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Federico Andres Bugni

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. Federico A. Bugni & Mengsi Gao, 2021. "Inference under Covariate-Adaptive Randomization with Imperfect Compliance," Papers 2102.03937, arXiv.org, revised Jul 2023.

    Cited by:

    1. 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.
    2. 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.

  2. Alexandre Belloni & Federico A. Bugni & Victor Chernozhukov, 2019. "Subvector inference in PI models with many moment inequalities," CeMMAP working papers CWP28/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Victor Aguirregabiria & Allan Collard-Wexler & Stephen P. Ryan, 2021. "Dynamic Games in Empirical Industrial Organization," Papers 2109.01725, arXiv.org, revised Sep 2021.
    2. 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.
    3. Thomas M. Russell, 2020. "Policy Transforms and Learning Optimal Policies," Papers 2012.11046, arXiv.org.

  3. Alexandre Belloni & Federico Bugni & Victor Chernozhukov, 2018. "Subvector Inference in Partially Identified Models with Many Moment Inequalities," Papers 1806.11466, arXiv.org.

    Cited by:

    1. Chesher, Andrew & Kim, Dongwoo & Rosen, Adam M., 2023. "IV methods for Tobit models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1700-1724.
    2. Arie Beresteanu, 2020. "Quantile Regression with Interval Data," Working Paper 6899, Department of Economics, University of Pittsburgh.
    3. Moyu Liao, 2020. "Estimating Economic Models with Testable Assumptions: Theory and Applications," Papers 2002.10415, arXiv.org, revised Mar 2022.
    4. Francesca Molinari, 2020. "Microeconometrics with Partial Identi?cation," CeMMAP working papers CWP15/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. 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.

  4. 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. Takuya Ishihara & Masayuki Sawada, 2020. "Manipulation-Robust Regression Discontinuity Designs," Papers 2009.07551, arXiv.org, revised Oct 2023.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Matias D. Cattaneo & Rocio Titiunik, 2021. "Regression Discontinuity Designs," Papers 2108.09400, arXiv.org, revised Feb 2022.
    7. Atı̇la Abdulkadı̇roğlu & Joshua D. Angrist & Yusuke Narita & Parag Pathak, 2022. "Breaking Ties: Regression Discontinuity Design Meets Market Design," Econometrica, Econometric Society, vol. 90(1), pages 117-151, January.
    8. Babii, Andrii & Kumar, Rohit, 2023. "Isotonic regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 234(2), pages 371-393.
    9. Marinho Bertanha & EunYi Chung, 2021. "Permutation Tests at Nonparametric Rates," Papers 2102.13638, arXiv.org, revised Apr 2022.
    10. 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).
    11. 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.
    12. Blaise Melly & Rafael Lalive, 2020. "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften dp2016, Universitaet Bern, Departement Volkswirtschaft.
    13. 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).
    14. Federico Crippa, 2024. "Manipulation Test for Multidimensional RDD," Papers 2402.10836, arXiv.org.

  5. Federico A. Bugni & Jackson Bunting, 2018. "On the iterated estimation of dynamic discrete choice games," Papers 1802.06665, arXiv.org, revised May 2020.

    Cited by:

    1. Adam Dearing & Jason R. Blevins, 2019. "Efficient and Convergent Sequential Pseudo-Likelihood Estimation of Dynamic Discrete Games," Papers 1912.10488, arXiv.org, revised Nov 2023.
    2. Victor Aguirregabiria & Mathieu Marcoux, 2019. "Imposing equilibrium restrictions in the estimation of dynamic discrete games," Cahiers de recherche 2019-08, Universite de Montreal, Departement de sciences economiques.
    3. Taisuke Otsu & Martin Pesendorfer, 2021. "Equilibrium multiplicity in dynamic games: testing and estimation," STICERD - Econometrics Paper Series 618, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    4. Taisuke Otsu & Martin Pesendorfer, 2023. "Equilibrium multiplicity in dynamic games: Testing and estimation," The Econometrics Journal, Royal Economic Society, vol. 26(1), pages 26-42.
    5. Blevins, Jason R. & Kim, Minhae, 2024. "Nested Pseudo likelihood estimation of continuous-time dynamic discrete games," Journal of Econometrics, Elsevier, vol. 238(2).

  6. Federico A. Bugni & Joel L. Horowitz, 2017. "Permutation tests for equality of distributions of functional data," CeMMAP working papers CWP17/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Marc Ditzhaus & Daniel Gaigall, 2022. "Testing marginal homogeneity in Hilbert spaces with applications to stock market returns," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 749-770, September.

  7. Aucejo, Esteban M. & Bugni, Federico A. & Hotz, V. Joseph, 2017. "Identification and inference on regressions with missing covariate data," LSE Research Online Documents on Economics 62524, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Jakiela,Pamela & Ozier,Owen, 2018. "Gendered language," Policy Research Working Paper Series 8464, The World Bank.
    2. Lixiong Li & D'esir'e K'edagni & Ismael Mourifi'e, 2020. "Discordant Relaxations of Misspecified Models," Papers 2012.11679, arXiv.org, revised Dec 2022.
    3. Francesca Molinari, 2020. "Microeconometrics with Partial Identi?cation," CeMMAP working papers CWP15/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  8. 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.

    Cited by:

    1. Andrew Chesher & Adam Rosen, 2019. "Generalized Instrumental Variable Models, Methods, and Applications," CeMMAP working papers CWP41/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Allen, Roy, 2018. "Testing moment inequalities: Selection versus recentering," Economics Letters, Elsevier, vol. 162(C), pages 124-126.
    3. Nick Koning & Paul Bekker, 2019. "Exact Testing of Many Moment Inequalities Against Multiple Violations," Papers 1904.12775, arXiv.org, revised Jun 2020.

  9. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2015. "Inference under covariate-adaptive randomization," CeMMAP working papers CWP45/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. 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.
    2. Ferman, Bruno, 2017. "Matching Estimators with Few Treated and Many Control Observations," MPRA Paper 78940, University Library of Munich, Germany.
    3. 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.
    4. 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.
    5. Sloczynski, Tymon, 2018. "A General Weighted Average Representation of the Ordinary and Two-Stage Least Squares Estimands," IZA Discussion Papers 11866, Institute of Labor Economics (IZA).
    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. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2017. "Inference under covariate-adaptive randomization," CeMMAP working papers 25/17, Institute for Fiscal Studies.
    8. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Aug 2023.
    9. Max Tabord-Meehan, 2018. "Stratification Trees for Adaptive Randomization in Randomized Controlled Trials," Papers 1806.05127, arXiv.org, revised Jul 2022.
    10. 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.
    11. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2017. "Inference under covariate-adaptive randomization with multiple treatments," CeMMAP working papers CWP34/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. 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.
    13. 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.
    14. 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.
    15. Simon Heß, 2017. "Randomization inference with Stata: A guide and software," Stata Journal, StataCorp LP, vol. 17(3), pages 630-651, September.
    16. Isaiah Andrews & Emily Oster, 2017. "A Simple Approximation for Evaluating External Validity Bias," NBER Working Papers 23826, National Bureau of Economic Research, Inc.
    17. 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.
    18. John A. List & Azeem M. Shaikh & Yang Xu, 2016. "Multiple Hypothesis Testing in Experimental Economics," NBER Working Papers 21875, National Bureau of Economic Research, Inc.
    19. James J. Heckman & Rodrigo Pinto & Azeem Shaikh, 2023. "Dealing with Imperfect Randomization: Inference for the HighScope Perry Preschool Program," Working Papers 2023-031, Human Capital and Economic Opportunity Working Group.
    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. Abhijit Banerjee & Sylvain Chassang & Sergio Montero & Erik Snowberg, 2017. "A Theory of Experimenters," NBER Working Papers 23867, National Bureau of Economic Research, Inc.
    22. 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.
    23. 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).
    24. Haoge Chang, 2023. "Design-based Estimation Theory for Complex Experiments," Papers 2311.06891, arXiv.org.
    25. 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.
    26. Athey, Susan & Imbens, Guido W. & Bayati, Mohsen, 2019. "Optimal Experimental Design for Staggered Rollouts," Research Papers 3837, Stanford University, Graduate School of Business.
    27. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
    28. 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.
    29. Luis Alvarez & Bruno Ferman & Raoni Oliveira, 2022. "Randomization Inference Tests for Shift-Share Designs," Papers 2206.00999, arXiv.org.
    30. 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.
    31. 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.
    32. Max Cytrynbaum, 2023. "Covariate Adjustment in Stratified Experiments," Papers 2302.03687, arXiv.org, revised Sep 2023.
    33. 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.
    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. Yuehao Bai, 2022. "Optimality of Matched-Pair Designs in Randomized Controlled Trials," Papers 2206.07845, arXiv.org.
    36. Max Cytrynbaum, 2021. "Optimal Stratification of Survey Experiments," Papers 2111.08157, arXiv.org, revised Aug 2023.
    37. John List & Azeem Shaikh & Atom Vayalinkal, 2023. "Multiple Testing with Covariate Adjustment in Experimental Economics," Natural Field Experiments 00732, The Field Experiments Website.
    38. Federico A. Bugni & Mengsi Gao, 2021. "Inference under Covariate-Adaptive Randomization with Imperfect Compliance," Papers 2102.03937, arXiv.org, revised Jul 2023.
    39. Jizhou Liu, 2023. "Inference for Two-stage Experiments under Covariate-Adaptive Randomization," Papers 2301.09016, arXiv.org, revised Oct 2023.
    40. 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.
    41. 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).
    42. 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.

  10. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Inference for functions of partially identified parameters in moment inequality models," CeMMAP working papers CWP22/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    2. 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.
    3. Gabrielle Fack & Julien Grenet & Yinghua He, 2019. "Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions," American Economic Review, American Economic Association, vol. 109(4), pages 1486-1529, April.
    4. 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.
    5. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confidence Intervals for Projections of Partially Identified Parameters," Papers 1601.00934, arXiv.org, revised Jun 2019.
    6. Victor Chernozhukov & Whitney K. Newey & Andres Santos, 2015. "Constrained conditional moment restriction models," CeMMAP working papers 59/15, Institute for Fiscal Studies.
    7. 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.
    8. 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.
    9. 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.

  11. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Specification tests for partially identified models defined by moment inequalities," CeMMAP working papers CWP19/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Matilde Bombardini & Bingjing Li & Francesco Trebbi, 2020. "Did U.S. Politicians Expect the China Shock?," NBER Working Papers 28073, National Bureau of Economic Research, Inc.
    2. 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.
    3. 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.
    4. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    5. Gabrielle Fack & Julien Grenet & Yinghua He, 2019. "Beyond Truth-Telling: Preference Estimation with Centralized School Choice and College Admissions," American Economic Review, American Economic Association, vol. 109(4), pages 1486-1529, April.
    6. 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," NBER Working Papers 23079, National Bureau of Economic Research, Inc.
    7. 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.
    8. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confidence Intervals for Projections of Partially Identified Parameters," Papers 1601.00934, arXiv.org, revised Jun 2019.
    9. Fan, Yanqin & Liu, Ruixuan, 2018. "Partial identification and inference in censored quantile regression," Journal of Econometrics, Elsevier, vol. 206(1), pages 1-38.
    10. Dovonon, Prosper & Gonçalves, Sílvia, 2017. "Bootstrapping the GMM overidentification test under first-order underidentification," Journal of Econometrics, Elsevier, vol. 201(1), pages 43-71.
    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. 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.
    13. Levon Barseghyan & Maura Coughlin & Francesca Molinari & Joshua C. Teitelbaum, 2021. "Heterogeneous Choice Sets and Preferences," Econometrica, Econometric Society, vol. 89(5), pages 2015-2048, September.
    14. Russell Davidson & Victoria Zinde-Walsh, 2017. "Advances in specification testing," Canadian Journal of Economics, Canadian Economics Association, vol. 50(5), pages 1595-1631, December.
    15. Francesca Molinari, 2020. "Microeconometrics with Partial Identi?cation," CeMMAP working papers CWP15/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Matias D. Cattaneo & Xinwei Ma & Yusufcan Masatlioglu & Elchin Suleymanov, 2020. "A Random Attention Model," Journal of Political Economy, University of Chicago Press, vol. 128(7), pages 2796-2836.
    17. Hong, Han & Li, Jessie, 2018. "The numerical delta method," Journal of Econometrics, Elsevier, vol. 206(2), pages 379-394.
    18. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    20. 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.
    21. Matthew A. Masten & Alexandre Poirier, 2021. "Salvaging Falsified Instrumental Variable Models," Econometrica, Econometric Society, vol. 89(3), pages 1449-1469, May.
    22. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  12. Peter Arcidiacono & Patrick Bayer & Federico Bugni & Jon James, 2012. "Approximating High-Dimensional Dynamic Models: Sieve Value Function Iteration," Working Papers 12-07, Duke University, Department of Economics.

    Cited by:

    1. Meredith Fowlie & Mar Reguant & Stephen P. Ryan, 2016. "Market-Based Emissions Regulation and Industry Dynamics," Journal of Political Economy, University of Chicago Press, vol. 124(1), pages 249-302.
    2. Panle Jia Barwick & Parag A. Pathak, 2011. "The Costs of Free Entry: An Empirical Study of Real Estate Agents in Greater Boston," NBER Working Papers 17227, National Bureau of Economic Research, Inc.
    3. Shintaro Yamaguchi, 2016. "Effects of Parental Leave Policies on Female Career and Fertility Choices," Department of Economics Working Papers 2016-10, McMaster University.

  13. Federico A Bugni, 2010. "Specification Test for Missing Functional Data," Working Papers 10-41, Duke University, Department of Economics.

    Cited by:

    1. Mojirsheibani, Majid & Shaw, Crystal, 2018. "Classification with incomplete functional covariates," Statistics & Probability Letters, Elsevier, vol. 139(C), pages 40-46.
    2. Kraus, David, 2019. "Inferential procedures for partially observed functional data," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 583-603.
    3. Kraus, David & Stefanucci, Marco, 2020. "Ridge reconstruction of partially observed functional data is asymptotically optimal," Statistics & Probability Letters, Elsevier, vol. 165(C).

Articles

  1. Federico A. Bugni & Joel L. Horowitz, 2021. "Permutation tests for equality of distributions of functional data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 861-877, November.
    See citations under working paper version above.
  2. 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.
  3. Aucejo, Esteban M. & Bugni, Federico A. & Hotz, V. Joseph, 2017. "Identification And Inference On Regressions With Missing Covariate Data," Econometric Theory, Cambridge University Press, vol. 33(1), pages 196-241, February.
    See citations under working paper version above.
  4. Bugni, Federico A., 2016. "Comparison Of Inferential Methods In Partially Identified Models In Terms Of Error In Coverage Probability," Econometric Theory, Cambridge University Press, vol. 32(1), pages 187-242, February.

    Cited by:

    1. Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2016. "Testing many moment inequalities," CeMMAP working papers CWP42/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Aug 2023.
    3. Joseph P. Romano & Azeem M. Shaikh & Michael Wolf, 2014. "A Practical Two‐Step Method for Testing Moment Inequalities," Econometrica, Econometric Society, vol. 82(5), pages 1979-2002, September.
    4. Matias D. Cattaneo & Xinwei Ma & Yusufcan Masatlioglu & Elchin Suleymanov, 2020. "A Random Attention Model," Journal of Political Economy, University of Chicago Press, vol. 128(7), pages 2796-2836.
    5. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    6. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  5. 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.
  6. Bugni, Federico A., 2012. "Specification Test For Missing Functional Data," Econometric Theory, Cambridge University Press, vol. 28(5), pages 959-1002, October.
    See citations under working paper version above.
  7. 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. 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.
    2. 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.
    3. Lavergne, Pascal, 2015. "Assessing the Approximate Validity of Moment Restrictions," TSE Working Papers 15-562, Toulouse School of Economics (TSE), revised May 2020.
    4. 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.
    5. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Oct 2021.
    6. 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.
    7. Stéphane Bonhomme & Martin Weidner, 2022. "Minimizing sensitivity to model misspecification," Quantitative Economics, Econometric Society, vol. 13(3), pages 907-954, July.
    8. Francesca Molinari, 2020. "Microeconometrics with Partial Identi?cation," CeMMAP working papers CWP15/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. 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. Kaido, Hiroaki & White, Halbert, 2014. "A two-stage procedure for partially identified models," Journal of Econometrics, Elsevier, vol. 182(1), pages 5-13.

  8. Federico A. Bugni, 2010. "Bootstrap Inference in Partially Identified Models Defined by Moment Inequalities: Coverage of the Identified Set," Econometrica, Econometric Society, vol. 78(2), pages 735-753, March.

    Cited by:

    1. Christian Bontemps & Thierry Magnac & Eric Maurin, 2012. "Set Identified Linear Models," Econometrica, Econometric Society, vol. 80(3), pages 1129-1155, May.
    2. Stoye, Jörg & Kitamura, Yuichi, 2013. "Nonparametric Analysis of Random Utility Models: Testing," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79753, Verein für Socialpolitik / German Economic Association.
    3. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    4. Hahn Jinyong & Ridder Geert, 2015. "Non-Standard Tests through a Composite Null and Alternative in Point-Identified Parameters," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 1-28, January.
    5. 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.
    6. 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.
    7. Wooyoung Kim & Koohyun Kwon & Soonwoo Kwon & Sokbae Lee, 2018. "The identification power of smoothness assumptions in models with counterfactual outcomes," Quantitative Economics, Econometric Society, vol. 9(2), pages 617-642, July.
    8. Laffers, Lukas, 2013. "Identification in Models with Discrete Variables," Discussion Paper Series in Economics 1/2013, Norwegian School of Economics, Department of Economics.
    9. 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.
    10. 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.
    11. Larry G. Epstein & Hiroaki Kaido & Kyoungwon Seo, 2015. "Robust Confidence Regions for Incomplete Models," Boston University - Department of Economics - Working Papers Series wp2015-008, Boston University - Department of Economics.
    12. Sokbae (Simon) Lee & Kyungchui (Kevin) Song & Yoon-Jae Whang, 2014. "Testing for a general class of functional inequalities," CeMMAP working papers CWP09/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Yuan Liao & Anna Simoni, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," Papers 1212.3267, arXiv.org, revised Nov 2013.
    14. Donald W.K. Andrews & Xiaoxia Shi, 2010. "Inference Based on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1761R2, Cowles Foundation for Research in Economics, Yale University, revised May 2012.
    15. Armstrong, Timothy B., 2014. "Weighted KS statistics for inference on conditional moment inequalities," Journal of Econometrics, Elsevier, vol. 181(2), pages 92-116.
    16. Jason R. Blevins, 2013. "Non-Standard Rates of Convergence of Criterion-Function-Based Set Estimators," Working Papers 13-02, Ohio State University, Department of Economics.
    17. Kim, Dongwoo, 2023. "Partially identifying competing risks models: An application to the war on cancer," Journal of Econometrics, Elsevier, vol. 234(2), pages 536-564.
    18. Adam Rosen, 2009. "Set identification via quantile restrictions in short panels," CeMMAP working papers CWP26/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Andrew Chesher & Adam Rosen, 2016. "Characterizations of identified sets delivered by structural econometric models," CeMMAP working papers CWP44/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    21. 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," NBER Working Papers 23079, National Bureau of Economic Research, Inc.
    22. 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.
    23. Bontemps, Christian & Kumar, Rohit, 2018. "A Geometric Approach to Inference in Set-Identified Entry Games," TSE Working Papers 18-943, Toulouse School of Economics (TSE), revised Mar 2019.
    24. Andrew Chesher & Adam Rosen & Konrad Smolinski, 2011. "An instrumental variable model of multiple discrete choice," CeMMAP working papers CWP39/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    25. Le-Yu Chen & Jerzy Szroeter, 2012. "Testing multiple inequality hypotheses: a smoothed indicator approach," CeMMAP working papers 16/12, Institute for Fiscal Studies.
    26. Marc Henry & Ismael Mourifié, 2013. "Set inference in latent variables models," Econometrics Journal, Royal Economic Society, vol. 16(1), pages 93-105, February.
    27. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confidence Intervals for Projections of Partially Identified Parameters," Papers 1601.00934, arXiv.org, revised Jun 2019.
    28. Arun Chandrasekhar & Victor Chernozhukov & Francesca Molinari & Paul Schrimpf, 2012. "Inference for best linear approximations to set identified functions," CeMMAP working papers CWP43/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Coroneo, Laura & Corradi, Valentina & Santos Monterio, Paulo, 2012. "Testing for optimal monetary policy via moment inequalities," Economic Research Papers 270654, University of Warwick - Department of Economics.
    30. Victor Aguirregabiria & Allan Collard-Wexler & Stephen P. Ryan, 2021. "Dynamic Games in Empirical Industrial Organization," Papers 2109.01725, arXiv.org, revised Sep 2021.
    31. Juan Passadore & Juan Xandri, 2019. "Robust Predictions in Dynamic Policy Games," 2019 Meeting Papers 1345, Society for Economic Dynamics.
    32. Blundell, Richard & Kristensen, Dennis & Matzkin, Rosa, 2014. "Bounding quantile demand functions using revealed preference inequalities," Journal of Econometrics, Elsevier, vol. 179(2), pages 112-127.
    33. 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.
    34. 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.
    35. Kaido, Hiroaki, 2016. "A dual approach to inference for partially identified econometric models," Journal of Econometrics, Elsevier, vol. 192(1), pages 269-290.
    36. Grant, Charles & Padula, Mario, 2013. "Using bounds to investigate household debt repayment behaviour," Research in Economics, Elsevier, vol. 67(4), pages 336-354.
    37. Okumura, Tsunao & 奥村, 綱雄 & オクムラ, ツナオ & Usui, Emiko & 臼井, 恵美子 & ウスイ, エミコ, 2010. "Concave-Monotone Treatment Response and Monotone Treatment Selection: With an Application to the Returns to Schooling," PIE/CIS Discussion Paper 475, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
    38. Yuan Liao & Anna Simoni, 2019. "Bayesian inference for partially identified smooth convex models," Post-Print hal-03089881, HAL.
    39. Andrew Chesher & Adam Rosen, 2019. "Generalized Instrumental Variable Models, Methods, and Applications," CeMMAP working papers CWP41/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    40. Jorg Stoye, 2020. "A Simple, Short, but Never-Empty Confidence Interval for Partially Identified Parameters," Papers 2010.10484, arXiv.org, revised Dec 2020.
    41. Donald W.K. Andrews & Panle Jia, 2008. "Inference for Parameters Defined by Moment Inequalities: A Recommended Moment Selection Procedure," Cowles Foundation Discussion Papers 1676, Cowles Foundation for Research in Economics, Yale University.
    42. Zeng-Hua Lu, 2020. "Bahadur intercept with applications to one-sided testing," Statistical Papers, Springer, vol. 61(2), pages 645-658, April.
    43. Donald S. Poskitt & Xueyan Zhao, 2023. "Bootstrap Hausdorff Confidence Regions for Average Treatment Effect Identified Sets," Monash Econometrics and Business Statistics Working Papers 9/23, Monash University, Department of Econometrics and Business Statistics.
    44. Arie Beresteanu & Ilya Molchanov & Francesca Molinari, 2010. "Partial identification using random set theory," CeMMAP working papers CWP40/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    45. Andriy Norets & Xun Tang, 2013. "Semi-Parametric Inference in Dynamic Binary Choice Models," PIER Working Paper Archive 13-054, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    46. Andrew Chesher & Adam Rosen, 2014. "Generalized instrumental variable models," CeMMAP working papers 04/14, Institute for Fiscal Studies.
    47. 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.
    48. Magnac, Thierry, 2014. "Identification partielle: méthodes et conséquences pour les applications empiriques," TSE Working Papers 14-458, Toulouse School of Economics (TSE).
    49. Donald W.K. Andrews, 2011. "Similar-on-the-Boundary Tests for Moment Inequalities Exist, But Have Poor Power," Cowles Foundation Discussion Papers 1815, Cowles Foundation for Research in Economics, Yale University.
    50. Laurens Cherchye & Thomas Demuynck & Bram De Rock, 2017. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Working Papers of Department of Economics, Leuven 598907, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    51. Dzemski, Andreas & Okui, Ryo, 2018. "Confidence Set for Group Membership," Working Papers in Economics 727, University of Gothenburg, Department of Economics.
    52. Krasnokutskaya, Elena & Song, Kyungchul & Tang, Xun, 2022. "Estimating unobserved individual heterogeneity using pairwise comparisons," Journal of Econometrics, Elsevier, vol. 226(2), pages 477-497.
    53. Zeng-Hua Lu & Alec Zuo, 2017. "Child disability, welfare payments, marital status and mothers’ labor supply: Evidence from Australia," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1339769-133, January.
    54. Armstrong, Timothy B. & Chan, Hock Peng, 2016. "Multiscale adaptive inference on conditional moment inequalities," Journal of Econometrics, Elsevier, vol. 194(1), pages 24-43.
    55. Francesca Molinari, 2020. "Microeconometrics with Partial Identi?cation," CeMMAP working papers CWP15/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    56. Xiaohong Chen & Elie Tamer & Alexander Torgovitsky, 2011. "Sensitivity Analysis in Semiparametric Likelihood Models," Cowles Foundation Discussion Papers 1836, Cowles Foundation for Research in Economics, Yale University.
    57. Denis Chetverikov, 2012. "Adaptive test of conditional moment inequalities," CeMMAP working papers 36/12, Institute for Fiscal Studies.
    58. Tamer, Elie & Kline, Brendan, 2016. "Bayesian inference in a class of partially identified models," Scholarly Articles 30780157, Harvard University Department of Economics.
    59. Denis Chetverikov, 2012. "Adaptive test of conditional moment inequalities," CeMMAP working papers CWP36/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    60. Christian Bontemps & Thierry Magnac, 2017. "Set Identification, Moment Restrictions, and Inference," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 103-129, September.
    61. Marine Carrasco & N'Golo Koné, 2023. "Test for Trading Costs Effect in a Portfolio Selection Problem with Recursive Utility," CIRANO Working Papers 2023s-03, CIRANO.
    62. Li, Tong & Oka, Tatsushi, 2015. "Set identification of the censored quantile regression model for short panels with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 363-377.
    63. Wooyoung Kim & Koohyun Kwon & Soonwoo Kwon & Sokbae (Simon) Lee, 2014. "The identification power of smoothness assumptions in models with counterfactual outcomes," CeMMAP working papers 17/14, Institute for Fiscal Studies.
    64. Arun Chandrasekhar & Victor Chernozhukov & Francesca Molinari & Paul Schrimpf, 2019. "Best linear approximations to set identified functions: with an application to the gender wage gap," CeMMAP working papers 09/19, Institute for Fiscal Studies.
    65. 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.
    66. Shosei Sakaguchi, 2020. "Partial Identification and Inference in Duration Models with Endogenous Censoring," CeMMAP working papers CWP8/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    67. Mammen, Enno & Polonik, Wolfgang, 2013. "Confidence regions for level sets," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 202-214.
    68. Madeira, Carlos, 2020. "Learning your own ability," Journal of Economic Dynamics and Control, Elsevier, vol. 121(C).
    69. Fan, Yanqin & Park, Sang Soo, 2012. "Confidence intervals for the quantile of treatment effects in randomized experiments," Journal of Econometrics, Elsevier, vol. 167(2), pages 330-344.
    70. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2017. "Monte Carlo confidence sets for identified sets," CeMMAP working papers 43/17, Institute for Fiscal Studies.
    71. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    72. Armstrong, Timothy B., 2015. "Asymptotically exact inference in conditional moment inequality models," Journal of Econometrics, Elsevier, vol. 186(1), pages 51-65.
    73. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    74. Andreas Tryphonides, 2017. "Set Identified Dynamic Economies and Robustness to Misspecification," Papers 1712.03675, arXiv.org, revised Jan 2018.
    75. 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).
    76. Shi, Xiaoxia, 2015. "Model selection tests for moment inequality models," Journal of Econometrics, Elsevier, vol. 187(1), pages 1-17.
    77. 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.
    78. Marc Henry & Romuald Méango & Maurice Queyranne, 2012. "Combinatorial Bootstrap Inference IN in Prtially Identified Incomplete Structural Models," CIRJE F-Series CIRJE-F-837, CIRJE, Faculty of Economics, University of Tokyo.
    79. Fan, Yanqin & Park, Sang Soo, 2014. "Nonparametric inference for counterfactual means: Bias-correction, confidence sets, and weak IV," Journal of Econometrics, Elsevier, vol. 178(P1), pages 45-56.
    80. Kaido, Hiroaki & White, Halbert, 2014. "A two-stage procedure for partially identified models," Journal of Econometrics, Elsevier, vol. 182(1), pages 5-13.
    81. Juan Carlos Escanciano & Lin Zhu, 2013. "Set inferences and sensitivity analysis in semiparametric conditionally identified models," CeMMAP working papers CWP55/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    82. Sokbae (Simon) Lee & Kyungchui (Kevin) Song & Yoon-Jae Whang, 2014. "Testing for a general class of functional inequalities," CeMMAP working papers 09/14, Institute for Fiscal Studies.
    83. 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.
    84. Fan, Yanqin & Park, Sang Soo, 2010. "Confidence sets for some partially identified parameters," MPRA Paper 37149, University Library of Munich, Germany.
    85. Yuan Liao & Anna Simoni, 2016. "Bayesian Inference for Partially Identified Convex Models: Is it Valid for Frequentist Inference?," Departmental Working Papers 201607, Rutgers University, Department of Economics.
    86. Claudia Noack, 2021. "Sensitivity of LATE Estimates to Violations of the Monotonicity Assumption," Papers 2106.06421, arXiv.org.
    87. Andreas Dzemski & Ryo Okui, 2017. "Confidence set for group membership," Papers 1801.00332, arXiv.org, revised Nov 2023.
    88. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  9. Federico A. Bugni & Peter Hall & Joel L. Horowitz & George R. Neumann, 2009. "Goodness-of-fit tests for functional data," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 1-18, January.

    Cited by:

    1. Federico A. Bugni & Joel L. Horowitz, 2018. "Permutation tests for equality of distributions of functional data," CeMMAP working papers CWP18/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Oleksandr Gromenko & Piotr Kokoszka & Matthew Reimherr, 2017. "Detection of change in the spatiotemporal mean function," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 29-50, January.
    3. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2019. "Parametric Inference on the Mean of Functional Data Applied to Lifetime Income Curves," Working papers 2019rwp-153, Yonsei University, Yonsei Economics Research Institute.
    4. Norbert Henze & María Dolores Jiménez‐Gamero, 2021. "A test for Gaussianity in Hilbert spaces via the empirical characteristic functional," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 406-428, June.
    5. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2022. "Parametric Conditional Mean Inference With Functional Data Applied To Lifetime Income Curves," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(1), pages 391-456, February.
    6. Meintanis, Simos G. & Hušková, Marie & Hlávka, Zdeněk, 2022. "Fourier-type tests of mutual independence between functional time series," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    7. Graciela Estévez-Pérez & Philippe Vieu, 2021. "A new way for ranking functional data with applications in diagnostic test," Computational Statistics, Springer, vol. 36(1), pages 127-154, March.
    8. Marc Ditzhaus & Daniel Gaigall, 2022. "Testing marginal homogeneity in Hilbert spaces with applications to stock market returns," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 749-770, September.

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