IDEAS home Printed from https://ideas.repec.org/r/ucd/wpaper/200830.html
   My bibliography  Save this item

Instrumental Variables In Models With Multiple Outcomes: The General Unordered Case

Citations

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


Cited by:

  1. 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.
  2. 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.
  3. Heckman, James & Pinto, Rodrigo, 2024. "Econometric causality: The central role of thought experiments," Journal of Econometrics, Elsevier, vol. 243(1).
  4. Heckman, James J. & Pinto, Rodrigo, 2022. "Causality and Econometrics," IZA Discussion Papers 15081, Institute of Labor Economics (IZA).
  5. Mogstad, Magne & Torgovitsky, Alexander, 2024. "Instrumental variables with unobserved heterogeneity in treatment effects," Handbook of Labor Economics,, Elsevier.
  6. 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.
  7. Gandil, Mikkel Høst, 2021. "Substitution Effects in College Admissions," Memorandum 3/2021, Oslo University, Department of Economics.
  8. Andrew Chesher & Adam M. Rosen, 2021. "Counterfactual Worlds," Annals of Economics and Statistics, GENES, issue 142, pages 311-335.
  9. Kamat, Vishal, 2019. "Identification with Latent Choice Sets," TSE Working Papers 19-1031, Toulouse School of Economics (TSE).
  10. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Aug 2023.
  11. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory, 2016. "Dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 191(2), pages 276-292.
  12. 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.
  13. Sokbae Lee & Bernard Salanié, 2018. "Identifying Effects of Multivalued Treatments," Econometrica, Econometric Society, vol. 86(6), pages 1939-1963, November.
  14. Kamat, Vishal, 2024. "Identifying the effects of a program offer with an application to Head Start," Journal of Econometrics, Elsevier, vol. 240(1).
  15. Mogstad, Magne & Torgovitsky, Alexander & Walters, Christopher R., 2024. "Policy evaluation with multiple instrumental variables," Journal of Econometrics, Elsevier, vol. 243(1).
  16. Feng, Junlong, 2024. "Matching points: Supplementing instruments with covariates in triangular models," Journal of Econometrics, Elsevier, vol. 238(1).
  17. Bhuller, Manudeep & Sigstad, Henrik, 2024. "2SLS with multiple treatments," Journal of Econometrics, Elsevier, vol. 242(1).
  18. Sun, Zhenting, 2023. "Instrument validity for heterogeneous causal effects," Journal of Econometrics, Elsevier, vol. 237(2).
  19. 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.
  20. 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.
  21. Fernando Saltiel, 2023. "Multi-Dimensional Skills and Gender Differences in Stem Majors," The Economic Journal, Royal Economic Society, vol. 133(651), pages 1217-1247.
  22. 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.
  23. 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).
  24. 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.
  25. Vishal Kamat & Samuel Norris & Matthew Pecenco, 2023. "Identification in Multiple Treatment Models under Discrete Variation," Papers 2307.06174, arXiv.org.
  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.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.