The Proximal Surrogate Index: Long-Term Treatment Effects under Unobserved Confounding
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- Peter Z. Schochet & John Burghardt & Steven Glazerman, 2001. "National Job Corps Study: The Impacts of Job Corps on Participants' Employment and Related Outcomes," Mathematica Policy Research Reports db6c4204b8e1408bb0c6289ec, Mathematica Policy Research.
- Constantine E. Frangakis & Donald B. Rubin, 2002. "Principal Stratification in Causal Inference," Biometrics, The International Biometric Society, vol. 58(1), pages 21-29, March.
- Chen, Jiafeng & Ritzwoller, David M., 2023. "Semiparametric estimation of long-term treatment effects," Journal of Econometrics, Elsevier, vol. 237(2).
- Imbens, Guido W., 2014.
"Instrumental Variables: An Econometrician's Perspective,"
IZA Discussion Papers
8048, IZA Network @ LISER.
- Guido Imbens, 2014. "Instrumental Variables: An Econometrician's Perspective," NBER Working Papers 19983, National Bureau of Economic Research, Inc.
- Yifan Cui & Hongming Pu & Xu Shi & Wang Miao & Eric Tchetgen Tchetgen, 2024. "Semiparametric Proximal Causal Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 119(546), pages 1348-1359, April.
- Imbens, Guido W & Angrist, Joshua D, 1994.
"Identification and Estimation of Local Average Treatment Effects,"
Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
- Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
- Tyler J. VanderWeele, 2013. "Surrogate Measures and Consistent Surrogates," Biometrics, The International Biometric Society, vol. 69(3), pages 561-565, September.
- Guido Imbens & Nathan Kallus & Xiaojie Mao, 2021. "Controlling for Unmeasured Confounding in Panel Data Using Minimal Bridge Functions: From Two-Way Fixed Effects to Factor Models," Papers 2108.03849, arXiv.org.
- Steffen L. Lauritzen, 2004. "Discussion on Causality," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(2), pages 189-193, June.
- Whitney K. Newey & James L. Powell, 2003. "Instrumental Variable Estimation of Nonparametric Models," Econometrica, Econometric Society, vol. 71(5), pages 1565-1578, September.
- Chunrong Ai & Xiaohong Chen, 2003. "Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions," Econometrica, Econometric Society, vol. 71(6), pages 1795-1843, November.
- Susan Athey & Raj Chetty & Guido Imbens, 2025. "The Experimental Selection Correction Estimator: Using Experiments to Remove Biases in Observational Estimates," NBER Working Papers 33817, National Bureau of Economic Research, Inc.
- Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, November.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018.
"Double/debiased machine learning for treatment and structural parameters,"
Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers CWP28/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers 28/17, Institute for Fiscal Studies.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2017. "Double/Debiased Machine Learning for Treatment and Structural Parameters," NBER Working Papers 23564, National Bureau of Economic Research, Inc.
- Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, January.
- Oliver Dukes & Ilya Shpitser & Eric J Tchetgen, 2023. "Proximal mediation analysis," Biometrika, Biometrika Trust, vol. 110(4), pages 973-987.
- Wang Miao & Zhi Geng & Eric J Tchetgen Tchetgen, 2018. "Identifying causal effects with proxy variables of an unmeasured confounder," Biometrika, Biometrika Trust, vol. 105(4), pages 987-993.
- An, Yonghong & Hu, Yingyao, 2012.
"Well-posedness of measurement error models for self-reported data,"
Journal of Econometrics, Elsevier, vol. 168(2), pages 259-269.
- Yonghong An & Yingyao Hu, 2009. "Well-posedness of measurement error models for self-reported data," CeMMAP working papers CWP35/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yonghong An & Yingyao Hu, 2009. "Well-Posedness of Measurement Error Models for Self-Reported Data," Economics Working Paper Archive 556, The Johns Hopkins University,Department of Economics.
- Marshall M. Joffe & Tom Greene, 2009. "Related Causal Frameworks for Surrogate Outcomes," Biometrics, The International Biometric Society, vol. 65(2), pages 530-538, June.
- Heckman, James & Pinto, Rodrigo, 2015.
"Causal Analysis After Haavelmo,"
Econometric Theory, Cambridge University Press, vol. 31(1), pages 115-151, February.
- James J. Heckman & Rodrigo Pinto, 2013. "Causal Analysis after Haavelmo," NBER Working Papers 19453, National Bureau of Economic Research, Inc.
- James J. Heckman & Rodrigo Pinto, 2013. "Causal Analysis after Haavelmo," Working Papers 2013-008, Human Capital and Economic Opportunity Working Group.
- Heckman, James J. & Pinto, Rodrigo, 2013. "Causal Analysis after Haavelmo," IZA Discussion Papers 7628, IZA Network @ LISER.
- Wang Miao & Xu Shi & Yilin Li & Eric J. Tchetgen Tchetgen, 2024. "A confounding bridge approach for double negative control inference on causal effects," Statistical Theory and Related Fields, Taylor & Francis Journals, vol. 8(4), pages 262-273, October.
- Zhengling Qi & Rui Miao & Xiaoke Zhang, 2024. "Proximal Learning for Individualized Treatment Regimes Under Unmeasured Confounding," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 119(546), pages 915-928, April.
- Amiremad Ghassami & Alan Yang & Ilya Shpitser & Eric Tchetgen Tchetgen, 2025. "Causal inference with hidden mediators," Biometrika, Biometrika Trust, vol. 112(1), pages 5633-5751.
- repec:mpr:mprres:2951 is not listed on IDEAS
- Jiafeng Chen & David M. Ritzwoller, 2021. "Semiparametric Estimation of Long-Term Treatment Effects," Papers 2107.14405, arXiv.org, revised Aug 2023.
- Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
- Hua Chen & Zhi Geng & Jinzhu Jia, 2007. "Criteria for surrogate end points," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 919-932, November.
- Ben Deaner, 2018. "Proxy Controls and Panel Data," Papers 1810.00283, arXiv.org, revised Nov 2023.
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This paper has been announced in the following NEP Reports:- NEP-ECM-2026-02-09 (Econometrics)
- NEP-EXP-2026-02-09 (Experimental Economics)
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