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Inverse Probability Tilting for Moment Condition Models with Missing Data

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Cited by:

  1. Saraswata Chaudhuriy & David T. Frazierz & Eric Renault, 2016. "Indirect Inference with Endogenously Missing Exogenous Variables," CIRANO Working Papers 2016s-15, CIRANO.
  2. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
  3. Martin Huber, 2019. "An introduction to flexible methods for policy evaluation," Papers 1910.00641, arXiv.org.
  4. Kitagawa, Toru & Muris, Chris, 2016. "Model averaging in semiparametric estimation of treatment effects," Journal of Econometrics, Elsevier, vol. 193(1), pages 271-289.
  5. Zichen Deng & Maarten Lindeboom, 2021. "Early-life Famine Exposure, Hunger Recall and Later-life Health," Tinbergen Institute Discussion Papers 21-054/V, Tinbergen Institute.
  6. Bryan S. Graham & Guido W. Imbens & Geert Ridder, 2020. "Identification and Efficiency Bounds for the Average Match Function Under Conditionally Exogenous Matching," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 303-316, April.
  7. Bryan S. Graham & Keisuke Hirano, 2011. "Robustness to Parametric Assumptions in Missing Data Models," American Economic Review, American Economic Association, vol. 101(3), pages 538-543, May.
  8. Słoczyński, Tymon & Wooldridge, Jeffrey M., 2018. "A General Double Robustness Result For Estimating Average Treatment Effects," Econometric Theory, Cambridge University Press, vol. 34(1), pages 112-133, February.
  9. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
  10. Zichen Deng & Maarten Lindeboom, 2022. "Early‐life famine exposure, hunger recall, and later‐life health," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 771-787, June.
  11. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
  12. Susan Athey & Guido Imbens & Thai Pham & Stefan Wager, 2017. "Estimating Average Treatment Effects: Supplementary Analyses and Remaining Challenges," American Economic Review, American Economic Association, vol. 107(5), pages 278-281, May.
  13. Samia FERHAT, 2022. "The impact of university openings on labor market outcomes," THEMA Working Papers 2022-18, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
  14. Michael Lechner & Jana Mareckova, 2024. "Comprehensive Causal Machine Learning," Papers 2405.10198, arXiv.org.
  15. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2021. "The Augmented Synthetic Control Method," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1789-1803, October.
  16. Michael C. Knaus, 2021. "A double machine learning approach to estimate the effects of musical practice on student’s skills," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 282-300, January.
  17. Tymon Sloczynski & S. Derya Uysal & Jeffrey M. Wooldridge & Derya Uysal, 2022. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," CESifo Working Paper Series 9715, CESifo.
  18. Samuel Bazzi & Sudarno Sumarto & Asep Suryahadi, "undated". "It’s All in the Timing: Household Expenditure and Labor Supply Responses to Unconditional Cash Transfers," Working Papers 280, Publications Department.
  19. Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2021. "A unified framework for efficient estimation of general treatment models," Quantitative Economics, Econometric Society, vol. 12(3), pages 779-816, July.
  20. Wang-Sheng Lee, 2013. "Propensity score matching and variations on the balancing test," Empirical Economics, Springer, vol. 44(1), pages 47-80, February.
  21. Òscar Jordà & Alan M. Taylor, 2016. "The Time for Austerity: Estimating the Average Treatment Effect of Fiscal Policy," Economic Journal, Royal Economic Society, vol. 126(590), pages 219-255, February.
  22. Christopher R. Bollinger & Barry T. Hirsch, 2010. "GDP & Beyond – die europäische Perspektive," RatSWD Working Papers 165, German Data Forum (RatSWD).
  23. Sean Yiu & Li Su, 2018. "Covariate association eliminating weights: a unified weighting framework for causal effect estimation," Biometrika, Biometrika Trust, vol. 105(3), pages 709-722.
  24. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
  25. Christopher R. Bollinger & Barry T. Hirsch, 2013. "Is Earnings Nonresponse Ignorable?," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 407-416, May.
  26. Filomena, Mattia & Picchio, Matteo, 2023. "You'll never walk alone: Unemployment, social networks and leisure activities," GLO Discussion Paper Series 1346, Global Labor Organization (GLO).
  27. Sasaki, Yuya & Ura, Takuya, 2023. "Estimation and inference for policy relevant treatment effects," Journal of Econometrics, Elsevier, vol. 234(2), pages 394-450.
  28. Zichen Deng & Maarten Lindeboom, 2021. "Early-life Famine Exposure, Hunger Recall and Later-life Health," Papers 2021-04, Centre for Health Economics, Monash University.
  29. Pierre Chausse & George Luta, 2017. "Casual Inference using Generalized Empirical Likelihood Methods," Working Papers 1707, University of Waterloo, Department of Economics, revised Dec 2017.
  30. Michael L. Anderson, 2017. "The Benefits of College Athletic Success: An Application of the Propensity Score Design," The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 119-134, March.
  31. Martin Cousineau & Vedat Verter & Susan A. Murphy & Joelle Pineau, 2022. "Estimating causal effects with optimization-based methods: A review and empirical comparison," Papers 2203.00097, arXiv.org.
  32. Carlos A. Flores & Oscar A. Mitnik, 2013. "Comparing Treatments across Labor Markets: An Assessment of Nonexperimental Multiple-Treatment Strategies," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1691-1707, December.
  33. Sean Yiu & Li Su, 2022. "Joint calibrated estimation of inverse probability of treatment and censoring weights for marginal structural models," Biometrics, The International Biometric Society, vol. 78(1), pages 115-127, March.
  34. Michael Zimmert, 2018. "The Finite Sample Performance of Treatment Effects Estimators based on the Lasso," Papers 1805.05067, arXiv.org.
  35. Knaus, Michael C. & Lechner, Michael & Reimers, Anne K., 2020. "For better or worse? – The effects of physical education on child development," Labour Economics, Elsevier, vol. 67(C).
  36. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
  37. Arun Advani & Toru Kitagawa & Tymon Słoczyński, 2019. "Mostly harmless simulations? Using Monte Carlo studies for estimator selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 893-910, September.
  38. Firpo, Sergio Pinheiro & Pinto, Rafael de Carvalho Cayres, 2012. "Combining Strategies for the Estimation of Treatment Effects," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 32(1), March.
  39. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2022. "Unconditional quantile regression with high‐dimensional data," Quantitative Economics, Econometric Society, vol. 13(3), pages 955-978, July.
  40. Toru Kitagawa & Chris Muris, 2013. "Covariate selection and model averaging in semiparametric estimation of treatment effects," CeMMAP working papers 61/13, Institute for Fiscal Studies.
  41. Victor Chernozhukov & Vira Semenova, 2018. "Simultaneous inference for Best Linear Predictor of the Conditional Average Treatment Effect and other structural functions," CeMMAP working papers CWP40/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  42. Hristache, Marian & Patilea, Valentin, 2021. "Equivalent models for observables under the assumption of missing at random," Econometrics and Statistics, Elsevier, vol. 20(C), pages 153-165.
  43. Kostas Bimpikis & Wedad J. Elmaghraby & Ken Moon & Wenchang Zhang, 2020. "Managing Market Thickness in Online Business-to-Business Markets," Management Science, INFORMS, vol. 66(12), pages 5783-5822, December.
  44. Hao Cheng & Ying Wei, 2018. "A fast imputation algorithm in quantile regression," Computational Statistics, Springer, vol. 33(4), pages 1589-1603, December.
  45. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
  46. Arun Advani & Tymon Słoczyński, 2013. "Mostly harmless simulations? On the internal validity of empirical Monte Carlo studies," CeMMAP working papers 64/13, Institute for Fiscal Studies.
  47. Elena Denisova-Schmidt & Martin Huber & Elvira Leontyeva, 2016. "Do Anti-Corruption Educational Campaigns Reach Students? Some Evidence from Russia and Ukraine," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 1, pages 61-83.
  48. Amilcar Velez, 2024. "On the Asymptotic Properties of Debiased Machine Learning Estimators," Papers 2411.01864, arXiv.org.
  49. Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2017. "The finite sample performance of semi- and non-parametric estimators for treatment effects and policy evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 91-102.
  50. Kwun Chuen Gary Chan & Sheung Chi Phillip Yam & Zheng Zhang, 2016. "Globally efficient non-parametric inference of average treatment effects by empirical balancing calibration weighting," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 673-700, June.
  51. Chaudhuri, Saraswata & Frazier, David T. & Renault, Eric, 2018. "Indirect Inference with endogenously missing exogenous variables," Journal of Econometrics, Elsevier, vol. 205(1), pages 55-75.
  52. Tommaso Manfè & Luca Nunziata, 2023. "Difference-In-Difference Design With Repeated Cross-Sections Under Compositional Changes: a Monte-Carlo Evaluation of Alternative Approaches," "Marco Fanno" Working Papers 0305, Dipartimento di Scienze Economiche "Marco Fanno".
  53. Fan, Yanqin & Shi, Xuetao & Tao, Jing, 2023. "Partial identification and inference in moment models with incomplete data," Journal of Econometrics, Elsevier, vol. 235(2), pages 418-443.
  54. Graham, Bryan S. & Pinto, Cristine Campos de Xavier, 2022. "Semiparametrically efficient estimation of the average linear regression function," Journal of Econometrics, Elsevier, vol. 226(1), pages 115-138.
  55. Samuel Bazzi & Sudarno Sumarto & Asep Suryahadi, . "It's All in the Timing: Cash Transfers and Consumption Smoothing in a Developing Country," Journal Article, Publications Department.
  56. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
  57. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2021. "Synthetic Difference-in-Differences," American Economic Review, American Economic Association, vol. 111(12), pages 4088-4118, December.
  58. Deng, Zichen & Lindeboom, Maarten, 2021. "Early-Life Famine Exposure, Hunger Recall and Later-Life Health," IZA Discussion Papers 14487, Institute of Labor Economics (IZA).
  59. Kosuke Imai & Marc Ratkovic, 2015. "Robust Estimation of Inverse Probability Weights for Marginal Structural Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1013-1023, September.
  60. Samuel Bazzi & Sudarno Sumarto & Asep Suryahadi, "undated". "Intinya Penentuan Waktu: Respons Belanja dan Suplai Kerja Rumah Tangga terhadap Bantuan Langsung Tunai," Working Papers 3610, Publications Department.
  61. Chris Muris, 2020. "Efficient GMM Estimation with Incomplete Data," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 518-530, July.
  62. He, Xin & Mao, Xiaojun & Wang, Zhonglei, 2024. "Nonparametric augmented probability weighting with sparsity," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
  63. Bryan S. Graham & Cristine Campos de Xavier Pinto & Daniel Egel, 2016. "Efficient Estimation of Data Combination Models by the Method of Auxiliary-to-Study Tilting (AST)," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 288-301, April.
  64. Denisova-Schmidt, Elena & Huber, Martin & Prytula, Yaroslav, 2015. "An experimental evaluation of an anti-corruption intervention among Ukrainian university students," FSES Working Papers 462, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
  65. Martin Huber & Michael Lechner & Andreas Steinmayr, 2015. "Radius matching on the propensity score with bias adjustment: tuning parameters and finite sample behaviour," Empirical Economics, Springer, vol. 49(1), pages 1-31, August.
  66. Rothe, Christoph & Firpo, Sergio Pinheiro, 2013. "Semiparametric estimation and inference using doubly robust moment conditions," Textos para discussão 330, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
  67. Denis Heng Yan Leung & Ken Yamada & Biao Zhang, 2015. "Enriching Surveys with Supplementary Data and its Application to Studying Wage Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 155-179, March.
  68. Bryan S. Graham & Guido Imbens & Geert Ridder, 2016. "Identification and efficiency bounds for the average match function under conditionally exogenous matching," CeMMAP working papers 10/16, Institute for Fiscal Studies.
  69. Marianne BLÉHAUT & Xavier D'HAULTFOEUILLE & Jérémy L'HOUR & Alexandre B. TSYBAKOV, 2020. "An alternative to synthetic control for models with many covariates under sparsity," Working Papers 2020-17, Center for Research in Economics and Statistics.
  70. Yukitoshi Matsushita & Taisuke Otsu & Keisuke Takahata, 2022. "Estimating density ratio of marginals to joint: Applications to causal inference," STICERD - Econometrics Paper Series 619, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  71. Hugo Bodory & Lorenzo Camponovo & Martin Huber & Michael Lechner, 2020. "The Finite Sample Performance of Inference Methods for Propensity Score Matching and Weighting Estimators," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 183-200, January.
  72. Yang Ning & Sida Peng & Jing Tao, 2020. "Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data," Papers 2009.03151, arXiv.org.
  73. Dmitry Arkhangelsky & David Hirshberg, 2023. "Large-Sample Properties of the Synthetic Control Method under Selection on Unobservables," Papers 2311.13575, arXiv.org, revised Dec 2023.
  74. Karun Adusumilli & Taisuke Otsu & Chen Qiu, 2020. "Reweighted nonparametric likelihood inference for linear functionals," STICERD - Econometrics Paper Series 614, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  75. Adusumilli, Karun & Otsu, Taisuke & Qiu, Chen, 2023. "Reweighted nonparametric likelihood inference for linear functionals," LSE Research Online Documents on Economics 120198, London School of Economics and Political Science, LSE Library.
  76. Susan Athey & Raj Chetty & Guido Imbens & Hyunseung Kang, 2016. "Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index," Papers 1603.09326, arXiv.org, revised Aug 2024.
  77. Nikolay Doudchenko & Guido W. Imbens, 2016. "Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis," NBER Working Papers 22791, National Bureau of Economic Research, Inc.
  78. Karun Adusumilli & Taisuke Otsu, 2018. "Likelihood ratio inference for missing data models," STICERD - Econometrics Paper Series 599, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  79. Bazzi, Samuel & Sumarto, Sudarno & Suryahadi, Asep, 2015. "It's all in the timing: Cash transfers and consumption smoothing in a developing country," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 267-288.
  80. Phillip Heiler, 2020. "Efficient Covariate Balancing for the Local Average Treatment Effect," Papers 2007.04346, arXiv.org.
  81. Cousineau, Martin & Verter, Vedat & Murphy, Susan A. & Pineau, Joelle, 2023. "Estimating causal effects with optimization-based methods: A review and empirical comparison," European Journal of Operational Research, Elsevier, vol. 304(2), pages 367-380.
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