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Instrumental Variables Estimation With Some Invalid Instruments and its Application to Mendelian Randomization

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Cited by:

  1. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
  2. Zhong, Wei & Gao, Yang & Zhou, Wei & Fan, Qingliang, 2021. "Endogenous treatment effect estimation using high-dimensional instruments and double selection," Statistics & Probability Letters, Elsevier, vol. 169(C).
  3. Nicola Barban & Elisabetta De Cao & Sonia Oreffice & Climent Quintana-Domeque, 2016. "Assortative Mating on Education: A Genetic Assessment," Working Papers 2016-034, Human Capital and Economic Opportunity Working Group.
  4. Nicolas Apfel & Helmut Farbmacher & Rebecca Groh & Martin Huber & Henrika Langen, 2022. "Detecting Grouped Local Average Treatment Effects and Selecting True Instruments," Papers 2207.04481, arXiv.org, revised Oct 2023.
  5. Nicolas Apfel & Frank Windmeijer, 2022. "The Falsification Adaptive Set in Linear Models with Instrumental Variables that Violate the Exclusion or Conditional Exogeneity Restriction," Papers 2212.04814, arXiv.org, revised Apr 2024.
  6. 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.
  7. Hans (J.L.W.) van Kippersluis & Niels (C.A.) Rietveld, 2017. "Beyond Plausibly Exogenous," Tinbergen Institute Discussion Papers 17-096/V, Tinbergen Institute.
  8. 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.
  9. Xiaoran Liang & Eleanor Sanderson & Frank Windmeijer, 2022. "Selecting Valid Instrumental Variables in Linear Models with Multiple Exposure Variables: Adaptive Lasso and the Median-of-Medians Estimator," Papers 2208.05278, arXiv.org.
  10. Frank Windmeijer & Helmut Farbmacher & Neil Davies & George Davey Smith, 2019. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(527), pages 1339-1350, July.
  11. Damian Clarke & Benjamín Matta, 2018. "Practical considerations for questionable IVs," Stata Journal, StataCorp LP, vol. 18(3), pages 663-691, September.
  12. Eric Gautier & Christiern Rose, 2022. "Fast, Robust Inference for Linear Instrumental Variables Models using Self-Normalized Moments," Papers 2211.02249, arXiv.org, revised Nov 2022.
  13. Sheng Wang & Hyunseung Kang, 2022. "Weak‐instrument robust tests in two‐sample summary‐data Mendelian randomization," Biometrics, The International Biometric Society, vol. 78(4), pages 1699-1713, December.
  14. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
  15. Nicolas Apfel, 2019. "Relaxing the Exclusion Restriction in Shift-Share Instrumental Variable Estimation," Papers 1907.00222, arXiv.org, revised Jul 2022.
  16. Barban, Nicola & De Cao, Elisabetta & Oreffice, Sonia & Quintana-Domeque, Climent, 2021. "The effect of education on spousal education: A genetic approach," Labour Economics, Elsevier, vol. 71(C).
  17. de Boer, Nina Sofie, 2020. "Exploring the Long-Term Health Consequences of ADHD using a Multivariable Mendelian Randomization Network Approach," Thesis Commons c4wz5, Center for Open Science.
  18. Nicolas Apfel & Xiaoran Liang, 2024. "Agglomerative hierarchical clustering for selecting valid instrumental variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1201-1219, November.
  19. Jessica M B Rees & Angela M Wood & Frank Dudbridge & Stephen Burgess, 2019. "Robust methods in Mendelian randomization via penalization of heterogeneous causal estimates," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-24, September.
  20. Zhaonan Qu & Yongchan Kwon, 2024. "Distributionally Robust Instrumental Variables Estimation," Papers 2410.15634, arXiv.org, revised Dec 2024.
  21. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
  22. Frank Windmeijer & Xiaoran Liang & Fernando P. Hartwig & Jack Bowden, 2021. "The confidence interval method for selecting valid instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 752-776, September.
  23. Daniel J. Benjamin & David Cesarini & Patrick Turley & Alexander Strudwick Young, 2024. "Social-Science Genomics: Progress, Challenges, and Future Directions," NBER Working Papers 32404, National Bureau of Economic Research, Inc.
  24. Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
  25. Andrés Martínez & Alfonso Salafranca & Ana E. Sipols & Clara Simon Blas & Daniel Hengel, 2024. "Distributed lags using elastic-net regularization for market response models: focus on predictive and explanatory capacity," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(2), pages 417-435, June.
  26. 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.
  27. Jason Hartford & Victor Veitch & Dhanya Sridhar & Kevin Leyton-Brown, 2020. "Valid Causal Inference with (Some) Invalid Instruments," Papers 2006.11386, arXiv.org.
  28. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
  29. Qingliang Fan & Zijian Guo & Ziwei Mei, 2022. "A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates," Papers 2205.00171, arXiv.org, revised May 2024.
  30. 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.
  31. Ruoyu Wang & Qihua Wang & Wang Miao, 2023. "A robust fusion-extraction procedure with summary statistics in the presence of biased sources," Biometrika, Biometrika Trust, vol. 110(4), pages 1023-1040.
  32. Hyunseung Kang, 2023. "Discussion on “Instrumented difference‐in‐differences” by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy & Dylan S. Small," Biometrics, The International Biometric Society, vol. 79(2), pages 592-596, June.
  33. Kumari, Meena & Bao, Yanchun & S. Clarke, Paul & Smart, Melissa, 2018. "A comparison of robust methods for Mendelian randomization using multiple genetic variants," ISER Working Paper Series 2018-08, Institute for Social and Economic Research.
  34. Ruoyao Shi & Zhipeng Liao, 2018. "An Averaging GMM Estimator Robust to Misspecification," Working Papers 201803, University of California at Riverside, Department of Economics.
  35. Rong Fu & Haruko Noguchi & Shuhei Kaneko & Akira Kawamura & Cheolmin Kang & Hideto Takahashi & Nanako Tamiya, 2019. "How do cardiovascular diseases harm labor force participation? Evidence of nationally representative survey data from Japan, a super-aged society," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-16, July.
  36. Xi Chen & Ralf van der Lans & Michael Trusov, 2021. "Efficient Estimation of Network Games of Incomplete Information: Application to Large Online Social Networks," Management Science, INFORMS, vol. 67(12), pages 7575-7598, December.
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