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Instrumental Variables in Models with Multiple Outcomes: The General Unordered Case

Citations

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Cited by:

  1. Sokbae Lee & Bernard Salanié, 2018. "Identifying Effects of Multivalued Treatments," Econometrica, Econometric Society, vol. 86(6), pages 1939-1963, November.
  2. Kamat, Vishal, 2019. "Identification with Latent Choice Sets," TSE Working Papers 19-1031, Toulouse School of Economics (TSE).
  3. 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.
  4. Kamat, Vishal, 2024. "Identifying the effects of a program offer with an application to Head Start," Journal of Econometrics, Elsevier, vol. 240(1).
  5. Heckman, James J. & Urzúa, Sergio, 2010. "Comparing IV with structural models: What simple IV can and cannot identify," Journal of Econometrics, Elsevier, vol. 156(1), pages 27-37, May.
  6. Fitzenberger, Bernd & Furdas, Marina & Sajons, Christoph, 2016. "End-of-year spending and the long-run employment effects of training programs for the unemployed," Freiburg Discussion Papers on Constitutional Economics 16/08, Walter Eucken Institut e.V..
  7. Joseph G. Altonji & Ling Zhong, 2021. "The Labor Market Returns to Advanced Degrees," Journal of Labor Economics, University of Chicago Press, vol. 39(2), pages 303-360.
  8. Carta, Francesca & Rizzica, Lucia, 2018. "Early kindergarten, maternal labor supply and children's outcomes: Evidence from Italy," Journal of Public Economics, Elsevier, vol. 158(C), pages 79-102.
  9. 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.
  10. Andrew Chesher & Adam M. Rosen, 2021. "Counterfactual Worlds," Annals of Economics and Statistics, GENES, issue 142, pages 311-335.
  11. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Aug 2023.
  12. Sun, Zhenting, 2023. "Instrument validity for heterogeneous causal effects," Journal of Econometrics, Elsevier, vol. 237(2).
  13. James J. Heckman & John Eric Humphries & Gregory Veramendi, 2018. "The Nonmarket Benefits of Education and Ability," Journal of Human Capital, University of Chicago Press, vol. 12(2), pages 282-304.
  14. Schmandt, Marco & Tielkes, Constantin & Weinhardt, Felix, 2025. "Random Placement but Real Bias," IZA Discussion Papers 18319, IZA Network @ LISER.
  15. Nibbering, Didier & Oosterveen, Matthijs & Silva, Pedro Luís, 2022. "Clustered Local Average Treatment Effects: Fields of Study and Academic Student Progress," IZA Discussion Papers 15159, IZA Network @ LISER.
  16. Bhuller, Manudeep & Sigstad, Henrik, 2024. "2SLS with multiple treatments," Journal of Econometrics, Elsevier, vol. 242(1).
  17. Costas Lambros & Emerson Melo, 2025. "Welfare at Risk: Distributional impact of policy interventions," Papers 2512.20918, arXiv.org.
  18. Heckman, James J. & Pinto, Rodrigo, 2022. "Causality and Econometrics," IZA Discussion Papers 15081, IZA Network @ LISER.
  19. Marco Schmandt & Constantin Tielkes & Felix Weinhardt, 2025. "Random Placement but Real Bias," Berlin School of Economics Discussion Papers 0085, Berlin School of Economics.
  20. Heckman, James & Pinto, Rodrigo, 2024. "Econometric causality: The central role of thought experiments," Journal of Econometrics, Elsevier, vol. 243(1).
  21. Mogstad, Magne & Torgovitsky, Alexander & Walters, Christopher R., 2024. "Policy evaluation with multiple instrumental variables," Journal of Econometrics, Elsevier, vol. 243(1).
  22. Vishal Kamat & Samuel Norris & Matthew Pecenco, 2023. "Identification in Multiple Treatment Models under Discrete Variation," Papers 2307.06174, arXiv.org, revised Jan 2026.
  23. Mario Fiorini & Katrien Stevens, 2021. "Scrutinizing the Monotonicity Assumption in IV and fuzzy RD designs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1475-1526, December.
  24. Fernando Saltiel, 2023. "Multi-Dimensional Skills and Gender Differences in Stem Majors," The Economic Journal, Royal Economic Society, vol. 133(651), pages 1217-1247.
  25. Mogstad, Magne & Torgovitsky, Alexander, 2024. "Instrumental variables with unobserved heterogeneity in treatment effects," Handbook of Labor Economics,, Elsevier.
  26. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory, 2016. "Dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 191(2), pages 276-292.
  27. Feng, Junlong, 2024. "Matching points: Supplementing instruments with covariates in triangular models," Journal of Econometrics, Elsevier, vol. 238(1).
  28. Aniket A. Kawatkar & Joel W. Hay & William Stohl & Michael B. Nichol, 2013. "Incremental Expenditure Of Biologic Disease Modifying Antirheumatic Treatment Using Instrumental Variables In Panel Data," Health Economics, John Wiley & Sons, Ltd., vol. 22(7), pages 807-823, July.
  29. David G. Lugo‐Palacios & Patrick Bidulka & Stephen O’Neill & Orlagh Carroll & Anirban Basu & Amanda Adler & Karla DíazOrdaz & Andrew Briggs & Richard Grieve, 2025. "Going beyond randomised controlled trials to assess treatment effect heterogeneity across target populations," Health Economics, John Wiley & Sons, Ltd., vol. 34(1), pages 85-104, January.
  30. Gandil, Mikkel Høst, 2021. "Substitution Effects in College Admissions," Memorandum 3/2021, Oslo University, Department of Economics.
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