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High-dimensional instrumental variables regression and confidence sets
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Cited by:
- 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 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 & 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 & Christian Hansen & Martin Spindler, 2015.
"Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments,"
American Economic Review, American Economic Association, vol. 105(5), pages 486-490, May.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments," Papers 1501.03185, arXiv.org.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers 02/15, Institute for Fiscal Studies.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers CWP02/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Mathieu Rosenbaum & Alexandre B. Tsybakov, 2017. "Linear and conic programming estimators in high dimensional errors-in-variables models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(3), pages 939-956, June.
- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018.
"High-dimensional econometrics and regularized GMM,"
CeMMAP working papers
CWP35/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
- 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.
- Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
- Christoph Breunig & Enno Mammen & Anna Simoni, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Post-Print hal-03089879, HAL.
- Aman Ullah & Huansha Wang, 2013. "Parametric and Nonparametric Frequentist Model Selection and Model Averaging," Econometrics, MDPI, vol. 1(2), pages 1-23, September.
- Alexandre Belloni & Victor Chernozhukov & Abhishek Kaul, 2017.
"Confidence bands for coefficients in high dimensional linear models with error-in-variables,"
CeMMAP working papers
CWP22/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Abhishek Kaul, 2017. "Confidence bands for coefficients in high dimensional linear models with error-in-variables," CeMMAP working papers 22/17, Institute for Fiscal Studies.
- A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012.
"Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain,"
Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
- Alexandre Belloni & D. Chen & Victor Chernozhukov & Christian Hansen, 2010. "Sparse models and methods for optimal instruments with an application to eminent domain," CeMMAP working papers CWP31/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Daniel Chen & Victor Chernozhukov & Christian Hansen, 2010. "Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain," Papers 1010.4345, arXiv.org, revised Apr 2015.
- Achim Ahrens & Arnab Bhattacharjee, 2015. "Two-Step Lasso Estimation of the Spatial Weights Matrix," Econometrics, MDPI, vol. 3(1), pages 1-28, March.
- Zhu, Ying, 2018. "Sparse linear models and l1-regularized 2SLS with high-dimensional endogenous regressors and instruments," Journal of Econometrics, Elsevier, vol. 202(2), pages 196-213.
- Hansen, Christian & Liao, Yuan, 2019.
"The Factor-Lasso And K-Step Bootstrap Approach For Inference In High-Dimensional Economic Applications,"
Econometric Theory, Cambridge University Press, vol. 35(3), pages 465-509, June.
- Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Departmental Working Papers 201610, Rutgers University, Department of Economics.
- Hansen, Christian & Liao, Yuan, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," MPRA Paper 75313, University Library of Munich, Germany.
- Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Papers 1611.09420, arXiv.org, revised Dec 2016.
- Eric Gautier & Alexandre Tsybakov, 2013.
"Pivotal estimation in high-dimensional regression via linear programming,"
Working Papers
hal-00805556, HAL.
- Eric Gautier & Alexandre Tsybakov, 2013. "Pivotal estimation in high-dimensional regression via linear programming," Papers 1303.7092, arXiv.org, revised Apr 2013.
- Eric Gautier & Alexandre B, Tsybakov, 2013. "Pivotal Estimation in High-Dimensional Regression via Linear Programming," Working Papers 2013-40, Center for Research in Economics and Statistics.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011.
"Inference for High-Dimensional Sparse Econometric Models,"
Papers
1201.0220, arXiv.org.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Inference for high-dimensional sparse econometric models," CeMMAP working papers CWP41/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Eliana Barrenho & Eric Gautier & Marisa Miraldo & Carol Propper & Christiern Rose, 2020.
"Innovation Diffusion and Physician Networks: Keyhole Surgery for Cancer in the English NHS,"
Discussion Papers Series
638, School of Economics, University of Queensland, Australia.
- Propper, Carol & Barrenho, Eliana & Gautier, Eric & Miraldo, Marisa & Rose, Christiern, 2020. "Innovation Diffusion and Physician Networks: Keyhole Surgery for Cancer in the English NHS," CEPR Discussion Papers 15515, C.E.P.R. Discussion Papers.
- Ã ureo de Paula & Imran Rasul & Pedro Souza, 2018.
"Recovering Social Networks from Panel Data: Identification, Simulations and an Application,"
Working Papers
2018-013, Human Capital and Economic Opportunity Working Group.
- Áureo de Paula & Imran Rasul & Pedro CL Souza, 2018. "Recovering social networks from panel data: identification, simulations and an application," CeMMAP working papers CWP58/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Áureo de Paula & Imran Rasul & Pedro CL Souza, 2018. "Recovering social networks from panel data: identification, simulations and an application," CeMMAP working papers CWP17/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Aureo de Paula & Imran Rasul & Pedro CL Souza, 2018. "Recovering social networks from panel data: Identification, simulations and an application," Documentos de Trabajo 16173, The Latin American and Caribbean Economic Association (LACEA).
- Áureo de Paula, 2015.
"Econometrics of network models,"
CeMMAP working papers
CWP52/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Áureo de Paula, 2016. "Econometrics of network models," CeMMAP working papers 06/16, Institute for Fiscal Studies.
- Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers 52/15, Institute for Fiscal Studies.
- Áureo de Paula, 2016. "Econometrics of network models," CeMMAP working papers CWP06/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Lie Wang, 2013.
"Pivotal estimation via square-root lasso in nonparametric regression,"
CeMMAP working papers
62/13, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Lie Wang, 2013. "Pivotal estimation via square-root lasso in nonparametric regression," CeMMAP working papers CWP62/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Mehmet Caner & Xu Han & Yoonseok Lee, 2018.
"Adaptive Elastic Net GMM Estimation With Many Invalid Moment Conditions: Simultaneous Model and Moment Selection,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 24-46, January.
- Yoonseok Lee & Mehmet Caner & Xu Han, 2015. "Adaptive Elastic Net GMM Estimation with Many Invalid Moment Conditions: Simultaneous Model and Moment Selection," Center for Policy Research Working Papers 177, Center for Policy Research, Maxwell School, Syracuse University.
- 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.
- Michal Kolesár & Raj Chetty & John Friedman & Edward Glaeser & Guido W. Imbens, 2015.
"Identification and Inference With Many Invalid Instruments,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 474-484, October.
- Michal Kolesár & Raj Chetty & John N. Friedman & Edward L. Glaeser & Guido W. Imbens, 2011. "Identification and Inference with Many Invalid Instruments," NBER Working Papers 17519, National Bureau of Economic Research, Inc.
- Kolesar, Michal & Chetty, Raj & Friedman, John & Glaeser, Edward Ludwig & Imbens, Guido, 2015. "Identification and Inference With Many Invalid Instruments," Scholarly Articles 27769098, Harvard University Department of Economics.
- Barrenho, E.; & Miraldo, M.; & Propper, C; & Rose, C.;, 2019. "Peer and network effects in medical innovation: the case of laparoscopic surgery in the English NHS," Health, Econometrics and Data Group (HEDG) Working Papers 19/10, HEDG, c/o Department of Economics, University of York.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014.
"High-Dimensional Methods and Inference on Structural and Treatment Effects,"
Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers 59/13, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Chang, Jinyuan & Chen, Cheng & Qiao, Xinghao & Yao, Qiwei, 2023. "An autocovariance-based learning framework for high-dimensional functional time series," LSE Research Online Documents on Economics 117910, London School of Economics and Political Science, LSE Library.
- 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.
- Cheng, Xu & Liao, Zhipeng, 2015. "Select the valid and relevant moments: An information-based LASSO for GMM with many moments," Journal of Econometrics, Elsevier, vol. 186(2), pages 443-464.
- Zhu, Ying, 2013. "Sparse Linear Models and Two-Stage Estimation in High-Dimensional Settings with Possibly Many Endogenous Regressors," MPRA Paper 49846, University Library of Munich, Germany.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011.
"Inference on Treatment Effects After Selection Amongst High-Dimensional Controls,"
Papers
1201.0224, arXiv.org, revised May 2012.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2012. "Inference on treatment effects after selection amongst high-dimensional controls," CeMMAP working papers CWP10/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "Inference on treatment effects after selection amongst high-dimensional controls," CeMMAP working papers 26/13, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2012. "Inference on treatment effects after selection amongst high-dimensional controls," CeMMAP working papers 10/12, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "Inference on treatment effects after selection amongst high-dimensional controls," CeMMAP working papers CWP26/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Nishanth Dikkala & Greg Lewis & Lester Mackey & Vasilis Syrgkanis, 2020. "Minimax Estimation of Conditional Moment Models," Papers 2006.07201, arXiv.org.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015.
"Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach,"
Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Papers 1501.03430, arXiv.org, revised Aug 2015.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers 36/16, Institute for Fiscal Studies.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Qinqin Hu & Lu Lin, 2022. "Feature Screening in High Dimensional Regression with Endogenous Covariates," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 949-969, October.
- 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.
- Nicolas Apfel, 2019. "Relaxing the Exclusion Restriction in Shift-Share Instrumental Variable Estimation," Papers 1907.00222, arXiv.org, revised Jul 2022.
- Alexandre Belloni & Mathieu Rosenbaum & Alexandre Tsybakov, 2016. "An {l1, l2, l-infinity} Regularization Approach to High-Dimensional Errors-in-variables Models," Working Papers 2016-12, Center for Research in Economics and Statistics.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Nov 2024.
- Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2012.
"Central limit theorems and multiplier bootstrap when p is much larger than n,"
CeMMAP working papers
45/12, Institute for Fiscal Studies.
- Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2012. "Central limit theorems and multiplier bootstrap when p is much larger than n," CeMMAP working papers CWP45/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Hansen, Christian & Kozbur, Damian, 2014. "Instrumental variables estimation with many weak instruments using regularized JIVE," Journal of Econometrics, Elsevier, vol. 182(2), pages 290-308.
- Chatterjee, A. & Gupta, S. & Lahiri, S.N., 2015. "On the residual empirical process based on the ALASSO in high dimensions and its functional oracle property," Journal of Econometrics, Elsevier, vol. 186(2), pages 317-324.
- Fan, Jianqing & Liao, Yuan, 2012. "Endogeneity in ultrahigh dimension," MPRA Paper 38698, University Library of Munich, Germany.
- Gold, David & Lederer, Johannes & Tao, Jing, 2020. "Inference for high-dimensional instrumental variables regression," Journal of Econometrics, Elsevier, vol. 217(1), pages 79-111.
- Martin Emil Jakobsen & Jonas Peters, 2022. "Distributional robustness of K-class estimators and the PULSE [The colonial origins of comparative development: An empirical investigation]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 404-432.
- repec:spo:wpmain:info:hdl:2441/1jgbspo1909q48svne93o55rca is not listed on IDEAS
- Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
- Alexandre Belloni & Mathieu Rosenbaum & Alexandre B. Tsybakov, 2014. "Linear and Conic Programming Estimators in High-Dimensional Errors-in-variables Models," Working Papers 2014-34, Center for Research in Economics and Statistics.
- Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Geonwoo Kim & Suyong Song, 2024. "Double/Debiased CoCoLASSO of Treatment Effects with Mismeasured High-Dimensional Control Variables," Papers 2408.14671, arXiv.org.
- Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
- Kolesár, Michal, 2018. "Minimum distance approach to inference with many instruments," Journal of Econometrics, Elsevier, vol. 204(1), pages 86-100.
- repec:hal:spmain:info:hdl:2441/1jgbspo1909q48svne93o55rca is not listed on IDEAS