IDEAS home Printed from https://ideas.repec.org/r/eee/econom/v212y2019i2p522-555.html

Instrumental variables and the sign of the average treatment effect

Citations

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


Cited by:

  1. Ismael Mourifié & Yuanyuan Wan, 2017. "Testing Local Average Treatment Effect Assumptions," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 305-313, May.
  2. Thomas Carr & Toru Kitagawa, 2021. "Testing Instrument Validity with Covariates," Papers 2112.08092, arXiv.org, revised Sep 2023.
  3. Hang Miao & Kui Zhao & Zhun Wang & Linbo Jiang & Quanhui Jia & Yanming Fang & Quan Yu, 2020. "Intelligent Credit Limit Management in Consumer Loans Based on Causal Inference," Papers 2007.05188, arXiv.org.
  4. David M Kaplan & Wei Zhao, 2023. "Comparing latent inequality with ordinal data," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 189-214.
  5. Vitor Possebom, 2019. "Sharp Bounds for the Marginal Treatment Effect with Sample Selection," Papers 1904.08522, arXiv.org.
  6. Santiago Acerenza & Otávio Bartalotti & Désiré Kédagni, 2023. "Testing identifying assumptions in bivariate probit models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 407-422, April.
  7. Denni Tommasi & Lina Zhang, 2024. "Identifying program benefits when participation is misreported," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(6), pages 1123-1148, September.
  8. Han, Sukjin & Yang, Shenshen, 2024. "A computational approach to identification of treatment effects for policy evaluation," Journal of Econometrics, Elsevier, vol. 240(1).
  9. Mogstad, Magne & Torgovitsky, Alexander, 2024. "Instrumental variables with unobserved heterogeneity in treatment effects," Handbook of Labor Economics,, Elsevier.
  10. Sung Jae Jun & Sokbae Lee, 2024. "Causal Inference Under Outcome-Based Sampling with Monotonicity Assumptions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 998-1009, July.
  11. Krumme, Anna & Westphal, Matthias, 2026. "Testing IV Validity and LATE Interpretation Using Flexible Covariate Specifications," IZA Discussion Papers 18573, IZA Network @ LISER.
  12. Ivan A. Canay & Azeem M. Shaikh, 2016. "Practical and theoretical advances in inference for partially identified models," CeMMAP working papers 05/16, Institute for Fiscal Studies.
  13. Mourifié, Ismael & Wan, Yuanyuan, 2025. "Layered policy analysis in program evaluation using the marginal treatment effect," Journal of Econometrics, Elsevier, vol. 251(C).
  14. Kyunghoon Ban & Désiré Kédagni, 2022. "Nonparametric bounds on treatment effects with imperfect instruments [Instrument-based estimation with binarized treatments: Issues and tests for the exclusion restriction]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 477-493.
  15. Yuehao Bai & Shunzhuang Huang & Sarah Moon & Azeem Shaikh & Edward J. Vytlacil, 2024. "On the Identifying Power of Generalized Monotonicity for Average Treatment Effects," NBER Working Papers 32983, National Bureau of Economic Research, Inc.
  16. Lina Zhang & David T. Frazier & D.S. Poskitt & Xueyan Zhao, 2025. "Decomposing identification gains and evaluating instrument identification power for partially identified average treatment effects," Econometric Reviews, Taylor & Francis Journals, vol. 44(7), pages 915-938, August.
  17. Han, Sukjin, 2021. "Identification in nonparametric models for dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 132-147.
  18. Molinari, Francesca, 2020. "Microeconometrics with partial identification," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 355-486, Elsevier.
  19. Hans Fricke & Markus Frölich & Martin Huber & Michael Lechner, 2020. "Endogeneity and non‐response bias in treatment evaluation – nonparametric identification of causal effects by instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 481-504, August.
  20. Pedro Picchetti, 2025. "Breakdown Analysis for Instrumental Variables with Binary Outcomes," Papers 2507.10242, arXiv.org, revised Oct 2025.
  21. John A. List & Azeem M. Shaikh & Yang Xu, 2019. "Multiple hypothesis testing in experimental economics," Experimental Economics, Springer;Economic Science Association, vol. 22(4), pages 773-793, December.
  22. Sung Jae Jun & Sokbae (Simon) Lee, 2020. "Causal inference in case-control studies," CeMMAP working papers CWP19/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  23. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
  24. Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2015. "Going Beyond LATE: Bounding Average Treatment Effects of Job Corps Training," IZA Discussion Papers 9511, IZA Network @ LISER.
  25. Magne Mogstad & Alexander Torgovitsky, 2024. "Instrumental Variables with Unobserved Heterogeneity in Treatment Effects," NBER Working Papers 32927, National Bureau of Economic Research, Inc.
  26. Stefan Boes, 2009. "Bounds on Counterfactual Distributions Under Semi-Monotonicity Constraints," SOI - Working Papers 0920, Socioeconomic Institute - University of Zurich.
  27. Julia Schmieder, 2020. "Fertility as a Driver of Maternal Employment," Discussion Papers of DIW Berlin 1882, DIW Berlin, German Institute for Economic Research.
  28. Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org, revised Apr 2025.
  29. Yuehao Bai & Shunzhuang Huang & Sarah Moon & Andres Santos & Azeem M. Shaikh & Edward J. Vytlacil, 2024. "Inference for Treatment Effects Conditional on Generalized Principal Strata using Instrumental Variables," Papers 2411.05220, arXiv.org, revised Nov 2025.
  30. Kitagawa, Toru, 2021. "The identification region of the potential outcome distributions under instrument independence," Journal of Econometrics, Elsevier, vol. 225(2), pages 231-253.
  31. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  32. Schmieder, Julia, 2021. "Fertility as a driver of maternal employment," Labour Economics, Elsevier, vol. 72(C).
  33. John A. List & Azeem M. Shaikh & Atom Vayalinkal, 2023. "Multiple testing with covariate adjustment in experimental economics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 920-939, September.
  34. Possebom, Vitor, 2018. "Sharp bounds on the MTE with sample selection," MPRA Paper 89785, University Library of Munich, Germany.
  35. Matthew A. Masten & Alexandre Poirier, 2021. "Salvaging Falsified Instrumental Variable Models," Econometrica, Econometric Society, vol. 89(3), pages 1449-1469, May.
  36. Yinchu Zhu, 2021. "Phase transition of the monotonicity assumption in learning local average treatment effects," Papers 2103.13369, arXiv.org.
  37. Guber, Raphael, 2018. "Instrument Validity Tests with Causal Trees: With an Application to the Same-sex Instrument," MEA discussion paper series 201805, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  38. Yuehao Bai & Shunzhuang Huang & Max Tabord-Meehan, 2024. "Sharp Testable Implications of Encouragement Designs," Papers 2411.09808, arXiv.org, revised Nov 2025.
  39. Zheng Fang & Andres Santos & Azeem M. Shaikh & Alexander Torgovitsky, 2023. "Inference for Large‐Scale Linear Systems With Known Coefficients," Econometrica, Econometric Society, vol. 91(1), pages 299-327, January.
  40. Claudia Noack, 2021. "Sensitivity of LATE Estimates to Violations of the Monotonicity Assumption," Papers 2106.06421, arXiv.org.
  41. Pedro Picchetti, 2026. "Sensitivity Analysis for Instrumental Variables Under Joint Relaxations of Monotonicity and Independence," Papers 2603.25529, arXiv.org, revised Mar 2026.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.