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Sensitivity Analysis for Instrumental Variables Regression With Overidentifying Restrictions

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Cited by:

  1. Jesse Y. Hsu & Dylan S. Small, 2013. "Calibrating Sensitivity Analyses to Observed Covariates in Observational Studies," Biometrics, The International Biometric Society, vol. 69(4), pages 803-811, December.
  2. Faqin Lin, 2018. "Cross†country diffusion of ideology via FDI : Micro†evidence from China," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 26(1), pages 3-34, January.
  3. Hyunseung Kang & Youjin Lee & T. Tony Cai & Dylan S. Small, 2022. "Two robust tools for inference about causal effects with invalid instruments," Biometrics, The International Biometric Society, vol. 78(1), pages 24-34, March.
  4. Hans (J.L.W.) van Kippersluis & Niels (C.A.) Rietveld, 2017. "Beyond Plausibly Exogenous," Tinbergen Institute Discussion Papers 17-096/V, Tinbergen Institute.
  5. Kraay, Aart, 2008. "Instrumental variables regressions with honestly uncertain exclusion restrictions," Policy Research Working Paper Series 4632, The World Bank.
  6. Gyuhyeong Goh & Jisang Yu, 2022. "Causal inference with some invalid instrumental variables: A quasi‐Bayesian approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1432-1451, December.
  7. Maria Luisa Mancusi & Andrea Vezzulli, 2014. "R&D AND CREDIT RATIONING IN SMEs," Economic Inquiry, Western Economic Association International, vol. 52(3), pages 1153-1172, July.
  8. Martin-Shields, Charles P. & Stojetz, Wolfgang, 2019. "Food security and conflict: Empirical challenges and future opportunities for research and policy making on food security and conflict," World Development, Elsevier, vol. 119(C), pages 150-164.
  9. Doko Tchatoka, Firmin Sabro, 2012. "Specification Tests with Weak and Invalid Instruments," MPRA Paper 40185, University Library of Munich, Germany.
  10. Damian Clarke & Benjamín Matta, 2018. "Practical considerations for questionable IVs," Stata Journal, StataCorp LP, vol. 18(3), pages 663-691, September.
  11. Kiviet, Jan F., 2016. "When is it really justifiable to ignore explanatory variable endogeneity in a regression model?," Economics Letters, Elsevier, vol. 145(C), pages 192-195.
  12. Timothy B. Armstrong & Michal Kolesár, 2021. "Sensitivity analysis using approximate moment condition models," Quantitative Economics, Econometric Society, vol. 12(1), pages 77-108, January.
  13. Jan F. Kiviet & Jerzy Niemczyk, 2014. "On the Limiting and Empirical Distributions of IV Estimators When Some of the Instruments are Actually Endogenous," Advances in Econometrics, in: Essays in Honor of Peter C. B. Phillips, volume 33, pages 425-490, Emerald Group Publishing Limited.
  14. Huber, Martin, 2012. "Statistical verification of a natural "natural experiment": Tests and sensitivity checks for the sibling sex ratio instrument," Economics Working Paper Series 1219, University of St. Gallen, School of Economics and Political Science.
  15. James Lomas & Stephen Martin & Karl Claxton, 2018. "Estimating the marginal productivity of the English National Health Service from 2003/04 to 2012/13," Working Papers 158cherp, Centre for Health Economics, University of York.
  16. Doko Tchatoka, Firmin Sabro & Dufour, Jean-Marie, 2008. "Instrument endogeneity and identification-robust tests: some analytical results," MPRA Paper 29613, University Library of Munich, Germany.
  17. Joffe Marshall M & Small Dylan & Ten Have Thomas & Brunelli Steve & Feldman Harold I, 2008. "Extended Instrumental Variables Estimation for Overall Effects," The International Journal of Biostatistics, De Gruyter, vol. 4(1), pages 1-22, April.
  18. Zhaonan Qu & Yongchan Kwon, 2024. "Distributionally Robust Instrumental Variables Estimation," Papers 2410.15634, arXiv.org, revised Dec 2024.
  19. Jonathan Siverskog & Martin Henriksson, 2019. "Estimating the marginal cost of a life year in Sweden’s public healthcare sector," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(5), pages 751-762, July.
  20. Xuran Wang & Yang Jiang & Nancy R. Zhang & Dylan S. Small, 2018. "Sensitivity analysis and power for instrumental variable studies," Biometrics, The International Biometric Society, vol. 74(4), pages 1150-1160, December.
  21. Paul R. Rosenbaum, 2015. "Bahadur Efficiency of Sensitivity Analyses in Observational Studies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 205-217, March.
  22. Guido Imbens, 2014. "Instrumental Variables: An Econometrician's Perspective," NBER Working Papers 19983, National Bureau of Economic Research, Inc.
  23. Shuxi Zeng & Fan Li & Peng Ding, 2020. "Is being an only child harmful to psychological health?: Evidence from an instrumental variable analysis of China's One-Child Policy," Papers 2005.09130, arXiv.org, revised Jun 2020.
  24. Weiming Zhang & Debashis Ghosh, 2021. "A General Approach to Sensitivity Analysis for Mendelian Randomization," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(1), pages 34-55, April.
  25. Matthew A. Masten & Alexandre Poirier, 2021. "Salvaging Falsified Instrumental Variable Models," Econometrica, Econometric Society, vol. 89(3), pages 1449-1469, May.
  26. Hans Gersbach & Hans Haller & Hideo Konishi, 2015. "Household formation and markets," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 59(3), pages 461-507, August.
  27. Richard Ashley & Christopher Parmeter, 2015. "Sensitivity analysis for inference in 2SLS/GMM estimation with possibly flawed instruments," Empirical Economics, Springer, vol. 49(4), pages 1153-1171, December.
  28. Guggenberger, Patrik, 2012. "A note on the (in)consistency of the test of overidentifying restrictions and the concepts of true and pseudo-true parameters," Economics Letters, Elsevier, vol. 117(3), pages 901-904.
  29. Hyunseung Kang & Anru Zhang & T. Tony Cai & Dylan S. Small, 2016. "Instrumental Variables Estimation With Some Invalid Instruments and its Application to Mendelian Randomization," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 132-144, March.
  30. Dylan S. Small & Jing Cheng, 2009. "Discussion of “Identifiability and Estimation of Causal Effects in Randomized Trials with Noncompliance and Completely Nonignorable Missing Data”," Biometrics, The International Biometric Society, vol. 65(3), pages 682-686, September.
  31. Yiqi Lin & Frank Windmeijer & Xinyuan Song & Qingliang Fan, 2022. "On the instrumental variable estimation with many weak and invalid instruments," Papers 2207.03035, arXiv.org, revised Dec 2023.
  32. Shuxi Zeng & Fan Li & Peng Ding, 2020. "Is being an only child harmful to psychological health?: evidence from an instrumental variable analysis of China's one‐child policy," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1615-1635, October.
  33. Faqin Lin & Ermias O. Weldemicael & Xiaosong Wang, 2017. "Export sophistication increases income in sub-Saharan Africa: evidence from 1981–2000," Empirical Economics, Springer, vol. 52(4), pages 1627-1649, June.
  34. Paul R. Rosenbaum, 2011. "A New u-Statistic with Superior Design Sensitivity in Matched Observational Studies," Biometrics, The International Biometric Society, vol. 67(3), pages 1017-1027, September.
  35. Weihua An & Ying Ding, 2018. "The Landscape of Causal Inference: Perspective From Citation Network Analysis," The American Statistician, Taylor & Francis Journals, vol. 72(3), pages 265-277, July.
  36. Ruoyao Shi & Zhipeng Liao, 2018. "An Averaging GMM Estimator Robust to Misspecification," Working Papers 201803, University of California at Riverside, Department of Economics.
  37. Ben B. Hansen & Paul R. Rosenbaum & Dylan S. Small, 2014. "Clustered Treatment Assignments and Sensitivity to Unmeasured Biases in Observational Studies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 133-144, March.
  38. Adam C. Sales, 2017. "Review," Journal of Educational and Behavioral Statistics, , vol. 42(1), pages 69-84, February.
  39. Rietveld, Cornelius A. & Webbink, Dinand, 2016. "On the genetic bias of the quarter of birth instrument," Economics & Human Biology, Elsevier, vol. 21(C), pages 137-146.
  40. Richard A. Ashley & Guo Li, 2013. "Re-Examining the Impact of Housing Wealth and Stock Wealth on Household Spending: Does Persistence in Wealth Changes Matter?," Working Papers e07-39, Virginia Polytechnic Institute and State University, Department of Economics.
  41. Stephen Martin & James Lomas & Karl Claxton, 2019. "Is an ounce of prevention worth a pound of cure? Estimates of the impact of English public health grant on mortality and morbidity," Working Papers 166cherp, Centre for Health Economics, University of York.
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