine learning [Identification of causal effects using instrumental variables]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 628-648.
    10. Kautz, Tim & Heckman, James J. & Diris, Ron & ter Weel, Bas & Borghans, Lex, 2014. "Fostering and Measuring Skills: Improving Cognitive and Non-Cognitive Skills to Promote Lifetime Success," IZA Discussion Papers 8696, Institute of Labor Economics (IZA).
    11. Lance Lochner, 2010. "Education Policy and Crime," NBER Chapters, in: Controlling Crime: Strategies and Tradeoffs, pages 465-515, National Bureau of Economic Research, Inc.
    12. Wooyoung Kim & Koohyun Kwon & Soonwoo Kwon & Sokbae (Simon) Lee, 2014. "The identification power of smoothness assumptions in models with counterfactual outcomes," CeMMAP working papers 17/14, Institute for Fiscal Studies.
    13. Phillip Heiler & Michael C. Knaus, 2021. "Effect or Treatment Heterogeneity? Policy Evaluation with Aggregated and Disaggregated Treatments," Papers 2110.01427, arXiv.org, revised Aug 2023.
    14. Peter Z. Schochet, "undated". "Is Regression Adjustment Supported by the Neyman Model for Causal Inference? (Presentation)," Mathematica Policy Research Reports abfc39d59c714499b2fe42f68, Mathematica Policy Research.
    15. Peter Z. Schochet & John A. Burghardt, 2008. "Do Job Corps performance measures track program impacts?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 27(3), pages 556-576.
    16. repec:mpr:mprres:7742 is not listed on IDEAS
    17. Carlos A. Flores & Alfonso Flores-Lagunes, 2007. "Identification and Estimation of Casual Mechanisms and Net Effects of a Treatment," Working Papers 0706, University of Miami, Department of Economics.
    18. Wooyoung Kim & Koohyun Kwon & Soonwoo Kwon & Sokbae Lee, 2018. "The identification power of smoothness assumptions in models with counterfactual outcomes," Quantitative Economics, Econometric Society, vol. 9(2), pages 617-642, July.
    19. German Blanco, 2017. "Who benefits from job placement services? A two-sided analysis," Journal of Productivity Analysis, Springer, vol. 47(1), pages 33-47, February.
    20. Peter Z. Schochet & Hanley Chiang, "undated". "Technical Methods Report: Estimation and Identification of the Complier Average Causal Effect Parameter in Education RCTs," Mathematica Policy Research Reports 947d1823e3ff42208532a763d, Mathematica Policy Research.
    21. Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2015. "Going Beyond LATE: Bounding Average Treatment Effects of Job Corps Training," IZA Discussion Papers 9511, Institute of Labor Economics (IZA).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:jnlbes:v:31:y:2013:i:4:p:534-545. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UBES20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.