IDEAS home Printed from https://ideas.repec.org/p/bfi/wpaper/2020-01.html

ivmte: An R Package for Implementing Marginal Treatment Effect Methods

Author

Listed:
  • Joshua Shea

    (University of Chicago - Department of Economics)

  • Alexander Torgovitsky

    (University of Chicago - Department of Economics)

Abstract

Instrumental variable (IV) strategies are widely used to estimate causal effects in economics, political science, epidemiology, and many other fields. When there is unobserved heterogeneity in causal effects, standard linear IV estimators only represent effects for complier subpopulations (Imbens and Angrist, 1994). Marginal treatment effect (MTE) methods (Heckman and Vytlacil, 1999, 2005) allow researchers to use additional assumptions to extrapolate beyond these subpopulations. In this paper, we introduce the ivmte package (Shea and Torgovitsky, 2019), which provides a flexible framework for implementing MTE methods in both point identified and partially identified settings.

Suggested Citation

  • Joshua Shea & Alexander Torgovitsky, 2020. "ivmte: An R Package for Implementing Marginal Treatment Effect Methods," Working Papers 2020-01, Becker Friedman Institute for Research In Economics.
    • Handle: RePEc:bfi:wpaper:2020-01
    as

    Download full text from publisher

    File URL: https://repec.bfi.uchicago.edu/RePEc/pdfs/BFI_WP_202001.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 389-432, August.
    2. Pedro Carneiro & James J. Heckman & Edward J. Vytlacil, 2011. "Estimating Marginal Returns to Education," American Economic Review, American Economic Association, vol. 101(6), pages 2754-2781, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Deniz Dutz & Ingrid Huitfeldt & Santiago Lacouture & Magne Mogstad & Alexander Torgovitsky & Winnie van Dijk, 2021. "Selection in Surveys," NBER Working Papers 29549, National Bureau of Economic Research, Inc.
      • Deniz Dutz & Ingrid Huitfeldt & Santiago Lacouture & Magne Mogstad & Alexander Torgovitsky & Winnie van Dijk, 2021. "Selection in Surveys," Discussion Papers 971, Statistics Norway, Research Department.
    2. Hoshino Tadao & Yanagi Takahide, 2022. "Estimating marginal treatment effects under unobserved group heterogeneity," Journal of Causal Inference, De Gruyter, vol. 10(1), pages 197-216, January.

    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. Domenico Depalo, 2020. "Explaining the causal effect of adherence to medication on cholesterol through the marginal patient," Health Economics, John Wiley & Sons, Ltd., vol. 29(S1), pages 110-126, October.
    2. Dionissi Aliprantis, 2017. "Assessing the evidence on neighborhood effects from Moving to Opportunity," Empirical Economics, Springer, vol. 52(3), pages 925-954, May.
    3. Giesecke, Matthias & Schuss, Eric, 2019. "Heterogeneity in marginal returns to language training of immigrants," IAB-Discussion Paper 201919, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    4. Sang Yoon (Tim) Lee & Yongseok Shin & Donghoon Lee, 2015. "The Option Value of Human Capital: Higher Education and Wage Inequality," NBER Working Papers 21724, National Bureau of Economic Research, Inc.
    5. Gloria Moroni & Cheti Nicoletti & Kjell G. Salvanes & Emma Tominey, 2025. "Gender equality through marriage," RFBerlin Discussion Paper Series 25140, ROCKWOOL Foundation Berlin (RFBerlin).
    6. Nadja van 't Hoff, 2023. "Identifying Causal Effects of Discrete, Ordered and ContinuousTreatments using Multiple Instrumental Variables," Papers 2311.17575, arXiv.org, revised Oct 2024.
    7. Shoya Ishimaru, 2024. "Empirical Decomposition of the IV-OLS Gap with Heterogeneous and Nonlinear Effects," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 505-520, March.
    8. Felfe, Christina & Lalive, Rafael, 2018. "Does early child care affect children's development?," Journal of Public Economics, Elsevier, vol. 159(C), pages 33-53.
    9. James J. Heckman & Stefano Mosso, 2014. "The Economics of Human Development and Social Mobility," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 689-733, August.
    10. Li, Meng & Jin, Tianyu & Liu, Shenglong & Zhou, Shaojie, 2021. "The cost of clean energy transition in rural China: Evidence based on marginal treatment effects," Energy Economics, Elsevier, vol. 97(C).
    11. Gabriel J. Power & Issouf Soumaré & Djerry C. Tandja M., 2022. "Certification by financial and legal advisors in private debt markets," The Financial Review, Eastern Finance Association, vol. 57(4), pages 893-923, November.
    12. Moffitt, Robert A. & Zahn, Matthew V., 2022. "The Marginal Labor Supply Disincentives of Welfare: Evidence from Administrative Barriers to Participation," Economics Working Paper Archive 66674, The Johns Hopkins University,Department of Economics.
    13. Sokbae Lee & Bernard Salanié, 2018. "Identifying Effects of Multivalued Treatments," Econometrica, Econometric Society, vol. 86(6), pages 1939-1963, November.
    14. Kirkebøen, Lars & Leuven, Edwin & Mogstad, Magne, 2014. "Field of Study, Earnings, and Self-Selection," Memorandum 29/2014, Oslo University, Department of Economics.
    15. Gaurab Aryal & Manudeep Bhuller & Fabian Lange, 2022. "Signaling and Employer Learning with Instruments," American Economic Review, American Economic Association, vol. 112(5), pages 1669-1702, May.
    16. Vitor Possebom, 2026. "Crime and Mismeasured Punishment: Marginal Treatment Effect with Misclassification," The Review of Economics and Statistics, MIT Press, vol. 108(1), pages 44-56, January.
    17. P. Lovaglio & S. Verzillo, 2016. "Heterogeneous economic returns to higher education: evidence from Italy," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(2), pages 791-822, March.
    18. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory & Urzua, Sergio, 2014. "Education, Health and Wages," IZA Discussion Papers 8027, IZA Network @ LISER.
    19. Martinez-Iriarte, Julian & Sun, Yixiao, 2024. "Identification and estimation of unconditional policy effects of an endogenous binary treatment: An unconditional MTE approach," Journal of Econometrics, Elsevier, vol. 244(1).
    20. Cornelissen, Thomas & Dustmann, Christian & Raute, Anna & Schönberg, Uta, 2016. "From LATE to MTE: Alternative methods for the evaluation of policy interventions," Labour Economics, Elsevier, vol. 41(C), pages 47-60.

    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:bfi:wpaper:2020-01. 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: Toni Shears The email address of this maintainer does not seem to be valid anymore. Please ask Toni Shears to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/mfichus.html .

    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.