Yinchu Zhu
Citations
Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.Blog mentions
As found by EconAcademics.org, the blog aggregator for Economics research:- Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2019.
"Distributional conformal prediction,"
Papers
1909.07889, arXiv.org, revised Aug 2021.
- Chernozhukov, Victor & Wüthrich, Kaspar & Zhu, Yinchu, 2021. "Distributional conformal prediction," University of California at San Diego, Economics Working Paper Series qt2zs6m5p5, Department of Economics, UC San Diego.
Mentioned in:
- Interval Prediction
by Francis Diebold in No Hesitations on 2019-10-12 19:16:00
Working papers
- Yinchu Zhu, 2019.
"How well can we learn large factor models without assuming strong factors?,"
Papers
1910.10382, arXiv.org, revised Nov 2019.
Cited by:
- Timothy B. Armstrong & Martin Weidner & Andrei Zeleneev, 2024. "Robust estimation and inference in panels with interactive fixed effects," CeMMAP working papers 28/24, Institute for Fiscal Studies.
- Jelena Bradic & Stefan Wager & Yinchu Zhu, 2019.
"Sparsity Double Robust Inference of Average Treatment Effects,"
Papers
1905.00744, arXiv.org.
Cited by:
- Jelena Bradic & Weijie Ji & Yuqian Zhang, 2021. "High-dimensional Inference for Dynamic Treatment Effects," Papers 2110.04924, arXiv.org, revised May 2023.
- Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
- Kuanhao Jiang & Rajarshi Mukherjee & Subhabrata Sen & Pragya Sur, 2022. "A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-Fit Covariance and Beyond," Papers 2205.10198, arXiv.org, revised Oct 2022.
- Jiang, Liang & Phillips, Peter C.B. & Tao, Yubo & Zhang, Yichong, 2023.
"Regression-adjusted estimation of quantile treatment effects under covariate-adaptive randomizations,"
Journal of Econometrics, Elsevier, vol. 234(2), pages 758-776.
- Liang Jiang & Xiaobin Liu & Peter C.B. Phillips & Yichong Zhang, 2021. "Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations," Cowles Foundation Discussion Papers 2288, Cowles Foundation for Research in Economics, Yale University.
- Liang Jiang & Peter C. B. Phillips & Yubo Tao & Yichong Zhang, 2021. "Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations," Papers 2105.14752, arXiv.org, revised Sep 2022.
- Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "Automatic Debiased Machine Learning via Riesz Regression," Papers 2104.14737, arXiv.org, revised Mar 2024.
- Zhichao Jiang & Shu Yang & Peng Ding, 2022. "Multiply robust estimation of causal effects under principal ignorability," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1423-1445, September.
- Xinkun Nie & Guido Imbens & Stefan Wager, 2021. "Covariate Balancing Sensitivity Analysis for Extrapolating Randomized Trials across Locations," Papers 2112.04723, arXiv.org.
- Chen, Jiafeng & Ritzwoller, David M., 2023. "Semiparametric estimation of long-term treatment effects," Journal of Econometrics, Elsevier, vol. 237(2).
- Xu, Wenfu & Tan, Zhiqiang, 2024. "High-dimensional model-assisted inference for treatment effects with multi-valued treatments," Journal of Econometrics, Elsevier, vol. 244(1).
- Liu, Lin & Mukherjee, Rajarshi & Robins, James M., 2024. "Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators," Journal of Econometrics, Elsevier, vol. 240(2).
- Harold D Chiang & Yukitoshi Matsushita & Taisuke Otsu, 2023. "Regression Adjustment, Cross-Fitting, and Randomized Experiments with Many Controls," Papers 2302.00469, arXiv.org, revised May 2025.
- Yuqian Zhang & Weijie Ji & Jelena Bradic, 2021. "Dynamic treatment effects: high-dimensional inference under model misspecification," Papers 2111.06818, arXiv.org, revised Jan 2025.
- Harold D Chiang & Yukitoshi Matsushita & Taisuke Otsu, 2023. "Regression adjustment in randomized controlled trials with many covariates," STICERD - Econometrics Paper Series 627, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Timmermann, Allan & Qu, Ritong & Zhu, Yinchu, 2019.
"Do Any Economists Have Superior Forecasting Skills?,"
CEPR Discussion Papers
14112, C.E.P.R. Discussion Papers.
Cited by:
- Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2020.
"Forecasting Skills in Experimental Markets: Illusion or Reality?,"
Working Papers
20-27, Chapman University, Economic Science Institute.
- Brice Corgnet & Cary Deck & Mark Desantis & David Porter, 2022. "Forecasting Skills in Experimental Market : Illusion or Reality?," Post-Print hal-04325544, HAL.
- Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2022. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Management Science, INFORMS, vol. 68(7), pages 5216-5232, July.
- Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2020. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Working Papers 2020, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
- Brice Corgnet & Cary Deck & Mark Desantis & David Porter, 2020. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Working Papers halshs-02893291, HAL.
- Qu, Ritong & Timmermann, Allan & Zhu, Yinchu, 2024. "Comparing forecasting performance with panel data," International Journal of Forecasting, Elsevier, vol. 40(3), pages 918-941.
- Qu, Ritong & Timmermann, Allan & Zhu, Yinchu, 2023. "Comparing forecasting performance in cross-sections," Journal of Econometrics, Elsevier, vol. 237(2).
- Tim Köhler & Jörg Döpke, 2023. "Will the last be the first? Ranking German macroeconomic forecasters based on different criteria," Empirical Economics, Springer, vol. 64(2), pages 797-832, February.
- Strunz, Franziska & Gödl, Maximilian, 2023. "An Evaluation of Professional Forecasts for the German Economy," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277707, Verein für Socialpolitik / German Economic Association.
- Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2020.
"Forecasting Skills in Experimental Markets: Illusion or Reality?,"
Working Papers
20-27, Chapman University, Economic Science Institute.
- Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu, 2019.
"Inference for heterogeneous effects using low-rank estimations,"
CeMMAP working papers
CWP31/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
Cited by:
- Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023.
"High-dimensional VARs with common factors,"
Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
- Ke Miao & Peter C.B. Phillips & Liangjun Su, 2020. "High-Dimensional VARs with Common Factors," Cowles Foundation Discussion Papers 2252, Cowles Foundation for Research in Economics, Yale University.
- Choi, Jungjun & Kwon, Hyukjun & Liao, Yuan, 2024. "Inference for low-rank completion without sample splitting with application to treatment effect estimation," Journal of Econometrics, Elsevier, vol. 240(1).
- Belloni, Alexandre & Chen, Mingli & Madrid Padilla, Oscar Hernan & Wang, Zixuan (Kevin), 2019.
"High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing,"
The Warwick Economics Research Paper Series (TWERPS)
1230, University of Warwick, Department of Economics.
- Alexandre Belloni & Mingli Chen & Oscar Hernan Madrid Padilla & Zixuan & Wang, 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," Papers 1912.02151, arXiv.org, revised Aug 2022.
- Pu, Dan & Fang, Kuangnan & Lan, Wei & Yu, Jihai & Zhang, Qingzhao, 2024. "Multivariate spatiotemporal models with low rank coefficient matrix," Journal of Econometrics, Elsevier, vol. 246(1).
- Junlong Feng, 2019. "Regularized Quantile Regression with Interactive Fixed Effects," Papers 1911.00166, arXiv.org, revised Mar 2021.
- Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
- Jungjun Choi & Hyukjun Kwon & Yuan Liao, 2023. "Inference for Low-rank Completion without Sample Splitting with Application to Treatment Effect Estimation," Papers 2307.16370, arXiv.org.
- Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
- Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org.
- Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023.
"High-dimensional VARs with common factors,"
Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
- Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2019.
"Distributional conformal prediction,"
Papers
1909.07889, arXiv.org, revised Aug 2021.
- Chernozhukov, Victor & Wüthrich, Kaspar & Zhu, Yinchu, 2021. "Distributional conformal prediction," University of California at San Diego, Economics Working Paper Series qt2zs6m5p5, Department of Economics, UC San Diego.
Cited by:
- Jingsen Kong & Yiming Liu & Guangren Yang & Wang Zhou, 2025. "Conformal prediction for robust deep nonparametric regression," Statistical Papers, Springer, vol. 66(1), pages 1-36, January.
- Leying Guan, 2023. "Localized conformal prediction: a generalized inference framework for conformal prediction," Biometrika, Biometrika Trust, vol. 110(1), pages 33-50.
- Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2019.
"Inference on average treatment effects in aggregate panel data settings,"
CeMMAP working papers
CWP32/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
Cited by:
- Masahiro Kato & Akari Ohda, 2023. "Asymptotically Unbiased Synthetic Control Methods by Density Matching," Papers 2307.11127, arXiv.org, revised Feb 2025.
- Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019.
"Synthetic Difference In Differences,"
NBER Working Papers
25532, National Bureau of Economic Research, Inc.
- Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019. "Synthetic Difference in Differences," Working Papers wp2019_1907, CEMFI.
- 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.
- Timmermann, Allan & Zhu, Yinchu, 2019.
"Comparing Forecasting Performance with Panel Data,"
CEPR Discussion Papers
13746, C.E.P.R. Discussion Papers.
Cited by:
- Coroneo, Laura & Iacone, Fabrizio & Paccagnini, Alessia & Santos Monteiro, Paulo, 2023.
"Testing the predictive accuracy of COVID-19 forecasts,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 606-622.
- Laura Coroneo & Fabrizio Iacone & Alessia Paccagnini & Paulo Santos Monteiro, 2020. "Testing the predictive accuracy of COVID-19 forecasts," Discussion Papers 20/10, Department of Economics, University of York.
- Laura Coroneo & Fabrizio Iacone & Alessia Paccagnini & Paulo Santos Monteiro, 2021. "Testing the predictive accuracy of COVID-19 forecasts," CAMA Working Papers 2021-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Nathan Goldstein & Ben‐Zion Zilberfarb, 2023. "The closer we get, the better we are?," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 364-376, April.
- María Paula Bonel & Daniel J. Aromí, 2021. "Assessing GDP forecasts from autoregressive models: the impact of model complexity and training dataset," Asociación Argentina de Economía Política: Working Papers 4440, Asociación Argentina de Economía Política.
- Tae-Hwy Lee & Tao Wang, 2023.
"Estimation and Testing of Forecast Rationality with Many Moments,"
Working Papers
202307, University of California at Riverside, Department of Economics.
- Tae-Hwy Lee & Tao Wang, 2023. "Estimation and Testing of Forecast Rationality with Many Moments," Papers 2309.09481, arXiv.org.
- Mücella Şahin & Turgut Ün, 2024. "Forecasting Performance Comparison With Panel Data Models: Environmental Kuznets Curve Analysis," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul Journal of Economics-Istanbul Iktisat Dergisi, vol. 0(40), pages 208-221, June.
- Oguzhan Akgun & Alain Pirotte & Giovanni Urga & Zhenlin Yang, 2020.
"Equal Predictive Ability Tests Based on Panel Data with Applications to OECD and IMF Forecasts,"
Papers
2003.02803, arXiv.org, revised Feb 2023.
- Akgun, Oguzhan & Pirotte, Alain & Urga, Giovanni & Yang, Zhenlin, 2024. "Equal predictive ability tests based on panel data with applications to OECD and IMF forecasts," International Journal of Forecasting, Elsevier, vol. 40(1), pages 202-228.
- Christophe BOUCHER & Wassim LE LANN & Stéphane MATTON & Sessi TOKPAVI, 2021. "Backtesting ESG Ratings," LEO Working Papers / DR LEO 2883, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
- Badi Baltagi & Long Liu, 2020.
"Forecasting with Unbalanced Panel Data,"
Center for Policy Research Working Papers
221, Center for Policy Research, Maxwell School, Syracuse University.
- Badi H. Baltagi & Long Liu, 2020. "Forecasting with unbalanced panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 709-724, August.
- Christophe Boucher & Wassim Le Lann & Stéphane Matton & Sessi Tokpavi, 2024. "Are ESG ratings informative to forecast idiosyncratic risk?," Working Papers hal-04140193, HAL.
- Tim Köhler & Jörg Döpke, 2023. "Will the last be the first? Ranking German macroeconomic forecasters based on different criteria," Empirical Economics, Springer, vol. 64(2), pages 797-832, February.
- Coroneo, Laura & Iacone, Fabrizio & Paccagnini, Alessia & Santos Monteiro, Paulo, 2023.
"Testing the predictive accuracy of COVID-19 forecasts,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 606-622.
- Yinchu Zhu, 2018.
"Learning non-smooth models: instrumental variable quantile regressions and related problems,"
Papers
1805.06855, arXiv.org, revised Sep 2019.
Cited by:
- Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020. "Bias correction for quantile regression estimators," Papers 2011.03073, arXiv.org, revised Feb 2025.
- Xin Liu, 2019.
"Averaging estimation for instrumental variables quantile regression,"
Papers
1910.04245, arXiv.org.
- Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Working Papers 1907, Department of Economics, University of Missouri.
- Xin Liu, 2024. "Averaging Estimation for Instrumental Variables Quantile Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(5), pages 1290-1312, October.
- Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2018.
"Debiasing and $t$-tests for synthetic control inference on average causal effects,"
Papers
1812.10820, arXiv.org, revised May 2025.
Cited by:
- Billy Ferguson & Brad Ross, 2020. "Assessing the Sensitivity of Synthetic Control Treatment Effect Estimates to Misspecification Error," Papers 2012.15367, arXiv.org, revised Feb 2021.
- Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
- Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
- 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.
- Li, Xingyu & Shen, Yan & Zhou, Qiankun, 2024.
"Confidence intervals of treatment effects in panel data models with interactive fixed effects,"
Journal of Econometrics, Elsevier, vol. 240(1).
- Xingyu Li & Yan Shen & Qiankun Zhou, 2022. "Confidence Intervals of Treatment Effects in Panel Data Models with Interactive Fixed Effects," Papers 2202.12078, arXiv.org.
- Bruno Ferman & Cristine Pinto, 2021.
"Synthetic controls with imperfect pretreatment fit,"
Quantitative Economics, Econometric Society, vol. 12(4), pages 1197-1221, November.
- Bruno Ferman & Cristine Pinto, 2019. "Synthetic Controls with Imperfect Pre-Treatment Fit," Papers 1911.08521, arXiv.org, revised Jan 2021.
- Erick Lahura & Rosario Sabrera, 2023. "The effect of infrastructure investment on tourism demand: a synthetic control approach for the case of Kuelap, Peru," Empirical Economics, Springer, vol. 65(1), pages 443-478, July.
- Nicolaj S{o}ndergaard Muhlbach & Mikkel Slot Nielsen, 2019. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," Papers 1909.03968, arXiv.org, revised Feb 2021.
- Fry, Joseph, 2024. "A method of moments approach to asymptotically unbiased Synthetic Controls," Journal of Econometrics, Elsevier, vol. 244(1).
- Anish Agarwal & Rahul Singh, 2021. "Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy," Papers 2107.02780, arXiv.org, revised Feb 2024.
- Jianfei Cao & Shirley Lu, 2019. "Synthetic Control Inference for Staggered Adoption: Estimating the Dynamic Effects of Board Gender Diversity Policies," Papers 1912.06320, arXiv.org.
- Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2018.
"Exact and robust conformal inference methods for predictive machine learning with dependent data,"
CeMMAP working papers
CWP16/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
Cited by:
- Fantazzini, Dean, 2024.
"Adaptive Conformal Inference for computing Market Risk Measures: an Analysis with Four Thousands Crypto-Assets,"
MPRA Paper
121214, University Library of Munich, Germany.
- Dean Fantazzini, 2024. "Adaptive Conformal Inference for Computing Market Risk Measures: An Analysis with Four Thousand Crypto-Assets," JRFM, MDPI, vol. 17(6), pages 1-44, June.
- Ajroldi, Niccolò & Diquigiovanni, Jacopo & Fontana, Matteo & Vantini, Simone, 2023. "Conformal prediction bands for two-dimensional functional time series," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
- Borgschulte, Mark & Vogler, Jacob, 2019.
"Did the ACA Medicaid Expansion Save Lives?,"
IZA Discussion Papers
12552, Institute of Labor Economics (IZA).
- Borgschulte, Mark & Vogler, Jacob, 2020. "Did the ACA Medicaid expansion save lives?," Journal of Health Economics, Elsevier, vol. 72(C).
- Federico A. Bugni & Jia Li & Qiyuan Li, 2023. "Permutation‐based tests for discontinuities in event studies," Quantitative Economics, Econometric Society, vol. 14(1), pages 37-70, January.
- Chernozhukov, Victor & Wüthrich, Kaspar & Zhu, Yinchu, 2021.
"Distributional conformal prediction,"
University of California at San Diego, Economics Working Paper Series
qt2zs6m5p5, Department of Economics, UC San Diego.
- Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2019. "Distributional conformal prediction," Papers 1909.07889, arXiv.org, revised Aug 2021.
- Viviano, Davide & Bradic, Jelena, 2023. "Synthetic Learner: Model-free inference on treatments over time," Journal of Econometrics, Elsevier, vol. 234(2), pages 691-713.
- Matteo Fontana & Gianluca Zeni & Simone Vantini, 2020. "Conformal Prediction: a Unified Review of Theory and New Challenges," Papers 2005.07972, arXiv.org, revised Jul 2022.
- Varun Gupta & Christopher Jung & Georgy Noarov & Mallesh M. Pai & Aaron Roth, 2021. "Online Multivalid Learning: Means, Moments, and Prediction Intervals," Papers 2101.01739, arXiv.org.
- Fantazzini, Dean, 2024.
"Adaptive Conformal Inference for computing Market Risk Measures: an Analysis with Four Thousands Crypto-Assets,"
MPRA Paper
121214, University Library of Munich, Germany.
- Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2017.
"An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls,"
Papers
1712.09089, arXiv.org, revised May 2021.
- Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2021. "An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1849-1864, October.
- Victor Chernozhukov & Kaspar Wüthrich & Yu Zhu, 2017. "An exact and robust conformal inference method for counterfactual and synthetic controls," CeMMAP working papers CWP62/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Victor Chernozhukov & Kaspar Wüthrich & Yu Zhu, 2017. "An exact and robust conformal inference method for counterfactual and synthetic controls," CeMMAP working papers 62/17, Institute for Fiscal Studies.
- Chernozhukov, Victor & Wüthrich, Kaspar & Zhu, Yinchu, 2021. "An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls," University of California at San Diego, Economics Working Paper Series qt90m9d66s, Department of Economics, UC San Diego.
Cited by:
- Masahiro Kato & Akari Ohda, 2023. "Asymptotically Unbiased Synthetic Control Methods by Density Matching," Papers 2307.11127, arXiv.org, revised Feb 2025.
- Lionel Fontagné & Francesca Micocci & Armando Rungi, 2025.
"The heterogeneous impact of the EU-Canada agreement with causal machine learning,"
Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers)
halshs-04913313, HAL.
- Lionel Fontagné & Francesca Micocci & Armando Rungi, 2025. "The heterogeneous impact of the EU-Canada agreement with causal machine learning," Working Papers halshs-04913313, HAL.
- Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2019.
"Synthetic Controls with Staggered Adoption,"
Papers
1912.03290, arXiv.org, revised Jan 2021.
- Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2021. "Synthetic Controls with Staggered Adoption," NBER Working Papers 28886, National Bureau of Economic Research, Inc.
- Eli Ben‐Michael & Avi Feller & Jesse Rothstein, 2022. "Synthetic controls with staggered adoption," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 351-381, April.
- Nuno Garoupa & Rok Spruk, 2024. "Populist Constitutional Backsliding and Judicial Independence: Evidence from Turkiye," Papers 2410.02439, arXiv.org.
- Billy Ferguson & Brad Ross, 2020. "Assessing the Sensitivity of Synthetic Control Treatment Effect Estimates to Misspecification Error," Papers 2012.15367, arXiv.org, revised Feb 2021.
- Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
- Yihong Xu & Quan Zhou, 2025. "Bayesian Synthetic Control with a Soft Simplex Constraint," Papers 2503.06454, arXiv.org.
- Ignacio Martinez & Jaume Vives-i-Bastida, 2022. "Bayesian and Frequentist Inference for Synthetic Controls," Papers 2206.01779, arXiv.org, revised Jul 2024.
- Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019.
"Synthetic Difference In Differences,"
NBER Working Papers
25532, National Bureau of Economic Research, Inc.
- Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019. "Synthetic Difference in Differences," Working Papers wp2019_1907, CEMFI.
- 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.
- Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
- Ferman, Bruno, 2017.
"Matching Estimators with Few Treated and Many Control Observations,"
MPRA Paper
78940, University Library of Munich, Germany.
- Bruno Ferman, 2019. "Matching Estimators with Few Treated and Many Control Observations," Papers 1909.05093, arXiv.org, revised Mar 2021.
- Ferman, Bruno, 2021. "Matching estimators with few treated and many control observations," Journal of Econometrics, Elsevier, vol. 225(2), pages 295-307.
- Joseph Fry, 2023. "A Method of Moments Approach to Asymptotically Unbiased Synthetic Controls," Papers 2312.01209, arXiv.org, revised Mar 2024.
- Alberto Abadie & Jinglong Zhao, 2021. "Synthetic Controls for Experimental Design," Papers 2108.02196, arXiv.org, revised Apr 2025.
- Lionel Fontagn'e & Francesca Micocci & Armando Rungi, 2024. "The heterogeneous impact of the EU-Canada agreement with causal machine learning," Papers 2407.07652, arXiv.org, revised Apr 2025.
- Dennis Shen & Peng Ding & Jasjeet Sekhon & Bin Yu, 2022. "Same Root Different Leaves: Time Series and Cross-Sectional Methods in Panel Data," Papers 2207.14481, arXiv.org, revised Oct 2022.
- Douglas Kiarelly Godoy de Araujo, 2024. "Synthetic controls with machine learning: application on the effect of labour deregulation on worker productivity in Brazil," BIS Working Papers 1181, Bank for International Settlements.
- Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2018.
"The Augmented Synthetic Control Method,"
Papers
1811.04170, arXiv.org, revised Jul 2020.
- 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.
- Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2021. "The Augmented Synthetic Control Method," NBER Working Papers 28885, National Bureau of Economic Research, Inc.
- Lucke, Bernd, 2022.
"Growth Effects of European Monetary Union: A Synthetic Control Approach,"
MPRA Paper
120662, University Library of Munich, Germany, revised 27 Mar 2024.
- Lucke, Bernd, 2022. "Growth Effects of European Monetary Union: A Synthetic Control Approach," MPRA Paper 115373, University Library of Munich, Germany.
- Bruno Ferman, 2021.
"On the Properties of the Synthetic Control Estimator with Many Periods and Many Controls,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1764-1772, October.
- Bruno Ferman, 2019. "On the Properties of the Synthetic Control Estimator with Many Periods and Many Controls," Papers 1906.06665, arXiv.org, revised May 2020.
- Robert Messerle & Jonas Schreyögg, 2024. "Country-level effects of diagnosis-related groups: evidence from Germany’s comprehensive reform of hospital payments," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(6), pages 1013-1030, August.
- Michael Funke & Kadri Männasoo & Helery Tasane, 2023. "Regional Economic Impacts of the Øresund Cross-Border Fixed Link: Cui Bono?," CESifo Working Paper Series 10557, CESifo.
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"American Treasure and the Decline of Spain,"
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"How new airport infrastructure promotes tourism: evidence from a synthetic control approach in German regions,"
Munich Reprints in Economics
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"The inclusive synthetic control method,"
Discussion Papers on Economics
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"Synthesizing Cash for Clunkers: Stabilizing the Car Market, Hurting the Environment,"
VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy
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"Synthetic controls with imperfect pretreatment fit,"
Quantitative Economics, Econometric Society, vol. 12(4), pages 1197-1221, November.
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- Yan Zhang & Zudi Lu, 2024. "A Time Series Synthetic Control Causal Evaluation of the UK’s Mini-Budget Policy on Stock Market," Mathematics, MDPI, vol. 12(20), pages 1-25, October.
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"Conditional cash lotteries increase COVID-19 vaccination rates,"
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- Jiafeng Chen, 2022. "Synthetic Control As Online Linear Regression," Papers 2202.08426, arXiv.org, revised Nov 2022.
- Giovanni Peri & Derek Rury & Justin C. Wiltshire, 2024.
"The Economic Impact of Migrants from Hurricane Maria,"
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- Erick Lahura & Rosario Sabrera, 2023. "The effect of infrastructure investment on tourism demand: a synthetic control approach for the case of Kuelap, Peru," Empirical Economics, Springer, vol. 65(1), pages 443-478, July.
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- Jason Poulos, 2019. "State-Building through Public Land Disposal? An Application of Matrix Completion for Counterfactual Prediction," Papers 1903.08028, arXiv.org, revised Dec 2023.
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"Imputation of Counterfactual Outcomes when the Errors are Predictable,"
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- Luis Alvarez & Bruno Ferman, 2023. "Extensions for Inference in Difference-in-Differences with Few Treated Clusters," Papers 2302.03131, arXiv.org.
- Isaiah Andrews & Drew Fudenberg & Lihua Lei & Annie Liang & Chaofeng Wu, 2022. "The Transfer Performance of Economic Models," Papers 2202.04796, arXiv.org, revised Mar 2025.
- Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2019. "Inference on average treatment effects in aggregate panel data settings," CeMMAP working papers CWP32/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Vivek F. Farias & Andrew A. Li & Tianyi Peng, 2021. "Learning Treatment Effects in Panels with General Intervention Patterns," Papers 2106.02780, arXiv.org, revised Mar 2023.
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- Melissa Dell, 2024. "Deep Learning for Economists," Papers 2407.15339, arXiv.org, revised Nov 2024.
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- Rong J. B. Zhu, 2023. "Synthetic Regressing Control Method," Papers 2306.02584, arXiv.org, revised Oct 2023.
- Hideki Shimada & Kenji Asano & Yu Nagai & Akito Ozawa, 2022. "Assessing the Impact of Offshore Wind Power Deployment on Fishery: A Synthetic Control Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(3), pages 791-829, November.
- David M. Ritzwoller & Joseph P. Romano & Azeem M. Shaikh, 2024. "Randomization Inference: Theory and Applications," Papers 2406.09521, arXiv.org, revised Feb 2025.
- Niklas Potrafke & Luisa Dörr & Klaus Gründler & Tuuli Tähtinen & Luisa Dörr, 2025. "Female Leaders and the Representation of Women in Government," CESifo Working Paper Series 11851, CESifo.
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- Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
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"Linear Hypothesis Testing in Dense High-Dimensional Linear Models,"
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- Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2019.
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- Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018. "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers 2018-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2018. "LASSO-driven inference in time and space," CeMMAP working papers CWP36/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Victor Chernozhukov & Wolfgang K. Hardle & Chen Huang & Weining Wang, 2018. "LASSO-Driven Inference in Time and Space," Papers 1806.05081, arXiv.org, revised May 2020.
- Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Jan 2025.
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"De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers,"
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- Jelena Bradic & Victor Chernozhukov & Whitney K. Newey & Yinchu Zhu, 2019. "Minimax Semiparametric Learning With Approximate Sparsity," Papers 1912.12213, arXiv.org, revised Aug 2022.
- Zemin Zheng & Jinchi Lv & Wei Lin, 2021. "Nonsparse Learning with Latent Variables," Operations Research, INFORMS, vol. 69(1), pages 346-359, January.
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"Comments on: High-dimensional simultaneous inference with the bootstrap,"
TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 720-728, December.
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