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

Citations

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Cited by:

  1. 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.
  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.
  3. Mogstad, Magne & Torgovitsky, Alexander, 2024. "Instrumental variables with unobserved heterogeneity in treatment effects," Handbook of Labor Economics,, Elsevier.
  4. 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.
  5. Gandil, Mikkel Høst, 2021. "Substitution Effects in College Admissions," Memorandum 3/2021, Oslo University, Department of Economics.
  6. Andrew Chesher & Adam M. Rosen, 2021. "Counterfactual Worlds," Annals of Economics and Statistics, GENES, issue 142, pages 311-335.
  7. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Aug 2023.
  8. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory, 2016. "Dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 191(2), pages 276-292.
  9. Sokbae Lee & Bernard Salanié, 2018. "Identifying Effects of Multivalued Treatments," Econometrica, Econometric Society, vol. 86(6), pages 1939-1963, November.
  10. 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.
  11. 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.
  12. Bhuller, Manudeep & Sigstad, Henrik, 2024. "2SLS with multiple treatments," Journal of Econometrics, Elsevier, vol. 242(1).
  13. Fernando Saltiel, 2023. "Multi-Dimensional Skills and Gender Differences in Stem Majors," The Economic Journal, Royal Economic Society, vol. 133(651), pages 1217-1247.
  14. 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.
  15. 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.
  16. Mogstad, Magne & Torgovitsky, Alexander & Walters, Christopher R., 2024. "Policy evaluation with multiple instrumental variables," Journal of Econometrics, Elsevier, vol. 243(1).
  17. Fitzenberger, Bernd & Furdas, Marina & Sajons, Christoph, 2016. "End-of-year spending and the long-run employment effects of training programs for the unemployed," ZEW Discussion Papers 16-084, ZEW - Leibniz Centre for European Economic Research.
  18. James J. Heckman & Rodrigo Pinto, 2022. "Causality and Econometrics," NBER Working Papers 29787, National Bureau of Economic Research, Inc.
  19. Vishal Kamat & Samuel Norris & Matthew Pecenco, 2023. "Identification in Multiple Treatment Models under Discrete Variation," Papers 2307.06174, arXiv.org.
  20. Heckman, James & Pinto, Rodrigo, 2024. "Econometric causality: The central role of thought experiments," Journal of Econometrics, Elsevier, vol. 243(1).
  21. Kamat, Vishal, 2019. "Identification with Latent Choice Sets," TSE Working Papers 19-1031, Toulouse School of Economics (TSE).
  22. Kamat, Vishal, 2024. "Identifying the effects of a program offer with an application to Head Start," Journal of Econometrics, Elsevier, vol. 240(1).
  23. Feng, Junlong, 2024. "Matching points: Supplementing instruments with covariates in triangular models," Journal of Econometrics, Elsevier, vol. 238(1).
  24. Sun, Zhenting, 2023. "Instrument validity for heterogeneous causal effects," Journal of Econometrics, Elsevier, vol. 237(2).
  25. Nibbering, Didier & Oosterveen, Matthijs & Silva, Pedro Luís, 2022. "Clustered Local Average Treatment Effects: Fields of Study and Academic Student Progress," IZA Discussion Papers 15159, Institute of Labor Economics (IZA).
  26. 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.
  27. 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.
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