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Robust, accurate confidence intervals with a weak instrument: quarter of birth and education

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Cited by:

  1. Chang, Pao-Li & Lee, Myoung-Jae, 2011. "The WTO trade effect," Journal of International Economics, Elsevier, vol. 85(1), pages 53-71, September.
  2. Siyu Heng & Dylan S. Small & Paul R. Rosenbaum, 2020. "Finding the strength in a weak instrument in a study of cognitive outcomes produced by Catholic high schools," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 935-958, June.
  3. Yusuke Narita & Kohei Yata, 2021. "Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules," Working Papers 2021-022, Human Capital and Economic Opportunity Working Group.
  4. Jeffrey Clemens & Benedic Ippolito, 2019. "Uncompensated Care and the Collapse of Hospital Payment Regulation: An Illustration of the Tinbergen Rule," Public Finance Review, , vol. 47(6), pages 1002-1041, November.
  5. Luke Keele & Dylan Small & Richard Grieve, 2017. "Randomization-based instrumental variables methods for binary outcomes with an application to the ‘IMPROVE’ trial," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 569-586, February.
  6. Clemens, Jeffrey & Wither, Michael, 2019. "The minimum wage and the Great Recession: Evidence of effects on the employment and income trajectories of low-skilled workers," Journal of Public Economics, Elsevier, vol. 170(C), pages 53-67.
  7. 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.
  8. Kirill Borusyak & Peter Hull & Xavier Jaravel, 2023. "Design-Based Identification with Formula Instruments: A Review," NBER Working Papers 31393, National Bureau of Economic Research, Inc.
  9. Andrews, Donald W.K. & Marmer, Vadim, 2008. "Exactly distribution-free inference in instrumental variables regression with possibly weak instruments," Journal of Econometrics, Elsevier, vol. 142(1), pages 183-200, January.
  10. Jeffrey Clemens, 2019. "Cross‐Country Evidence on Labor Market Institutions and Young Adult Employment through the Financial Crisis," Southern Economic Journal, John Wiley & Sons, vol. 86(2), pages 573-612, October.
  11. Cabus, Sofie J. & De Witte, Kristof, 2011. "Does school time matter?—On the impact of compulsory education age on school dropout," Economics of Education Review, Elsevier, vol. 30(6), pages 1384-1398.
  12. Clemens, Jeffrey, 2017. "Pitfalls in the Development of Falsification Tests: An Illustration from the Recent Minimum Wage Literature," MPRA Paper 80154, University Library of Munich, Germany.
  13. Purevdorj Tuvaandorj, 2024. "A Combinatorial Central Limit Theorem for Stratified Randomization," Papers 2402.14764, arXiv.org, revised Apr 2024.
  14. Eduardo Fé & Mario Pezzino, 2015. "On The Local Causal Effects of Retirement on Human Capital," Economics Discussion Paper Series 1508, Economics, The University of Manchester.
  15. Kasey S. Buckles & Daniel M. Hungerman, 2013. "Season of Birth and Later Outcomes: Old Questions, New Answers," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 711-724, July.
  16. Bekker, Paul A. & Lawford, Steve, 2008. "Symmetry-based inference in an instrumental variable setting," Journal of Econometrics, Elsevier, vol. 142(1), pages 28-49, January.
  17. De Haas, Ralph & Baranov, Victoria & Grosjean, Pauline, 2020. "Male-biased Sex Ratios and Masculinity Norms: Evidence from Australia's Colonial Past," CEPR Discussion Papers 14493, C.E.P.R. Discussion Papers.
  18. Borusyak, Kirill & Hull, Peter, 2020. "Non-Random Exposure to Exogenous Shocks: Theory and Applications," CEPR Discussion Papers 15319, C.E.P.R. Discussion Papers.
  19. Eduardo Fé, 2021. "Pension eligibility rules and the local causal effect of retirement on cognitive functioning," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 812-841, July.
  20. Myoung Lee & Sang Lee, 2009. "Sensitivity analysis of job-training effects on reemployment for Korean women," Empirical Economics, Springer, vol. 36(1), pages 81-107, February.
  21. 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.
  22. Marcelo Arbex & Justin M. Carre & Shawn N. Geniole & Enlinson Mattos, 2018. "Testosterone, personality traits and tax evasion," Working Papers 1801, University of Windsor, Department of Economics.
  23. Luke Keele & Steve Harris & Samuel D. Pimentel & Richard Grieve, 2020. "Stronger instruments and refined covariate balance in an observational study of the effectiveness of prompt admission to intensive care units," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1501-1521, October.
  24. Xavier D'Haultf{oe}uille & Purevdorj Tuvaandorj, 2022. "A Robust Permutation Test for Subvector Inference in Linear Regressions," Papers 2205.06713, arXiv.org, revised Sep 2023.
  25. Guido Imbens, 2014. "Instrumental Variables: An Econometrician's Perspective," NBER Working Papers 19983, National Bureau of Economic Research, Inc.
  26. Adam C. Sales & Ben B. Hansen, 2020. "Limitless Regression Discontinuity," Journal of Educational and Behavioral Statistics, , vol. 45(2), pages 143-174, April.
  27. Purevdorj Tuvaandorj, 2021. "Robust Permutation Tests in Linear Instrumental Variables Regression," Papers 2111.13774, arXiv.org, revised Jul 2024.
  28. Wang, Wenjie, 2021. "Wild Bootstrap for Instrumental Variables Regression with Weak Instruments and Few Clusters," MPRA Paper 106227, University Library of Munich, Germany.
  29. Jeffrey P. Clemens & Parker Rogers, 2020. "Demand Shocks, Procurement Policies, and the Nature of Medical Innovation: Evidence from Wartime Prosthetic Device Patents," CESifo Working Paper Series 8781, CESifo.
  30. Fan Yang & José R. Zubizarreta & Dylan S. Small & Scott Lorch & Paul R. Rosenbaum, 2014. "Dissonant Conclusions When Testing the Validity of an Instrumental Variable," The American Statistician, Taylor & Francis Journals, vol. 68(4), pages 253-263, November.
  31. Arbex, Marcelo Aarestru & Carré, Justin M. & Geniole, Shawn N. & Mattos, Enlinson, 2018. "Tax evasion, testosterone and personality traits," Textos para discussão 466, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
  32. Vladimir Atanasov & Bernard Black, 2021. "The Trouble with Instruments: The Need for Pretreatment Balance in Shock-Based Instrumental Variable Designs," Management Science, INFORMS, vol. 67(2), pages 1270-1302, February.
  33. John J. Donohue & Daniel E. Ho, 2007. "The Impact of Damage Caps on Malpractice Claims: Randomization Inference with Difference‐in‐Differences," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 4(1), pages 69-102, March.
  34. Marinho Bertanha & Eunyi Chung, 2023. "Permutation Tests at Nonparametric Rates," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(544), pages 2833-2846, October.
  35. Alberto Abadie & Susan Athey & Guido W. Imbens & Jeffrey M. Wooldridge, 2014. "Finite Population Causal Standard Errors," NBER Working Papers 20325, National Bureau of Economic Research, Inc.
  36. Bo Zhang & Siyu Heng & Emily J. MacKay & Ting Ye, 2022. "Bridging preference‐based instrumental variable studies and cluster‐randomized encouragement experiments: Study design, noncompliance, and average cluster effect ratio," Biometrics, The International Biometric Society, vol. 78(4), pages 1639-1650, December.
  37. Ganong, Peter & Jäger, Simon, 2014. "A Permutation Test and Estimation Alternatives for the Regression Kink Design," IZA Discussion Papers 8282, Institute of Labor Economics (IZA).
  38. Peter Ganong & Simon Jäger, 2018. "A Permutation Test for the Regression Kink Design," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 494-504, April.
  39. Jaeger, Simon C & Ganong, Peter Nathan, 2014. "A Permutation Test and Estimation Alternatives for the Regression Kink Design," Scholarly Articles 34222894, Harvard University Department of Economics.
  40. Hyunseung Kang & Laura Peck & Luke Keele, 2018. "Inference for instrumental variables: a randomization inference approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1231-1254, October.
  41. David S. Abrams & Marianne Bertrand & Sendhil Mullainathan, 2012. "Do Judges Vary in Their Treatment of Race?," The Journal of Legal Studies, University of Chicago Press, vol. 41(2), pages 347-383.
  42. Anustubh Agnihotri & Rahul Verma, 2016. "Design-based Approach in Social Science Research," Studies in Indian Politics, , vol. 4(2), pages 241-248, December.
  43. 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.
  44. David I. Stern, 2011. "From Correlation to Granger Causality," Crawford School Research Papers 1113, Crawford School of Public Policy, The Australian National University.
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