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Keisuke Hirano

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.

Working papers

  1. Keisuke Hirano & Jack R. Porter, 2023. "Asymptotic Representations for Sequential Decisions, Adaptive Experiments, and Batched Bandits," Papers 2302.03117, arXiv.org.

    Cited by:

    1. Masahiro Kato, 2023. "Worst-Case Optimal Multi-Armed Gaussian Best Arm Identification with a Fixed Budget," Papers 2310.19788, arXiv.org, revised Mar 2024.
    2. Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org.
    3. Karun Adusumilli, 2023. "Optimal tests following sequential experiments," Papers 2305.00403, arXiv.org, revised Jun 2023.

  2. Hahn, Jinyong & Hirano, Keisuke & Karlan, Dean S., 2009. "Adaptive Experimental Design Using the Propensity Score," Center Discussion Papers 47107, Yale University, Economic Growth Center.

    Cited by:

    1. Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
    2. Alan Andre Borges da Costa & Sergio Pinheiro Firpo, 2018. "An analysis of the distributive effects of public policies and their spillovers," Working Papers, Department of Economics 2018_06, University of São Paulo (FEA-USP).
    3. Debopam Bhattacharya & Pascaline Dupas, 2008. "Inferring Welfare Maximizing Treatment Assignment under Budget Constraints," NBER Working Papers 14447, National Bureau of Economic Research, Inc.
    4. Aufenanger, Tobias, 2017. "Machine learning to improve experimental design," FAU Discussion Papers in Economics 16/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2017.
    5. Castillo-Manzano, José I. & López-Valpuesta, Lourdes & Sánchez-Braza, Antonio, 2018. "When the mall is in the airport: Measuring the effect of the airport mall on passengers’ consumer behavior," Journal of Air Transport Management, Elsevier, vol. 72(C), pages 32-38.
    6. 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.
    7. Max Tabord-Meehan, 2018. "Stratification Trees for Adaptive Randomization in Randomized Controlled Trials," Papers 1806.05127, arXiv.org, revised Jul 2022.
    8. Masahiro Kato & Masaaki Imaizumi & Takuya Ishihara & Toru Kitagawa, 2023. "Asymptotically Optimal Fixed-Budget Best Arm Identification with Variance-Dependent Bounds," Papers 2302.02988, arXiv.org, revised Jul 2023.
    9. Liang Jiang & Xiaobin Liu & Peter C.B. Phillips & Yichong Zhang, 2020. "Bootstrap Inference for Quantile Treatment Effects in Randomized Experiments with Matched Pairs," Cowles Foundation Discussion Papers 2249, Cowles Foundation for Research in Economics, Yale University.
    10. Ahnaf Rafi, 2023. "Efficient Semiparametric Estimation of Average Treatment Effects Under Covariate Adaptive Randomization," Papers 2305.08340, arXiv.org.
    11. Yong Cai & Ahnaf Rafi, 2022. "On the Performance of the Neyman Allocation with Small Pilots," Papers 2206.04643, arXiv.org, revised Jun 2024.
    12. Timothy B. Armstrong & Shu Shen, 2013. "Inference on Optimal Treatment Assignments," Cowles Foundation Discussion Papers 1927, Cowles Foundation for Research in Economics, Yale University.
    13. Kyungchul Song, 2009. "Efficient Estimation of Average Treatment Effects under Treatment-Based Sampling," PIER Working Paper Archive 09-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    14. Dean Karlan & Daniel H. Wood, 2014. "The Effect of Effectiveness: Donor Response to Aid Effectiveness in a Direct Mail Fundraising Experiment," NBER Working Papers 20047, National Bureau of Economic Research, Inc.
    15. Yusuke Narita, 2018. "Toward an Ethical Experiment," Cowles Foundation Discussion Papers 2127, Cowles Foundation for Research in Economics, Yale University.
    16. Jinglong Zhao, 2024. "Experimental Design For Causal Inference Through An Optimization Lens," Papers 2408.09607, arXiv.org, revised Aug 2024.
    17. Masahiro Kato & Kenshi Abe & Kaito Ariu & Shota Yasui, 2020. "A Practical Guide of Off-Policy Evaluation for Bandit Problems," Papers 2010.12470, arXiv.org.
    18. Ravichandran Arun & Pashley Nicole E. & Libgober Brian & Dasgupta Tirthankar, 2024. "Optimal allocation of sample size for randomization-based inference from 2K factorial designs," Journal of Causal Inference, De Gruyter, vol. 12(1), pages 1-18, January.
    19. Yusuke Narita, 2018. "Experiment-as-Market: Incorporating Welfare into Randomized Controlled Trials," Cowles Foundation Discussion Papers 2127r, Cowles Foundation for Research in Economics, Yale University, revised May 2019.
    20. Jian, L. & Linton, O. B. & Tang, H. & Zhang, Y., 2023. "Improving Estimation Efficiency via Regression-Adjustment in Covariate-Adaptive Randomizations with Imperfect Compliance," Janeway Institute Working Papers 2315, Faculty of Economics, University of Cambridge.
    21. Yichong Zhang & Xin Zheng, 2020. "Quantile treatment effects and bootstrap inference under covariate‐adaptive randomization," Quantitative Economics, Econometric Society, vol. 11(3), pages 957-982, July.
    22. Fink, Günther & McConnell, Margaret & Vollmer, Sebastian, 2011. "Testing for Heterogeneous Treatment Effects in Experimental Data: False Discovery Risks and Correction Procedures," Hannover Economic Papers (HEP) dp-477, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    23. John A. List & Sally Sadoff & Mathis Wagner, 2010. "So you want to run an experiment, now what? Some Simple Rules of Thumb for Optimal Experimental Design," CeRP Working Papers 94, Center for Research on Pensions and Welfare Policies, Turin (Italy).
    24. Masahiro Kato, 2024. "Generalized Neyman Allocation for Locally Minimax Optimal Best-Arm Identification," Papers 2405.19317, arXiv.org, revised Dec 2024.
    25. Masahiro Kato, 2023. "Worst-Case Optimal Multi-Armed Gaussian Best Arm Identification with a Fixed Budget," Papers 2310.19788, arXiv.org, revised Mar 2024.
    26. Víctor Casero-Alonso & Jesús López-Fidalgo, 2015. "Experimental designs in triangular simultaneous equations models," Statistical Papers, Springer, vol. 56(2), pages 273-290, May.
    27. Masahiro Kato, 2023. "Locally Optimal Fixed-Budget Best Arm Identification in Two-Armed Gaussian Bandits with Unknown Variances," Papers 2312.12741, arXiv.org, revised Mar 2024.
    28. Aufenanger, Tobias, 2018. "Treatment allocation for linear models," FAU Discussion Papers in Economics 14/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2018.
    29. Masahiro Kato & Takuya Ishihara & Junya Honda & Yusuke Narita, 2020. "Efficient Adaptive Experimental Design for Average Treatment Effect Estimation," Papers 2002.05308, arXiv.org, revised Oct 2021.
    30. Masahiro Kato & Kaito Ariu, 2021. "The Role of Contextual Information in Best Arm Identification," Papers 2106.14077, arXiv.org, revised Feb 2024.
    31. Masahiro Kato & Shota Yasui & Kenichiro McAlinn, 2020. "The Adaptive Doubly Robust Estimator for Policy Evaluation in Adaptive Experiments and a Paradox Concerning Logging Policy," Papers 2010.03792, arXiv.org, revised Jun 2021.
    32. Masahiro Kato, 2020. "Confidence Interval for Off-Policy Evaluation from Dependent Samples via Bandit Algorithm: Approach from Standardized Martingales," Papers 2006.06982, arXiv.org.
    33. Masahiro Kato, 2021. "Adaptive Doubly Robust Estimator from Non-stationary Logging Policy under a Convergence of Average Probability," Papers 2102.08975, arXiv.org, revised Mar 2021.
    34. Ruicheng Ao & Hongyu Chen & David Simchi-Levi, 2024. "Prediction-Guided Active Experiments," Papers 2411.12036, arXiv.org, revised Nov 2024.
    35. Masahiro Kato & Masaaki Imaizumi & Takuya Ishihara & Toru Kitagawa, 2022. "Best Arm Identification with Contextual Information under a Small Gap," Papers 2209.07330, arXiv.org, revised Jan 2023.
    36. Michael Gechter & Keisuke Hirano & Jean Lee & Mahreen Mahmud & Orville Mondal & Jonathan Morduch & Saravana Ravindran & Abu S. Shonchoy, 2024. "Selecting Experimental Sites for External Validity," Papers 2405.13241, arXiv.org.
    37. Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org.
    38. Harrison H. Li & Art B. Owen, 2023. "Double machine learning and design in batch adaptive experiments," Papers 2309.15297, arXiv.org.
    39. Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2017. "Optimal Design of Experiments in the Presence of Interference*, Second Version," PIER Working Paper Archive 16-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 30 Nov 2017.
    40. Masahiro Kato & Akihiro Oga & Wataru Komatsubara & Ryo Inokuchi, 2024. "Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choices," Papers 2403.03589, arXiv.org, revised Jun 2024.
    41. Cai, Yong & Rafi, Ahnaf, 2024. "On the performance of the Neyman Allocation with small pilots," Journal of Econometrics, Elsevier, vol. 242(1).
    42. Max Cytrynbaum, 2021. "Optimal Stratification of Survey Experiments," Papers 2111.08157, arXiv.org, revised Aug 2023.
    43. Masahiro Kato & Yusuke Kaneko, 2020. "Off-Policy Evaluation of Bandit Algorithm from Dependent Samples under Batch Update Policy," Papers 2010.13554, arXiv.org.

  3. Hirano, Keisuke & Porter, Jack, 2009. "Impossibility Results for Nondifferentiable Functionals," MPRA Paper 15990, University Library of Munich, Germany.

    Cited by:

    1. Hiroaki Kaido, 2014. "Asymptotically efficient estimation of weighted average derivatives with an interval censored variable," CeMMAP working papers 03/14, Institute for Fiscal Studies.
    2. Lorenzo Almada & Ian McCarthy & Rusty Tchernis, 2016. "What Can We Learn about the Effects of Food Stamps on Obesity in the Presence of Misreporting?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 997-1017.
    3. Isaiah Andrews & Timothy B. Armstrong, 2015. "Unbiased Instrumental Variables Estimation under Known First-Stage Sign," Cowles Foundation Discussion Papers 1984R, Cowles Foundation for Research in Economics, Yale University, revised Mar 2015.
    4. Lafférs, Lukáš & Mellace, Giovanni, 2020. "Identification of the average treatment effect when SUTVA is violated," Discussion Papers on Economics 3/2020, University of Southern Denmark, Department of Economics.
    5. Jiannan Lu & Peng Ding & Tirthankar Dasgupta, 2018. "Treatment Effects on Ordinal Outcomes: Causal Estimands and Sharp Bounds," Journal of Educational and Behavioral Statistics, , vol. 43(5), pages 540-567, October.
    6. Germinario, Giuseppe & Amin, Vikesh & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2022. "What can we learn about the effect of mental health on labor market outcomes under weak assumptions? Evidence from the NLSY79," Labour Economics, Elsevier, vol. 79(C).
    7. Amin, Vikesh & Behrman, Jere R. & Fletcher, Jason M. & Flores, Carlos A. & Flores-Lagunes, Alfonso & Kohler, Hans-Peter, 2022. "Does Schooling Improve Cognitive Abilities at Older Ages? Causal Evidence from Nonparametric Bounds," GLO Discussion Paper Series 1114, Global Labor Organization (GLO).
    8. Sjölander Arvid, 2020. "A note on a sensitivity analysis for unmeasured confounding, and the related E-value," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 229-248, January.
    9. Gyungbae Park, 2024. "Debiased Machine Learning when Nuisance Parameters Appear in Indicator Functions," Papers 2403.15934, arXiv.org.
    10. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2017. "Confidence intervals for projections of partially identified parameters," CeMMAP working papers 49/17, Institute for Fiscal Studies.
    11. Lukáš Lafférs, 2019. "Bounding average treatment effects using linear programming," Empirical Economics, Springer, vol. 57(3), pages 727-767, September.
    12. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "Coverage Error Optimal Confidence Intervals for Local Polynomial Regression," Papers 1808.01398, arXiv.org, revised Jul 2021.
    13. Hongyi Jiang & Zhenting Sun & Shiyun Hu, 2023. "A Nonparametric Test of $m$th-degree Inverse Stochastic Dominance," Papers 2306.12271, arXiv.org, revised Jul 2023.
    14. Qihui Chen & Zheng Fang, 2019. "Inference on Functionals under First Order Degeneracy," Papers 1901.04861, arXiv.org.
    15. Ting Ye & Luke Keele & Raiden Hasegawa & Dylan S. Small, 2020. "A Negative Correlation Strategy for Bracketing in Difference-in-Differences," Papers 2006.02423, arXiv.org, revised Jun 2022.
    16. Gerard, François & Rokkanen, Miikka & Rothe, Christoph, 2016. "Identification and Inference in Regression Discontinuity Designs with a Manipulated Running Variable," CEPR Discussion Papers 11048, C.E.P.R. Discussion Papers.
    17. Lee, Y-Y. & Bhattacharya, D., 2018. "Applied Welfare Analysis for Discrete Choice with Interval-data on Income," Cambridge Working Papers in Economics 1882, Faculty of Economics, University of Cambridge.
    18. Victor Chernozhukov & Christian Hansen & Yuan Liao, 2015. "A lava attack on the recovery of sums of dense and sparse signals," CeMMAP working papers 05/15, Institute for Fiscal Studies.
    19. Juan Carlos Escanciano, 2020. "Irregular Identification of Structural Models with Nonparametric Unobserved Heterogeneity," Papers 2005.08611, arXiv.org.
    20. Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2017. "Going beyond LATE: Bounding Average Treatment Effects of Job Corps Training," GLO Discussion Paper Series 93, Global Labor Organization (GLO).
    21. Jiannan Lu & Yunshu Zhang & Peng Ding, 2020. "Sharp bounds on the relative treatment effect for ordinal outcomes," Biometrics, The International Biometric Society, vol. 76(2), pages 664-669, June.
    22. Marcelo J. Moreira & Geert Ridder, 2020. "Efficiency Loss of Asymptotically Efficient Tests in an Instrumental Variables Regression," Papers 2008.13042, arXiv.org, revised Sep 2021.
    23. Wang, Xintong & Flores-Lagunes, Alfonso, 2020. "Conscription and Military Service: Do They Result in Future Violent and Non-Violent Incarcerations and Recidivism?," IZA Discussion Papers 14003, Institute of Labor Economics (IZA).
    24. Hiroaki Kaido & Yi Zhang, 2019. "Robust likelihood ratio tests for incomplete economic models," CeMMAP working papers CWP68/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    25. Kirill Ponomarev & Vira Semenova, 2024. "On the Lower Confidence Band for the Optimal Welfare," Papers 2410.07443, arXiv.org, revised Oct 2024.
    26. Bulat Gafarov, 2019. "Simple subvector inference on sharp identified set in affine models," Papers 1904.00111, arXiv.org, revised Jul 2024.
    27. Song, Kyungchul, 2014. "Local asymptotic minimax estimation of nonregular parameters with translation-scale equivariant maps," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 136-158.
    28. Gerard, François & Rothe, Christoph & Rokkanen, Miikka, 2016. "Bounds on Treatment Effects in Regression Discontinuity Designs under Manipulation of the Running Variable, with an Application," CEPR Discussion Papers 11668, C.E.P.R. Discussion Papers.
    29. Riccardo D'Adamo, 2021. "Orthogonal Policy Learning Under Ambiguity," Papers 2111.10904, arXiv.org, revised Dec 2022.
    30. Donald W.K. Andrews, 2011. "Similar-on-the-Boundary Tests for Moment Inequalities Exist, But Have Poor Power," Cowles Foundation Discussion Papers 1815R, Cowles Foundation for Research in Economics, Yale University, revised Mar 2012.
    31. Ham, John C. & Woutersen, Tiemen, 2011. "Calculating Confidence Intervals for Continuous and Discontinuous Functions of Estimated Parameters," IZA Discussion Papers 5816, Institute of Labor Economics (IZA).
    32. Nathan Kallus & Xiaojie Mao & Angela Zhou, 2022. "Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination," Management Science, INFORMS, vol. 68(3), pages 1959-1981, March.
    33. Timothy B. Armstrong, 2014. "A Note on Minimax Testing and Confidence Intervals in Moment Inequality Models," Cowles Foundation Discussion Papers 1975, Cowles Foundation for Research in Economics, Yale University.
    34. Tetsuya Kaji, 2019. "Theory of Weak Identification in Semiparametric Models," Papers 1908.10478, arXiv.org, revised Aug 2020.
    35. Ying Huang & Eric Laber, 2016. "Personalized Evaluation of Biomarker Value: A Cost-Benefit Perspective," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 8(1), pages 43-65, June.
    36. Brent Kreider & John V. Pepper & Manan Roy, 2020. "Does The Women, Infants, And Children Program Improve Infant Health Outcomes?," Economic Inquiry, Western Economic Association International, vol. 58(4), pages 1731-1756, October.
    37. Daido Kido, 2023. "Locally Asymptotically Minimax Statistical Treatment Rules Under Partial Identification," Papers 2311.08958, arXiv.org.
    38. Toru Kitagawa & Jose Luis Montiel Olea & Jonathan Payne & Amilcar Velez, 2019. "Posterior distribution of nondifferentiable functions," CeMMAP working papers CWP17/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    39. Kyungchul Song, 2009. "Point Decisions for Interval-Identified Parameters," PIER Working Paper Archive 09-036, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    40. Sun, Zhenting, 2023. "Instrument validity for heterogeneous causal effects," Journal of Econometrics, Elsevier, vol. 237(2).
    41. Tuvaandorj, Purevdorj, 2020. "Regression discontinuity designs, white noise models, and minimax," Journal of Econometrics, Elsevier, vol. 218(2), pages 587-608.
    42. François Gerard & Miikka Rokkanen & Christoph Rothe, 2020. "Bounds on treatment effects in regression discontinuity designs with a manipulated running variable," Quantitative Economics, Econometric Society, vol. 11(3), pages 839-870, July.
    43. Phillip Heiler & Asbj{o}rn Kaufmann & Bezirgen Veliyev, 2024. "Treatment Evaluation at the Intensive and Extensive Margins," Papers 2412.11179, arXiv.org.
    44. Hiroaki Kaido & Jiaxuan Li & Marc Rysman, 2018. "Moment Inequalities in the Context of Simulated and Predicted Variables," Papers 1804.03674, arXiv.org.
    45. Amin, Vikesh & Flores, Carlos A. & Flores-Lagunes, Alfonso & Parisian, Daniel J., 2016. "The Effect of Degree Attainment on Arrests: Evidence from a Randomized Social Experiment," IZA Discussion Papers 9695, Institute of Labor Economics (IZA).
    46. Ganesh Karapakula, 2022. "An Axiomatic Framework for Cost-Benefit Analysis," Papers 2207.13033, arXiv.org.
    47. Hong, Han & Li, Jessie, 2018. "The numerical delta method," Journal of Econometrics, Elsevier, vol. 206(2), pages 379-394.
    48. Daido Kido, 2022. "Distributionally Robust Policy Learning with Wasserstein Distance," Papers 2205.04637, arXiv.org, revised Aug 2022.
    49. Chen, Qihui & Fang, Zheng, 2019. "Inference on functionals under first order degeneracy," Journal of Econometrics, Elsevier, vol. 210(2), pages 459-481.
    50. Millimet, Daniel L. & Roy, Manan, 2013. "Partial Identification of the Long-Run Causal Effect of Food Security on Child Health," IZA Discussion Papers 7457, Institute of Labor Economics (IZA).
    51. Fan Yang & Dylan S. Small, 2016. "Using post-outcome measurement information in censoring-by-death problems," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 299-318, January.

  4. Hirano, Keisuke & Porter, Jack, 2006. "Asymptotics for statistical treatment rules," MPRA Paper 1173, University Library of Munich, Germany.

    Cited by:

    1. Hiroaki Kaido, 2014. "Asymptotically efficient estimation of weighted average derivatives with an interval censored variable," CeMMAP working papers 03/14, Institute for Fiscal Studies.
    2. Karun Adusumilli, 2022. "How to sample and when to stop sampling: The generalized Wald problem and minimax policies," Papers 2210.15841, arXiv.org, revised Feb 2024.
    3. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Toru Kitagawa & Aleksey Tetenov, 2018. "Who Should Be Treated? Empirical Welfare Maximization Methods for Treatment Choice," Econometrica, Econometric Society, vol. 86(2), pages 591-616, March.
    5. Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999R, Cowles Foundation for Research in Economics, Yale University, revised Jun 2018.
    6. Cordier, J.; & Salvi, I.; & Steinbeck, V.; & Geissler, A.; & Vogel, J.;, 2023. "Is rapid recovery always the best recovery? - Developing a machine learning approach for optimal assignment rules under capacity constraints for knee replacement patients," Health, Econometrics and Data Group (HEDG) Working Papers 23/08, HEDG, c/o Department of Economics, University of York.
    7. Toru Kitagawa & Aleksey Tetenov, 2018. "Equality-minded treatment choice," CeMMAP working papers CWP71/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    9. Toru Kitagawa & Chris Muris, 2015. "Model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP46/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Stoye, Jörg, 2012. "Minimax regret treatment choice with covariates or with limited validity of experiments," Journal of Econometrics, Elsevier, vol. 166(1), pages 138-156.
    11. Tetenov, Aleksey, 2012. "Statistical treatment choice based on asymmetric minimax regret criteria," Journal of Econometrics, Elsevier, vol. 166(1), pages 157-165.
    12. Debopam Bhattacharya & Pascaline Dupas, 2008. "Inferring Welfare Maximizing Treatment Assignment under Budget Constraints," NBER Working Papers 14447, National Bureau of Economic Research, Inc.
    13. Charles F. Manski, 2021. "Probabilistic Prediction for Binary Treatment Choice: with Focus on Personalized Medicine," NBER Working Papers 29358, National Bureau of Economic Research, Inc.
    14. Alex Chin & Dean Eckles & Johan Ugander, 2022. "Evaluating Stochastic Seeding Strategies in Networks," Management Science, INFORMS, vol. 68(3), pages 1714-1736, March.
    15. Juliano Assunção & Robert McMillan & Joshua Murphy & Eduardo Souza-Rodrigues, 2019. "Optimal Environmental Targeting in the Amazon Rainforest," NBER Working Papers 25636, National Bureau of Economic Research, Inc.
    16. Xinkun Nie & Stefan Wager, 2017. "Quasi-Oracle Estimation of Heterogeneous Treatment Effects," Papers 1712.04912, arXiv.org, revised Aug 2020.
    17. Yan Liu, 2022. "Policy Learning under Endogeneity Using Instrumental Variables," Papers 2206.09883, arXiv.org, revised Mar 2024.
    18. Masahiro Kato & Masaaki Imaizumi & Takuya Ishihara & Toru Kitagawa, 2023. "Asymptotically Optimal Fixed-Budget Best Arm Identification with Variance-Dependent Bounds," Papers 2302.02988, arXiv.org, revised Jul 2023.
    19. Takanori Ida & Takunori Ishihara & Koichiro Ito & Daido Kido & Toru Kitagawa & Shosei Sakaguchi & Shusaku Sasaki, 2022. "Choosing Who Chooses: Selection-Driven Targeting in Energy Rebate Programs," NBER Working Papers 30469, National Bureau of Economic Research, Inc.
    20. Eric Mbakop & Max Tabord‐Meehan, 2021. "Model Selection for Treatment Choice: Penalized Welfare Maximization," Econometrica, Econometric Society, vol. 89(2), pages 825-848, March.
    21. Yuya Sasaki & Takuya Ura, 2020. "Welfare Analysis via Marginal Treatment Effects," Papers 2012.07624, arXiv.org.
    22. Isaiah Andrews & Toru Kitagawa & Adam McCloskey, 2018. "Inference on winners," CeMMAP working papers CWP31/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. Qingyuan Zhao & Dylan S. Small & Ashkan Ertefaie, 2022. "Selective inference for effect modification via the lasso," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 382-413, April.
    24. Debopam Bhattacharya & Pascaline Dupas & Shin Kanaya, 2013. "Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets," Economics Series Working Papers 646, University of Oxford, Department of Economics.
    25. Toru Kitagawa & Shosei Sakaguchi & Aleksey Tetenov, 2021. "Constrained Classification and Policy Learning," Papers 2106.12886, arXiv.org, revised Jul 2023.
    26. Anders Bredahl Kock & Martin Thyrsgaard, 2017. "Optimal sequential treatment allocation," Papers 1705.09952, arXiv.org, revised Aug 2018.
    27. Garbero, Alessandra & Sakos, Grayson & Cerulli, Giovanni, 2023. "Towards data-driven project design: Providing optimal treatment rules for development projects," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    28. Susan Athey & Raj Chetty & Guido Imbens, 2020. "Combining Experimental and Observational Data to Estimate Treatment Effects on Long Term Outcomes," Papers 2006.09676, arXiv.org.
    29. Toru Kitagawa & Aleksey Tetenov, 2015. "Who should be treated? Empirical welfare maximization methods for treatment choice," CeMMAP working papers 10/15, Institute for Fiscal Studies.
    30. Timothy B. Armstrong & Shu Shen, 2013. "Inference on Optimal Treatment Assignments," Cowles Foundation Discussion Papers 1927, Cowles Foundation for Research in Economics, Yale University.
    31. Sergio Firpo & Antonio F. Galvao & Martyna Kobus & Thomas Parker & Pedro Rosa-Dias, 2020. "Loss aversion and the welfare ranking of policy interventions," Papers 2004.08468, arXiv.org, revised Sep 2023.
    32. David M. Kaplan & Longhao Zhuo, 2018. "Frequentist size of Bayesian inequality tests," Working Papers 1802, Department of Economics, University of Missouri, revised 14 Jul 2019.
    33. Kohei Yata, 2021. "Optimal Decision Rules Under Partial Identification," Papers 2111.04926, arXiv.org, revised Aug 2023.
    34. Carlos Fern'andez-Lor'ia & Foster Provost & Jesse Anderton & Benjamin Carterette & Praveen Chandar, 2020. "A Comparison of Methods for Treatment Assignment with an Application to Playlist Generation," Papers 2004.11532, arXiv.org, revised Apr 2022.
    35. Karun Adusumilli & Friedrich Geiecke & Claudio Schilter, 2019. "Dynamically Optimal Treatment Allocation," Papers 1904.01047, arXiv.org, revised Nov 2024.
    36. Undral Byambadalai, 2022. "Identification and Inference for Welfare Gains without Unconfoundedness," Papers 2207.04314, arXiv.org.
    37. Karun Adusumilli, 2022. "Neyman allocation is minimax optimal for best arm identification with two arms," Papers 2204.05527, arXiv.org, revised Aug 2022.
    38. Abhijit V. Banerjee & Esther Duflo, 2008. "The Experimental Approach to Development Economics," NBER Working Papers 14467, National Bureau of Economic Research, Inc.
    39. Toru Kitagawa & Guanyi Wang, 2020. "Who Should Get Vaccinated? Individualized Allocation of Vaccines Over SIR Network," Papers 2012.04055, arXiv.org, revised Jul 2021.
    40. Charles F. Manski & Aleksey Tetenov, 2023. "Statistical Decision Theory Respecting Stochastic Dominance," Papers 2308.05171, arXiv.org.
    41. Takanori Ida & Takunori Ishihara & Koichiro Ito & Daido Kido & Toru Kitagawa & Shosei Sakaguchi & Shusaku Sasaki, 2021. "Paternalism, Autonomy, or Both? Experimental Evidence from Energy Saving Programs," Papers 2112.09850, arXiv.org.
    42. Toru Kitagawa & Sokbae Lee & Chen Qiu, 2022. "Treatment Choice with Nonlinear Regret," Papers 2205.08586, arXiv.org, revised Oct 2024.
    43. Takuya Ishihara & Daisuke Kurisu, 2022. "Shrinkage Methods for Treatment Choice," Papers 2210.17063, arXiv.org, revised Jun 2024.
    44. Carlos Fernández-Loría & Foster Provost & Jesse Anderton & Benjamin Carterette & Praveen Chandar, 2023. "A Comparison of Methods for Treatment Assignment with an Application to Playlist Generation," Information Systems Research, INFORMS, vol. 34(2), pages 786-803, June.
    45. Lai Xinglin, 2021. "Modelling hetegeneous treatment effects by quantitle local polynomial decision tree and forest," Papers 2111.15320, arXiv.org, revised Mar 2022.
    46. Giovanni Cerulli, 2020. "Optimal Policy Learning: From Theory to Practice," Papers 2011.04993, arXiv.org.
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    56. Aleksey Tetenov, 2016. "An economic theory of statistical testing," CeMMAP working papers 50/16, Institute for Fiscal Studies.
    57. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
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    59. Toru Kitagawa & Chris Muris, 2013. "Covariate selection and model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP61/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    60. Denteh, Augustine & Liebert, Helge, 2022. "Who Increases Emergency Department Use? New Insights from the Oregon Health Insurance Experiment," IZA Discussion Papers 15192, Institute of Labor Economics (IZA).
    61. Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev, 2020. "Treatment recommendation with distributional targets," Papers 2005.09717, arXiv.org, revised Apr 2022.
    62. Achim Ahrens & Alessandra Stampi‐Bombelli & Selina Kurer & Dominik Hangartner, 2024. "Optimal multi‐action treatment allocation: A two‐phase field experiment to boost immigrant naturalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1379-1395, November.
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    64. Seungjin Han & Julius Owusu & Youngki Shin, 2022. "Statistical Treatment Rules under Social Interaction," Papers 2209.09077, arXiv.org, revised Nov 2022.
    65. Susan Athey & Stefan Wager, 2021. "Policy Learning With Observational Data," Econometrica, Econometric Society, vol. 89(1), pages 133-161, January.
    66. Charles F. Manski & Aleksey Tetenov, 2014. "The Quantile Performance Of Statistical Treatment Rules Using Hypothesis Tests To Allocate A Population To Two Treatments," Carlo Alberto Notebooks 361, Collegio Carlo Alberto.
    67. Bryan S. Graham & Guido W. Imbens & Geert Ridder, 2009. "Complementarity and Aggregate Implications of Assortative Matching: A Nonparametric Analysis," NBER Working Papers 14860, National Bureau of Economic Research, Inc.
    68. Masahiro Kato, 2023. "Worst-Case Optimal Multi-Armed Gaussian Best Arm Identification with a Fixed Budget," Papers 2310.19788, arXiv.org, revised Mar 2024.
    69. Liyang Sun, 2024. "Empirical welfare maximization with constraints," CeMMAP working papers 19/24, Institute for Fiscal Studies.
    70. Toru Kitagawa & Guanyi Wang, 2023. "Individualized Treatment Allocation in Sequential Network Games," Papers 2302.05747, arXiv.org, revised Jul 2024.
    71. Otsu, Taisuke, 2008. "Large deviation asymptotics for statistical treatment rules," Economics Letters, Elsevier, vol. 101(1), pages 53-56, October.
    72. Davide Viviano & Kaspar Wuthrich & Paul Niehaus, 2021. "A model of multiple hypothesis testing," Papers 2104.13367, arXiv.org, revised Apr 2024.
    73. Charles F. Manski, 2019. "Econometrics For Decision Making: Building Foundations Sketched By Haavelmo And Wald," NBER Working Papers 26596, National Bureau of Economic Research, Inc.
    74. Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
    75. Karun Adusumilli, 2021. "Risk and optimal policies in bandit experiments," Papers 2112.06363, arXiv.org, revised Jan 2024.
    76. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    77. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
    78. Daniel F. Pellatt, 2022. "PAC-Bayesian Treatment Allocation Under Budget Constraints," Papers 2212.09007, arXiv.org, revised Jun 2023.
    79. Daido Kido, 2023. "Locally Asymptotically Minimax Statistical Treatment Rules Under Partial Identification," Papers 2311.08958, arXiv.org.
    80. Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev, 2018. "Functional Sequential Treatment Allocation," Papers 1812.09408, arXiv.org, revised Aug 2020.
    81. Takuya Ishihara & Toru Kitagawa, 2021. "Evidence Aggregation for Treatment Choice," Papers 2108.06473, arXiv.org, revised Jul 2024.
    82. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    83. Shosei Sakaguchi, 2021. "Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraints," Papers 2106.05031, arXiv.org, revised Aug 2024.
    84. Susan Athey & Guido Imbens, 2016. "The Econometrics of Randomized Experiments," Papers 1607.00698, arXiv.org.
    85. Henrika Langen & Martin Huber, 2022. "How causal machine learning can leverage marketing strategies: Assessing and improving the performance of a coupon campaign," Papers 2204.10820, arXiv.org, revised Jun 2022.
    86. Toru Kitagawa & Aleksey Tetenov, 2017. "Equality-minded treatment choice," CeMMAP working papers 10/17, Institute for Fiscal Studies.
    87. Daido Kido, 2023. "Incorporating Preferences Into Treatment Assignment Problems," Papers 2311.08963, arXiv.org.
    88. Kyungchul Song, 2009. "Point Decisions for Interval-Identified Parameters," PIER Working Paper Archive 09-036, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    89. Masahiro Kato & Masaaki Imaizumi & Takuya Ishihara & Toru Kitagawa, 2022. "Best Arm Identification with Contextual Information under a Small Gap," Papers 2209.07330, arXiv.org, revised Jan 2023.
    90. Keisuke Hirano & Jack R. Porter, 2012. "Impossibility Results for Nondifferentiable Functionals," Econometrica, Econometric Society, vol. 80(4), pages 1769-1790, July.
    91. Stoye, Jörg, 2009. "Minimax regret treatment choice with finite samples," Journal of Econometrics, Elsevier, vol. 151(1), pages 70-81, July.
    92. Keisuke Hirano & Jack R. Porter, 2016. "Panel Asymptotics and Statistical Decision Theory," The Japanese Economic Review, Springer, vol. 67(1), pages 33-49, March.
    93. Julia Hatamyar & Noemi Kreif, 2023. "Policy Learning with Rare Outcomes," Papers 2302.05260, arXiv.org, revised Oct 2023.
    94. Toru Kitagawa & Guanyi Wang, 2020. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers CWP59/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    95. Davide Viviano & Jelena Bradic, 2020. "Fair Policy Targeting," Papers 2005.12395, arXiv.org, revised Jun 2022.
    96. Tuvaandorj, Purevdorj, 2020. "Regression discontinuity designs, white noise models, and minimax," Journal of Econometrics, Elsevier, vol. 218(2), pages 587-608.
    97. Charles F. Manski, 2005. "Fractional Treatment Rules for Social Diversification of Indivisible Private Risks," NBER Working Papers 11675, National Bureau of Economic Research, Inc.
    98. Aleksey Tetenov, 2016. "An economic theory of statistical testing," CeMMAP working papers CWP50/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    99. Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org.
    100. David Glynn & John Giardina & Julia Hatamyar & Ankur Pandya & Marta Soares & Noemi Kreif, 2024. "Integrating decision modeling and machine learning to inform treatment stratification," Health Economics, John Wiley & Sons, Ltd., vol. 33(8), pages 1772-1792, August.
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    104. Toru Kitagawa & Guanyi Wang, 2021. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers CWP28/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    105. Yu-Chang Chen & Haitian Xie, 2022. "Personalized Subsidy Rules," Papers 2202.13545, arXiv.org, revised Mar 2022.
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  5. Keisuke Hirano & Jack R. Porter, 2002. "Asymptotic Efficiency in Parametric Structural Models with Parameter-Dependent Support," Harvard Institute of Economic Research Working Papers 1988, Harvard - Institute of Economic Research.

    Cited by:

    1. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2017. "Monte Carlo confidence sets for identified sets," CeMMAP working papers CWP43/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Xiaohong Chen & Timothy M. Christensen & Keith O'Hara & Elie Tamer, 2016. "MCMC confidence sets for identified sets," CeMMAP working papers CWP28/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Vukina, Tomislav & Zheng, Xiaoyong & Marra, Michele & Levy, Armando, 2008. "Do farmers value the environment? Evidence from a conservation reserve program auction," International Journal of Industrial Organization, Elsevier, vol. 26(6), pages 1323-1332, November.
    4. Michael Jansson, 2008. "Semiparametric Power Envelopes for Tests of the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 76(5), pages 1103-1142, September.
    5. Tong Li & Xiaoyong Zheng, 2009. "Entry and Competition Effects in First-Price Auctions: Theory and Evidence from Procurement Auctions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(4), pages 1397-1429.
    6. Joris Pinkse & Margaret Slade, 2007. "Semi-structural models of advertising competition," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(7), pages 1227-1246.
    7. Simon Loertscher & Andras Niedermayer, 2012. "Assessing the Performance of Simple Contracts Empirically:The Case of Percentage Fees," Department of Economics - Working Papers Series 1163, The University of Melbourne.
    8. Keisuke Hirano & Jack R. Porter, 2023. "Asymptotic Representations for Sequential Decisions, Adaptive Experiments, and Batched Bandits," Papers 2302.03117, arXiv.org.
    9. Li, Tong, 2010. "Indirect inference in structural econometric models," Journal of Econometrics, Elsevier, vol. 157(1), pages 120-128, July.
    10. Hickman Brent R. & Hubbard Timothy P. & Sağlam Yiğit, 2012. "Structural Econometric Methods in Auctions: A Guide to the Literature," Journal of Econometric Methods, De Gruyter, vol. 1(1), pages 67-106, August.
    11. Yao Luo, 2018. "Unobserved Heterogeneity in Auctions under Restricted Stochastic Dominance," Working Papers tecipa-606, University of Toronto, Department of Economics.
    12. Xie, Haitian & Zhu, Ying & Shishkin, Denis, 0. "On the limitations of data-based price discrimination," Theoretical Economics, Econometric Society.
    13. Emmanuel Guerre & Yao Luo, 2019. "Nonparametric Identification of First-Price Auction with Unobserved Competition: A Density Discontinuity Framework," Papers 1908.05476, arXiv.org, revised Dec 2024.
    14. Patrick Bayer & Shakeeb Khan & Christopher Timmins, 2008. "Nonparametric Identification and Estimation in a Generalized Roy Model," NBER Working Papers 13949, National Bureau of Economic Research, Inc.
    15. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2017. "Monte Carlo confidence sets for identified sets," CeMMAP working papers 43/17, Institute for Fiscal Studies.
    16. Zhou, Haiming & Huang, Xianzheng, 2022. "Bayesian beta regression for bounded responses with unknown supports," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
    17. Yu, Ping, 2012. "Likelihood estimation and inference in threshold regression," Journal of Econometrics, Elsevier, vol. 167(1), pages 274-294.
    18. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    19. Ploberger, Werner & Phillips, Peter C.B., 2012. "Optimal estimation under nonstandard conditions," Journal of Econometrics, Elsevier, vol. 169(2), pages 258-265.
    20. Gong, Aibo & Ke, Shaowei & Qiu, Yawen & Shen, Rui, 2022. "Robust pricing under strategic trading," Journal of Economic Theory, Elsevier, vol. 199(C).
    21. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2009. "The asymptotic structure of nearly unstable non negative integer-valued AR(1) models," Other publications TiSEM ac0494ae-7a32-43ca-b5b4-d, Tilburg University, School of Economics and Management.
    22. Gourieroux, C. & Jasiak, J., 2008. "Dynamic quantile models," Journal of Econometrics, Elsevier, vol. 147(1), pages 198-205, November.
    23. Yu, Ping, 2015. "Adaptive estimation of the threshold point in threshold regression," Journal of Econometrics, Elsevier, vol. 189(1), pages 83-100.
    24. Wang, Haiying & Sun, Dongchu, 2012. "Objective Bayesian analysis for a truncated model," Statistics & Probability Letters, Elsevier, vol. 82(12), pages 2125-2135.
    25. Sağlam, Yiğit, 2012. "Structural Econometric Methods in Auctions: A Guide to the Literature," Working Paper Series 19224, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
    26. Harold D. Chiang & Ryutah Kato & Yuya Sasaki, 2024. "Extremal quantiles of intermediate orders under two-way clustering," Papers 2402.19268, arXiv.org, revised Mar 2024.
    27. Alessandro Casini & Pierre Perron, 2018. "Generalized Laplace Inference in Multiple Change-Points Models," Papers 1803.10871, arXiv.org, revised Jan 2021.
    28. 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.
    29. Gimenes, Nathalie & Guerre, Emmanuel, 2022. "Quantile regression methods for first-price auctions," Journal of Econometrics, Elsevier, vol. 226(2), pages 224-247.
    30. Gaurab Aryal & Dong-Hyuk Kim, 2013. "Emprical Relevance of Ambiguity in First Price Auction Models," ANU Working Papers in Economics and Econometrics 2013-607, Australian National University, College of Business and Economics, School of Economics.
    31. Yanqin Fan & Hyeonseok Park, 2024. "Minimum Sliced Distance Estimation in a Class of Nonregular Econometric Models," Papers 2412.05621, arXiv.org.
    32. Tuvaandorj, Purevdorj, 2020. "Regression discontinuity designs, white noise models, and minimax," Journal of Econometrics, Elsevier, vol. 218(2), pages 587-608.
    33. Li, Tong & Zheng, Xiaoyong, 2012. "Information acquisition and/or bid preparation: A structural analysis of entry and bidding in timber sale auctions," Journal of Econometrics, Elsevier, vol. 168(1), pages 29-46.
    34. Li, Tong, 2009. "Simulation based selection of competing structural econometric models," Journal of Econometrics, Elsevier, vol. 148(2), pages 114-123, February.
    35. Xiaohong Chen & Timothy M. Christensen & Keith O'Hara & Elie Tamer, 2016. "MCMC confidence sets for identified sets," CeMMAP working papers 28/16, Institute for Fiscal Studies.
    36. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    37. Aryal, Gaurab & Grundl, Serafin & Kim, Dong-Hyuk & Zhu, Yu, 2018. "Empirical relevance of ambiguity in first-price auctions," Journal of Econometrics, Elsevier, vol. 204(2), pages 189-206.

  6. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc.

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    1. James J. Heckman & Petra E. Todd, 2009. "A note on adapting propensity score matching and selection models to choice based samples," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 230-234, January.
    2. Huber, Martin & Steinmayr, Andreas, 2017. "A Framework for Separating Individual Treatment Effects from Spillover, Interaction, and General Equilibrium Effects," IZA Discussion Papers 10648, Institute of Labor Economics (IZA).
    3. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Nonparametric Tests for Treatment Effect Heterogeneity," NBER Technical Working Papers 0324, National Bureau of Economic Research, Inc.
    4. Federico A. Bugni & Mengsi Gao & Filip Obradovic & Amilcar Velez, 2024. "Identification and Inference on Treatment Effects under Covariate-Adaptive Randomization and Imperfect Compliance," Papers 2406.08419, arXiv.org, revised Jun 2024.
    5. van de Walle, Dominique & Mu, Ren, 2007. "Fungibility and the flypaper effect of project aid: Micro-evidence for Vietnam," Journal of Development Economics, Elsevier, vol. 84(2), pages 667-685, November.
    6. Saraswata Chaudhuriy & David T. Frazierz & Eric Renault, 2016. "Indirect Inference with Endogenously Missing Exogenous Variables," CIRANO Working Papers 2016s-15, CIRANO.
    7. TODO Yasuyuki & INUI Tomohiko & YUAN Yuan, 2012. "Effects of Privatization on Exporting Decisions: Firm-level evidence from Chinese state-owned enterprises," Discussion papers 12015, Research Institute of Economy, Trade and Industry (RIETI).
    8. David Kaplan & Jianshen Chen, 2012. "A Two-Step Bayesian Approach for Propensity Score Analysis: Simulations and Case Study," Psychometrika, Springer;The Psychometric Society, vol. 77(3), pages 581-609, July.
    9. de Brauw, Alan & Gilligan, Daniel O. & Hoddinott, John & Roy, Shalini, 2014. "The Impact of Bolsa Família on Women’s Decision-Making Power," World Development, Elsevier, vol. 59(C), pages 487-504.
    10. 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.
    11. Busso, Matias & Kline, Patrick, 2008. "Do Local Economic Development Programs Work? Evidence from the Federal Empowerment Zone Program," Working Papers 36, Yale University, Department of Economics.
    12. Chabé-Ferret, Sylvain, 2015. "Analysis of the bias of Matching and Difference-in-Difference under alternative earnings and selection processes," Journal of Econometrics, Elsevier, vol. 185(1), pages 110-123.
    13. Clément de Chaisemartin & Luc Behaghel, 2020. "Estimating the Effect of Treatments Allocated by Randomized Waiting Lists," Econometrica, Econometric Society, vol. 88(4), pages 1453-1477, July.
    14. Lv, Xiaofeng & Li, Rui & Fang, Zheng, 2017. "Efficient semiparametric estimation for Gini inequality treatment effects," Economics Letters, Elsevier, vol. 154(C), pages 96-100.
    15. Kyoo il Kim, 2019. "Efficiency of Average Treatment Effect Estimation When the True Propensity Is Parametric," Econometrics, MDPI, vol. 7(2), pages 1-13, May.
    16. Nguezet, Paul Martin Dontsop & Diagne, Aliou & Okoruwa, Victor Olusegun & Ojehomon, Vivian, 2011. "Impact of Improved Rice Technology (NERICA varieties) on Income and Poverty among Rice Farming Households in Nigeria: A Local Average Treatment Effect (LATE) Approach," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 50(3), pages 1-25.
    17. Gunther Bensch & Jörg Peters, 2013. "Alleviating Deforestation Pressures? Impacts of Improved Stove Dissemination on Charcoal Consumption in Urban Senegal," Land Economics, University of Wisconsin Press, vol. 89(4), pages 676-698.
    18. Gabriel V. Montes-Rojas, 2011. "Nonparametric Estimation of ATE and QTE: An Application of Fractile Graphical Analysis," Journal of Probability and Statistics, Hindawi, vol. 2011, pages 1-23, October.
    19. Bruno Cirillo & Stefano Brusoni & Giovanni Valentini, 2014. "The Rejuvenation of Inventors Through Corporate Spinouts," Organization Science, INFORMS, vol. 25(6), pages 1764-1784, December.
    20. Leonardo Becchetti & Pierluigi Conzo & Alessandro Romeo, 2014. "Violence, trust, and trustworthiness: evidence from a Nairobi slum," Oxford Economic Papers, Oxford University Press, vol. 66(1), pages 283-305, January.
    21. Hang Miao & Kui Zhao & Zhun Wang & Linbo Jiang & Quanhui Jia & Yanming Fang & Quan Yu, 2020. "Intelligent Credit Limit Management in Consumer Loans Based on Causal Inference," Papers 2007.05188, arXiv.org.
    22. Hayri A. Arslan & Necati Tereyağoğlu & Övünç Yılmaz, 2023. "Scoring a Touchdown with Variable Pricing: Evidence from a Quasi-Experiment in the NFL Ticket Markets," Management Science, INFORMS, vol. 69(8), pages 4435-4456, August.
    23. Barragan, Luis, 2006. "¿Cuánto es el premio al salario por pertenecer a un sindicato en el Ecuador?: Un análisis usando Propensity Score Matching [How much it is the prize to the wage to belong to a union in Ecuador?: An," MPRA Paper 3947, University Library of Munich, Germany.
    24. Xiong, Ruoxuan & Koenecke, Allison & Powell, Michael & Shen, Zhu & Vogelstein, Joshua T. & Athey, Susan, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Research Papers 3990, Stanford University, Graduate School of Business.
    25. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    26. Toru Kitagawa & Chris Muris, 2015. "Model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP46/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    27. Taneli Mäkinen & Fan Li & Andrea Mercatanti & Andrea Silvestrini, 2020. "Effects of eligibility for central bank purchases on corporate bond spreads," BIS Working Papers 894, Bank for International Settlements.
    28. Cansino, José M. & Lopez-Melendo, Jaime & Pablo-Romero, María del P. & Sánchez-Braza, Antonio, 2013. "An economic evaluation of public programs for internationalization: The case of the Diagnostic program in Spain," Evaluation and Program Planning, Elsevier, vol. 41(C), pages 38-46.
    29. Rajeev Dehejia, 2013. "The Porous Dialectic: Experimental and Non-Experimental Methods in Development Economics," WIDER Working Paper Series wp-2013-011, World Institute for Development Economic Research (UNU-WIDER).
    30. John C. Ham & Xianghong Li & Patricia B. Reagan, 2004. "Propensity Score Matching, a Distance-Based Measure of Migration, and the Wage Growth of Young Men," Working Papers 2004_3, York University, Department of Economics.
    31. Yamauchi, Futoshi & Liu, Yanyan, 2012. "Impacts of an early stage education intervention on students'learning achievement : evidence from the Philippines," Policy Research Working Paper Series 6246, The World Bank.
    32. Jessamyn Schaller & Mariana Zerpa, 2019. "Short-Run Effects of Parental Job Loss on Child Health," American Journal of Health Economics, University of Chicago Press, vol. 5(1), pages 8-41, Winter.
    33. Erlend E. Bø & Elin Halvorsen & Thor O. Thoresen, 2019. "Heterogeneity of the Carnegie Effect," Journal of Human Resources, University of Wisconsin Press, vol. 54(3), pages 726-759.
    34. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    35. Bryan S. Graham & Guido W. Imbens & Geert Ridder, 2016. "Identification and Efficiency Bounds for the Average Match Function under Conditionally Exogenous Matching," NBER Working Papers 22098, National Bureau of Economic Research, Inc.
    36. 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.
    37. Peter Eppinger & Hong Ma, 2023. "Optimal Ownership and Firm Performance: An Analysis of China’s FDI Liberalization," CESifo Working Paper Series 10551, CESifo.
    38. 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.
    39. Tommaso Agasisti & Ekaterina Abalmasova & Ekaterina Shibanova & Aleksei Egorov, 2019. "The Causal Impact Of Performance-Based Funding On University Performance: Quasi-Experimental Evidence From A Policy In Russian Higher Education," HSE Working papers WP BRP 221/EC/2019, National Research University Higher School of Economics.
    40. Birthal, Pratap S. & Roy, Devesh & Negi, Digvijay S., 2015. "Assessing the Impact of Crop Diversification on Farm Poverty in India," World Development, Elsevier, vol. 72(C), pages 70-92.
    41. Töpfer, Marina, 2017. "Detailed RIF decomposition with selection: The gender pay gap in Italy," Hohenheim Discussion Papers in Business, Economics and Social Sciences 26-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    42. TODO Yasuyuki, 2008. "Impacts of Aid-Funded Technical Assistance Programs: Firm-Level Evidence from the Indonesian Foundry Industry," Discussion papers 08024, Research Institute of Economy, Trade and Industry (RIETI).
    43. Katie Meara & Francesco Pastore & Allan Webster, 2020. "The gender pay gap in the USA: a matching study," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(1), pages 271-305, January.
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    39. Seik Kim, "undated". "Economic Assimilation of Foreign-Born Workers in the United States: An Overlapping Rotating Panel Analysis," Working Papers UWEC-2008-19, University of Washington, Department of Economics.
    40. Alia El Mahdi & Ali Rashed, 2007. "The Changing Economic Environment and the Development of the Micro and Small Enterprises in Egypt 2006," Working Papers 706, Economic Research Forum, revised 01 Jan 2007.
    41. Seik Kim, 2013. "Wage Mobility of Foreign-Born Workers in the United States," Journal of Human Resources, University of Wisconsin Press, vol. 48(3), pages 628-658.
    42. Paul J. Devereux & Gautam Tripathi, 2008. "Optimally combining censored and uncensored datasets," Working Papers 200820, School of Economics, University College Dublin.
    43. Emre Ekinci & Insan Tunah & Berk Yavuzoglu, 2017. "Rescaled Additivity Non-Ignorable (RAN) Model of Generalized Attrition," Working Papers 1702, Nazarbayev University, Department of Economics, revised Mar 2017.
    44. Tom Wansbeek & Erik Meijer, 2007. "Comments on: Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 33-36, May.
    45. Olanrewaju Akande & Gabriel Madson & D. Sunshine Hillygus & Jerome P. Reiter, 2021. "Leveraging auxiliary information on marginal distributions in nonignorable models for item and unit nonresponse," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 643-662, April.
    46. Insan Tunali & Emre Ekinci & Berk Yavuzoglu, 2012. "Rescaled Additively Non-ignorable (RAN) Model of Attrition and Substitution," Koç University-TUSIAD Economic Research Forum Working Papers 1220, Koc University-TUSIAD Economic Research Forum.
    47. Honggao Cao & Daniel H. Hill, 2005. "Active versus Passive Sample Attrition: The Health and Retirement Study," Econometrics 0505006, University Library of Munich, Germany.
    48. Aviv Nevo, 2001. "Using Weights to Adjust for Sample Selection When Auxiliary Information is Available," NBER Technical Working Papers 0275, National Bureau of Economic Research, Inc.
    49. Paquet, Marie-France & Bolduc, Denis, 2004. "Le problème des données longitudinales incomplètes : une nouvelle approche," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 341-361, Juin-Sept.
    50. Yamana Kazufumi, 2020. "Monte Carlo Evidence on the Estimation Method for Industry Dynamics," Journal of Econometric Methods, De Gruyter, vol. 9(1), pages 1-12, January.
    51. Kosuke Imai, 2009. "Statistical analysis of randomized experiments with non‐ignorable missing binary outcomes: an application to a voting experiment," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(1), pages 83-104, February.
    52. Breunig, Christoph, 2017. "Testing Missing At Random Using Instrumental Variables," Rationality and Competition Discussion Paper Series 59, CRC TRR 190 Rationality and Competition.
    53. Simon Calmar Andersen & Louise Beuchert & Phillip Heiler & Helena Skyt Nielsen, 2023. "A Guide to Impact Evaluation under Sample Selection and Missing Data: Teacher's Aides and Adolescent Mental Health," Papers 2308.04963, arXiv.org.
    54. Sasaki, Yuya, 2015. "Heterogeneity and selection in dynamic panel data," Journal of Econometrics, Elsevier, vol. 188(1), pages 236-249.
    55. Joachim Inkmann, 2010. "Estimating Firm Size Elasticities of Product and Process R&D," Economica, London School of Economics and Political Science, vol. 77(306), pages 384-402, April.
    56. Bryan S. Graham & Cristine Campos De Xavier Pinto & Daniel Egel, 2012. "Inverse Probability Tilting for Moment Condition Models with Missing Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 1053-1079.
    57. Bert Van Landeghem, 2012. "Panel Conditioning and Self-Reported Satisfaction: Evidence from International Panel Data and Repeated Cross-Sections," SOEPpapers on Multidisciplinary Panel Data Research 484, DIW Berlin, The German Socio-Economic Panel (SOEP).
    58. Laurent Davezies & Xavier d'Haultfoeuille, 2013. "Endogenous Attrition in Panels," Working Papers 2013-17, Center for Research in Economics and Statistics.
    59. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian Instrumental Variables Estimation for Nonignorable Missing Instruments," Discussion Paper Series DP2020-06, Research Institute for Economics & Business Administration, Kobe University.
    60. Mark McGovern & David Canning & Till Bärnighausen, 2018. "Accounting for Non-Response Bias using Participation Incentives and Survey Design," CHaRMS Working Papers 18-02, Centre for HeAlth Research at the Management School (CHaRMS).
    61. Yuehao Bai & Meng Hsuan Hsieh & Jizhou Liu & Max Tabord‐Meehan, 2024. "Revisiting the analysis of matched‐pair and stratified experiments in the presence of attrition," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 256-268, March.
    62. Emre Ekinci, 2009. "Dealing with Attrition When Refreshment Samples are Available: An Application to the Turkish Household Labor Force Survey," 2009 Meeting Papers 353, Society for Economic Dynamics.

Articles

  1. Hirano, Keisuke & Wright, Jonathan H., 2022. "Analyzing cross-validation for forecasting with structural instability," Journal of Econometrics, Elsevier, vol. 226(1), pages 139-154.

    Cited by:

    1. Skrobotov, Anton, 2024. "Time series forecasting under structural breaks," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 76, pages 120-139.

  2. Keisuke Hirano & Jonathan H. Wright, 2017. "Forecasting With Model Uncertainty: Representations and Risk Reduction," Econometrica, Econometric Society, vol. 85, pages 617-643, March.

    Cited by:

    1. Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
    2. Siemsen, Thomas & Vilsmeier, Johannes, 2017. "A stress test framework for the German residential mortgage market: Methodology and application," Discussion Papers 37/2017, Deutsche Bundesbank.
    3. Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics, Canadian Economics Association, vol. 51(3), pages 695-746, August.
    4. Keisuke Hirano & Jack R. Porter, 2023. "Asymptotic Representations for Sequential Decisions, Adaptive Experiments, and Batched Bandits," Papers 2302.03117, arXiv.org.
    5. Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting the Hodrick-Prescott Filter," Cowles Foundation Discussion Papers 2192, Cowles Foundation for Research in Economics, Yale University.
    6. Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022. "On LASSO for predictive regression," Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
    7. Travis J. Berge, 2017. "Understanding Survey Based Inflation Expectations," Finance and Economics Discussion Series 2017-046, Board of Governors of the Federal Reserve System (U.S.).
    8. Gourieroux, Christian & Jasiak, Joann, 2010. "Inference for Noisy Long Run Component Process," MPRA Paper 98987, University Library of Munich, Germany.
    9. Yi-Ting Chen & Chu-An Liu, 2021. "Model Averaging for Asymptotically Optimal Combined Forecasts," IEAS Working Paper : academic research 21-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    10. Boot, Tom & Nibbering, Didier, 2019. "Forecasting using random subspace methods," Journal of Econometrics, Elsevier, vol. 209(2), pages 391-406.
    11. Wright, Jonathan H., 2019. "Some observations on forecasting and policy," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1186-1192.
    12. Norman R. Swanson & Weiqi Xiong & Xiye Yang, 2020. "Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 587-613, August.
    13. Yinchu Zhu, 2021. "Phase transition of the monotonicity assumption in learning local average treatment effects," Papers 2103.13369, arXiv.org.
    14. Benjamin Garcia & Arsenios Skaperdas, 2017. "Inferring the Shadow Rate from Real Activity," Finance and Economics Discussion Series 2017-106, Board of Governors of the Federal Reserve System (U.S.).

  3. Daniel Ackerberg & Keisuke Hirano & Quazi Shahriar, 2017. "Identification of time and risk preferences in buy price auctions," Quantitative Economics, Econometric Society, vol. 8(3), pages 809-849, November.

    Cited by:

    1. David Freeman & Erik O. Kimbrough & J. Philipp Reiss, 2017. "Opportunity cost, inattention and the bidder's curse," Discussion Papers dp17-04, Department of Economics, Simon Fraser University.
    2. Xiaohong Chen & Matthew Gentry & Tong Li & Jingfeng Lu, 2020. "Identification and Inference in First-Price Auctions with Risk Averse Bidders and Selective Entry," Cowles Foundation Discussion Papers 2257, Cowles Foundation for Research in Economics, Yale University.
    3. Federico Zincenko, 2019. "Testing for Risk Aversion in First-Price Sealed-Bid Auctions," Working Paper 6641, Department of Economics, University of Pittsburgh.
    4. Barkley, Aaron & Groeger, Joachim R. & Miller, Robert A., 2021. "Bidding frictions in ascending auctions," Journal of Econometrics, Elsevier, vol. 223(2), pages 376-400.

  4. Keisuke Hirano & Jack R. Porter, 2016. "Panel Asymptotics and Statistical Decision Theory," The Japanese Economic Review, Japanese Economic Association, vol. 67(1), pages 33-49, March.

    Cited by:

    1. Susan Athey & Stefan Wager, 2021. "Policy Learning With Observational Data," Econometrica, Econometric Society, vol. 89(1), pages 133-161, January.

  5. Keisuke Hirano & Jack R. Porter, 2015. "Location Properties of Point Estimators in Linear Instrumental Variables and Related Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 720-733, December.

    Cited by:

    1. Isaiah Andrews & Timothy B. Armstrong, 2015. "Unbiased Instrumental Variables Estimation under Known First-Stage Sign," Cowles Foundation Discussion Papers 1984R, Cowles Foundation for Research in Economics, Yale University, revised Mar 2015.
    2. Silvia Moler‐Zapata & Richard Grieve & Anirban Basu & Stephen O’Neill, 2023. "How does a local instrumental variable method perform across settings with instruments of differing strengths? A simulation study and an evaluation of emergency surgery," Health Economics, John Wiley & Sons, Ltd., vol. 32(9), pages 2113-2126, September.
    3. Tetsuya Kaji, 2021. "Theory of Weak Identification in Semiparametric Models," Econometrica, Econometric Society, vol. 89(2), pages 733-763, March.
    4. Roach, Travis & Nath, Saheli, 2023. "Counties with More Vietnam Veterans Have Higher Suicide Rates," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 53(1), April.
    5. David M. Kaplan, 2019. "Unbiased Estimation as a Public Good," Working Papers 1911, Department of Economics, University of Missouri.
    6. Karthik Rajkumar, 2019. "Ridge regularization for Mean Squared Error Reduction in Regression with Weak Instruments," Papers 1904.08580, arXiv.org.

  6. Keisuke Hirano & Jack R. Porter, 2012. "Impossibility Results for Nondifferentiable Functionals," Econometrica, Econometric Society, vol. 80(4), pages 1769-1790, July.
    See citations under working paper version above.
  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.

    Cited by:

    1. Keisuke Hirano & Jack R. Porter, 2016. "Panel Asymptotics and Statistical Decision Theory," The Japanese Economic Review, Springer, vol. 67(1), pages 33-49, March.

  8. Hahn, Jinyong & Hirano, Keisuke & Karlan, Dean, 2011. "Adaptive Experimental Design Using the Propensity Score," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 96-108.
    See citations under working paper version above.
  9. Hirano, Keisuke & Hahn, Jinyong, 2010. "Design of randomized experiments to measure social interaction effects," Economics Letters, Elsevier, vol. 106(1), pages 51-53, January.

    Cited by:

    1. Steven N. Durlauf & Yannis M. Ioannides, 2009. "Social Interactions," Discussion Papers Series, Department of Economics, Tufts University 0739, Department of Economics, Tufts University.
    2. Sarah Baird & Aislinn Bohren & Berk Ozler & Craig McIntosh, 2014. "Designing Experiments to Measure Spillover Effects," Working Papers 2014-11, The George Washington University, Institute for International Economic Policy.
    3. Braun, Martin & Verdier, Valentin, 2023. "Estimation of spillover effects with matched data or longitudinal network data," Journal of Econometrics, Elsevier, vol. 233(2), pages 689-714.
    4. Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2015. "Designing Experiments to Measure Spillover Effects, Second Version," PIER Working Paper Archive 15-021, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Jun 2015.
    5. Cruces, Guillermo & Tortarolo, Dario & Vazquez-Bare, Gonzalo, 2024. "Design of Partial Population Experiments with an Application to Spillovers in Tax Compliance," IZA Discussion Papers 17256, Institute of Labor Economics (IZA).
    6. Vazquez-Bare, Gonzalo, 2023. "Identification and estimation of spillover effects in randomized experiments," Journal of Econometrics, Elsevier, vol. 237(1).
    7. Angelucci,M. & Di Maro,Vincenzo, 2015. "Program evaluation and spillover effects," Policy Research Working Paper Series 7243, The World Bank.
    8. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
    9. Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2017. "Optimal Design of Experiments in the Presence of Interference*, Second Version," PIER Working Paper Archive 16-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 30 Nov 2017.
    10. Michael P. Leung, 2020. "Treatment and Spillover Effects Under Network Interference," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 368-380, May.

  10. Keisuke Hirano & Jack R. Porter, 2009. "Asymptotics for Statistical Treatment Rules," Econometrica, Econometric Society, vol. 77(5), pages 1683-1701, September.
    See citations under working paper version above.
  11. Keisuke Hirano & Jack R. Porter, 2003. "Asymptotic Efficiency in Parametric Structural Models with Parameter-Dependent Support," Econometrica, Econometric Society, vol. 71(5), pages 1307-1338, September.
    See citations under working paper version above.
  12. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
    See citations under working paper version above.
  13. Keisuke Hirano, 2002. "Semiparametric Bayesian Inference in Autoregressive Panel Data Models," Econometrica, Econometric Society, vol. 70(2), pages 781-799, March.

    Cited by:

    1. Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
    2. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    3. Griffin, J.E. & Steel, M.F.J., 2011. "Stick-breaking autoregressive processes," Journal of Econometrics, Elsevier, vol. 162(2), pages 383-396, June.
    4. Fisher, Mark & Jensen, Mark J., 2022. "Bayesian nonparametric learning of how skill is distributed across the mutual fund industry," Journal of Econometrics, Elsevier, vol. 230(1), pages 131-153.
    5. Tong Li & Xiaoyong Zheng, 2009. "Entry and Competition Effects in First-Price Auctions: Theory and Evidence from Procurement Auctions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(4), pages 1397-1429.
    6. Martin Burda & Matthew C. Harding & Jerry Hausman, 2008. "A Bayesian mixed logit-probit model for multinomial choice," CeMMAP working papers CWP23/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
    8. Fernández-Val, Iván & Gao, Wayne Yuan & Liao, Yuan & Vella, Francis, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," IZA Discussion Papers 15236, Institute of Labor Economics (IZA).
    9. Griffin, J. E. & Steel, M. F. J., 2004. "Semiparametric Bayesian inference for stochastic frontier models," Journal of Econometrics, Elsevier, vol. 123(1), pages 121-152, November.
    10. Magnac, Thierry & Roux, Sébastien, 2007. "Dynamique des salaires dans une cohorte," IDEI Working Papers 436, Institut d'Économie Industrielle (IDEI), Toulouse.
    11. Sasaki, Yuya & Xin, Yi, 2017. "Unequal spacing in dynamic panel data: Identification and estimation," Journal of Econometrics, Elsevier, vol. 196(2), pages 320-330.
    12. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2017. "Forecasting with Dynamic Panel Data Models," Papers 1709.10193, arXiv.org.
    13. Mikkel Plagborg-Moller & Gita Gopinath & Emine Boz, 2017. "Global Trade and the Dollar," 2017 Meeting Papers 1041, Society for Economic Dynamics.
    14. Jiaying Gu & Roger Koenker, 2014. "Unobserved heterogeneity in income dynamics: an empirical Bayes perspective," CeMMAP working papers 43/14, Institute for Fiscal Studies.
    15. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    16. Pelenis, Justinas, 2014. "Bayesian regression with heteroscedastic error density and parametric mean function," Journal of Econometrics, Elsevier, vol. 178(P3), pages 624-638.
    17. Antonio Pacifico, 2023. "Obesity and labour market outcomes in Italy: a dynamic panel data evidence with correlated random effects," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(4), pages 557-574, June.
    18. Masao Ogaki, 2016. "Announcement," The Japanese Economic Review, Japanese Economic Association, vol. 67(1), pages 31-32, March.
    19. Jaeho Kim & Le Wang, 2019. "Hidden group patterns in democracy developments: Bayesian inference for grouped heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 1016-1028, September.
    20. Federico Bassetti & Roberto Casarin & Marco Del Negro, 2022. "A Bayesian Approach to Inference on Probabilistic Surveys," Staff Reports 1025, Federal Reserve Bank of New York.
    21. Botosaru, Irene, 2023. "Time-varying unobserved heterogeneity in earnings shocks," Journal of Econometrics, Elsevier, vol. 235(2), pages 1378-1393.
    22. Abel Rodriguez & Enrique ter Horst, 2008. "Measuring expectations in options markets: An application to the SP500 index," Papers 0901.0033, arXiv.org.
    23. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian multiple imputation for regression models with missing mixed continuous–discrete covariates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 803-825, June.
    24. Casarin Roberto & Peruzzi Antonio, 2024. "A Dynamic Latent-Space Model for Asset Clustering," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 379-402, April.
    25. Jensen Mark J., 2016. "Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 455-475, September.
    26. Juarez, Miguel A. & Steel, Mark F. J., 2006. "Non-Gaussian dynamic Bayesian modelling for panel data," MPRA Paper 450, University Library of Munich, Germany.
    27. Rajeev Dehejia, 1999. "Program Evaluation as a Decision Problem," NBER Working Papers 6954, National Bureau of Economic Research, Inc.
    28. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2015. "Bayesian nonparametric calibration and combination of predictive distributions," Working Paper 2015/03, Norges Bank.
    29. Abel Rodr�guez & Enrique ter Horst, 2011. "Measuring expectations in options markets: an application to the S&P500 index," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1393-1405, July.
    30. Mark J. Jensen, 2004. "Semiparametric Bayesian Inference of Long‐Memory Stochastic Volatility Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(6), pages 895-922, November.
    31. Chib, Siddhartha & Greenberg, Edward, 2010. "Additive cubic spline regression with Dirichlet process mixture errors," Journal of Econometrics, Elsevier, vol. 156(2), pages 322-336, June.
    32. Laura Liu, 2017. "Density Forecasts in Panel Models: A semiparametric Bayesian Perspective," PIER Working Paper Archive 17-006, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 28 Apr 2017.
    33. Martin Burda & Artem Prokhorov, 2012. "Copula Based Factorization in Bayesian Multivariate Infinite Mixture Models," Working Papers 12012, Concordia University, Department of Economics.
    34. Razzak Humera & Heumann Christian, 2019. "Hybrid Multiple Imputation In A Large Scale Complex Survey," Statistics in Transition New Series, Statistics Poland, vol. 20(4), pages 33-58, December.
    35. Yu, Ping, 2015. "Adaptive estimation of the threshold point in threshold regression," Journal of Econometrics, Elsevier, vol. 189(1), pages 83-100.
    36. Kim, Jung Seek & Ratchford, Brian T., 2013. "A Bayesian multivariate probit for ordinal data with semiparametric random-effects," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 192-208.
    37. Tong Li & Xiaoyong Zheng, 2008. "Semiparametric Bayesian inference for dynamic Tobit panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 699-728.
    38. Stéphane Bonhomme & Jean-Marc Robin, 2008. "Generalized nonparametric deconvolution with an application to earnings dynamics," CeMMAP working papers CWP03/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    39. Yajuan Si & Jerome P. Reiter, 2013. "Nonparametric Bayesian Multiple Imputation for Incomplete Categorical Variables in Large-Scale Assessment Surveys," Journal of Educational and Behavioral Statistics, , vol. 38(5), pages 499-521, October.
    40. Han, Yufeng, 2012. "State uncertainty in stock markets: How big is the impact on the cost of equity?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2575-2592.
    41. Laura Liu, 2020. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," CAEPR Working Papers 2020-003, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    42. Burda, Martin & Harding, Matthew, 2014. "Environmental Justice: Evidence from Superfund cleanup durations," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 380-401.
    43. Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
    44. Jiaying Gu & Roger Koenker, 2014. "Unobserved heterogeneity in income dynamics: an empirical Bayes perspective," CeMMAP working papers CWP43/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    45. Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019. "Bayesian nonparametric sparse VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
    46. Casarin, Roberto & Costola, Michele, 2019. "Structural changes in large economic datasets: A nonparametric homogeneity test," Economics Letters, Elsevier, vol. 176(C), pages 55-59.
    47. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    48. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Instrumental Variable Estimation with Many Weak Instruments," Discussion Paper Series DP2018-14, Research Institute for Economics & Business Administration, Kobe University.
    49. Li Tan, 2021. "Imputing Top‐Coded Income Data in Longitudinal Surveys," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(1), pages 66-87, February.
    50. Paserman, M. Daniele, 2004. "Bayesian Inference for Duration Data with Unobserved and Unknown Heterogeneity: Monte Carlo Evidence and an Application," IZA Discussion Papers 996, Institute of Labor Economics (IZA).
    51. Magnac, Thierry & Pistolesi, Nicolas & Roux, Sébastien, 2013. "Post schooling human capital investments and the life cycle variance of earnings," IDEI Working Papers 765, Institut d'Économie Industrielle (IDEI), Toulouse.
    52. Juarez, Miguel A. & Steel, Mark F. J., 2006. "Model-based Clustering of non-Gaussian Panel Data," MPRA Paper 880, University Library of Munich, Germany.
    53. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    54. Hasegawa, Hikaru & Kozumi, Hideo, 2003. "Estimation of Lorenz curves: a Bayesian nonparametric approach," Journal of Econometrics, Elsevier, vol. 115(2), pages 277-291, August.
    55. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    56. Pelenis, Justinas, 2012. "Bayesian Semiparametric Regression," Economics Series 285, Institute for Advanced Studies.
    57. Federico Bassetti & Roberto Casarin & Fabrizio Leisen, 2013. "Beta-Product Dependent Pitman-Yor Processes for Bayesian Inference," Working Papers 2013:13, Department of Economics, University of Venice "Ca' Foscari".
    58. Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse seemingly unrelated regression model (SUR)," Working Papers 2016:20, Department of Economics, University of Venice "Ca' Foscari".
    59. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Multiple Imputation for Regression Models with Missing Mixed Continuous-Discrete Covariates," Discussion Paper Series DP2018-15, Research Institute for Economics & Business Administration, Kobe University.
    60. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian Instrumental Variables Estimation for Nonignorable Missing Instruments," Discussion Paper Series DP2020-06, Research Institute for Economics & Business Administration, Kobe University.
    61. Sugawara, Shinya, 2012. "A nonparametric Bayesian approach for counterfactual prediction with an application to the Japanese private nursing home market," MPRA Paper 42154, University Library of Munich, Germany.
    62. Zheng, Xiaoyong, 2008. "Semiparametric Bayesian estimation of mixed count regression models," Economics Letters, Elsevier, vol. 100(3), pages 435-438, September.
    63. Cem Çakmakli, 2012. "Bayesian Semiparametric Dynamic Nelson-Siegel Model," Working Paper series 59_12, Rimini Centre for Economic Analysis, revised Sep 2012.
    64. Peluso, Stefano & Mira, Antonietta & Muliere, Pietro, 2015. "Reinforced urn processes for credit risk models," Journal of Econometrics, Elsevier, vol. 184(1), pages 1-12.

  14. Keisuke Hirano & Guido W. Imbens & Geert Ridder & Donald B. Rubin, 2001. "Combining Panel Data Sets with Attrition and Refreshment Samples," Econometrica, Econometric Society, vol. 69(6), pages 1645-1659, November.
    See citations under working paper version above.
  15. Gary Chamberlain & Keisuke Hirano, 1999. "Predictive Distributions based on Longitudinal Earnings Data," Annals of Economics and Statistics, GENES, issue 55-56, pages 211-242.

    Cited by:

    1. Fatih Guvenen & Fatih Karahan & Serdar Ozkan & Jae Song, 2015. "What Do Data on Millions of U.S. Workers Reveal about Life-Cycle Earnings Risk?," Working Papers 719, Federal Reserve Bank of Minneapolis.
    2. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2017. "Forecasting with Dynamic Panel Data Models," Papers 1709.10193, arXiv.org.
    3. Stephen Jenkins & Peter Lambert, 2011. "Robert Moffitt and Peter Gottschalk’s 1995 paper ‘Trends in the covariance structure of earnings in the US: 1969–1987’," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(3), pages 433-437, September.
    4. Hospido, Laura, 2010. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," IZA Discussion Papers 4712, Institute of Labor Economics (IZA).
    5. Baltagi, Badi H., 2013. "Panel Data Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 995-1024, Elsevier.
    6. Gary Chamberlain, 2000. "Econometric applications of maxmin expected utility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 625-644.
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