IDEAS home Printed from https://ideas.repec.org/r/ecm/emetrp/v79y2011i3p949-955.html
   My bibliography  Save this item

Partial Identification in Triangular Systems of Equations With Binary Dependent Variables

Citations

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


Cited by:

  1. Ismaël Mourifié & Marc Henry & Romuald Méango, 2020. "Sharp Bounds and Testability of a Roy Model of STEM Major Choices," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 3220-3283.
  2. Wooyoung Kim & Koohyun Kwon & Soonwoo Kwon & Sokbae Lee, 2018. "The identification power of smoothness assumptions in models with counterfactual outcomes," Quantitative Economics, Econometric Society, vol. 9(2), pages 617-642, July.
  3. Lukáš Lafférs, 2019. "Identification in Models with Discrete Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 657-696, February.
  4. Vitor Possebom, 2019. "Sharp Bounds for the Marginal Treatment Effect with Sample Selection," Papers 1904.08522, arXiv.org.
  5. Gu, Jiaying & Russell, Thomas M., 2023. "Partial identification in nonseparable binary response models with endogenous regressors," Journal of Econometrics, Elsevier, vol. 235(2), pages 528-562.
  6. Koen Jochmans, 2011. "Identification in Bivariate binary-choice Models with elliptical innovations," Working Papers hal-01069483, HAL.
  7. Han, Sukjin & Yang, Shenshen, 2024. "A computational approach to identification of treatment effects for policy evaluation," Journal of Econometrics, Elsevier, vol. 240(1).
  8. Ismael Mourifie & Yuanyuan Wan, 2015. "(Partially) Identifying potential outcome distributions in triangular systems," Working Papers tecipa-532, University of Toronto, Department of Economics.
  9. Han, Sukjin, 2021. "Identification in nonparametric models for dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 132-147.
  10. Chesher, Andrew, 2013. "Semiparametric Structural Models Of Binary Response: Shape Restrictions And Partial Identification," Econometric Theory, Cambridge University Press, vol. 29(2), pages 231-266, April.
  11. Shakeeb Khan & Arnaud Maurel & Yichong Zhang, 2023. "Informational Content of Factor Structures in Simultaneous Binary Response Models," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 385-410, Emerald Group Publishing Limited.
  12. Stefan Hoderlein & Yuya Sasaki, 2011. "On the role of time in nonseparable panel data models," CeMMAP working papers CWP15/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  13. 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.
  14. repec:hal:spmain:info:hdl:2441/eu4vqp9ompqllr09ij4oogc0g is not listed on IDEAS
  15. Alexander Torgovitsky, 2019. "Partial identification by extending subdistributions," Quantitative Economics, Econometric Society, vol. 10(1), pages 105-144, January.
  16. Bhattacharya, Jay & Shaikh, Azeem M. & Vytlacil, Edward, 2012. "Treatment effect bounds: An application to Swan–Ganz catheterization," Journal of Econometrics, Elsevier, vol. 168(2), pages 223-243.
  17. Nianqing Liu & Quang Vuong & Haiqing Xu, 2012. "Rationalization and Identification of Discrete Games with Correlated Types," Department of Economics Working Papers 130915, The University of Texas at Austin, Department of Economics.
  18. Sukjin Han & Sungwon Lee, 2019. "Estimation in a generalization of bivariate probit models with dummy endogenous regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 994-1015, September.
  19. Jiaying Gu & Thomas M. Russell, 2021. "Partial Identification in Nonseparable Binary Response Models with Endogenous Regressors," Papers 2101.01254, arXiv.org, revised Jul 2022.
  20. Lina Zhang & David T. Frazier & Don S. Poskitt & Xueyan Zhao, 2020. "Decomposing Identification Gains and Evaluating Instrument Identification Power for Partially Identified Average Treatment Effects," Monash Econometrics and Business Statistics Working Papers 34/20, Monash University, Department of Econometrics and Business Statistics.
  21. Li, Chuhui & Poskitt, D.S. & Zhao, Xueyan, 2019. "The bivariate probit model, maximum likelihood estimation, pseudo true parameters and partial identification," Journal of Econometrics, Elsevier, vol. 209(1), pages 94-113.
  22. Marc Henry & Ismael Mourifié, 2012. "Sharp Bounds in the Binary Roy Model," CIRJE F-Series CIRJE-F-835, CIRJE, Faculty of Economics, University of Tokyo.
  23. Sokbae Lee & Bernard Salanié, 2018. "Identifying Effects of Multivalued Treatments," Econometrica, Econometric Society, vol. 86(6), pages 1939-1963, November.
  24. Kasy, Maximilian, "undated". "Instrumental variables with unrestricted heterogeneity and continuous treatment - DON'T CITE! SEE ERRATUM BELOW," Working Paper 33257, Harvard University OpenScholar.
  25. Anirban Basu & Norma B. Coe & Cole G. Chapman, 2018. "2SLS versus 2SRI: Appropriate methods for rare outcomes and/or rare exposures," Health Economics, John Wiley & Sons, Ltd., vol. 27(6), pages 937-955, June.
  26. J. E. Prieger & A. Choi, 2024. "E-cigarettes and Smoking: Correlation, Causation, and Selection Bias," Journal of Consumer Policy, Springer, vol. 47(4), pages 471-498, December.
  27. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
  28. Balat, Jorge F. & Han, Sukjin, 2023. "Multiple treatments with strategic substitutes," Journal of Econometrics, Elsevier, vol. 234(2), pages 732-757.
  29. Mourifié, Ismael, 2015. "Sharp bounds on treatment effects in a binary triangular system," Journal of Econometrics, Elsevier, vol. 187(1), pages 74-81.
  30. 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.
  31. repec:spo:wpmain:info:hdl:2441/eu4vqp9ompqllr09ij4oogc0g is not listed on IDEAS
  32. Sung Jae Jun & Joris Pinkse & Haiqing Xu & Nese Yildiz, 2012. "Identification of treatment effects in a triangular system of equations," Department of Economics Working Papers 130910, The University of Texas at Austin, Department of Economics, revised Oct 2012.
  33. Galichon, Alfred & Henry, Marc, 2013. "Dilation bootstrap," Journal of Econometrics, Elsevier, vol. 177(1), pages 109-115.
  34. Liu, Nianqing & Vuong, Quang & Xu, Haiqing, 2017. "Rationalization and identification of binary games with correlated types," Journal of Econometrics, Elsevier, vol. 201(2), pages 249-268.
  35. Brent Kreider & John V. Pepper & Manan Roy, 2016. "Identifying the Effects of WIC on Food Insecurity Among Infants and Children," Southern Economic Journal, John Wiley & Sons, vol. 82(4), pages 1106-1122, April.
  36. James L. Powell, 2017. "Identification and Asymptotic Approximations: Three Examples of Progress in Econometric Theory," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 107-124, Spring.
  37. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
  38. Florian Gunsilius, 2019. "A path-sampling method to partially identify causal effects in instrumental variable models," Papers 1910.09502, arXiv.org, revised Jun 2020.
  39. Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2015. "Going Beyond LATE: Bounding Average Treatment Effects of Job Corps Training," IZA Discussion Papers 9511, Institute of Labor Economics (IZA).
  40. Jorge Balat & Sukjin Han, 2018. "Multiple Treatments with Strategic Interaction," Papers 1805.08275, arXiv.org, revised Sep 2019.
  41. Kédagni, Désiré, 2023. "Identifying treatment effects in the presence of confounded types," Journal of Econometrics, Elsevier, vol. 234(2), pages 479-511.
  42. Andrew Chesher & Adam M. Rosen, 2013. "What Do Instrumental Variable Models Deliver with Discrete Dependent Variables?," American Economic Review, American Economic Association, vol. 103(3), pages 557-562, May.
  43. Klein, Roger & Shen, Chan & Vella, Francis, 2015. "Estimation of marginal effects in semiparametric selection models with binary outcomes," Journal of Econometrics, Elsevier, vol. 185(1), pages 82-94.
  44. John C. Ham & Serkan Ozbeklik & Lara D. Shore-Sheppard, 2014. "Estimating Heterogeneous Takeup and Crowd-Out Responses to Existing Medicaid Income Limits and their Nonmarginal Expansions," Journal of Human Resources, University of Wisconsin Press, vol. 49(4), pages 872-905.
  45. Magne Mogstad & Andres Santos & Alexander Torgovitsky, 2018. "Using Instrumental Variables for Inference About Policy Relevant Treatment Parameters," Econometrica, Econometric Society, vol. 86(5), pages 1589-1619, September.
  46. Fan, Yanqin & Park, Sang Soo, 2012. "Confidence intervals for the quantile of treatment effects in randomized experiments," Journal of Econometrics, Elsevier, vol. 167(2), pages 330-344.
  47. Anirban Basu & Norma Coe & Cole G. Chapman, 2017. "Comparing 2SLS vs 2SRI for Binary Outcomes and Binary Exposures," NBER Working Papers 23840, National Bureau of Economic Research, Inc.
  48. Kitagawa, Toru, 2021. "The identification region of the potential outcome distributions under instrument independence," Journal of Econometrics, Elsevier, vol. 225(2), pages 231-253.
  49. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  50. Kédagni, Désiré & Mourifié, Ismael, 2014. "Tightening bounds in triangular systems," Economics Letters, Elsevier, vol. 125(3), pages 455-458.
  51. Shaomin Wu, 2024. "Identification and Estimation of Nonseparable Triangular Equations with Mismeasured Instruments," Papers 2404.13735, arXiv.org.
  52. Songnian Chen & Shakeeb Khan & Xun Tang, 2020. "Dummy Endogenous Variables in Weakly Separable Multiple Index Models without Monotonicity," Boston College Working Papers in Economics 996, Boston College Department of Economics.
  53. Songnian Chen & Shakeeb Khan & Xun Tang, 2022. "Endogeneity in Weakly Separable Models without Monotonicity," Papers 2208.05047, arXiv.org.
  54. Possebom, Vitor, 2018. "Sharp bounds on the MTE with sample selection," MPRA Paper 89785, University Library of Munich, Germany.
  55. Philipp Eisenhauer & James J. Heckman & Edward Vytlacil, 2015. "The Generalized Roy Model and the Cost-Benefit Analysis of Social Programs," Journal of Political Economy, University of Chicago Press, vol. 123(2), pages 413-443.
  56. Roger Klein & Chan Shen & Francis Vella, 2011. "Semiparametric selection models with binary outcomes," CeMMAP working papers CWP30/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  57. Lee, Jinhyun, 2013. "Sharp Bounds on Heterogeneous Individual Treatment Responses," SIRE Discussion Papers 2013-89, Scottish Institute for Research in Economics (SIRE).
  58. Maximilian Kasy, 2014. "Instrumental Variables with Unrestricted Heterogeneity and Continuous Treatment," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(4), pages 1614-1636.
  59. Martin Huber & Giovanni Mellace, 2010. "Sharp IV bounds on average treatment effects under endogeneity and noncompliance," University of St. Gallen Department of Economics working paper series 2010 2010-31, Department of Economics, University of St. Gallen.
  60. Shuowen Chen & Hiroaki Kaido, 2022. "Robust Tests of Model Incompleteness in the Presence of Nuisance Parameters," Papers 2208.11281, arXiv.org, revised Sep 2023.
  61. Jinhyun Lee, 2013. "Sharp Bounds on Heterogeneous Individual Treatment Responses," Discussion Paper Series, School of Economics and Finance 201310, School of Economics and Finance, University of St Andrews.
  62. Chen, Songnian & Khan, Shakeeb & Tang, Xun, 2024. "Endogeneity in weakly separable models without monotonicity," Journal of Econometrics, Elsevier, vol. 238(1).
  63. Austin Nichols, 2011. "Causal inference for binary regression with observational data," CHI11 Stata Conference 6, Stata Users Group.
  64. Shakeeb Khan & Elie Tamer & Qingsong Yao, 2024. "Inference on High Dimensional Selective Labeling Models," Papers 2410.18381, arXiv.org, revised Oct 2024.
  65. Sung Jae Jun & Joris Pinkse & Haiqing Xu & Neşe Yıldız, 2016. "Multiple Discrete Endogenous Variables in Weakly-Separable Triangular Models," Econometrics, MDPI, vol. 4(1), pages 1-21, February.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.