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Ivan Alexis Canay

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.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Ivan A Canay & Vishal Kamat, 2018. "Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(3), pages 1577-1608.

    Mentioned in:

    1. Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design (REStud 2018) in ReplicationWiki ()

Working papers

  1. Yong Cai & Ivan A. Canay & Deborah Kim & Azeem M. Shaikh, 2021. "On the implementation of Approximate Randomization Tests in Linear Models with a Small Number of Clusters," Papers 2102.09058, arXiv.org, revised Mar 2022.

    Cited by:

    1. James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2022. "Cluster-Robust Inference: A Guide to Empirical Practice," Papers 2205.03285, arXiv.org.
    2. Yong Cai, 2021. "Panel Data with Unknown Clusters," Papers 2106.05503, arXiv.org, revised Jan 2022.
    3. Heckman, James J. & Pinto, Rodrigo & Shaikh, Azeem M., 2023. "Dealing With Imperfect Randomization: Inference for the Highscope Perry Preschool Program," IZA Discussion Papers 16675, Institute of Labor Economics (IZA).
    4. Michael P. Leung, 2023. "Network Cluster‐Robust Inference," Econometrica, Econometric Society, vol. 91(2), pages 641-667, March.

  2. Ivan A. Canay & Magne Mogstad & Jack Mountjoy, 2020. "On the Use of Outcome Tests for Detecting Bias in Decision Making," Working Papers 2020-125, Becker Friedman Institute for Research In Economics.

    Cited by:

    1. Will Dobbie & Crystal S. Yang, 2021. "The US Pretrial System: Balancing Individual Rights and Public Interests," Journal of Economic Perspectives, American Economic Association, vol. 35(4), pages 49-70, Fall.
    2. David Arnold & Will Dobbie & Peter Hull, 2022. "Measuring Racial Discrimination in Bail Decisions," American Economic Review, American Economic Association, vol. 112(9), pages 2992-3038, September.
    3. Arcidiacono, Peter & Kinsler, Josh & Ransom, Tyler, 2020. "Asian American Discrimination in Harvard Admissions," IZA Discussion Papers 13172, Institute of Labor Economics (IZA).
    4. Laura Blattner & Scott Nelson, 2021. "How Costly is Noise? Data and Disparities in Consumer Credit," Papers 2105.07554, arXiv.org.
    5. Rahul Deb & Ludovic Renou, 2022. "Which wage distributions are consistent with statistical discrimination?," Working Papers tecipa-736, University of Toronto, Department of Economics.
    6. Lee, Ji Hyung & Park, Byoung G., 2023. "Nonparametric identification and estimation of the extended Roy model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1087-1113.

  3. Federico A. Bugni & Ivan A. Canay, 2018. "Testing Continuity of a Density via g-order statistics in the Regression Discontinuity Design," Papers 1803.07951, arXiv.org, revised Feb 2020.

    Cited by:

    1. Lu, Jiaxuan, 2023. "The economics of China’s between-city height competition: A regression discontinuity approach," Regional Science and Urban Economics, Elsevier, vol. 100(C).
    2. Marinho Bertanha & Eunyi Chung, 2023. "Permutation Tests at Nonparametric Rates," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(544), pages 2833-2846, October.
    3. Abdulkadiroglu, Atila & Angrist, Joshua & Narita, Yusuke & Pathak, Parag A., 2019. "Breaking Ties: Regression Discontinuity Design Meets Market Design," IZA Discussion Papers 12205, Institute of Labor Economics (IZA).
    4. Takuya Ishihara & Masayuki Sawada, 2020. "Manipulation-Robust Regression Discontinuity Designs," Papers 2009.07551, arXiv.org, revised Oct 2023.
    5. Matias D. Cattaneo & Rocio Titiunik & Gonzalo Vazquez-Bare, 2019. "The Regression Discontinuity Design," Papers 1906.04242, arXiv.org, revised Jun 2020.
    6. Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2021. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP16/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Cavalcanti, T. & Mohaddes, K. & Nian, H. & Yin, H., 2023. "Air Pollution and Firm-Level Human Capital, Knowledge and Innovation," Janeway Institute Working Papers 2301, Faculty of Economics, University of Cambridge.
    8. Andrii Babii & Rohit Kumar, 2019. "Isotonic Regression Discontinuity Designs," Papers 1908.05752, arXiv.org, revised Dec 2020.
    9. Leopoldo Fergusson & Arturo Harker & Carlos Molina & Juan Camilo Yamín, 2023. "Political incentives and corruption evidence from ghost students," Documentos CEDE 20732, Universidad de los Andes, Facultad de Economía, CEDE.
    10. Koki Fusejima & Takuya Ishihara & Masayuki Sawada, 2022. "Joint diagnostic test of regression discontinuity designs: multiple testing problem," Papers 2205.04345, arXiv.org, revised Oct 2023.
    11. Yingying DONG & Ying-Ying LEE & Michael GOU, 2019. "Regression Discontinuity Designs with a Continuous Treatment," Discussion papers 19058, Research Institute of Economy, Trade and Industry (RIETI).
    12. Blaise Melly & Rafael Lalive, 2020. "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften dp2016, Universitaet Bern, Departement Volkswirtschaft.
    13. Federico Crippa, 2024. "Manipulation Test for Multidimensional RDD," Papers 2402.10836, arXiv.org.
    14. Yan Zhu & Hongfeng Zhang & Xu He, 2023. "Impact of New and Old Driving Force Conversion on Air Quality: Empirical Analysis Based on RDD," Sustainability, MDPI, vol. 15(4), pages 1-12, February.

  4. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2018. "Inference under Covariate-Adaptive Randomization with Multiple Treatments," Papers 1806.04206, arXiv.org, revised Jan 2019.

    Cited by:

    1. 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.
    2. Browne, Oliver R. & Gazze, Ludovica & Greenstone, Michael & Olga Rostapshova, 2022. "Man vs. Machine : Technological Promise and Political Limits of Automated Regulation Enforcement," The Warwick Economics Research Paper Series (TWERPS) 1440, University of Warwick, Department of Economics.
    3. Yuehao Bai & Joseph P. Romano & Azeem M. Shaikh, 2022. "Inference in Experiments With Matched Pairs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(540), pages 1726-1737, October.
    4. Liang Jiang & Xiaobin Liu & Peter C. B. Phillips & Yichong Zhang, 2020. "Bootstrap Inference for Quantile Treatment Effects in Randomized Experiments with Matched Pairs," Papers 2005.11967, arXiv.org, revised May 2021.
    5. Ruoxuan Xiong & Susan Athey & Mohsen Bayati & Guido Imbens, 2019. "Optimal Experimental Design for Staggered Rollouts," Papers 1911.03764, arXiv.org, revised Sep 2023.
    6. Christina Korting & Carl Lieberman & Jordan Matsudaira & Zhuan Pei & Yi Shen, 2020. "Visual Inference and Graphical Representation in Regression Discontinuity Designs," Working Papers 638, Princeton University, Department of Economics, Industrial Relations Section..
    7. Heß, Simon & Jaimovich, Dany & Schündeln, Matthias, 2021. "Environmental effects of development programs: Experimental evidence from West African dryland forests," Journal of Development Economics, Elsevier, vol. 153(C).
    8. Yujia Gu & Hanzhong Liu & Wei Ma, 2023. "Regression‐based multiple treatment effect estimation under covariate‐adaptive randomization," Biometrics, The International Biometric Society, vol. 79(4), pages 2869-2880, December.
    9. Young, Alwyn, 2019. "Channeling Fisher: randomization tests and the statistical insignificance of seemingly significant experimental results," LSE Research Online Documents on Economics 101401, London School of Economics and Political Science, LSE Library.
    10. 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.
    11. Federico A. Bugni & Ivan A. Canay & Steve McBride, 2023. "Decomposition and Interpretation of Treatment Effects in Settings with Delayed Outcomes," Papers 2302.11505, arXiv.org, revised Oct 2023.
    12. Yuehao Bai & Jizhou Liu & Azeem M. Shaikh & Max Tabord-Meehan, 2023. "On the Efficiency of Finely Stratified Experiments," Papers 2307.15181, arXiv.org, revised Feb 2024.
    13. Guillermo Cruces & Dario Tortarolo & Gonzalo Vazquez-Bare, 2022. "Design of two-stage experiments with an application to spillovers in tax compliance," IFS Working Papers W22/32, Institute for Fiscal Studies.
    14. Maximiliano Lauletta & Martín Rossi & Christian Ruzzier, 2021. "Playing Whac-A-Mole in the Fight against Corruption: Evidence from Random Audits in Brazil," Working Papers 157, Universidad de San Andres, Departamento de Economia, revised Sep 2021.
    15. Liang Jiang & Oliver B. Linton & Haihan Tang & Yichong Zhang, 2022. "Improving Estimation Efficiency via Regression-Adjustment in Covariate-Adaptive Randomizations with Imperfect Compliance," Papers 2201.13004, arXiv.org, revised Jun 2023.
    16. John A. List & Azeem M. Shaikh & Atom Vayalinkal, 2023. "Multiple testing with covariate adjustment in experimental economics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 920-939, September.
    17. Yuehao Bai, 2022. "Optimality of Matched-Pair Designs in Randomized Controlled Trials," Papers 2206.07845, arXiv.org.
    18. Haoge Chang, 2023. "Design-based Estimation Theory for Complex Experiments," Papers 2311.06891, arXiv.org.
    19. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    20. Zhao, Anqi & Ding, Peng, 2021. "Covariate-adjusted Fisher randomization tests for the average treatment effect," Journal of Econometrics, Elsevier, vol. 225(2), pages 278-294.
    21. Liang Jiang & Liyao Li & Ke Miao & Yichong Zhang, 2023. "Adjustment with Many Regressors Under Covariate-Adaptive Randomizations," Papers 2304.08184, arXiv.org, revised Feb 2024.
    22. Yuehao Bai & Jizhou Liu & Max Tabord-Meehan, 2022. "Inference for Matched Tuples and Fully Blocked Factorial Designs," Papers 2206.04157, arXiv.org, revised Nov 2023.

  5. Ivan A. Canay & Andres Santos & Azeem M. Shaikh, 2018. "The wild bootstrap with a "small" number of "large" clusters," CeMMAP working papers CWP27/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. James G. MacKinnon & Matthew D. Webb, 2020. "When and How to Deal with Clustered Errors in Regression Models," Working Paper 1421, Economics Department, Queen's University.
    2. Yong Cai, 2021. "Some Finite Sample Properties of the Sign Test," Papers 2103.01412, arXiv.org, revised Feb 2024.
    3. Hwang, Jungbin, 2021. "Simple and trustworthy cluster-robust GMM inference," Journal of Econometrics, Elsevier, vol. 222(2), pages 993-1023.
    4. Akwasi Ampofo & Terence C Cheng & Firmin Doko Tchatoka, 2021. "Oil extraction and spillover effects into local labour market: Evidence from Ghana," School of Economics and Public Policy Working Papers 2021-03 Classification-O1, University of Adelaide, School of Economics and Public Policy.
    5. Yong Cai, 2021. "A Modified Randomization Test for the Level of Clustering," Papers 2105.01008, arXiv.org, revised Jan 2022.
    6. Laurent Davezies & Xavier D'Haultfoeuille & Yannick Guyonvarch, 2018. "Asymptotic results under multiway clustering," Papers 1807.07925, arXiv.org, revised Aug 2018.

  6. Ivan A. Canay & Vishal Kamat, 2017. "Approximate permutation tests and induced order statistics in the regression discontinuity design," CeMMAP working papers CWP21/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Federico A. Bugni & Ivan A. Canay, 2018. "Testing continuity of a density via g -order statistics in the regression discontinuity design," CeMMAP working papers CWP20/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Marinho Bertanha & Eunyi Chung, 2023. "Permutation Tests at Nonparametric Rates," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(544), pages 2833-2846, October.
    3. Abdulkadiroglu, Atila & Angrist, Joshua & Narita, Yusuke & Pathak, Parag A., 2019. "Breaking Ties: Regression Discontinuity Design Meets Market Design," IZA Discussion Papers 12205, Institute of Labor Economics (IZA).
    4. Takuya Ishihara & Masayuki Sawada, 2020. "Manipulation-Robust Regression Discontinuity Designs," Papers 2009.07551, arXiv.org, revised Oct 2023.
    5. Muñoz, Pablo & Prem, Mounu, 2021. "Managers' Productivity and Recruitment in the Public Sector: The Case of School Principals," SocArXiv 7zn2b, Center for Open Science.
    6. Benjamin Marx & Vincent Pons & Vincent Rollet, 2022. "Electoral Turnovers," Working Papers hal-03812816, HAL.
    7. Purevdorj Tuvaandorj, 2021. "Robust Permutation Tests in Linear Instrumental Variables Regression," Papers 2111.13774, arXiv.org, revised Jun 2023.
    8. Matias D. Cattaneo & Rocio Titiunik & Gonzalo Vazquez-Bare, 2019. "The Regression Discontinuity Design," Papers 1906.04242, arXiv.org, revised Jun 2020.
    9. Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2021. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP16/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Chen, Heng & Fan, Yanqin, 2019. "Identification and wavelet estimation of weighted ATE under discontinuous and kink incentive assignment mechanisms," Journal of Econometrics, Elsevier, vol. 212(2), pages 476-502.
    11. Robin Harding & Mounu Prem & Nelson A. Ruiz & David Vargas, 2021. "Buying a Blind Eye: Campaign Donations, Forbearance, and Deforestation in Colombia," Documentos de Trabajo 19296, Universidad del Rosario.
    12. David M. Kaplan & Matt Goldman, 2018. "Comparing distributions by multiple testing across quantiles or CDF values," Working Papers 1801, Department of Economics, University of Missouri.
    13. Leonardo Bonilla-Mejía & Erika Londoño-Ortega, 2021. "Geographic Isolation and Learning in Rural Schools," Borradores de Economia 1169, Banco de la Republica de Colombia.
    14. Makarin, Alexey & Piqué, Ricardo & Aragón, Fernando, 2020. "National or sub-national parties: Does party geographic scope matter?," Journal of Development Economics, Elsevier, vol. 146(C).
    15. Toshiaki Iizuka & Katsuhiko Nishiyama & Brian Chen & Karen Eggleston, 2017. "False Alarm? Estimating the Marginal Value of Health Signals," NBER Working Papers 23413, National Bureau of Economic Research, Inc.
    16. Zhang, Yali & Li, Wenqi & Wu, Feng, 2020. "Does energy transition improve air quality? Evidence derived from China’s Winter Clean Heating Pilot (WCHP) project," Energy, Elsevier, vol. 206(C).
    17. Andrii Babii & Rohit Kumar, 2019. "Isotonic Regression Discontinuity Designs," Papers 1908.05752, arXiv.org, revised Dec 2020.
    18. Eric Auerbach & Max Tabord-Meehan, 2021. "The Local Approach to Causal Inference under Network Interference," Papers 2105.03810, arXiv.org, revised Jun 2023.
    19. David M. Kaplan & Matt Goldman, 2013. "Comparing distributions by multiple testing across quantiles," Working Papers 1319, Department of Economics, University of Missouri, revised Feb 2018.
    20. 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.
    21. Bonilla-Mejía, Leonardo & Higuera-Mendieta, Iván, 2019. "Protected Areas under Weak Institutions: Evidence from Colombia," World Development, Elsevier, vol. 122(C), pages 585-596.
    22. Cai Yong & Canay Ivan A. & Kim Deborah & Shaikh Azeem M., 2023. "On the Implementation of Approximate Randomization Tests in Linear Models with a Small Number of Clusters," Journal of Econometric Methods, De Gruyter, vol. 12(1), pages 85-103, January.
    23. Heckman, James J. & Pinto, Rodrigo & Shaikh, Azeem M., 2023. "Dealing With Imperfect Randomization: Inference for the Highscope Perry Preschool Program," IZA Discussion Papers 16675, Institute of Labor Economics (IZA).
    24. Giuntella, Osea & Mazzonna, Fabrizio, 2019. "Sunset time and the economic effects of social jetlag: evidence from US time zone borders," Journal of Health Economics, Elsevier, vol. 65(C), pages 210-226.
    25. Zuleika Ferre & Patricia Triunfo & José‐Ignacio Antón, 2023. "Subdermal contraceptive implants and repeat teenage motherhood: Evidence from a major maternity hospital‐based program in Uruguay," Health Economics, John Wiley & Sons, Ltd., vol. 32(12), pages 2679-2693, December.
    26. David Wuepper & Robert Finger, 2023. "Regression discontinuity designs in agricultural and environmental economics," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(1), pages 1-28.
    27. Koki Fusejima & Takuya Ishihara & Masayuki Sawada, 2022. "Joint diagnostic test of regression discontinuity designs: multiple testing problem," Papers 2205.04345, arXiv.org, revised Oct 2023.
    28. Federico A. Bugni & Jia Li & Qiyuan Li, 2020. "Permutation-based tests for discontinuities in event studies," Papers 2007.09837, arXiv.org, revised Jul 2022.
    29. Yingying DONG & Ying-Ying LEE & Michael GOU, 2019. "Regression Discontinuity Designs with a Continuous Treatment," Discussion papers 19058, Research Institute of Economy, Trade and Industry (RIETI).
    30. Blaise Melly & Rafael Lalive, 2020. "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften dp2016, Universitaet Bern, Departement Volkswirtschaft.
    31. Sida Peng & Yang Ning, 2019. "Regression Discontinuity Design under Self-selection," Papers 1911.09248, arXiv.org.
    32. Federico Crippa, 2024. "Manipulation Test for Multidimensional RDD," Papers 2402.10836, arXiv.org.
    33. Heng Chen & Kim Huynh & Oz Shy, 2017. "Cash Versus Card: Payment Discontinuities and the Burden of Holding Coins," Staff Working Papers 17-47, Bank of Canada.
    34. Fernando Aragón & Ricardo Pique, 2020. "Better the devil you know? Reelected politicians and policy outcomes under no term limits," Public Choice, Springer, vol. 182(1), pages 1-16, January.
    35. Adam C. Sales & Ben B. Hansen, 2020. "Limitless Regression Discontinuity," Journal of Educational and Behavioral Statistics, , vol. 45(2), pages 143-174, April.
    36. Yang Lixiong, 2019. "Regression discontinuity designs with unknown state-dependent discontinuity points: estimation and testing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-18, April.

  7. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2016. "Inference under Covariate-Adaptive Randomization," CeMMAP working papers CWP21/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2016. "Inference under Covariate-Adaptive Randomization," CeMMAP working papers CWP21/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. 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.
    3. Federico A. Bugni & Mengsi Gao, 2021. "Inference under Covariate-Adaptive Randomization with Imperfect Compliance," Papers 2102.03937, arXiv.org, revised Jul 2023.
    4. Jizhou Liu, 2023. "Inference for Two-stage Experiments under Covariate-Adaptive Randomization," Papers 2301.09016, arXiv.org, revised Oct 2023.
    5. Tymon S{l}oczy'nski, 2018. "Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights," Papers 1810.01576, arXiv.org, revised May 2020.
    6. Yuehao Bai & Joseph P. Romano & Azeem M. Shaikh, 2022. "Inference in Experiments With Matched Pairs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(540), pages 1726-1737, October.
    7. Liang Jiang & Xiaobin Liu & Peter C. B. Phillips & Yichong Zhang, 2020. "Bootstrap Inference for Quantile Treatment Effects in Randomized Experiments with Matched Pairs," Papers 2005.11967, arXiv.org, revised May 2021.
    8. Ruoxuan Xiong & Susan Athey & Mohsen Bayati & Guido Imbens, 2019. "Optimal Experimental Design for Staggered Rollouts," Papers 1911.03764, arXiv.org, revised Sep 2023.
    9. Tymon Sloczynski, 2018. "A General Weighted Average Representation of the Ordinary and Two-Stage Least Squares Estimands," Working Papers 125, Brandeis University, Department of Economics and International Business School.
    10. Yuehao Bai & Meng Hsuan Hsieh & Jizhou Liu & Max Tabord-Meehan, 2022. "Revisiting the Analysis of Matched-Pair and Stratified Experiments in the Presence of Attrition," Papers 2209.11840, arXiv.org, revised Oct 2023.
    11. Ivan A Canay & Vishal Kamat, 2018. "Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(3), pages 1577-1608.
    12. Simon Heß, 2017. "Randomization inference with Stata: A guide and software," Stata Journal, StataCorp LP, vol. 17(3), pages 630-651, September.
    13. Yujia Gu & Hanzhong Liu & Wei Ma, 2023. "Regression‐based multiple treatment effect estimation under covariate‐adaptive randomization," Biometrics, The International Biometric Society, vol. 79(4), pages 2869-2880, December.
    14. Guiteras, Raymond P. & Levine, David I. & Polley, Thomas H., 2016. "The pursuit of balance in sequential randomized trials," Development Engineering, Elsevier, vol. 1(C), pages 12-25.
    15. Ting Ye & Jun Shao, 2020. "Robust tests for treatment effect in survival analysis under covariate‐adaptive randomization," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1301-1323, December.
    16. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Aug 2023.
    17. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
    18. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2017. "Inference under covariate-adaptive randomization with multiple treatments," CeMMAP working papers 34/17, Institute for Fiscal Studies.
    19. Young, Alwyn, 2019. "Channeling Fisher: randomization tests and the statistical insignificance of seemingly significant experimental results," LSE Research Online Documents on Economics 101401, London School of Economics and Political Science, LSE Library.
    20. Max Cytrynbaum, 2023. "Covariate Adjustment in Stratified Experiments," Papers 2302.03687, arXiv.org, revised Sep 2023.
    21. Luis Alvarez & Bruno Ferman & Raoni Oliveira, 2022. "Randomization Inference Tests for Shift-Share Designs," Papers 2206.00999, arXiv.org.
    22. Isaiah Andrews & Emily Oster, 2017. "A Simple Approximation for Evaluating External Validity Bias," NBER Working Papers 23826, National Bureau of Economic Research, Inc.
    23. John List & Azeem Shaikh & Yang Xu, 2016. "Multiple Hypothesis Testing in Experimental Economics," Artefactual Field Experiments 00402, The Field Experiments Website.
    24. Max Tabord-Meehan, 2018. "Stratification Trees for Adaptive Randomization in Randomized Controlled Trials," Papers 1806.05127, arXiv.org, revised Jul 2022.
    25. Okeke, Edward N. & Abubakar, Isa S., 2020. "Healthcare at the beginning of life and child survival: Evidence from a cash transfer experiment in Nigeria," Journal of Development Economics, Elsevier, vol. 143(C).
    26. Edward N. Okeke, 2021. "Money and my mind: Maternal cash transfers and mental health," Health Economics, John Wiley & Sons, Ltd., vol. 30(11), pages 2879-2904, November.
    27. 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.
    28. Abhijit Banerjee & Sylvain Chassang & Sergio Montero & Erik Snowberg, 2017. "A Theory of Experimenters," CESifo Working Paper Series 6678, CESifo.
    29. Heckman, James J. & Pinto, Rodrigo & Shaikh, Azeem M., 2023. "Dealing With Imperfect Randomization: Inference for the Highscope Perry Preschool Program," IZA Discussion Papers 16675, Institute of Labor Economics (IZA).
    30. Federico A. Bugni & Ivan A. Canay & Steve McBride, 2023. "Decomposition and Interpretation of Treatment Effects in Settings with Delayed Outcomes," Papers 2302.11505, arXiv.org, revised Oct 2023.
    31. Yang, Haoyu & Qin, Yichen & Wang, Fan & Li, Yang & Hu, Feifang, 2023. "Balancing covariates in multi-arm trials via adaptive randomization," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    32. Ferman, Bruno, 2021. "Matching estimators with few treated and many control observations," Journal of Econometrics, Elsevier, vol. 225(2), pages 295-307.
    33. Chung, EunYi & Olivares, Mauricio, 2021. "Permutation test for heterogeneous treatment effects with a nuisance parameter," Journal of Econometrics, Elsevier, vol. 225(2), pages 148-174.
    34. Liang Jiang & Oliver B. Linton & Haihan Tang & Yichong Zhang, 2022. "Improving Estimation Efficiency via Regression-Adjustment in Covariate-Adaptive Randomizations with Imperfect Compliance," Papers 2201.13004, arXiv.org, revised Jun 2023.
    35. John A. List & Azeem M. Shaikh & Atom Vayalinkal, 2023. "Multiple testing with covariate adjustment in experimental economics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 920-939, September.
    36. Yuehao Bai, 2022. "Optimality of Matched-Pair Designs in Randomized Controlled Trials," Papers 2206.07845, arXiv.org.
    37. Haoge Chang, 2023. "Design-based Estimation Theory for Complex Experiments," Papers 2311.06891, arXiv.org.
    38. Zhao, Anqi & Ding, Peng, 2021. "Covariate-adjusted Fisher randomization tests for the average treatment effect," Journal of Econometrics, Elsevier, vol. 225(2), pages 278-294.
    39. Max Cytrynbaum, 2021. "Optimal Stratification of Survey Experiments," Papers 2111.08157, arXiv.org, revised Aug 2023.
    40. Liang Jiang & Liyao Li & Ke Miao & Yichong Zhang, 2023. "Adjustment with Many Regressors Under Covariate-Adaptive Randomizations," Papers 2304.08184, arXiv.org, revised Feb 2024.
    41. Yuehao Bai & Jizhou Liu & Max Tabord-Meehan, 2022. "Inference for Matched Tuples and Fully Blocked Factorial Designs," Papers 2206.04157, arXiv.org, revised Nov 2023.
    42. Tong Wang & Wei Ma, 2021. "The impact of misclassification on covariate‐adaptive randomized clinical trials," Biometrics, The International Biometric Society, vol. 77(2), pages 451-464, June.

  8. Ivan A. Canay & Azeem M. Shaikh, 2016. "Practical and theoretical advances in inference for partially identified models," CeMMAP working papers CWP05/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Matthew A. Masten & Alexandre Poirier, 2017. "Identification of Treatment Effects under Conditional Partial Independence," Papers 1707.09563, arXiv.org.
    2. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    3. Battey, Heather & Feng, Qiang & Smith, Richard J., 2016. "Improving confidence set estimation when parameters are weakly identified," Statistics & Probability Letters, Elsevier, vol. 118(C), pages 117-123.
    4. Dzemski, Andreas & Okui, Ryo, 2018. "Confidence Set for Group Membership," Working Papers in Economics 727, University of Gothenburg, Department of Economics.
    5. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Aug 2023.
    6. Peter Z. Schochet, 2020. "The Complier Average Causal Effect Parameter for Multiarmed RCTs," Evaluation Review, , vol. 44(5-6), pages 410-436, October.
    7. Oliver R. Cutbill & Rami V. Tabri, 2022. "The Impossibility of Testing for Dependence Using Kendall’s Ƭ Under Missing Data of Unknown Form," Working Papers 2022-03, University of Sydney, School of Economics.
    8. Machado, Cecilia & Shaikh, Azeem M. & Vytlacil, Edward J., 2019. "Instrumental variables and the sign of the average treatment effect," Journal of Econometrics, Elsevier, vol. 212(2), pages 522-555.
    9. Matthew Masten & Alexandre Poirier, 2016. "Partial independence in nonseparable models," CeMMAP working papers 26/16, Institute for Fiscal Studies.
    10. Matthew Masten & Alexandre Poirier, 2017. "Inference on breakdown frontiers," CeMMAP working papers 20/17, Institute for Fiscal Studies.
    11. Andreas Dzemski & Ryo Okui, 2017. "Confidence set for group membership," Papers 1801.00332, arXiv.org, revised Nov 2023.

  9. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Inference for functions of partially identified parameters in moment inequality models," CeMMAP working papers CWP05/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Ivan A. Canay & Azeem M. Shaikh, 2016. "Practical and theoretical advances in inference for partially identified models," CeMMAP working papers 05/16, Institute for Fiscal Studies.
    2. 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.
    3. Fack, Gabrielle & Grenet, Julien & He, YingHua, 2015. "Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions," CEPR Discussion Papers 10907, C.E.P.R. Discussion Papers.
    4. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2013. "Specification tests for partially identified models defined by moment inequalities," CeMMAP working papers 01/13, Institute for Fiscal Studies.
    5. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    6. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confi dence Intervals for Projections of Partially Identi fied Parameters," Boston University - Department of Economics - Working Papers Series wp2016-001, Boston University - Department of Economics.
    7. Battey, Heather & Feng, Qiang & Smith, Richard J., 2016. "Improving confidence set estimation when parameters are weakly identified," Statistics & Probability Letters, Elsevier, vol. 118(C), pages 117-123.
    8. Victor Chernozhukov & Whitney K. Newey & Andres Santos, 2015. "Constrained conditional moment restriction models," CeMMAP working papers CWP59/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Arkadiusz Szydlowski, 2015. "Endogenous Censoring in the Mixed Proportional Hazard Model with an Application to Optimal Unemployment Insurance," Discussion Papers in Economics 15/06, Division of Economics, School of Business, University of Leicester.

  10. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2013. "Specification tests for partially identified models defined by moment inequalities," CeMMAP working papers CWP01/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Matilde Bombardini & Bingjing Li & Francesco Trebbi, 2023. "Did US Politicians Expect the China Shock?," American Economic Review, American Economic Association, vol. 113(1), pages 174-209, January.
    2. Ivan A. Canay & Azeem M. Shaikh, 2016. "Practical and theoretical advances in inference for partially identified models," CeMMAP working papers 05/16, Institute for Fiscal Studies.
    3. Prosper Dovonon & Silvia Gonçalves, 2014. "Bootstrapping the GMM overidentification test Under first-order underidentification," CIRANO Working Papers 2014s-25, CIRANO.
    4. Yuichi Kitamura & Jorg Stoye, 2016. "Nonparametric analysis of random utility models," CeMMAP working papers CWP27/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Cattaneo, Matias D & Ma, Xinwei & Masatlioglu, Yusufcan & Suleymanov, Elchin, 2020. "A Random Attention Model," University of California at San Diego, Economics Working Paper Series qt34m788c3, Department of Economics, UC San Diego.
    6. Fack, Gabrielle & Grenet, Julien & He, YingHua, 2015. "Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions," CEPR Discussion Papers 10907, C.E.P.R. Discussion Papers.
    7. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Inference for functions of partially identified parameters in moment inequality models," CeMMAP working papers 22/14, Institute for Fiscal Studies.
    8. Russell Davidson & Victoria Zinde‐Walsh, 2017. "Advances in specification testing," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(5), pages 1595-1631, December.
    9. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    10. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confi dence Intervals for Projections of Partially Identi fied Parameters," Boston University - Department of Economics - Working Papers Series wp2016-001, Boston University - Department of Economics.
    11. Jorg Stoye, 2020. "A Simple, Short, but Never-Empty Confidence Interval for Partially Identified Parameters," Papers 2010.10484, arXiv.org, revised Dec 2020.
    12. Levon Barseghyan & Maura Coughlin & Francesca Molinari & Joshua C. Teitelbaum, 2019. "Heterogeneous Choice Sets and Preferences," Papers 1907.02337, arXiv.org, revised Feb 2021.
    13. Hong, Han & Li, Jessie, 2018. "The numerical delta method," Journal of Econometrics, Elsevier, vol. 206(2), pages 379-394.
    14. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Matthew A. Masten & Alexandre Poirier, 2021. "Salvaging Falsified Instrumental Variable Models," Econometrica, Econometric Society, vol. 89(3), pages 1449-1469, May.
    16. Arkadiusz Szydlowski, 2015. "Endogenous Censoring in the Mixed Proportional Hazard Model with an Application to Optimal Unemployment Insurance," Discussion Papers in Economics 15/06, Division of Economics, School of Business, University of Leicester.
    17. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    18. Gualdani, Cristina, 2018. "An Econometric Model of Network Formation with an Application to Board Interlocks between Firms," TSE Working Papers 17-898, Toulouse School of Economics (TSE), revised Jul 2019.
    19. Kristin F. Butcher & Kyung H. Park & Anne Morrison Piehl, 2017. "Comparing Apples to Oranges: Differences in Women’s and Men’s Incarceration and Sentencing Outcomes," Journal of Labor Economics, University of Chicago Press, vol. 35(S1), pages 201-234.
    20. Fan, Yanqin & Liu, Ruixuan, 2018. "Partial identification and inference in censored quantile regression," Journal of Econometrics, Elsevier, vol. 206(1), pages 1-38.
    21. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    22. JoonHwan Cho & Thomas M. Russell, 2018. "Simple Inference on Functionals of Set-Identified Parameters Defined by Linear Moments," Papers 1810.03180, arXiv.org, revised May 2023.

  11. Ivan A. Canay & Andres Santos & Azeem M. Shaikh, 2012. "On the testability of identification in some nonparametric models with endogeneity," CeMMAP working papers CWP18/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Davezies, Laurent & Le Barbanchon, Thomas, 2017. "Regression Discontinuity Design with Continuous Measurement Error in the Running Variable," IZA Discussion Papers 10801, Institute of Labor Economics (IZA).
    2. Juan Carlos Escanciano & Wei Li, 2018. "Optimal Linear Instrumental Variables Approximations," Papers 1805.03275, arXiv.org, revised Feb 2020.
    3. Marinho Bertanha & Marcelo J. Moreira, 2016. "Impossible Inference in Econometrics: Theory and Applications," Papers 1612.02024, arXiv.org, revised Feb 2020.
    4. Joachim Freyberger & Joel L. Horowitz, 2013. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers CWP31/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
    6. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers 40/15, Institute for Fiscal Studies.
    7. Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999, Cowles Foundation for Research in Economics, Yale University.
    8. Cui, Liyuan & Hong, Yongmiao & Li, Yingxing, 2021. "Solving Euler equations via two-stage nonparametric penalized splines," Journal of Econometrics, Elsevier, vol. 222(2), pages 1024-1056.
    9. Rodrigo Adao & Arnaud Costinot & Dave Donaldson, 2015. "Nonparametric Counterfactual Predictions in Neoclassical Models of International Trade," NBER Working Papers 21401, National Bureau of Economic Research, Inc.
    10. Marek Jarocinski & Albert Marcet, 2013. "Priors about Observables in Vector Autoregressions," UFAE and IAE Working Papers 929.13, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    11. S. Centorrino & J. S. Racine, 2016. "Semiparametric Varying Coefficient Models with Endogenous Covariates," Department of Economics Working Papers 2016-02, McMaster University.
    12. Manuel Arellano & Stéphane Bonhomme, 2017. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Working Papers wp2017_1703, CEMFI.
    13. Zheng Fang & Juwon Seo, 2019. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Papers 1910.07689, arXiv.org, revised Sep 2021.
    14. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers CWP06/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Denis Chetverikov & Daniel Wilhelm, 2017. "Nonparametric instrumental variable estimation under monotonicity," CeMMAP working papers CWP14/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Caetano, Carolina & Rothe, Christoph & Yıldız, Neşe, 2016. "A discontinuity test for identification in triangular nonseparable models," Journal of Econometrics, Elsevier, vol. 193(1), pages 113-122.
    17. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers 34/15, Institute for Fiscal Studies.
    18. Moretti, Enrico & Kline, Patrick, 2013. "Local Economic Development, Agglomeration Economies, and the Big Push: 100 Years of Evidence from the Tennessee Valley Authorit," CEPR Discussion Papers 9593, C.E.P.R. Discussion Papers.
    19. Denis Chetverikov & Daniel Wilhelm, 2015. "Nonparametric instrumental variable estimation under monotonicity," CeMMAP working papers 39/15, Institute for Fiscal Studies.
    20. Hu, Yingyao & Schennach, Susanne & Shiu, Ji-Liang, 2022. "Identification of nonparametric monotonic regression models with continuous nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 226(2), pages 269-294.
    21. Yilin Li & Wang Miao & Ilya Shpitser & Eric J. Tchetgen Tchetgen, 2023. "A self‐censoring model for multivariate nonignorable nonmonotone missing data," Biometrics, The International Biometric Society, vol. 79(4), pages 3203-3214, December.
    22. Ben Deaner, 2019. "Nonparametric Instrumental Variables Estimation Under Misspecification," Papers 1901.01241, arXiv.org, revised Dec 2022.
    23. Hu, Yingyao, 2017. "The Econometrics of Unobservables -- Latent Variable and Measurement Error Models and Their Applications in Empirical Industrial Organization and Labor Economics [The Econometrics of Unobservables]," Economics Working Paper Archive 64578, The Johns Hopkins University,Department of Economics, revised 2021.
    24. Andrews, Donald W.K., 2017. "Examples of L2-complete and boundedly-complete distributions," Journal of Econometrics, Elsevier, vol. 199(2), pages 213-220.
    25. Daniel Wilhelm, 2019. "Testing for the presence of measurement error," CeMMAP working papers CWP48/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Babii, Andrii, 2020. "Honest Confidence Sets In Nonparametric Iv Regression And Other Ill-Posed Models," Econometric Theory, Cambridge University Press, vol. 36(4), pages 658-706, August.
    27. Victor Chernozhukov & Whitney K. Newey & Andres Santos, 2015. "Constrained conditional moment restriction models," CeMMAP working papers CWP59/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    28. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers CWP37/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2022. "Inference on Strongly Identified Functionals of Weakly Identified Functions," Papers 2208.08291, arXiv.org, revised Jun 2023.
    30. Joachim Freyberger & Joel L. Horowitz, 2012. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers CWP15/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    31. Centorrino Samuele & Feve Frederique & Florens Jean-Pierre, 2017. "Additive Nonparametric Instrumental Regressions: A Guide to Implementation," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-25, January.
    32. Andrew Chesher & Adam Rosen, 2013. "Generalized instrumental variable models," CeMMAP working papers CWP43/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    33. Krief, Jerome M., 2017. "Direct instrumental nonparametric estimation of inverse regression functions," Journal of Econometrics, Elsevier, vol. 201(1), pages 95-107.
    34. Loh, Isaac, 2023. "Genericity of the completeness condition with constrained instruments," Economics Letters, Elsevier, vol. 224(C).
    35. Wang, Ao, 2021. "A BLP Demand Model of Product-Level Market Shares with Complementarity," The Warwick Economics Research Paper Series (TWERPS) 1351, University of Warwick, Department of Economics.
    36. Pietro Tebaldi & Alexander Torgovitsky & Hanbin Yang, 2019. "Nonparametric Estimates of Demand in the California Health Insurance Exchange," NBER Working Papers 25827, National Bureau of Economic Research, Inc.
    37. Matthew A. Masten & Alexandre Poirier, 2021. "Salvaging Falsified Instrumental Variable Models," Econometrica, Econometric Society, vol. 89(3), pages 1449-1469, May.
    38. Yu Zhu, 2020. "Inference in nonparametric/semiparametric moment equality models with shape restrictions," Quantitative Economics, Econometric Society, vol. 11(2), pages 609-636, May.
    39. Jason R. Blevins & Wei Shi & Donald R. Haurin & Stephanie Moulton, 2020. "A Dynamic Discrete Choice Model Of Reverse Mortgage Borrower Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(4), pages 1437-1477, November.
    40. Rodrigo Adão & Costas Arkolakis & Sharat Ganapati, 2020. "Aggregate Implications of Firm Heterogeneity: A Nonparametric Analysis of Monopolistic Competition Trade Models," NBER Working Papers 28081, National Bureau of Economic Research, Inc.
    41. Sasaki, Yuya, 2015. "Heterogeneity and selection in dynamic panel data," Journal of Econometrics, Elsevier, vol. 188(1), pages 236-249.
    42. Hu, Yingyao & Yao, Jiaxiong, 2022. "Illuminating economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 359-378.
    43. Chen, Qihui, 2021. "Robust and optimal estimation for partially linear instrumental variables models with partial identification," Journal of Econometrics, Elsevier, vol. 221(2), pages 368-380.
    44. Hu, Yingyao & Schennach, Susanne M. & Shiu, Ji-Liang, 2017. "Injectivity of a class of integral operators with compactly supported kernels," Journal of Econometrics, Elsevier, vol. 200(1), pages 48-58.
    45. Nail Kashaev, 2022. "Identification and Estimation of Multinomial Choice Models with Latent Special Covariates," University of Western Ontario, Departmental Research Report Series 20224, University of Western Ontario, Department of Economics.
    46. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    47. Joachim Freyberger & Joel L. Horowitz, 2013. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers 31/13, Institute for Fiscal Studies.
    48. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
    49. Christoph Breunig & Peter Haan, 2018. "Nonparametric Regression with Selectively Missing Covariates," Papers 1810.00411, arXiv.org, revised Oct 2020.
    50. Takahiro Hoshino & Keisuke Takahata, 2018. "Identification of heterogeneous treatment effects as a function of potential untreated outcome under the nonignorable assignment condition," Keio-IES Discussion Paper Series 2018-005, Institute for Economics Studies, Keio University.
    51. Denis Chetverikov & Daniel Wilhelm, 2016. "Nonparametric instrumental variable estimation under monotonicity," CeMMAP working papers 48/16, Institute for Fiscal Studies.
    52. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers 37/13, Institute for Fiscal Studies.
    53. Joachim Freyberger & Joel L. Horowitz, 2012. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers 15/12, Institute for Fiscal Studies.

  12. Ivan Canay & Taisuke Otsu, 2011. "Hodges-Lehmann Optimality for Testing Moment," Cowles Foundation Discussion Papers 1789, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Canay, Ivan A., 2010. "EL inference for partially identified models: Large deviations optimality and bootstrap validity," Journal of Econometrics, Elsevier, vol. 156(2), pages 408-425, June.
    2. Otsu, Taisuke, 2010. "On Bahadur efficiency of empirical likelihood," Journal of Econometrics, Elsevier, vol. 157(2), pages 248-256, August.

Articles

  1. Bugni, Federico A. & Canay, Ivan A., 2021. "Testing continuity of a density via g-order statistics in the regression discontinuity design," Journal of Econometrics, Elsevier, vol. 221(1), pages 138-159.
    See citations under working paper version above.
  2. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2019. "Inference under covariate‐adaptive randomization with multiple treatments," Quantitative Economics, Econometric Society, vol. 10(4), pages 1747-1785, November.
    See citations under working paper version above.
  3. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2018. "Inference Under Covariate-Adaptive Randomization," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(524), pages 1784-1796, October.
    See citations under working paper version above.
  4. Ivan A Canay & Vishal Kamat, 2018. "Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(3), pages 1577-1608.
    See citations under working paper version above.
  5. Ivan A. Canay & Joseph P. Romano & Azeem M. Shaikh, 2017. "Randomization Tests Under an Approximate Symmetry Assumption," Econometrica, Econometric Society, vol. 85, pages 1013-1030, May.

    Cited by:

    1. James G. MacKinnon & Matthew D. Webb, 2019. "Randomization Inference For Difference-in-differences With Few Treated Clusters," Working Paper 1355, Economics Department, Queen's University.
    2. Michael P. Leung, 2020. "Dependence-Robust Inference Using Resampled Statistics," Papers 2002.02097, arXiv.org, revised Aug 2021.
    3. Federico A. Bugni & Ivan A. Canay, 2018. "Testing continuity of a density via g -order statistics in the regression discontinuity design," CeMMAP working papers CWP20/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Ivan A. Canay & Vishal Kamat, 2017. "Approximate permutation tests and induced order statistics in the regression discontinuity design," CeMMAP working papers 21/17, Institute for Fiscal Studies.
    5. James G. MacKinnon & Matthew D. Webb, 2020. "When and How to Deal with Clustered Errors in Regression Models," Working Paper 1421, Economics Department, Queen's University.
    6. Purevdorj Tuvaandorj, 2021. "Robust Permutation Tests in Linear Instrumental Variables Regression," Papers 2111.13774, arXiv.org, revised Jun 2023.
    7. Sylvain Chabé-Ferret & Philippe Le Coent & Caroline Lefebvre & Raphaële Préget & François Salanié & Julie Subervie & Sophie S. Thoyer, 2023. "When Nudges backfire : Evidence from a Randomized Field Experiment to Boost Biological Pest Control," Working Papers hal-03971193, HAL.
    8. Brendan K. Beare & Juwon Seo, 2019. "Randomization tests of copula symmetry," Papers 1911.05307, arXiv.org.
    9. Uri Gneezy & John A. List & Jeffrey A. Livingston & Xiangdong Qin & Sally Sadoff & Yang Xu, 2019. "Measuring Success in Education: The Role of Effort on the Test Itself," American Economic Review: Insights, American Economic Association, vol. 1(3), pages 291-308, December.
    10. James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2022. "Cluster-Robust Inference: A Guide to Empirical Practice," Papers 2205.03285, arXiv.org.
    11. James G. MacKinnon & Matthew D. Webb, 2017. "Pitfalls When Estimating Treatment Effects Using Clustered Data," Working Paper 1387, Economics Department, Queen's University.
    12. Rustam Ibragimov & Paul Kattuman & Anton Skrobotov, 2021. "Robust Inference on Income Inequality: $t$-Statistic Based Approaches," Papers 2105.05335, arXiv.org, revised Nov 2021.
    13. Wang, Wenjie, 2021. "Wild Bootstrap for Instrumental Variables Regression with Weak Instruments and Few Clusters," MPRA Paper 106227, University Library of Munich, Germany.
    14. Ivan A Canay & Vishal Kamat, 2018. "Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(3), pages 1577-1608.
    15. Ivan A. Canay & Andres Santos & Azeem M. Shaikh, 2018. "The wild bootstrap with a "small" number of "large" clusters," CeMMAP working papers CWP27/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Yusuke Narita, 2020. "A Theory of Quasi-Experimental Evaluation of School Quality," Working Papers 2020-085, Human Capital and Economic Opportunity Working Group.
    17. Andreas Hagemann, 2019. "Permutation inference with a finite number of heterogeneous clusters," Papers 1907.01049, arXiv.org, revised Feb 2023.
    18. Timothy Conley & Silvia Gonçalves & Christian Hansen, 2018. "Inference with Dependent Data in Accounting and Finance Applications," Journal of Accounting Research, Wiley Blackwell, vol. 56(4), pages 1139-1203, September.
    19. Bruce E. Hansen & Seojeong Jay Lee, 2017. "Asymptotic Theory for Clustered Samples," Discussion Papers 2017-18, School of Economics, The University of New South Wales.
    20. Bruno Ferman, 2023. "Inference in difference‐in‐differences: How much should we trust in independent clusters?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 358-369, April.
    21. Yong Cai, 2021. "Some Finite Sample Properties of the Sign Test," Papers 2103.01412, arXiv.org, revised Feb 2024.
    22. Jesse Hemerik & Jelle J. Goeman & Livio Finos, 2020. "Robust testing in generalized linear models by sign flipping score contributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 841-864, July.
    23. Yong Cai, 2021. "Panel Data with Unknown Clusters," Papers 2106.05503, arXiv.org, revised Jan 2022.
    24. Cai Yong & Canay Ivan A. & Kim Deborah & Shaikh Azeem M., 2023. "On the Implementation of Approximate Randomization Tests in Linear Models with a Small Number of Clusters," Journal of Econometric Methods, De Gruyter, vol. 12(1), pages 85-103, January.
    25. Hwang, Jungbin, 2021. "Simple and trustworthy cluster-robust GMM inference," Journal of Econometrics, Elsevier, vol. 222(2), pages 993-1023.
    26. Heckman, James J. & Pinto, Rodrigo & Shaikh, Azeem M., 2023. "Dealing With Imperfect Randomization: Inference for the Highscope Perry Preschool Program," IZA Discussion Papers 16675, Institute of Labor Economics (IZA).
    27. Luis Alvarez & Bruno Ferman, 2020. "Inference in Difference-in-Differences with Few Treated Units and Spatial Correlation," Papers 2006.16997, arXiv.org, revised Apr 2023.
    28. Michael P. Leung, 2023. "Network Cluster‐Robust Inference," Econometrica, Econometric Society, vol. 91(2), pages 641-667, March.
    29. Chen, Qiang & Yan, Guanpeng, 2023. "A mixed placebo test for synthetic control method," Economics Letters, Elsevier, vol. 224(C).
    30. Valentin Verdier, 2020. "Estimation and Inference for Linear Models with Two-Way Fixed Effects and Sparsely Matched Data," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 1-16, March.
    31. Yong Cai, 2021. "A Modified Randomization Test for the Level of Clustering," Papers 2105.01008, arXiv.org, revised Jan 2022.
    32. Yusuke Narita, 2021. "A Theory of Quasi-Experimental Evaluation of School Quality," Management Science, INFORMS, vol. 67(8), pages 4982-5010, August.
    33. Ferman, Bruno, 2021. "Matching estimators with few treated and many control observations," Journal of Econometrics, Elsevier, vol. 225(2), pages 295-307.
    34. Johannes W. Ligtenberg, 2023. "Inference in IV models with clustered dependence, many instruments and weak identification," Papers 2306.08559, arXiv.org, revised Mar 2024.
    35. Stefan Beierl & Marina Dodlova, 2022. "Public Works Programmes and Cooperation for the Common Good: Evidence from Malawi," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(3), pages 1264-1284, June.
    36. Jorge González Chapela & Sergi Jiménez-Martín & Judith Vall Castello, 2021. "Education and Internal Migration: Evidence from a Child Labor Reform in Spain," Studies on the Spanish Economy eee2021-34, FEDEA.
    37. Djogbenou, Antoine & Sufana, Razvan, 2024. "Tests for group-specific heterogeneity in high-dimensional factor models," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    38. Hagemann, Andreas, 2019. "Placebo inference on treatment effects when the number of clusters is small," Journal of Econometrics, Elsevier, vol. 213(1), pages 190-209.
    39. Guido W. Imbens & Davide Viviano, 2023. "Identification and Inference for Synthetic Controls with Confounding," Papers 2312.00955, arXiv.org.
    40. Andreas Hagemann, 2023. "Inference on quantile processes with a finite number of clusters," Papers 2301.04687, arXiv.org, revised Jun 2023.
    41. Michael P. Leung & Hyungsik Roger Moon, 2019. "Normal Approximation in Large Network Models," Papers 1904.11060, arXiv.org, revised Feb 2023.
    42. Zhao, Anqi & Ding, Peng, 2021. "Covariate-adjusted Fisher randomization tests for the average treatment effect," Journal of Econometrics, Elsevier, vol. 225(2), pages 278-294.
    43. Andreas Hagemann, 2020. "Inference with a single treated cluster," Papers 2010.04076, arXiv.org.
    44. Juwon Seo, 2018. "Randomization Tests for Equality in Dependence Structure," Papers 1811.02105, arXiv.org.
    45. Ruoyao Shi & Jinyong Hahn, 2016. "Synthetic Control and Inference," Working Papers 201802, University of California at Riverside, Department of Economics, revised Nov 2017.
    46. Mehmet Guven Gunver, 2022. "Norm-Referenced Scoring on Real Data: A Comparative Study of GRiSTEN and STEN," SAGE Open, , vol. 12(2), pages 21582440221, April.
    47. Dmitry Arkhangelsky & Vasily Korovkin, 2020. "On Policy Evaluation with Aggregate Time-Series Shocks," CERGE-EI Working Papers wp657, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    48. Roth, Jonathan & Sant’Anna, Pedro H.C. & Bilinski, Alyssa & Poe, John, 2023. "What’s trending in difference-in-differences? A synthesis of the recent econometrics literature," Journal of Econometrics, Elsevier, vol. 235(2), pages 2218-2244.
    49. Timmermann, Allan & Zhu, Yinchu, 2019. "Comparing Forecasting Performance with Panel Data," CEPR Discussion Papers 13746, C.E.P.R. Discussion Papers.
    50. Alex Chin & Dean Eckles & Johan Ugander, 2022. "Evaluating Stochastic Seeding Strategies in Networks," Management Science, INFORMS, vol. 68(3), pages 1714-1736, March.

  6. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2017. "Inference for subvectors and other functions of partially identified parameters in moment inequality models," Quantitative Economics, Econometric Society, vol. 8(1), pages 1-38, March.

    Cited by:

    1. 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.
    2. Isaiah Andrews & Jonathan Roth & Ariel Pakes, 2023. "Inference for Linear Conditional Moment Inequalities," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(6), pages 2763-2791.
    3. Zheng Fang & Andres Santos & Azeem Shaikh & Alexander Torgovitsky, 2020. "Inference for Large-Scale Linear Systems with Known Coefficients," Working Papers 2020-134, Becker Friedman Institute for Research In Economics.
    4. Kaido, Hiroaki & Molinari, Francesca & Stoye, Jörg, 2022. "Constraint Qualifications In Partial Identification," Econometric Theory, Cambridge University Press, vol. 38(3), pages 596-619, June.
    5. Ashesh Rambachan & Jonathan Roth, 2023. "A More Credible Approach to Parallel Trends," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(5), pages 2555-2591.
    6. Patrik Guggenberge & Frank Kleibergen & Sophocles Mavroeidis, 2021. "A Powerful Subvector Anderson Rubin Test in Linear Instrumental Variables Regression with Conditional Heteroskedasticity," Economics Series Working Papers 960, University of Oxford, Department of Economics.
    7. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    8. Raffaella Giacomini & Toru Kitagawa, 2018. "Robust Bayesian inference for set-identified models," CeMMAP working papers CWP61/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Yuan Liao & Anna Simoni, 2019. "Bayesian inference for partially identified smooth convex models," Post-Print hal-03089881, HAL.
    10. Arkadiusz Szydłowski, 2019. "Endogenous censoring in the mixed proportional hazard model with an application to optimal unemployment insurance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1086-1101, November.
    11. Andrew Chesher & Adam Rosen, 2020. "Econometric Modeling of Interdependent Discrete Choice with Applications to Market Structure," CeMMAP working papers CWP25/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. 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.
    13. Kiviet, Jan F., 2023. "Instrument-free inference under confined regressor endogeneity and mild regularity," Econometrics and Statistics, Elsevier, vol. 25(C), pages 1-22.
    14. Hiroaki Kaido & Yi Zhang, 2019. "Robust Likelihood Ratio Tests for Incomplete Economic Models," Papers 1910.04610, arXiv.org, revised Dec 2019.
    15. Filip Obradovi'c, 2022. "Measuring Diagnostic Test Performance Using Imperfect Reference Tests: A Partial Identification Approach," Papers 2204.00180, arXiv.org, revised Feb 2023.
    16. Victor Chernozhukov & Whitney K. Newey & Andres Santos, 2015. "Constrained conditional moment restriction models," CeMMAP working papers CWP59/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. Jean‐François Houde & Peter Newberry & Katja Seim, 2023. "Nexus Tax Laws and Economies of Density in E‐Commerce: A Study of Amazon's Fulfillment Center Network," Econometrica, Econometric Society, vol. 91(1), pages 147-190, January.
    18. Taehoon Kim & Jacob Schwartz & Kyungchul Song & Yoon-Jae Whang, 2019. "Monte Carlo Inference on Two-Sided Matching Models," Econometrics, MDPI, vol. 7(1), pages 1-15, March.
    19. Joel L. Horowitz, 2018. "Non-asymptotic inference in instrumental variables estimation," CeMMAP working papers CWP52/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    21. Yu Zhu, 2020. "Inference in nonparametric/semiparametric moment equality models with shape restrictions," Quantitative Economics, Econometric Society, vol. 11(2), pages 609-636, May.
    22. Haider, Steven J. & Stephens Jr., Melvin, 2020. "Correcting for Misclassied Binary Regressors Using Instrumental Variables," IZA Discussion Papers 13593, Institute of Labor Economics (IZA).
    23. Sasaki, Yuya & Takahashi, Yuya & Xin, Yi & Hu, Yingyao, 2023. "Dynamic discrete choice models with incomplete data: Sharp identification," Journal of Econometrics, Elsevier, vol. 236(1).
    24. Kiviet, Jan, 2019. "Instrument-free inference under confined regressor endogeneity; derivations and applications," MPRA Paper 96839, University Library of Munich, Germany.
    25. 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.
    26. Joel L. Horowitz, 2018. "Non-Asymptotic Inference in Instrumental Variables Estimation," Papers 1809.03600, arXiv.org.
    27. Hsieh, Yu-Wei & Shi, Xiaoxia & Shum, Matthew, 2022. "Inference on estimators defined by mathematical programming," Journal of Econometrics, Elsevier, vol. 226(2), pages 248-268.
    28. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. JoonHwan Cho & Thomas M. Russell, 2018. "Simple Inference on Functionals of Set-Identified Parameters Defined by Linear Moments," Papers 1810.03180, arXiv.org, revised May 2023.

  7. Bugni, Federico A. & Canay, Ivan A. & Shi, Xiaoxia, 2015. "Specification tests for partially identified models defined by moment inequalities," Journal of Econometrics, Elsevier, vol. 185(1), pages 259-282.
    See citations under working paper version above.
  8. Ivan A. Canay & Andres Santos & Azeem M. Shaikh, 2013. "On the Testability of Identification in Some Nonparametric Models With Endogeneity," Econometrica, Econometric Society, vol. 81(6), pages 2535-2559, November.
    See citations under working paper version above.
  9. Canay, Ivan A. & Otsu, Taisuke, 2012. "Hodges–Lehmann optimality for testing moment conditions," Journal of Econometrics, Elsevier, vol. 171(1), pages 45-53.

    Cited by:

    1. Zeng-Hua Lu, 2020. "Bahadur intercept with applications to one-sided testing," Statistical Papers, Springer, vol. 61(2), pages 645-658, April.

  10. Federico A. Bugni & Ivan A. Canay & Patrik Guggenberger, 2012. "Distortions of Asymptotic Confidence Size in Locally Misspecified Moment Inequality Models," Econometrica, Econometric Society, vol. 80(4), pages 1741-1768, July.

    Cited by:

    1. Kaido, Hiroaki & White, Halbert, 2014. "A two-stage procedure for partially identified models," Journal of Econometrics, Elsevier, vol. 182(1), pages 5-13.
    2. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2013. "Specification tests for partially identified models defined by moment inequalities," CeMMAP working papers 01/13, Institute for Fiscal Studies.
    3. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Inference for functions of partially identified parameters in moment inequality models," CeMMAP working papers 22/14, Institute for Fiscal Studies.
    4. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Oct 2021.
    5. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    6. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Stéphane Bonhomme & Martin Weidner, 2022. "Minimizing sensitivity to model misspecification," Quantitative Economics, Econometric Society, vol. 13(3), pages 907-954, July.
    8. Stéphane Bonhomme & Martin Weidner, 2020. "Minimizing Sensitivity to Model Misspecification," CeMMAP working papers CWP37/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Lavergne, Pascal, 2015. "Assessing the Approximate Validity of Moment Restrictions," TSE Working Papers 15-562, Toulouse School of Economics (TSE), revised May 2020.
    10. Federico A. Bugni & Mehmet Caner & Anders Bredahl Kock & Soumendra Lahiri, 2016. "Inference in partially identified models with many moment inequalities using Lasso," CREATES Research Papers 2016-12, Department of Economics and Business Economics, Aarhus University.
    11. Guggenberger, Patrik, 2012. "A note on the relation between local power and robustness to misspecification," Economics Letters, Elsevier, vol. 116(2), pages 133-135.

  11. Ivan A. Canay, 2011. "A simple approach to quantile regression for panel data," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 368-386, October.

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    1. Galina Besstremyannaya & Sergei Golovan, 2018. "Reconsideration of a simple approach to quantile regression for panel data," Working Papers w0248, Center for Economic and Financial Research (CEFIR).
    2. Tewodros Ayenew Wassie, 2019. "Revisiting the Causal Effects of Exporting on Productivity: Does Price Heterogeneity Matter?," Journal of Industry, Competition and Trade, Springer, vol. 19(2), pages 185-210, June.
    3. Bonaccolto-Töpfer, Marina & Castagnetti, Carolina, 2021. "The COVID-19 pandemic: A threat to higher education?," Discussion Papers 117, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Labour and Regional Economics.
    4. Georgios Bampinas & Panagiotis Konstantinou & Theodore Panagiotidis, 2017. "Inequality, Demographics and the Housing Wealth Effect: Panel Quantile Regression Evidence for the US States," Working Paper series 17-01, Rimini Centre for Economic Analysis.
    5. Brantly Callaway, 2020. "Bounds on Distributional Treatment Effect Parameters using Panel Data with an Application on Job Displacement," Papers 2008.08117, arXiv.org.
    6. Bruno Albuquerque, 2021. "Corporate debt booms, financial constraints, and the investment nexus," CeBER Working Papers 2021-08, Centre for Business and Economics Research (CeBER), University of Coimbra.
    7. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    8. Eric Bartelsman & Sabien Dobbelaere & Bettina Peters, 2013. "Allocation of Human Capital and Innovation at the Frontier: Firm-level Evidence on Germany and the Netherlands," Tinbergen Institute Discussion Papers 13-095/VII, Tinbergen Institute.
    9. Piotr Ciżkowicz & Michał Kowalczuk & Andrzej Rzońca, 2016. "Heterogeneous determinants of local unemployment in Poland," Post-Communist Economies, Taylor & Francis Journals, vol. 28(4), pages 487-519, October.
    10. Elheddad, Mohamed & Benjasak, Chonlakan & Deljavan, Rana & Alharthi, Majed & Almabrok, Jaballa M., 2021. "The effect of the Fourth Industrial Revolution on the environment: The relationship between electronic finance and pollution in OECD countries," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    11. Sinem Koçak & Özge Barış-Tüzemen, 2022. "Impact of the COVID-19 on foreign direct investment inflows in emerging economies: evidence from panel quantile regression," Future Business Journal, Springer, vol. 8(1), pages 1-12, December.
    12. Asako Ohinata & Jan C. Ours, 2016. "Quantile Peer Effects of Immigrant Children at Primary Schools," LABOUR, CEIS, vol. 30(2), pages 135-157, June.
    13. Alessia Matano & Paolo Naticchioni, 2017. "The Extent of Rent Sharing along the Wage Distribution," British Journal of Industrial Relations, London School of Economics, vol. 55(4), pages 751-777, December.
    14. Aysit Tansel & Elif Oznur Kan, 2012. "The Formal/Informal Employment Earnings Gap: Evidence From Turkey," ERC Working Papers 1204, ERC - Economic Research Center, Middle East Technical University, revised Apr 2012.
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    17. Alvarado, Rafael & Cuesta, Lizeth & Kumar, Pavan & Rehman, Abdul & Murshed, Muntasir & Işık, Cem & Vega, Nora & Ochoa-Moreno, Santiago & Tillaguango, Brayan, 2022. "Impact of natural resources on economic progress: Evidence for trading blocs in Latin America using non-linear econometric methods," Resources Policy, Elsevier, vol. 79(C).
    18. Spyridon Boikos & Theodore Panagiotidis & Georgios Voucharas, 2022. "Financial Development, Reforms and Growth," Discussion Paper Series 2022_07, Department of Economics, University of Macedonia, revised Sep 2022.
    19. Meng Lingyan & Ze Zhao & Haider Ali Malik & Asif Razzaq & Hui An & Marria Hassan, 2022. "Asymmetric impact of fiscal decentralization and environmental innovation on carbon emissions: Evidence from highly decentralized countries," Energy & Environment, , vol. 33(4), pages 752-782, June.
    20. Goedele Van den Broeck & Johan Swinnen & Miet Maertens, 2016. "Global value chains, large-scale farming, and poverty: long-term effects in Senegal," Working Papers of Department of Economics, Leuven 546809, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    21. Gnangnon, Sèna Kimm, 2023. "Has the Least developed countries' TRIPS Waiver Delivered on its Promise of Creating a Viable Technological Base?," EconStor Preprints 275666, ZBW - Leibniz Information Centre for Economics.
    22. Stelian STANCU & Eugenia GRECU & Mirela Ionela ACELEANU & Daniela Livia TRAŞCĂ & Claudiu Tiberiu ALBULESCU, 2021. "Does Firm Size Matters for Firm Growth? Evidence from the Romanian Health Sector," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 17-31, December.
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    27. Jingfang Zhang & Emir Malikov, 2023. "Off-Balance Sheet Activities and Scope Economies in U.S. Banking," Papers 2302.14603, arXiv.org.
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    32. Galina Besstremyannaya, 2014. "The efficiency of labor matching and remuneration reforms: a panel data quantile regression approach with endogenous treatment variables," Working Papers w0206, Center for Economic and Financial Research (CEFIR).
    33. Umer Shahzad & Mohamed Elheddad & Julia Swart & Sudeshna Ghosh & Buhari Dogan, 2023. "The role of biomass energy consumption and economic complexity on environmental sustainability in G7 economies," Business Strategy and the Environment, Wiley Blackwell, vol. 32(1), pages 781-801, January.
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    35. Elena Groß & Felicitas Nowak‐Lehmann Danzinger, 2022. "What effect does development aid have on productivity in recipient countries?," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1438-1465, August.
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  12. Canay, Ivan A., 2010. "Simultaneous selection and weighting of moments in GMM using a trapezoidal kernel," Journal of Econometrics, Elsevier, vol. 156(2), pages 284-303, June.

    Cited by:

    1. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
    2. Kuersteiner, Guido M., 2012. "Kernel-weighted GMM estimators for linear time series models," Journal of Econometrics, Elsevier, vol. 170(2), pages 399-421.
    3. Marine Carrasco & Guy Tchuente, 2015. "Regularized LIML for many instruments," Studies in Economics 1515, School of Economics, University of Kent.
    4. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
    5. Martins, Luis F. & Gabriel, Vasco J., 2014. "Linear instrumental variables model averaging estimation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 709-724.

  13. Canay, Ivan A., 2010. "EL inference for partially identified models: Large deviations optimality and bootstrap validity," Journal of Econometrics, Elsevier, vol. 156(2), pages 408-425, June.

    Cited by:

    1. Ivan A. Canay & Azeem M. Shaikh, 2016. "Practical and theoretical advances in inference for partially identified models," CeMMAP working papers 05/16, Institute for Fiscal Studies.
    2. Seojeong Lee, 2014. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for GEL Estimators," Discussion Papers 2014-02, School of Economics, The University of New South Wales.
    3. Donald W.K. Andrews & Patrik Guggenberger, 2007. "Validity of Subsampling and "Plug-in Asymptotic" Inference for Parameters Defined by Moment Inequalities," Cowles Foundation Discussion Papers 1620, Cowles Foundation for Research in Economics, Yale University.
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