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Jörg Stoye
(Joerg Stoye)

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. Yuichi Kitamura & Jörg Stoye, 2018. "Nonparametric Analysis of Random Utility Models," Econometrica, Econometric Society, vol. 86(6), pages 1883-1909, November.

    Mentioned in:

    1. Nonparametric Analysis of Random Utility Models (ECTA 2018) in ReplicationWiki ()

Working papers

  1. Orlov, George & McKee, Douglas & Berry, James & Boyle, Austin & DiCiccio, Thomas J. & Ransom, Tyler & Rees-Jones, Alex & Stoye, Joerg, 2020. "Learning during the COVID-19 Pandemic: It Is Not Who You Teach, but How You Teach," IZA Discussion Papers 13813, Institute of Labor Economics (IZA).

    Cited by:

    1. List, John A. & Shah, Rohen, 2022. "The impact of team incentives on performance in graduate school: Evidence from two pilot RCTs," Economics Letters, Elsevier, vol. 221(C).
    2. David Hardt & Markus Nagler & Johannes Rincke, 2022. "Tutoring in (Online) Higher Education: Experimental Evidence," CESifo Working Paper Series 9555, CESifo.
    3. Binelli, Chiara & Comi, Simona Lorena & Meschi, Elena & Pagani, Laura, 2024. "Every Cloud Has a Silver Lining: The Role of Study Time and Class Recordings on University Students' Performance during COVID-19," IZA Discussion Papers 17173, Institute of Labor Economics (IZA).
    4. Ragni, Alessandra & Ippolito, Daniel & Masci, Chiara, 2024. "Assessing the impact of hybrid teaching on students’ academic performance via multilevel propensity score-based techniques," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    5. Hugues Champeaux & Lucia Mangiavacchi & Francesca Marchetta & Luca Piccoli, 2022. "Child Development and Distance Learning in the Age of COVID-19," Post-Print hal-03656711, HAL.
    6. Sarah Cattan & Christine Farquharson & Sonya Krutikova & Angus Phimister & Adam Salisbury & Almudena Sevilla, 2021. "Inequalities in responses to school closures over the course of the first COVID-19 lockdown," IFS Working Papers W21/4, Institute for Fiscal Studies.
    7. David Hardt & Markus Nagler & Johannes Rincke, 2020. "Can Peer Mentoring Improve Online Teaching Effectiveness? An RCT during the Covid-19 Pandemic," CESifo Working Paper Series 8671, CESifo.
    8. Monroy-Gómez-Franco, Luis & Vélez-Grajales, Roberto & López-Calva, Luis F., 2022. "The potential effects of the COVID-19 pandemic on learnings," International Journal of Educational Development, Elsevier, vol. 91(C).
    9. Li, Haizheng & Ma, Mingyu & Liu, Qinyi, 2022. "How the COVID-19 pandemic affects job sentiments of rural teachers," China Economic Review, Elsevier, vol. 72(C).
    10. Haelermans, Carla & Korthals, Roxanne & Jacobs, Madelon & de Leeuw, Suzanne & Vermeulen, Stan & van Vugt, Lynn & Aarts, Bas & Breuer, Tijana & van der Velden, Rolf & van Wetten, Sanne & de Wolf, Inge, 2021. "Sharp increase in inequality in education in times of the COVID-19-pandemic," Research Memorandum 022, Maastricht University, Graduate School of Business and Economics (GSBE).
    11. Badruddoza, Syed & Amin, Modhurima Dey, 2023. "Impacts of Teaching Modality on U.S. COVID-19 Spread in Fall 2020 Semester," Applied Economics Teaching Resources (AETR), Agricultural and Applied Economics Association, vol. 5(1), January.
    12. Picault, Julien, 2021. "Structure, Flexibility, and Consistency: A Dynamic Learning Approach for an Online Asynchronous Course," Applied Economics Teaching Resources (AETR), Agricultural and Applied Economics Association, vol. 3(4), October.
    13. Birdi, Alvin & Cook, Steve & Elliott, Caroline & Lait, Ashley & Mehari, Tesfa & Wood, Max, 2023. "A critical review of recent economics pedagogy literature, 2020–2021," International Review of Economics Education, Elsevier, vol. 43(C).
    14. Szabó, Andrea & Fekete, Mariann & Böcskei, Balázs & Nagy, Ádám, 2023. "Real-time experiences of Hungarian youth in digital education as an example of the impact of pandemia. “I’ve never had better grades on average: I got straight all the time”," International Journal of Educational Development, Elsevier, vol. 99(C).
    15. Douglas McKee & Steven Zhu & George Orlov, 2023. "Econ-assessments.org: Automated Assessment of Economics Skills," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 49(1), pages 4-14, January.
    16. Kenneth G. Elzinga & Daniel Q. Harper, 2023. "In‐person versus online instruction: Evidence from principles of economics," Southern Economic Journal, John Wiley & Sons, vol. 90(1), pages 3-30, July.
    17. De Paola, Maria & Gioia, Francesca & Scoppa, Vincenzo, 2022. "Online Teaching, Procrastination and Students’ Achievement: Evidence from COVID-19 Induced Remote Learning," IZA Discussion Papers 15031, Institute of Labor Economics (IZA).
    18. Wang, Qingyu & Huang, Qing & Wu, Xiangfang & Tan, Jin & Sun, Panxu, 2023. "Categorical uncertainty in policy and bitcoin volatility," Finance Research Letters, Elsevier, vol. 58(PC).
    19. Elena-Aurelia Botezat & Alexandru Constăngioară & Anca-Otilia Dodescu & Ioana-Crina Pop-Cohuţ, 2022. "How Stable Are Students’ Entrepreneurial Intentions in the COVID-19 Pandemic Context?," Sustainability, MDPI, vol. 14(9), pages 1-22, May.
    20. Bratti, Massimiliano & Lippo, Enrico, 2022. "COVID-19 and the Gender Gap in University Student Performance," IZA Discussion Papers 15456, Institute of Labor Economics (IZA).
    21. Ahlstrom, Laura J. & Harter, Cynthia & Asarta, Carlos J., 2023. "Teaching methods and materials in undergraduate economics courses: School, instructor, and department effects," International Review of Economics Education, Elsevier, vol. 44(C).
    22. Sanchayan Banerjee & Beatriz Jambrina-Canseco & Benjamin Brundu-Gonzalez & Claire Gordon & Jenni Carr, 2023. "Nudge or not, university teachers have mixed feelings about online teaching," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.

  2. Jorg Stoye, 2020. "A Simple, Short, but Never-Empty Confidence Interval for Partially Identified Parameters," Papers 2010.10484, arXiv.org, revised Dec 2020.

    Cited by:

    1. Phillip Heiler, 2022. "Heterogeneous Treatment Effect Bounds under Sample Selection with an Application to the Effects of Social Media on Political Polarization," Papers 2209.04329, arXiv.org, revised Jul 2024.
    2. Mathieu Marcoux & Thomas Russell & Yuanyuan Wan, 2023. "A Simple Specification Test for Models with Many Conditional Moment Inequalities," Working Papers tecipa-764, University of Toronto, Department of Economics.
    3. Sokbae Lee & Martin Weidner, 2021. "Bounding Treatment Effects by Pooling Limited Information across Observations," Papers 2111.05243, arXiv.org, revised Dec 2023.
    4. Aibo Gong, 2021. "Bounds for Treatment Effects in the Presence of Anticipatory Behavior," Papers 2111.06573, arXiv.org, revised Dec 2022.

  3. Jorg Stoye, 2020. "Bounding Infection Prevalence by Bounding Selectivity and Accuracy of Tests: With Application to Early COVID-19," Papers 2008.06178, arXiv.org, revised Jan 2021.

    Cited by:

    1. Kitagawa, Toru & Wang, Guanyi, 2023. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," Journal of Econometrics, Elsevier, vol. 232(1), pages 109-131.
    2. Bollinger, Christopher R. & van Hasselt, Martijn, 2020. "Estimating the cumulative rate of SARS-CoV-2 infection," Economics Letters, Elsevier, vol. 197(C).
    3. Filip Obradovi'c, 2022. "Measuring Diagnostic Test Performance Using Imperfect Reference Tests: A Partial Identification Approach," Papers 2204.00180, arXiv.org, revised Aug 2024.

  4. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2019. "Constraint Qualifications in Partial Identification," Papers 1908.09103, arXiv.org, revised Apr 2021.

    Cited by:

    1. 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.
    2. 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.
    3. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    4. Gregory Cox, 2022. "A Generalized Argmax Theorem with Applications," Papers 2209.08793, arXiv.org.
    5. Mathieu Marcoux & Thomas Russell & Yuanyuan Wan, 2023. "A Simple Specification Test for Models with Many Conditional Moment Inequalities," Working Papers tecipa-764, University of Toronto, Department of Economics.
    6. Thomas M. Russell, 2020. "Policy Transforms and Learning Optimal Policies," Papers 2012.11046, arXiv.org.
    7. Bei, Xinyue, 2024. "Local linearization based subvector inference in moment inequality models," Journal of Econometrics, Elsevier, vol. 238(1).

  5. Yuichi Kitamura & Jorg Stoye, 2019. "Nonparametric Counterfactuals in Random Utility Models," Papers 1902.08350, arXiv.org, revised May 2019.

    Cited by:

    1. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    2. Wilfried Youmbi, 2024. "Nonparametric Analysis of Random Utility Models Robust to Nontransitive Preferences," Papers 2406.13969, arXiv.org.
    3. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    4. Bram De Rock & Laurens Cherchye & Bart Smeulders, 2019. "Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing," Working Papers ECARES 2019-19, ULB -- Universite Libre de Bruxelles.

  6. Jorg Stoye, 2018. "Revealed Stochastic Preference: A One-Paragraph Proof and Generalization," Papers 1810.10604, arXiv.org, revised Feb 2019.

    Cited by:

    1. Wilfried Youmbi, 2024. "Nonparametric Analysis of Random Utility Models Robust to Nontransitive Preferences," Papers 2406.13969, arXiv.org.
    2. Christopher Turansick, 2023. "An Alternative Approach for Nonparametric Analysis of Random Utility Models," Papers 2303.14249, arXiv.org, revised May 2024.
    3. Mark Dean & Dilip Ravindran & Jorg Stoye, 2022. "A Better Test of Choice Overload," Papers 2212.03931, arXiv.org, revised Jul 2024.
    4. Yuichi Kitamura & Jorg Stoye, 2019. "Nonparametric Counterfactuals in Random Utility Models," Papers 1902.08350, arXiv.org, revised May 2019.
    5. Daniele Caliari & Henrik Petri, 2024. "Irrational Random Utility Models," Papers 2403.10208, arXiv.org.

  7. Rahul Deb & Yuichi Kitamura & John K. -H. Quah & Jorg Stoye, 2018. "Revealed Price Preference: Theory and Empirical Analysis," Papers 1801.02702, arXiv.org, revised Apr 2021.

    Cited by:

    1. Roy Allen & Pawel Dziewulski & John Rehbeck, 2019. "Revealed Statistical Consumer Theory," University of Western Ontario, Departmental Research Report Series 20195, University of Western Ontario, Department of Economics.
    2. 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.
    3. Khushboo Surana, 2022. "How different are we? Identifying the degree of revealed preference heterogeneity," Discussion Papers 22/09, Department of Economics, University of York.
    4. Han, Sukjin & Yang, Shenshen, 2024. "A computational approach to identification of treatment effects for policy evaluation," Journal of Econometrics, Elsevier, vol. 240(1).
    5. Changkuk Im & John Rehbeck, 2021. "Non-rationalizable Individuals, Stochastic Rationalizability, and Sampling," Papers 2102.03436, arXiv.org, revised Oct 2021.
    6. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    7. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    8. Stoye, Jörg, 2019. "Revealed Stochastic Preference: A one-paragraph proof and generalization," Economics Letters, Elsevier, vol. 177(C), pages 66-68.
    9. Wilfried Youmbi, 2024. "Nonparametric Analysis of Random Utility Models Robust to Nontransitive Preferences," Papers 2406.13969, arXiv.org.
    10. Natalia Lazzati & John K.-H. Quah & Koji Shirai, 2018. "Nonparametric analysis of monotone choice," Discussion Paper Series 184, School of Economics, Kwansei Gakuin University.
    11. John K. -H. Quah & Gerelt Tserenjigmid, 2022. "Price Heterogeneity as a source of Heterogenous Demand," Papers 2201.03784, arXiv.org, revised Jan 2022.
    12. Daniele Caliari & Henrik Petri, 2024. "Irrational Random Utility Models," Papers 2403.10208, arXiv.org.

  8. Rahul Deb & Yuichi Kitamura & John K.-H. Quah & Jorg Stoye, 2017. "Revealed Price Preference: Theory and Stochastic Testing," Cowles Foundation Discussion Papers 2087, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. 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.
    2. Legacy, Crystal & Stone, John, 2019. "Consensus planning in transport: The case of Vancouver’s transportation plebiscite," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 295-305.
    3. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    4. Victor H. Aguiar & Roberto Serrano, 2018. "Cardinal Revealed Preference, Price-Dependent Utility, and Consistent Binary Choice," Working Papers 2018-3, Brown University, Department of Economics.
    5. Nail Kashaev & Victor H. Aguiar, 2022. "Nonparametric Analysis of Dynamic Random Utility Models," Papers 2204.07220, arXiv.org.
    6. Victor H. Aguiar & Nail Kashaev, 2018. "Stochastic Revealed Preferences with Measurement Error," Papers 1810.05287, arXiv.org, revised Sep 2020.
    7. Aguiar, Victor H. & Serrano, Roberto, 2021. "Cardinal revealed preference: Disentangling transitivity and consistent binary choice," Journal of Mathematical Economics, Elsevier, vol. 94(C).
    8. Bram De Rock & Laurens Cherchye & Bart Smeulders, 2019. "Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing," Working Papers ECARES 2019-19, ULB -- Universite Libre de Bruxelles.
    9. Bart Smeulders, 2018. "Column Generation Algorithms for Nonparametric Analysis of Random Utility Models," Papers 1812.01400, arXiv.org.
    10. de Jong, Gerben & Behrens, Christiaan & van Ommeren, Jos, 2019. "Airline loyalty (programs) across borders: A geographic discontinuity approach," International Journal of Industrial Organization, Elsevier, vol. 62(C), pages 251-272.

  9. Yuichi Kitamura & Jorg Stoye, 2016. "Nonparametric Analysis of Random Utility Models," Papers 1606.04819, arXiv.org, revised Sep 2018.

    Cited by:

    1. Mira Frick & Ryota Iijima & Tomasz Strzalecki, 2019. "Dynamic Random Utility," Econometrica, Econometric Society, vol. 87(6), pages 1941-2002, November.
    2. Rahul Deb & Yuichi Kitamura & John Quah & Jorg Stoye, 2018. "Revealed price preference: theory and empirical analysis," CeMMAP working papers CWP57/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Roy Allen & Pawel Dziewulski & John Rehbeck, 2019. "Revealed Statistical Consumer Theory," University of Western Ontario, Departmental Research Report Series 20195, University of Western Ontario, Department of Economics.
    4. Sam Cosaert & Thomas Demuynck, 2018. "Nonparametric welfare and demand analysis with unobserved individual heterogeneity," ULB Institutional Repository 2013/251988, ULB -- Universite Libre de Bruxelles.
    5. Nobuo Koida & Koji Shirai, 2024. "A dual approach to nonparametric characterization for random utility models," Papers 2403.04328, arXiv.org, revised Jun 2024.
    6. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    7. Arie Beresteanu, 2021. "Identification of Incomplete Preferences," Working Paper 7145, Department of Economics, University of Pittsburgh.
    8. 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.
    9. Sebastiaan Maes & Raghav Malhotra, 2024. "Beyond the Mean: Testing Consumer Rationality through Higher Moments of Demand," Papers 2407.01538, arXiv.org.
    10. Arthur Lewbel & Krishna Pendakur, 2017. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 1100-1148.
    11. Áureo de Paula & Seth Richards-Shubik & Elie Tamer, 2017. "Identifying preferences in networks with bounded degree," CeMMAP working papers CWP35/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Natalia Lazzati & John K.-H. Quah & Koji Shirai, 2016. "A revealed preference theory of monotone choice and strategic complementarity," Discussion Paper Series 147, School of Economics, Kwansei Gakuin University, revised Oct 2016.
    13. Matthew Kovach & Gerelt Tserenjigmid, 2023. "The Focal Quantal Response Equilibrium," Papers 2304.00438, arXiv.org.
    14. Turansick, Christopher, 2022. "Identification in the random utility model," Journal of Economic Theory, Elsevier, vol. 203(C).
    15. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    16. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2022. "Nonlinear Budget Set Regressions for the Random Utility Model," Working Papers 2219, Federal Reserve Bank of Dallas.
    17. Victor H. Aguiar & Per Hjertstrand & Roberto Serrano, 2020. "Rationalizable Incentives: Interim Implementation of Sets in Rationalizable Strategies," Working Papers 2020-16, Brown University, Department of Economics.
    18. Pawe{l} Dziewulski & Joshua Lanier & John K. -H. Quah, 2024. "Revealed preference and revealed preference cycles: a survey," Papers 2405.08459, arXiv.org.
    19. Bhattacharya, D., 2018. "The Empirical Content of Binary Choice Models," Cambridge Working Papers in Economics 1883, Faculty of Economics, University of Cambridge.
    20. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    21. Joshua Lanier & John K. -H. Quah, 2024. "Goodness-of-fit and utility estimation: what's possible and what's not," Papers 2405.08464, arXiv.org.
    22. Whitney K. Newey & Sami Stouli, 2018. "Heterogenous coefficients, discrete instruments, and identification of treatment effects," CeMMAP working papers CWP66/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. Victor H. Aguiar & Maria Jose Boccardi & Nail Kashaev & Jeongbin Kim, 2018. "Random Utility and Limited Consideration," Papers 1812.09619, arXiv.org, revised Jul 2022.
    24. Aguiar, Victor H. & Kimya, Mert, 2019. "Adaptive stochastic search," Journal of Mathematical Economics, Elsevier, vol. 81(C), pages 74-83.
    25. Whitney K. Newey & Sami Stouli, 2018. "Control variables, discrete instruments, and identification of structural functions," CeMMAP working papers CWP55/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Im, Changkuk & Rehbeck, John, 2022. "Non-rationalizable individuals and stochastic rationalizability," Economics Letters, Elsevier, vol. 219(C).
    27. Adams-Prassl, Abigail, 2019. "Mutually Consistent Revealed Preference Demand Predictions," CEPR Discussion Papers 13580, C.E.P.R. Discussion Papers.
    28. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    30. Cherchye, Laurens & Demuynck, Thomas & Rock, Bram De, 2019. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Journal of Econometrics, Elsevier, vol. 211(2), pages 483-506.
    31. Stoye, Jörg, 2019. "Revealed Stochastic Preference: A one-paragraph proof and generalization," Economics Letters, Elsevier, vol. 177(C), pages 66-68.
    32. Wilfried Youmbi, 2024. "Nonparametric Analysis of Random Utility Models Robust to Nontransitive Preferences," Papers 2406.13969, arXiv.org.
    33. Victor H. Aguiar & Nail Kashaev, 2019. "Identification and Estimation of Discrete Choice Models with Unobserved Choice Sets," Papers 1907.04853, arXiv.org, revised Jun 2021.
    34. Ian Crawford, 2019. "Nonparametric Analysis of Labour Supply Using Random Fields," Economics Papers 2019-W06, Economics Group, Nuffield College, University of Oxford.
    35. Nail Kashaev & Victor H. Aguiar, 2022. "Nonparametric Analysis of Dynamic Random Utility Models," Papers 2204.07220, arXiv.org.
    36. Natalia Lazzati & John K.-H. Quah & Koji Shirai, 2018. "Nonparametric analysis of monotone choice," Discussion Paper Series 184, School of Economics, Kwansei Gakuin University.
    37. Victor H. Aguiar & Nail Kashaev, 2018. "Stochastic Revealed Preferences with Measurement Error," Papers 1810.05287, arXiv.org, revised Sep 2020.
    38. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    39. Christopher Turansick, 2023. "An Alternative Approach for Nonparametric Analysis of Random Utility Models," Papers 2303.14249, arXiv.org, revised May 2024.
    40. Charles F. Manski, 2014. "Identification of income–leisure preferences and evaluation of income tax policy," Quantitative Economics, Econometric Society, vol. 5, pages 145-174, March.
    41. Demuynck, Thomas & Hjertstrand, Per, 2019. "Samuelson's Approach to Revealed Preference Theory: Some Recent Advances," Working Paper Series 1274, Research Institute of Industrial Economics.
    42. Nail Kashaev & Victor H. Aguiar, 2022. "A Random Attention and Utility Model," University of Western Ontario, Departmental Research Report Series 20223, University of Western Ontario, Department of Economics.
    43. Dziewulski, Paweł & Lanier, Joshua & Quah, John K.-H., 2024. "Revealed preference and revealed preference cycles: A survey," Journal of Mathematical Economics, Elsevier, vol. 113(C).
    44. David M. Kaplan & Longhao Zhuo, 2018. "Frequentist size of Bayesian inequality tests," Working Papers 1802, Department of Economics, University of Missouri, revised 14 Jul 2019.
    45. Victor H. Aguiar & Per Hjertstrand & Roberto Serrano, 2022. "A Rationalization of the Weak Axiom of Revealed Preference," University of Western Ontario, Departmental Research Report Series 20229, University of Western Ontario, Department of Economics.
    46. Bram De Rock & Laurens Cherchye & Bart Smeulders, 2019. "Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing," Working Papers ECARES 2019-19, ULB -- Universite Libre de Bruxelles.
    47. Maes, Sebastiaan & Malhotra, Raghav, 2024. "Beyond the Mean : Testing Consumer Rationality through Higher Moments of Demand," CRETA Online Discussion Paper Series 85, Centre for Research in Economic Theory and its Applications CRETA.
    48. Charles F. Manski, 2012. "Identification of Preferences and Evaluation of Income Tax Policy," NBER Working Papers 17755, National Bureau of Economic Research, Inc.
    49. Mark Dean & Dilip Ravindran & Jorg Stoye, 2022. "A Better Test of Choice Overload," Papers 2212.03931, arXiv.org, revised Jul 2024.
    50. Roy Allen & John Rehbeck, 2023. "Revealed stochastic choice with attributes," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 75(1), pages 91-112, January.
    51. Thomas Demuynck & Tom Potoms, 2022. "Testing revealed preference models with unobserved randomness: a column generation approach," Working Papers ECARES 2022-42, ULB -- Universite Libre de Bruxelles.
    52. Daniele Caliari & Henrik Petri, 2024. "Irrational Random Utility Models," Papers 2403.10208, arXiv.org.
    53. Laurens Cherchye & Thomas Demuynck & Bram De Rock & Joshua Lanier, 2020. "Are Consumers Rational ?Shifting the Burden of Proof," Working Papers ECARES 2020-19, ULB -- Universite Libre de Bruxelles.
    54. Allen, Roy & Dziewulski, Paweł & Rehbeck, John, 2022. "Making sense of monkey business: Re-examining tests of animal rationality," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 220-228.
    55. Qingyou Yan & Guangyu Qin & Meijuan Zhang & Bowen Xiao, 2019. "Research on Real Purchasing Behavior Analysis of Electric Cars in Beijing Based on Structural Equation Modeling and Multinomial Logit Model," Sustainability, MDPI, vol. 11(20), pages 1-15, October.
    56. Maes, Sebastiaan & Malhotra, Raghav, 2024. "Robust Hicksian Welfare Analysis under Individual Heterogeneity," CRETA Online Discussion Paper Series 84, Centre for Research in Economic Theory and its Applications CRETA.
    57. Hubner, Stefan, 2023. "Identification of unobserved distribution factors and preferences in the collective household model," Journal of Econometrics, Elsevier, vol. 234(1), pages 301-326.

  10. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confidence Intervals for Projections of Partially Identified Parameters," Papers 1601.00934, arXiv.org, revised Jun 2019.

    Cited by:

    1. 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.
    2. Xiaohong Chen & Timothy Christensen & Keith O’Hara & Elie Tamer, 2016. "MCMC Confidence sets for Identified Sets," Cowles Foundation Discussion Papers 2037R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2016.
    3. 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.
    4. 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.
    5. Cherchye, Laurens & Cosaert, Sam & De Rock, Bram & Kerstens, Pieter Jan & Vermeulen, Frederic, 2018. "Individual welfare analysis for collective households," Journal of Public Economics, Elsevier, vol. 166(C), pages 98-114.
    6. Steven T Berry & Giovanni Compiani, 2023. "An Instrumental Variable Approach to Dynamic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(4), pages 1724-1758.
    7. Lafférs, Lukáš & Mellace, Giovanni, 2020. "Identification of the average treatment effect when SUTVA is violated," Discussion Papers on Economics 3/2020, University of Southern Denmark, Department of Economics.
    8. Christian Bontemps & Thierry Magnac, 2017. "Set identification, moment restrictions, and inference," Post-Print hal-01575813, HAL.
    9. 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.
    10. 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.
    11. Nirav Mehta, 2022. "A Partial Identification Approach to Identifying the Determinants of Human Capital Accumulation: An Application to Teachers," CESifo Working Paper Series 9681, CESifo.
    12. 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.
    13. Victor H. Aguiar & Roy Allen & Nail Kashaev, 2020. "Prices, Profits, Proxies, and Production," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20202, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
    14. Khushboo Surana, 2022. "How different are we? Identifying the degree of revealed preference heterogeneity," Discussion Papers 22/09, Department of Economics, University of York.
    15. Brendan Kline & Elie Tamer, 2024. "Counterfactual Analysis in Empirical Games," Papers 2410.12731, arXiv.org.
    16. Patrik Guggenberger & Frank Kleibergen & Sophocles Mavroeidis, 2021. "A Powerful Subvector Anderson Rubin Test in Linear Instrumental Variables Regression with Conditional Heteroskedasticity," Papers 2103.11371, arXiv.org, revised Oct 2022.
    17. 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.
    18. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2017. "Monte Carlo confidence sets for identified sets," CeMMAP working papers 43/17, Institute for Fiscal Studies.
    19. Adam Lee & Geert Mesters, 2021. "Robust non-Gaussian inference for linear simultaneous equations models," Economics Working Papers 1792, Department of Economics and Business, Universitat Pompeu Fabra.
    20. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    21. Pakes, Ariel, 2017. "Empirical tools and competition analysis: Past progress and current problems," Scholarly Articles 34710163, Harvard University Department of Economics.
    22. 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.
    23. Hiroaki Kaido & Jiaxuan Li & Marc Rysman, 2018. "Moment Inequalities in the Context of Simulated and Predicted Variables," Papers 1804.03674, arXiv.org.
    24. Shengjie Hong & Yu-Chin Hsu & Yuanyuan Wan, 2023. "Subvector inference for Varying Coefficient Models with Partial Identification," Working Papers tecipa-756, University of Toronto, Department of Economics.
    25. Flynn, Zach, 2018. "Identifying productivity when it is a factor of production," SocArXiv bwxfz, Center for Open Science.
    26. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Aug 2023.
    27. 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.
    28. Levon Barseghyan & Maura Coughlin & Francesca Molinari & Joshua C. Teitelbaum, 2019. "Heterogeneous Choice Sets and Preferences," Papers 1907.02337, arXiv.org, revised Feb 2021.
    29. Ganesh Karapakula, 2022. "An Axiomatic Framework for Cost-Benefit Analysis," Papers 2207.13033, arXiv.org.
    30. Panos Toulis, 2020. "Estimation of Covid-19 Prevalence from Serology Tests: A Partial Identification Approach," Papers 2006.16214, arXiv.org.
    31. Lee, Ying-Ying & Bhattacharya, Debopam, 2019. "Applied welfare analysis for discrete choice with interval-data on income," Journal of Econometrics, Elsevier, vol. 211(2), pages 361-387.
    32. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2019. "Constraint Qualifications in Partial Identification," Papers 1908.09103, arXiv.org, revised Apr 2021.
    33. 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.
    34. Arie Beresteanu, 2016. "Quantile Regression with Interval Data," Working Paper 5991, Department of Economics, University of Pittsburgh.
    35. Xiaohong Chen & Timothy M. Christensen & Keith O'Hara & Elie Tamer, 2016. "MCMC confidence sets for identified sets," CeMMAP working papers 28/16, Institute for Fiscal Studies.
    36. Laurens Cherchye & Bram De Rock & Khushboo Surana & Frederic Vermeulen, 2020. "Marital Matching, Economies of Scale, and Intrahousehold Allocations," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 823-837, October.
    37. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    38. Yuan Liao & Anna Simoni, 2019. "Bayesian inference for partially identified smooth convex models," Post-Print hal-03089881, HAL.
    39. 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.
    40. Felix Chan & Laszlo Matyas & Agoston Reguly, 2024. "Modelling with Discretized Variables," Papers 2403.15220, arXiv.org.
    41. 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.
    42. Shuowen Chen & Hiroaki Kaido, 2022. "Robust Tests of Model Incompleteness in the Presence of Nuisance Parameters," Papers 2208.11281, arXiv.org, revised Sep 2023.
    43. Toulis, Panos, 2021. "Estimation of Covid-19 prevalence from serology tests: A partial identification approach," Journal of Econometrics, Elsevier, vol. 220(1), pages 193-213.
    44. Mathieu Marcoux & Thomas Russell & Yuanyuan Wan, 2023. "A Simple Specification Test for Models with Many Conditional Moment Inequalities," Working Papers tecipa-764, University of Toronto, Department of Economics.
    45. Hiroaki Kaido & Francesca Molinari & Jorg Stoye & Matthew Thirkettle, 2017. "Calibrated Projection in MATLAB: Users' Manual," Papers 1710.09707, arXiv.org.
    46. Sylvain Chassang & Kei Kawai & Jun Nakabayashi & Juan Ortner, 2022. "Robust Screens for Noncompetitive Bidding in Procurement Auctions," Econometrica, Econometric Society, vol. 90(1), pages 315-346, January.
    47. Paul S. Koh, 2022. "Estimating Discrete Games of Complete Information: Bringing Logit Back in the Game," Papers 2205.05002, arXiv.org, revised Aug 2024.
    48. Freyberger, Joachim & Rai, Yoshiyasu, 2018. "Uniform confidence bands: Characterization and optimality," Journal of Econometrics, Elsevier, vol. 204(1), pages 119-130.
    49. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.
    50. Bei, Xinyue, 2024. "Local linearization based subvector inference in moment inequality models," Journal of Econometrics, Elsevier, vol. 238(1).
    51. Panos Toulis, 2020. "Estimation of COVID-19 Prevalence from Serology Tests: A Partial Identification Approach," Working Papers 2020-54_Revised, Becker Friedman Institute for Research In Economics.

  11. Yuichi Kitamura & Jörg Stoye, 2013. "Nonparametric analysis of random utility models: testing," CeMMAP working papers 36/13, Institute for Fiscal Studies.

    Cited by:

    1. Mira Frick & Ryota Iijima & Tomasz Strzalecki, 2019. "Dynamic Random Utility," Econometrica, Econometric Society, vol. 87(6), pages 1941-2002, November.
    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. Sam Cosaert & Thomas Demuynck, 2018. "Nonparametric welfare and demand analysis with unobserved individual heterogeneity," ULB Institutional Repository 2013/251988, ULB -- Universite Libre de Bruxelles.
    4. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    5. Cherchye, Laurens & Cosaert, Sam & De Rock, Bram & Kerstens, Pieter Jan & Vermeulen, Frederic, 2018. "Individual welfare analysis for collective households," Journal of Public Economics, Elsevier, vol. 166(C), pages 98-114.
    6. 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.
    7. Giovanni Compiani & Yuichi Kitamura, 2016. "Using mixtures in econometric models: a brief review and some new results," Econometrics Journal, Royal Economic Society, vol. 19(3), pages 95-127, October.
    8. Laurens Cherchye & Thomas Demuynck & Bram De Rock, 2015. "Transitivity of Preferences: When Doest it Matter ?," Working Papers ECARES ECARES 2015-44, ULB -- Universite Libre de Bruxelles.
    9. Natalia Lazzati & John K.-H. Quah & Koji Shirai, 2016. "A revealed preference theory of monotone choice and strategic complementarity," Discussion Paper Series 147, School of Economics, Kwansei Gakuin University, revised Oct 2016.
    10. Stefan Hoderlein & Jörg Stoye, 2015. "Testing stochastic rationality and predicting stochastic demand: the case of two goods," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 3(2), pages 313-328, October.
    11. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    12. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers 60/17, Institute for Fiscal Studies.
    13. Laurens Cherchye & Thomas Demuynck & Bram De Rock & Frederic Vermeulen, 2017. "Household Consumption When the Marriage is Stable," ULB Institutional Repository 2013/251990, ULB -- Universite Libre de Bruxelles.
    14. Alexander Torgovitsky, 2019. "Partial identification by extending subdistributions," Quantitative Economics, Econometric Society, vol. 10(1), pages 105-144, January.
    15. David M. Kaplan & Longhao Zhuo, 2017. "Frequentist size of Bayesian inequality tests," Working Papers 1709, Department of Economics, University of Missouri, revised 14 Jul 2019.
    16. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    17. Ian Crawford & Matthew Polisson, 2015. "Demand analysis with partially observed prices," IFS Working Papers W15/16, Institute for Fiscal Studies.
    18. Kawaguchi, Kohei, 2017. "Testing rationality without restricting heterogeneity," Journal of Econometrics, Elsevier, vol. 197(1), pages 153-171.
    19. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    20. Rahul Deb & Yuichi Kitamura & John K.-H. Quah & Jorg Stoye, 2017. "Revealed Price Preference: Theory and Stochastic Testing," Cowles Foundation Discussion Papers 2087, Cowles Foundation for Research in Economics, Yale University.
    21. Yuichi Kitamura & Jorg Stoye, 2019. "Nonparametric Counterfactuals in Random Utility Models," Papers 1902.08350, arXiv.org, revised May 2019.
    22. Bart Smeulders, 2018. "Column Generation Algorithms for Nonparametric Analysis of Random Utility Models," Papers 1812.01400, arXiv.org.

  12. Stefan Hoderlein & Jörg Stoye, 2009. "Revealed Preferences in a Heterogeneous Population," Boston College Working Papers in Economics 745, Boston College Department of Economics.

    Cited by:

    1. Rahul Deb & Yuichi Kitamura & John Quah & Jorg Stoye, 2018. "Revealed price preference: theory and empirical analysis," CeMMAP working papers CWP57/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Ian Crawford & Bram De Rock, 2014. "Empirical Revealed Preference," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 503-524, August.
    3. Sam Cosaert & Thomas Demuynck, 2018. "Nonparametric welfare and demand analysis with unobserved individual heterogeneity," ULB Institutional Repository 2013/251988, ULB -- Universite Libre de Bruxelles.
    4. Nobuo Koida & Koji Shirai, 2024. "A dual approach to nonparametric characterization for random utility models," Papers 2403.04328, arXiv.org, revised Jun 2024.
    5. 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.
    6. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    7. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    8. Cherchye, Laurens & Cosaert, Sam & De Rock, Bram & Kerstens, Pieter Jan & Vermeulen, Frederic, 2018. "Individual welfare analysis for collective households," Journal of Public Economics, Elsevier, vol. 166(C), pages 98-114.
    9. Sebastiaan Maes & Raghav Malhotra, 2024. "Beyond the Mean: Testing Consumer Rationality through Higher Moments of Demand," Papers 2407.01538, arXiv.org.
    10. 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.
    11. Arthur Lewbel & Krishna Pendakur, 2017. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 1100-1148.
    12. Richard Blundell & Joel L. Horowitz & Matthias Parey, 2013. "Nonparametric estimation of a heterogeneous demand function under the Slutsky inequality restriction," CeMMAP working papers 54/13, Institute for Fiscal Studies.
    13. Hoderlein, Stefan & Su, Liangjun & White, Halbert & Yang, Thomas Tao, 2016. "Testing for monotonicity in unobservables under unconfoundedness," Journal of Econometrics, Elsevier, vol. 193(1), pages 183-202.
    14. Laurens Cherchye & Thomas Demuynck & Bram De Rock, 2015. "Transitivity of Preferences: When Doest it Matter ?," Working Papers ECARES ECARES 2015-44, ULB -- Universite Libre de Bruxelles.
    15. Laurens Cherchye & Thomas Demuynck & Bram De Rock & Marijn Verschelde, 2018. "Nonparametric identification of unobserved technological heterogeneity in production," Working Paper Research 335, National Bank of Belgium.
    16. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    17. Victor H. Aguiar & Per Hjertstrand & Roberto Serrano, 2020. "Rationalizable Incentives: Interim Implementation of Sets in Rationalizable Strategies," Working Papers 2020-16, Brown University, Department of Economics.
    18. Pawe{l} Dziewulski & Joshua Lanier & John K. -H. Quah, 2024. "Revealed preference and revealed preference cycles: a survey," Papers 2405.08459, arXiv.org.
    19. Stefan Hoderlein & Jörg Stoye, 2015. "Testing stochastic rationality and predicting stochastic demand: the case of two goods," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 3(2), pages 313-328, October.
    20. Bhattacharya, D., 2018. "The Empirical Content of Binary Choice Models," Cambridge Working Papers in Economics 1883, Faculty of Economics, University of Cambridge.
    21. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    22. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers 60/17, Institute for Fiscal Studies.
    23. Laurens Cherchye & Thomas Demuynck & Bram De Rock & Frederic Vermeulen, 2017. "Household Consumption When the Marriage is Stable," ULB Institutional Repository 2013/251990, ULB -- Universite Libre de Bruxelles.
    24. Arman Bidarbakht Nia, 2017. "A generalization to QUAIDS," Empirical Economics, Springer, vol. 52(1), pages 393-410, February.
    25. Kobus, Martyna & Kurek, Radosław, 2018. "Copula-based measurement of interdependence for discrete distributions," Journal of Mathematical Economics, Elsevier, vol. 79(C), pages 27-39.
    26. Im, Changkuk & Rehbeck, John, 2022. "Non-rationalizable individuals and stochastic rationalizability," Economics Letters, Elsevier, vol. 219(C).
    27. Laurens CHERCHYE & Thomas DEMUYNCK & Bram DE ROCK, 2011. "Nash bargained consumption decisions: a revealed preference analysis," Working Papers of Department of Economics, Leuven ces11.07, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    28. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    30. Cherchye, Laurens & Demuynck, Thomas & Rock, Bram De, 2019. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Journal of Econometrics, Elsevier, vol. 211(2), pages 483-506.
    31. Mark Dean & Daniel Martin, 2011. "Testing for Rationality with Consumption Data: Demographics and Heterogeneity," Working Papers 2011-11, Brown University, Department of Economics.
    32. Wilfried Youmbi, 2024. "Nonparametric Analysis of Random Utility Models Robust to Nontransitive Preferences," Papers 2406.13969, arXiv.org.
    33. Ian Crawford & Matthew Polisson, 2015. "Demand analysis with partially observed prices," IFS Working Papers W15/16, Institute for Fiscal Studies.
    34. Nail Kashaev & Victor H. Aguiar, 2022. "Nonparametric Analysis of Dynamic Random Utility Models," Papers 2204.07220, arXiv.org.
    35. Jerry Hausman & Whitney K. Newey, 2013. "Individual heterogeneity and average welfare," CeMMAP working papers 34/13, Institute for Fiscal Studies.
    36. Sam Cosaert & Thomas Demuynck, 2015. "Revealed preference theory for finite choice sets," ULB Institutional Repository 2013/251997, ULB -- Universite Libre de Bruxelles.
    37. Cherchye, Laurens & Demuynck, Thomas & De Rock, Bram & Hjertstrand, Per, 2015. "Revealed preference tests for weak separability: An integer programming approach," Journal of Econometrics, Elsevier, vol. 186(1), pages 129-141.
    38. Apostolos Serletis & Maksim Isakin, "undated". "Stochastic Volatility Demand Systems," Working Papers 2014-74, Department of Economics, University of Calgary, revised 29 Sep 2014.
    39. Holger Dette & Stefan Hoderlein & Natalie Neumeyer, 2013. "Testing Multivariate Economic Restrictions Using Quantiles: The Example of Slutsky Negative Semidefiniteness," Boston College Working Papers in Economics 836, Boston College Department of Economics.
    40. Demuynck, Thomas & Hjertstrand, Per, 2019. "Samuelson's Approach to Revealed Preference Theory: Some Recent Advances," Working Paper Series 1274, Research Institute of Industrial Economics.
    41. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    42. Dziewulski, Paweł & Lanier, Joshua & Quah, John K.-H., 2024. "Revealed preference and revealed preference cycles: A survey," Journal of Mathematical Economics, Elsevier, vol. 113(C).
    43. Victor H. Aguiar & Per Hjertstrand & Roberto Serrano, 2022. "A Rationalization of the Weak Axiom of Revealed Preference," University of Western Ontario, Departmental Research Report Series 20229, University of Western Ontario, Department of Economics.
    44. Rahul Deb & Yuichi Kitamura & John K.-H. Quah & Jorg Stoye, 2017. "Revealed Price Preference: Theory and Stochastic Testing," Cowles Foundation Discussion Papers 2087, Cowles Foundation for Research in Economics, Yale University.
    45. Bram De Rock & Laurens Cherchye & Bart Smeulders, 2019. "Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing," Working Papers ECARES 2019-19, ULB -- Universite Libre de Bruxelles.
    46. Maes, Sebastiaan & Malhotra, Raghav, 2024. "Beyond the Mean : Testing Consumer Rationality through Higher Moments of Demand," CRETA Online Discussion Paper Series 85, Centre for Research in Economic Theory and its Applications CRETA.
    47. Dieter Saelens, 2022. "Unitary or collective households? A nonparametric rationality and separability test using detailed data on consumption expenditures and time use," Empirical Economics, Springer, vol. 62(2), pages 637-677, February.
    48. Jerry Hausman & Whitney K. Newey, 2014. "Individual Heterogeneity and Average Welfare," CeMMAP working papers 42/14, Institute for Fiscal Studies.
    49. Daniele Caliari & Henrik Petri, 2024. "Irrational Random Utility Models," Papers 2403.10208, arXiv.org.
    50. Hubner, Stefan, 2023. "Identification of unobserved distribution factors and preferences in the collective household model," Journal of Econometrics, Elsevier, vol. 234(1), pages 301-326.

  13. Jorg Stoye, 2008. "More on confidence intervals for partially identified parameters," CeMMAP working papers CWP11/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Xiaohong Chen & Timothy Christensen & Keith O’Hara & Elie Tamer, 2016. "MCMC Confidence sets for Identified Sets," Cowles Foundation Discussion Papers 2037R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2016.
    2. Christian Bontemps & Thierry Magnac & Eric Maurin, 2012. "Set Identified Linear Models," Econometrica, Econometric Society, vol. 80(3), pages 1129-1155, May.
    3. Sam Cosaert & Thomas Demuynck, 2018. "Nonparametric welfare and demand analysis with unobserved individual heterogeneity," ULB Institutional Repository 2013/251988, ULB -- Universite Libre de Bruxelles.
    4. 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.
    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. 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.
    7. Stefan Boes, 2009. "Bounds on Counterfactual Distributions Under Semi-Monotonicity Constraints," SOI - Working Papers 0920, Socioeconomic Institute - University of Zurich.
    8. Karthik Muralidharan & Mauricio Romero & Kaspar Wüthrich, 2020. "Factorial Designs, Model Selection, and (Incorrect) Inference in Randomized Experiments," CESifo Working Paper Series 8137, CESifo.
    9. 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.
    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. 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.
    12. Christian Bontemps & Thierry Magnac, 2017. "Set identification, moment restrictions, and inference," Post-Print hal-01575813, HAL.
    13. 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.
    14. Christoph Rothe, 2012. "Partial Distributional Policy Effects," Econometrica, Econometric Society, vol. 80(5), pages 2269-2301, September.
    15. Michael Lechner & Blaise Melly, 2010. "Partial Idendification of Wage Effects of Training Programs," Working Papers 2010-8, Brown University, Department of Economics.
    16. 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.
    17. Brian Krauth, 2011. "Bounding a linear causal effect using relative correlation restrictions," Discussion Papers dp11-02, Department of Economics, Simon Fraser University.
    18. Charles Grant & Mario Padula, 2012. "Using Bounds to Investigate Household Debt Repayment Behaviour," CEDI Discussion Paper Series 12-06, Centre for Economic Development and Institutions(CEDI), Brunel University.
    19. Wenlong Ji & Lihua Lei & Asher Spector, 2023. "Model-Agnostic Covariate-Assisted Inference on Partially Identified Causal Effects," Papers 2310.08115, arXiv.org, revised Nov 2024.
    20. Yuan Liao & Anna Simoni, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," Papers 1212.3267, arXiv.org, revised Nov 2013.
    21. 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.
    22. Mikkel Plagborg-M{o}ller & Christian K. Wolf, 2020. "Instrumental Variable Identification of Dynamic Variance Decompositions," Papers 2011.01380, arXiv.org, revised Jul 2021.
    23. 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.
    24. Clément de Chaisemartin, 2012. "Fuzzy differences in differences," PSE Working Papers halshs-00671368, HAL.
    25. Yiwei Sun, 2023. "Extrapolating Away from the Cutoff in Regression Discontinuity Designs," Papers 2311.18136, arXiv.org.
    26. Zahra Siddique, 2013. "Partially Identified Treatment Effects Under Imperfect Compliance: The Case of Domestic Violence," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(502), pages 504-513, June.
    27. Nirav Mehta, 2022. "A Partial Identification Approach to Identifying the Determinants of Human Capital Accumulation: An Application to Teachers," CESifo Working Paper Series 9681, CESifo.
    28. Armstrong, Timothy B., 2014. "Weighted KS statistics for inference on conditional moment inequalities," Journal of Econometrics, Elsevier, vol. 181(2), pages 92-116.
    29. Tiemen M. Woutersen & John Ham, 2013. "Calculating confidence intervals for continuous and discontinuous functions of parameters," CeMMAP working papers 23/13, Institute for Fiscal Studies.
    30. Phillip Heiler & Michael C. Knaus, 2021. "Effect or Treatment Heterogeneity? Policy Evaluation with Aggregated and Disaggregated Treatments," Papers 2110.01427, arXiv.org, revised Aug 2023.
    31. 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.
    32. Guido Imbens & Jeffrey M. Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    33. 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.
    34. Adam McCloskey, 2012. "Bonferroni-Based Size-Correction for Nonstandard Testing Problems," Working Papers 2012-16, Brown University, Department of Economics.
    35. Mariagiovanna Baccara & Ayse Imrohoroglu & Alistair J. Wilson & Leeat Yariv, 2012. "A Field Study on Matching with Network Externalities," American Economic Review, American Economic Association, vol. 102(5), pages 1773-1804, August.
    36. Gerard, Francois & Rokkanen, Miikka & Rothe, Christoph, 2015. "Identification and Inference in Regression Discontinuity Designs with a Manipulated Running Variable," IZA Discussion Papers 9604, Institute of Labor Economics (IZA).
    37. Blanco, German & Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2018. "Bounds on Average and Quantile Treatment Effects on Duration Outcomes under Censoring, Selection, and Noncompliance," GLO Discussion Paper Series 288, Global Labor Organization (GLO).
    38. Chen, Le-Yu & Szroeter, Jerzy, 2014. "Testing multiple inequality hypotheses: A smoothed indicator approach," Journal of Econometrics, Elsevier, vol. 178(P3), pages 678-693.
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    40. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2017. "Monte Carlo confidence sets for identified sets," CeMMAP working papers 43/17, Institute for Fiscal Studies.
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    43. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
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    50. de Chaisemartin, Clement & D'Haultfoeuille, Xavier, "undated". "Supplement to Fuzzy Differences-in-Differences," Economic Research Papers 270217, University of Warwick - Department of Economics.
    51. Sung Jae Jun & Sokbae (Simon) Lee, 2022. "Identifying the effect of persuasion," CeMMAP working papers 24/22, Institute for Fiscal Studies.
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    56. Panos Toulis, 2020. "Estimation of Covid-19 Prevalence from Serology Tests: A Partial Identification Approach," Papers 2006.16214, arXiv.org.
    57. Lee, Ying-Ying & Bhattacharya, Debopam, 2019. "Applied welfare analysis for discrete choice with interval-data on income," Journal of Econometrics, Elsevier, vol. 211(2), pages 361-387.
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    59. Fan, Yanqin & Guerre, Emmanuel & Zhu, Dongming, 2017. "Partial identification of functionals of the joint distribution of “potential outcomes”," Journal of Econometrics, Elsevier, vol. 197(1), pages 42-59.
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    63. Timothy B. Armstrong & Hock Peng Chan, 2013. "Multiscale Adaptive Inference on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1885R, Cowles Foundation for Research in Economics, Yale University, revised Oct 2014.
    64. Jörg Stoye, 2022. "Bounding infection prevalence by bounding selectivity and accuracy of tests: with application to early COVID-19," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 1-14.
    65. Gerard, François & Rothe, Christoph & Rokkanen, Miikka, 2016. "Bounds on Treatment Effects in Regression Discontinuity Designs under Manipulation of the Running Variable, with an Application," CEPR Discussion Papers 11668, C.E.P.R. Discussion Papers.
    66. 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).
    67. Alistair Wilson & Mariagiovanna Baccara & Ayse Imrohoroglu & Leeat Yariv, 2009. "A Field Study on Matching with Network Externalities," Working Paper 486, Department of Economics, University of Pittsburgh, revised Sep 2011.
    68. Magnac, Thierry, 2014. "Identification partielle: méthodes et conséquences pour les applications empiriques," IDEI Working Papers 814, Institut d'Économie Industrielle (IDEI), Toulouse.
    69. Karim Chalak, 2012. "Identification of Average Random Coefficients under Magnitude and Sign Restrictions on Confounding," Boston College Working Papers in Economics 816, Boston College Department of Economics.
    70. 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.
    71. Donald W.K. Andrews, 2011. "Similar-on-the-Boundary Tests for Moment Inequalities Exist, But Have Poor Power," Cowles Foundation Discussion Papers 1815R, Cowles Foundation for Research in Economics, Yale University, revised Mar 2012.
    72. Hübler, Olaf, 2013. "Methods in empirical economics - a selective review with applications," Hannover Economic Papers (HEP) dp-513, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    73. Phillip Heiler, 2022. "Heterogeneous Treatment Effect Bounds under Sample Selection with an Application to the Effects of Social Media on Political Polarization," Papers 2209.04329, arXiv.org, revised Jul 2024.
    74. 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.
    75. Chen, Heng & Fan, Yanqin & Liu, Ruixuan, 2016. "Inference for the correlation coefficient between potential outcomes in the Gaussian switching regime model," Journal of Econometrics, Elsevier, vol. 195(2), pages 255-270.
    76. 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.
    77. 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.
    78. Tetsuya Kaji & Jianfei Cao, 2023. "Assessing Heterogeneity of Treatment Effects," Papers 2306.15048, arXiv.org.
    79. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    80. 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.
    81. Yuan Liao & Anna Simoni, 2019. "Bayesian inference for partially identified smooth convex models," Post-Print hal-03089881, HAL.
    82. Fan, Yanqin & Park, Sang Soo, 2009. "Partial identification of the distribution of treatment effects and its confidence sets," MPRA Paper 37148, University Library of Munich, Germany.
    83. 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.
    84. Bedoya, Guadalupe & Bittarello, Luca & Davis, Jonathan & Mittag, Nikolas, 2018. "Distributional Impact Analysis: Toolkit and Illustrations of Impacts beyond the Average Treatment Effect," IZA Discussion Papers 11863, Institute of Labor Economics (IZA).
    85. 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.
    86. 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.
    87. Allen, Roy, 2018. "Testing moment inequalities: Selection versus recentering," Economics Letters, Elsevier, vol. 162(C), pages 124-126.
    88. Demuynck, Thomas, 2015. "Bounding average treatment effects: A linear programming approach," Economics Letters, Elsevier, vol. 137(C), pages 75-77.
    89. 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.
    90. 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.
    91. Kyungchul Song, 2009. "Point Decisions for Interval-Identified Parameters," PIER Working Paper Archive 09-036, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    92. Toulis, Panos, 2021. "Estimation of Covid-19 prevalence from serology tests: A partial identification approach," Journal of Econometrics, Elsevier, vol. 220(1), pages 193-213.
    93. Yvonne Jie Chen & Deniz Dutz & Li Li & Sarah Moon & Edward J. Vytlacil & Songfa Zhong, 2023. "Eliciting Willingness-to-Pay to Decompose Beliefs and Preferences that Determine Selection into Competition in Lab Experiments," NBER Working Papers 31930, National Bureau of Economic Research, Inc.
    94. Juan Carlos Escanciano & Lin Zhu, 2013. "Set inferences and sensitivity analysis in semiparametric conditionally identified models," CeMMAP working papers 55/13, Institute for Fiscal Studies.
    95. Holford, Angus J., 2016. "Youth Employment and Academic Performance: Production Functions and Policy Effects," IZA Discussion Papers 10009, Institute of Labor Economics (IZA).
    96. Brigham R. Frandsen & Lars J. Lefgren, 2021. "Partial identification of the distribution of treatment effects with an application to the Knowledge is Power Program (KIPP)," Quantitative Economics, Econometric Society, vol. 12(1), pages 143-171, January.
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    100. Sokbae Lee & Martin Weidner, 2021. "Bounding Treatment Effects by Pooling Limited Information across Observations," Papers 2111.05243, arXiv.org, revised Dec 2023.
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    102. Fan, Yanqin & Park, Sang Soo, 2010. "Confidence sets for some partially identified parameters," MPRA Paper 37149, University Library of Munich, Germany.
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    108. Joachim Freyberger & Joel L. Horowitz, 2012. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers 15/12, Institute for Fiscal Studies.
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Articles

  1. Rahul Deb & Yuichi Kitamura & John K H Quah & Jörg Stoye, 2023. "Revealed Price Preference: Theory and Empirical Analysis," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(2), pages 707-743.
    See citations under working paper version above.
  2. Kaido, Hiroaki & Molinari, Francesca & Stoye, Jörg, 2022. "Constraint Qualifications In Partial Identification," Econometric Theory, Cambridge University Press, vol. 38(3), pages 596-619, June.
    See citations under working paper version above.
  3. Jörg Stoye, 2022. "Bounding infection prevalence by bounding selectivity and accuracy of tests: with application to early COVID-19," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 1-14.
    See citations under working paper version above.
  4. Orlov, George & McKee, Douglas & Berry, James & Boyle, Austin & DiCiccio, Thomas & Ransom, Tyler & Rees-Jones, Alex & Stoye, Jörg, 2021. "Learning during the COVID-19 pandemic: It is not who you teach, but how you teach," Economics Letters, Elsevier, vol. 202(C).
    See citations under working paper version above.
  5. Hiroaki Kaido & Francesca Molinari & Jörg Stoye, 2019. "Confidence Intervals for Projections of Partially Identified Parameters," Econometrica, Econometric Society, vol. 87(4), pages 1397-1432, July.
    See citations under working paper version above.
  6. Stoye, Jörg, 2019. "Revealed Stochastic Preference: A one-paragraph proof and generalization," Economics Letters, Elsevier, vol. 177(C), pages 66-68.
    See citations under working paper version above.
  7. Yuichi Kitamura & Jörg Stoye, 2018. "Nonparametric Analysis of Random Utility Models," Econometrica, Econometric Society, vol. 86(6), pages 1883-1909, November.
    See citations under working paper version above.
  8. Stoye, Jörg, 2015. "Choice theory when agents can randomize," Journal of Economic Theory, Elsevier, vol. 155(C), pages 131-151.

    Cited by:

    1. Georgios Gerasimou, 2018. "Indecisiveness, Undesirability and Overload Revealed Through Rational Choice Deferral," Economic Journal, Royal Economic Society, vol. 128(614), pages 2450-2479, September.
    2. Simone Cerreia-Vioglio & David Dillenberger & Pietro Ortoleva & Gil Riella, 2019. "Deliberately Stochastic," American Economic Review, American Economic Association, vol. 109(7), pages 2425-2445, July.
      • Simone Cerreia-Vioglio & David Dillenberger & Pietro Ortoleva & Gil Riella, 2012. "Deliberately Stochastic," PIER Working Paper Archive 17-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 May 2017.
    3. Joseph Halpern & Samantha Leung, 2015. "Weighted sets of probabilities and minimax weighted expected regret: a new approach for representing uncertainty and making decisions," Theory and Decision, Springer, vol. 79(3), pages 415-450, November.
    4. Georgios Gerasimou, 2021. "Eliciting and Distinguishing Between Weak and Incomplete Preferences: Theory, Experiment and Computation," Papers 2111.14431, arXiv.org, revised Dec 2024.
    5. Kuzmics, Christoph, 2017. "Abraham Wald's complete class theorem and Knightian uncertainty," Games and Economic Behavior, Elsevier, vol. 104(C), pages 666-673.

  9. Stefan Hoderlein & Jörg Stoye, 2015. "Testing stochastic rationality and predicting stochastic demand: the case of two goods," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 3(2), pages 313-328, October.

    Cited by:

    1. Sam Cosaert & Thomas Demuynck, 2018. "Nonparametric welfare and demand analysis with unobserved individual heterogeneity," ULB Institutional Repository 2013/251988, ULB -- Universite Libre de Bruxelles.
    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. Sebastiaan Maes & Raghav Malhotra, 2024. "Beyond the Mean: Testing Consumer Rationality through Higher Moments of Demand," Papers 2407.01538, arXiv.org.
    4. Changkuk Im & John Rehbeck, 2021. "Non-rationalizable Individuals, Stochastic Rationalizability, and Sampling," Papers 2102.03436, arXiv.org, revised Oct 2021.
    5. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    6. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers 60/17, Institute for Fiscal Studies.
    7. Im, Changkuk & Rehbeck, John, 2022. "Non-rationalizable individuals and stochastic rationalizability," Economics Letters, Elsevier, vol. 219(C).
    8. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    9. Adams-Prassl, Abigail, 2019. "Mutually Consistent Revealed Preference Demand Predictions," CEPR Discussion Papers 13580, C.E.P.R. Discussion Papers.
    10. Stoye, Jörg, 2019. "Revealed Stochastic Preference: A one-paragraph proof and generalization," Economics Letters, Elsevier, vol. 177(C), pages 66-68.
    11. Ian Crawford & Matthew Polisson, 2015. "Demand analysis with partially observed prices," IFS Working Papers W15/16, Institute for Fiscal Studies.
    12. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    13. Charles F. Manski, 2014. "Identification of income–leisure preferences and evaluation of income tax policy," Quantitative Economics, Econometric Society, vol. 5, pages 145-174, March.
    14. Maes, Sebastiaan & Malhotra, Raghav, 2024. "Beyond the Mean : Testing Consumer Rationality through Higher Moments of Demand," CRETA Online Discussion Paper Series 85, Centre for Research in Economic Theory and its Applications CRETA.
    15. Sebastiaan Maes & Raghav Malhotra, 2023. "Robust Hicksian Welfare Analysis under Individual Heterogeneity," Papers 2303.01231, arXiv.org, revised Nov 2023.
    16. Yuichi Kitamura & Jorg Stoye, 2019. "Nonparametric Counterfactuals in Random Utility Models," Papers 1902.08350, arXiv.org, revised May 2019.
    17. Daniele Caliari & Henrik Petri, 2024. "Irrational Random Utility Models," Papers 2403.10208, arXiv.org.
    18. Allen, Roy & Dziewulski, Paweł & Rehbeck, John, 2022. "Making sense of monkey business: Re-examining tests of animal rationality," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 220-228.
    19. Hubner, Stefan, 2023. "Identification of unobserved distribution factors and preferences in the collective household model," Journal of Econometrics, Elsevier, vol. 234(1), pages 301-326.

  10. Stefan Hoderlein & Jörg Stoye, 2014. "Revealed Preferences in a Heterogeneous Population," The Review of Economics and Statistics, MIT Press, vol. 96(2), pages 197-213, May.
    See citations under working paper version above.
  11. Jörg Stoye, 2012. "New Perspectives on Statistical Decisions Under Ambiguity," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 257-282, July.

    Cited by:

    1. Tamini, Lota Dabio, 2012. "Optimal quality choice under uncertainty on market development," Working Papers 148589, Structure and Performance of Agriculture and Agri-products Industry (SPAA).
    2. Yuan Liao & Anna Simoni, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," Papers 1212.3267, arXiv.org, revised Nov 2013.
    3. Stoye, Jörg, 2015. "Choice theory when agents can randomize," Journal of Economic Theory, Elsevier, vol. 155(C), pages 131-151.
    4. Bruce A. Reinig & Ira Horowitz, 2018. "Using Mathematical Programming to Select and Seed Teams for the NCAA Tournament," Interfaces, INFORMS, vol. 48(3), pages 181-188, June.
    5. Jörg Stoye, 2022. "Bounding infection prevalence by bounding selectivity and accuracy of tests: with application to early COVID-19," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 1-14.
    6. Isaiah Andrews & Jesse M. Shapiro, 2020. "A Model of Scientific Communication," NBER Working Papers 26824, National Bureau of Economic Research, Inc.
    7. Tamini, Lota D., 2012. "Optimal quality choice under uncertainty on market development," MPRA Paper 40845, University Library of Munich, Germany.
    8. Gabriel Carroll, 2015. "Robustness and Linear Contracts," American Economic Review, American Economic Association, vol. 105(2), pages 536-563, February.
    9. Karun Adusumilli & Friedrich Geiecke & Claudio Schilter, 2019. "Dynamically Optimal Treatment Allocation," Papers 1904.01047, arXiv.org, revised Nov 2024.
    10. T. D. Pol & S. Gabbert & H.-P. Weikard & E. C. Ierland & E. M. T. Hendrix, 2017. "A Minimax Regret Analysis of Flood Risk Management Strategies Under Climate Change Uncertainty and Emerging Information," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(4), pages 1087-1109, December.

  12. Stoye, Jörg, 2012. "Dominance and admissibility without priors," Economics Letters, Elsevier, vol. 116(1), pages 118-120.

    Cited by:

    1. Stoye, Jörg, 2015. "Choice theory when agents can randomize," Journal of Economic Theory, Elsevier, vol. 155(C), pages 131-151.
    2. Baker, Erin & Bosetti, Valentina & Salo, Ahti, 2020. "Robust portfolio decision analysis: An application to the energy research and development portfolio problem," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1107-1120.

  13. Stoye, Jörg, 2012. "Minimax regret treatment choice with covariates or with limited validity of experiments," Journal of Econometrics, Elsevier, vol. 166(1), pages 138-156.

    Cited by:

    1. Manski, Charles F., 2023. "Probabilistic prediction for binary treatment choice: With focus on personalized medicine," Journal of Econometrics, Elsevier, vol. 234(2), pages 647-663.
    2. Charles F. Manski, 2018. "Reasonable patient care under uncertainty," Health Economics, John Wiley & Sons, Ltd., vol. 27(10), pages 1397-1421, October.
    3. Charles F. Manski, 2017. "Improving Clinical Guidelines and Decisions under Uncertainty," NBER Working Papers 23915, National Bureau of Economic Research, Inc.
    4. Federico Crippa, 2024. "Regret Analysis in Threshold Policy Design," Papers 2404.11767, arXiv.org.
    5. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised May 2024.
    6. Yuchen Hu & Henry Zhu & Emma Brunskill & Stefan Wager, 2024. "Minimax-Regret Sample Selection in Randomized Experiments," Papers 2403.01386, arXiv.org, revised Jun 2024.
    7. Nathan Kallus & Angela Zhou, 2021. "Minimax-Optimal Policy Learning Under Unobserved Confounding," Management Science, INFORMS, vol. 67(5), pages 2870-2890, May.
    8. Knaus, Michael C., 2020. "Double Machine Learning based Program Evaluation under Unconfoundedness," Economics Working Paper Series 2004, University of St. Gallen, School of Economics and Political Science.
    9. Charles F. Manski, 2019. "Econometrics For Decision Making: Building Foundations Sketched By Haavelmo And Wald," Papers 1912.08726, arXiv.org, revised Feb 2021.
    10. Charles F. Manski & Aleksey Tetenov, 2014. "The Quantile Performance of Statistical Treatment Rules Using Hypothesis Tests to Allocate a Population to Two Treatments," CeMMAP working papers 44/14, Institute for Fiscal Studies.
    11. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
    12. Alexei Parakhonyak & Anton Sobolev, 2015. "Non‐Reservation Price Equilibrium and Search without Priors," Economic Journal, Royal Economic Society, vol. 0(584), pages 887-909, May.
    13. Anders Bredahl Kock & David Preinerstorfer, 2024. "Regularizing Discrimination in Optimal Policy Learning with Distributional Targets," Papers 2401.17909, arXiv.org.
    14. Susan Athey & Stefan Wager, 2017. "Policy Learning with Observational Data," Papers 1702.02896, arXiv.org, revised Sep 2020.
    15. Charles F. Manski, 2017. "Optimize, satisfice, or choose without deliberation? A simple minimax-regret assessment," Theory and Decision, Springer, vol. 83(2), pages 155-173, August.
    16. Charles F. Manski, 2019. "Statistical inference for statistical decisions," Papers 1909.06853, arXiv.org.
    17. Kitagawa, Toru & Wang, Guanyi, 2023. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," Journal of Econometrics, Elsevier, vol. 232(1), pages 109-131.
    18. Charles F. Manski, 2019. "Meta-Analysis for Medical Decisions," NBER Working Papers 25504, National Bureau of Economic Research, Inc.
    19. Evan Sadler, 2015. "Minimax and the value of information," Theory and Decision, Springer, vol. 78(4), pages 575-586, April.
    20. Daido Kido, 2023. "Locally Asymptotically Minimax Statistical Treatment Rules Under Partial Identification," Papers 2311.08958, arXiv.org.
    21. Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev, 2022. "Functional Sequential Treatment Allocation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(539), pages 1311-1323, September.
    22. Masahiro Kato & Masaaki Imaizumi & Takuya Ishihara & Toru Kitagawa, 2023. "Asymptotically Optimal Fixed-Budget Best Arm Identification with Variance-Dependent Bounds," Papers 2302.02988, arXiv.org, revised Jul 2023.
    23. Eric Mbakop & Max Tabord‐Meehan, 2021. "Model Selection for Treatment Choice: Penalized Welfare Maximization," Econometrica, Econometric Society, vol. 89(2), pages 825-848, March.
    24. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    25. Augustine Denteh & Helge Liebert, 2022. "Who Increases Emergency Department Use? New Insights from the Oregon Health Insurance Experiment," CESifo Working Paper Series 9664, CESifo.
    26. Azevedo, Eduardo M. & Mao, David & Montiel Olea, José Luis & Velez, Amilcar, 2023. "The A/B testing problem with Gaussian priors," Journal of Economic Theory, Elsevier, vol. 210(C).
    27. Kock, Anders Bredahl & Preinerstorfer, David & Veliyev, Bezirgen, 2023. "Treatment recommendation with distributional targets," Journal of Econometrics, Elsevier, vol. 234(2), pages 624-646.
    28. Christopher Adjaho & Timothy Christensen, 2022. "Externally Valid Policy Choice," Papers 2205.05561, arXiv.org, revised Jul 2023.
    29. Chunrong Ai & Yue Fang & Haitian Xie, 2024. "Data-driven Policy Learning for Continuous Treatments," Papers 2402.02535, arXiv.org, revised Nov 2024.
    30. Charles F. Manski & Aleksey Tetenov, 2015. "Clinical trial design enabling e-optimal treatment rules," CeMMAP working papers CWP60/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    31. Jeff Dominitz & Charles F. Manski, 2024. "Comprehensive OOS Evaluation of Predictive Algorithms with Statistical Decision Theory," Papers 2403.11016, arXiv.org, revised May 2024.
    32. Charles F. Manski, 2020. "Towards Reasonable Patient Care Under Uncertainty," Contemporary Economic Policy, Western Economic Association International, vol. 38(2), pages 227-245, April.
    33. Haitian Xie, 2020. "Finite-Sample Average Bid Auction," Papers 2008.10217, arXiv.org, revised Feb 2022.
    34. Keisuke Hirano & Jack R. Porter, 2016. "Panel Asymptotics and Statistical Decision Theory," The Japanese Economic Review, Japanese Economic Association, vol. 67(1), pages 33-49, March.
    35. Thomas M. Russell, 2020. "Policy Transforms and Learning Optimal Policies," Papers 2012.11046, arXiv.org.
    36. Charles F. Manski & Aleksey Tetenov, 2023. "Statistical Decision Theory Respecting Stochastic Dominance," Papers 2308.05171, arXiv.org.
    37. Toru Kitagawa & Sokbae Lee & Chen Qiu, 2022. "Treatment Choice with Nonlinear Regret," Papers 2205.08586, arXiv.org, revised Oct 2024.
    38. Davide Viviano & Jelena Bradic, 2020. "Fair Policy Targeting," Papers 2005.12395, arXiv.org, revised Jun 2022.
    39. Charles F. Manski & Aleksey Tetenov, 2015. "Clinical trial design enabling epsilon-optimal treatment rules," Carlo Alberto Notebooks 430, Collegio Carlo Alberto.
    40. Neil Christy & A. E. Kowalski, 2024. "Starting Small: Prioritizing Safety over Efficacy in Randomized Experiments Using the Exact Finite Sample Likelihood," Papers 2407.18206, arXiv.org.

  14. Jörg Stoye, 2011. "Statistical decisions under ambiguity," Theory and Decision, Springer, vol. 70(2), pages 129-148, February.

    Cited by:

    1. Stoye, Jörg, 2011. "Axioms for minimax regret choice correspondences," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2226-2251.
    2. Ludovic Renou & Karl H. Schlag, 2008. "Minimax regret and strategic uncertainty," Discussion Papers in Economics 08/2, Division of Economics, School of Business, University of Leicester, revised Apr 2008.
    3. William A. Brock & Steven N. Durlauf & James M. Nason & Giacomo Rondina, 2007. "Simple versus optimal rules as guides to policy," FRB Atlanta Working Paper 2007-07, Federal Reserve Bank of Atlanta.
    4. Moti Michaeli, 2014. "Riskiness for sets of gambles," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 56(3), pages 515-547, August.
    5. Tetenov, Aleksey, 2012. "Statistical treatment choice based on asymmetric minimax regret criteria," Journal of Econometrics, Elsevier, vol. 166(1), pages 157-165.
    6. Iverson, Terrence, 2013. "Minimax regret discounting," Journal of Environmental Economics and Management, Elsevier, vol. 66(3), pages 598-608.
    7. Karl H. Schlag, 2007. "Distribution-Free Learning," Economics Working Papers ECO2007/01, European University Institute.
    8. Zhe Yang & Yong Pu, 2012. "Existence and stability of minimax regret equilibria," Journal of Global Optimization, Springer, vol. 54(1), pages 17-26, September.
    9. Bergemann, Dirk & Schlag, Karl, 2011. "Robust monopoly pricing," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2527-2543.
    10. Di Bartolomeo, Giovanni & Di Pietro, Marco, 2018. "Optimal Inflation Targeting Rule Under Positive Hazard Functions For Price Changes," Macroeconomic Dynamics, Cambridge University Press, vol. 22(1), pages 135-152, January.
    11. Anderson, Edward & Zachary, Stan, 2023. "Minimax decision rules for planning under uncertainty: Drawbacks and remedies," European Journal of Operational Research, Elsevier, vol. 311(2), pages 789-800.
    12. Baker, Erin & Olaleye, Olaitan & Aleluia Reis, Lara, 2015. "Decision frameworks and the investment in R&D," Energy Policy, Elsevier, vol. 80(C), pages 275-285.
    13. Evan Sadler, 2015. "Minimax and the value of information," Theory and Decision, Springer, vol. 78(4), pages 575-586, April.
    14. Takashi Hayashi, 2011. "Context dependence and consistency in dynamic choice under uncertainty: the case of anticipated regret," Theory and Decision, Springer, vol. 70(4), pages 399-430, April.
    15. Takashi Hayashi, 2008. "Context dependence and consistency in dynamic choice under uncertainty: the case of anticipated regret," KIER Working Papers 659, Kyoto University, Institute of Economic Research.
    16. Stoye, Jörg, 2015. "Choice theory when agents can randomize," Journal of Economic Theory, Elsevier, vol. 155(C), pages 131-151.
    17. Stoye, Jörg, 2012. "Dominance and admissibility without priors," Economics Letters, Elsevier, vol. 116(1), pages 118-120.
    18. Massimo Marinacci, 2015. "Model Uncertainty," Journal of the European Economic Association, European Economic Association, vol. 13(6), pages 1022-1100, December.
    19. Renou, Ludovic & Schlag, Karl H., 2011. "Implementation in minimax regret equilibrium," Games and Economic Behavior, Elsevier, vol. 71(2), pages 527-533, March.
    20. Joseph Halpern & Samantha Leung, 2015. "Weighted sets of probabilities and minimax weighted expected regret: a new approach for representing uncertainty and making decisions," Theory and Decision, Springer, vol. 79(3), pages 415-450, November.
    21. Isaiah Andrews & Jesse M. Shapiro, 2020. "A Model of Scientific Communication," NBER Working Papers 26824, National Bureau of Economic Research, Inc.
    22. William A. Brock & Steven N. Durlauf, 2015. "On Sturdy Policy Evaluation," The Journal of Legal Studies, University of Chicago Press, vol. 44(S2), pages 447-473.
    23. Erin Baker & Valentina Bosetti & Ahti Salo, 2017. "Finding common ground when experts disagree: Robust portfolio decision analysis," Working Papers 2017/11, Institut d'Economia de Barcelona (IEB).
    24. Herweg, Fabian & Müller, Daniel, 2021. "A comparison of regret theory and salience theory for decisions under risk," Journal of Economic Theory, Elsevier, vol. 193(C).
    25. Clemens Puppe & Karl Schlag, 2009. "Choice under complete uncertainty when outcome spaces are state dependent," Theory and Decision, Springer, vol. 66(1), pages 1-16, January.
    26. Shafer, Rachel C., 2020. "Minimax regret and failure to converge to efficiency in large markets," Games and Economic Behavior, Elsevier, vol. 124(C), pages 281-287.
    27. Yihao Luo & Jinhui Pang & Weibin Han & Huafei Sun, 2021. "New Solution based on Hodge Decomposition for Abstract Games," Papers 2109.14539, arXiv.org, revised Jul 2024.
    28. Hayashi, Takashi, 2009. "Stopping with anticipated regret," Journal of Mathematical Economics, Elsevier, vol. 45(7-8), pages 479-490, July.
    29. Baker, Erin & Bosetti, Valentina & Salo, Ahti, 2020. "Robust portfolio decision analysis: An application to the energy research and development portfolio problem," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1107-1120.
    30. Giordani, Paolo E. & Schlag, Karl H. & Zwart, Sanne, 2010. "Decision makers facing uncertainty: Theory versus evidence," Journal of Economic Psychology, Elsevier, vol. 31(4), pages 659-675, August.
    31. Tamini, Lota D., 2012. "Optimal quality choice under uncertainty on market development," MPRA Paper 40845, University Library of Munich, Germany.
    32. Diecidue, Enrico & Somasundaram, Jeeva, 2017. "Regret theory: A new foundation," Journal of Economic Theory, Elsevier, vol. 172(C), pages 88-119.
    33. Stoye, Jörg, 2009. "Minimax regret treatment choice with finite samples," Journal of Econometrics, Elsevier, vol. 151(1), pages 70-81, July.
    34. Thomas M. Russell, 2020. "Policy Transforms and Learning Optimal Policies," Papers 2012.11046, arXiv.org.

  15. Stoye, Jörg, 2011. "Axioms for minimax regret choice correspondences," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2226-2251.

    Cited by:

    1. Bonanno, Giacomo, 2022. "Minimax regret with imperfect ex-post knowledge of the state," Research in Economics, Elsevier, vol. 76(4), pages 403-412.
    2. Moti Michaeli, 2014. "Riskiness for sets of gambles," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 56(3), pages 515-547, August.
    3. Dirk Bergemann & Karl H Schlag, 2007. "Pricing without Priors," Levine's Bibliography 122247000000001557, UCLA Department of Economics.
    4. Paolo Galeazzi & Johannes Marti, 2023. "Choice Structures in Games," Papers 2304.11575, arXiv.org.
    5. Sabino, Emerson Rodrigues & Rêgo, Leandro Chaves, 2024. "Minimax regret stability in the graph model for conflict resolution," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1087-1097.
    6. Joseph Y. Halpern & Samantha Leung, 2016. "Minimizing regret in dynamic decision problems," Theory and Decision, Springer, vol. 81(1), pages 123-151, June.
    7. Halpern, Joseph Y. & Pass, Rafael, 2012. "Iterated regret minimization: A new solution concept," Games and Economic Behavior, Elsevier, vol. 74(1), pages 184-207.
    8. Bernhard Kasberger & Kyle Woodward, 2021. "Bidding in Multi-Unit Auctions under Limited Information," Papers 2112.11320, arXiv.org, revised Apr 2023.
    9. Heydari, Pedram, 2024. "Regret, responsibility, and randomization: A theory of stochastic choice," Journal of Economic Theory, Elsevier, vol. 217(C).
    10. René Caldentey & Ying Liu & Ilan Lobel, 2017. "Intertemporal Pricing Under Minimax Regret," Operations Research, INFORMS, vol. 65(1), pages 104-129, February.
    11. Alexei Parakhonyak & Anton Sobolev, 2015. "Non‐Reservation Price Equilibrium and Search without Priors," Economic Journal, Royal Economic Society, vol. 0(584), pages 887-909, May.
    12. Gökhan Buturaky & Özgür Evren, 2016. "Choice Overload and Asymmetric Regret," Working Papers w0235, New Economic School (NES).
    13. Benjamin R. Handel & Kanishka Misra, 2015. "Robust New Product Pricing," Marketing Science, INFORMS, vol. 34(6), pages 864-881, November.
    14. Zhe Yang & Yong Pu, 2012. "Existence and stability of minimax regret equilibria," Journal of Global Optimization, Springer, vol. 54(1), pages 17-26, September.
    15. Xiaoyu Cheng, 2022. "Robust Data-Driven Decisions Under Model Uncertainty," Papers 2205.04573, arXiv.org.
    16. Dirk Bergemann & Tan Gan & Yingkai Li, 2023. "Managing Persuasion Robustly: The Optimality of Quota Rules," Cowles Foundation Discussion Papers 2372, Cowles Foundation for Research in Economics, Yale University.
    17. Bergemann, Dirk & Schlag, Karl, 2011. "Robust monopoly pricing," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2527-2543.
    18. Anderson, Edward & Zachary, Stan, 2023. "Minimax decision rules for planning under uncertainty: Drawbacks and remedies," European Journal of Operational Research, Elsevier, vol. 311(2), pages 789-800.
    19. García-Pola, Bernardo, 2020. "Do people minimize regret in strategic situations? A level-k comparison," Games and Economic Behavior, Elsevier, vol. 124(C), pages 82-104.
    20. Takashi Hayashi, 2011. "Context dependence and consistency in dynamic choice under uncertainty: the case of anticipated regret," Theory and Decision, Springer, vol. 70(4), pages 399-430, April.
    21. Takashi Hayashi, 2008. "Context dependence and consistency in dynamic choice under uncertainty: the case of anticipated regret," KIER Working Papers 659, Kyoto University, Institute of Economic Research.
    22. Stoye, Jörg, 2015. "Choice theory when agents can randomize," Journal of Economic Theory, Elsevier, vol. 155(C), pages 131-151.
    23. Evan Calford & Ryan Oprea, 2017. "Continuity, Inertia, and Strategic Uncertainty: A Test of the Theory of Continuous Time Games," Econometrica, Econometric Society, vol. 85, pages 915-935, May.
    24. Joseph Halpern & Samantha Leung, 2015. "Weighted sets of probabilities and minimax weighted expected regret: a new approach for representing uncertainty and making decisions," Theory and Decision, Springer, vol. 79(3), pages 415-450, November.
    25. Mass, Helene, 2018. "Strategies under strategic uncertainty," ZEW Discussion Papers 18-055, ZEW - Leibniz Centre for European Economic Research.
    26. Jörg Stoye, 2011. "Statistical decisions under ambiguity," Theory and Decision, Springer, vol. 70(2), pages 129-148, February.
    27. Eddie Dekel & Barton L. Lipman, 2009. "How (Not) to Do Decision Theory," Levine's Working Paper Archive 814577000000000339, David K. Levine.
    28. Hayashi, Takashi, 2009. "Stopping with anticipated regret," Journal of Mathematical Economics, Elsevier, vol. 45(7-8), pages 479-490, July.
    29. Yingni Guo & Eran Shmaya, 2023. "Regret-Minimizing Project Choice," Papers 2309.00214, arXiv.org.
    30. Galeazzi, Paolo & Marti, Johannes, 2023. "Choice structures in games," Games and Economic Behavior, Elsevier, vol. 140(C), pages 431-455.
    31. Sebastian Silva-Leander & Suman Seth, 2017. "Revealed preferences with plural motives: axiomatic foundations of normative assessments in non-utilitarian welfare economics," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 48(3), pages 505-517, March.
    32. John Hey & Gianna Lotito & Anna Maffioletti, 2010. "The descriptive and predictive adequacy of theories of decision making under uncertainty/ambiguity," Journal of Risk and Uncertainty, Springer, vol. 41(2), pages 81-111, October.
    33. Stoye, Jörg, 2009. "Minimax regret treatment choice with finite samples," Journal of Econometrics, Elsevier, vol. 151(1), pages 70-81, July.
    34. Wanchang Zhang, 2022. "Auctioning Multiple Goods without Priors," Papers 2204.13726, arXiv.org.
    35. Jerry Anunrojwong & Santiago R. Balseiro & Omar Besbes, 2024. "The Best of Many Robustness Criteria in Decision Making: Formulation and Application to Robust Pricing," Papers 2403.12260, arXiv.org.
    36. Bernhard Kasberger, 2022. "An Equilibrium Model of the First-Price Auction with Strategic Uncertainty: Theory and Empirics," Papers 2202.07517, arXiv.org, revised Mar 2022.
    37. Zhuzhu Zhou, 2024. "Ranking blame," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 78(2), pages 403-441, September.
    38. René Caldentey & Ying Liu & Ilan Lobel, 2017. "Intertemporal Pricing Under Minimax Regret," Operations Research, INFORMS, vol. 65(1), pages 104-129, February.
    39. Yingni Guo & Eran Shmaya, 2023. "Regret‐Minimizing Project Choice," Econometrica, Econometric Society, vol. 91(5), pages 1567-1593, September.
    40. Daniele Pennesi, 2021. "Between Commitment and Flexibility: Revealing Anticipated Regret and Elation," Working papers 071, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    41. Kanishka Misra & Eric M. Schwartz & Jacob Abernethy, 2019. "Dynamic Online Pricing with Incomplete Information Using Multiarmed Bandit Experiments," Marketing Science, INFORMS, vol. 38(2), pages 226-252, March.

  16. Jörg Stoye, 2010. "Partial identification of spread parameters," Quantitative Economics, Econometric Society, vol. 1(2), pages 323-357, November.

    Cited by:

    1. Ismael Mourifie & Marc Henry & Romuald Meango, 2017. "Sharp bounds and testability of a Roy model of STEM major choices," Papers 1709.09284, arXiv.org, revised Nov 2019.
    2. Xavier d'Haultfoeuille & Roland Rathelot, 2011. "Measuring Segregation on Small Units : A Partial Identification Analysis," Working Papers 2011-18, Center for Research in Economics and Statistics.
    3. 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.
    4. Černý, Michal & Hladík, Milan, 2014. "The complexity of computation and approximation of the t-ratio over one-dimensional interval data," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 26-43.
    5. Christoph Rothe, 2012. "Partial Distributional Policy Effects," Econometrica, Econometric Society, vol. 80(5), pages 2269-2301, September.
    6. David M. Kaplan & Longhao Zhuo, 2019. "Comparing latent inequality with ordinal data," Working Papers 1909, Department of Economics, University of Missouri.
    7. Girsberger, Esther Mirjam & Meango, Romuald & Rapoport, Hillel, 2018. "Regional Migration and Wage Inequality in the West African Economic and Monetary Union," IZA Discussion Papers 12048, Institute of Labor Economics (IZA).
    8. Manski, Charles F., 2016. "Credible interval estimates for official statistics with survey nonresponse," Journal of Econometrics, Elsevier, vol. 191(2), pages 293-301.
    9. Stefan Hoderlein & Jörg Stoye, 2015. "Testing stochastic rationality and predicting stochastic demand: the case of two goods," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 3(2), pages 313-328, October.
    10. Firpo, Sergio & Ridder, Geert, 2019. "Partial identification of the treatment effect distribution and its functionals," Journal of Econometrics, Elsevier, vol. 213(1), pages 210-234.
    11. François Gerard & Miikka Rokkanen & Christoph Rothe, 2020. "Bounds on treatment effects in regression discontinuity designs with a manipulated running variable," Quantitative Economics, Econometric Society, vol. 11(3), pages 839-870, July.
    12. Matthew A. Masten & Alexandre Poirier, 2017. "Identification of Treatment Effects under Conditional Partial Independence," Papers 1707.09563, arXiv.org.
    13. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Aug 2023.
    14. Fan, Yanqin & Guerre, Emmanuel & Zhu, Dongming, 2017. "Partial identification of functionals of the joint distribution of “potential outcomes”," Journal of Econometrics, Elsevier, vol. 197(1), pages 42-59.
    15. Angela Blanco-Fernández & Peter Winker, 2016. "Data generation processes and statistical management of interval data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 475-494, October.
    16. Philip Marx, 2020. "Sharp Bounds in the Latent Index Selection Model," Papers 2012.02390, arXiv.org, revised Apr 2023.
    17. Fan, Yanqin & Park, Sang Soo, 2009. "Partial identification of the distribution of treatment effects and its confidence sets," MPRA Paper 37148, University Library of Munich, Germany.
    18. Kock, Anders Bredahl & Preinerstorfer, David & Veliyev, Bezirgen, 2023. "Treatment recommendation with distributional targets," Journal of Econometrics, Elsevier, vol. 234(2), pages 624-646.
    19. Matthew Masten & Alexandre Poirier, 2016. "Partial independence in nonseparable models," CeMMAP working papers CWP26/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Etheridge, Ben, 2015. "A test of the household income process using consumption and wealth data," European Economic Review, Elsevier, vol. 78(C), pages 129-157.
    21. Tobias Eckernkemper & Bastian Gribisch, 2021. "Classical and Bayesian Inference for Income Distributions using Grouped Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(1), pages 32-65, February.
    22. Yuichi Kitamura & Jorg Stoye, 2019. "Nonparametric Counterfactuals in Random Utility Models," Papers 1902.08350, arXiv.org, revised May 2019.
    23. Luther Yap, 2022. "Sensitivity of Policy Relevant Treatment Parameters to Violations of Monotonicity," Working Papers 655, Princeton University, Department of Economics, Industrial Relations Section..

  17. Jorg Stoye, 2009. "More on Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 77(4), pages 1299-1315, July.
    See citations under working paper version above.
  18. Stoye, Jörg, 2009. "Minimax regret treatment choice with finite samples," Journal of Econometrics, Elsevier, vol. 151(1), pages 70-81, July.

    Cited by:

    1. Stoye, Jörg, 2011. "Axioms for minimax regret choice correspondences," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2226-2251.
    2. Toru Kitagawa & Aleksey Tetenov, 2018. "Who Should Be Treated? Empirical Welfare Maximization Methods for Treatment Choice," Econometrica, Econometric Society, vol. 86(2), pages 591-616, March.
    3. Manski, Charles F., 2023. "Probabilistic prediction for binary treatment choice: With focus on personalized medicine," Journal of Econometrics, Elsevier, vol. 234(2), pages 647-663.
    4. Cordier, J.; & Salvi, I.; & Steinbeck, V.; & Geissler, A.; & Vogel, J.;, 2023. "Is rapid recovery always the best recovery? - Developing a machine learning approach for optimal assignment rules under capacity constraints for knee replacement patients," Health, Econometrics and Data Group (HEDG) Working Papers 23/08, HEDG, c/o Department of Economics, University of York.
    5. Timothy B. Armstrong & Shu Shen, 2013. "Inference on Optimal Treatment Assignments," Cowles Foundation Discussion Papers 1927RR, Cowles Foundation for Research in Economics, Yale University, revised Apr 2015.
    6. Charles F. Manski, 2018. "Reasonable patient care under uncertainty," Health Economics, John Wiley & Sons, Ltd., vol. 27(10), pages 1397-1421, October.
    7. Toru Kitagawa & Aleksey Tetenov, 2018. "Equality-minded treatment choice," CeMMAP working papers CWP71/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    9. Charles F. Manski, 2017. "Improving Clinical Guidelines and Decisions under Uncertainty," NBER Working Papers 23915, National Bureau of Economic Research, Inc.
    10. Karl Schlag, 2006. "ELEVEN - Tests needed for a Recommendation," Economics Working Papers ECO2006/2, European University Institute.
    11. Charles F. Manski, 2007. "Adaptive Minimax-Regret Treatment Choice, With Application To Drug Approval," NBER Working Papers 13312, National Bureau of Economic Research, Inc.
    12. Kirill Ponomarev & Vira Semenova, 2024. "On the Lower Confidence Band for the Optimal Welfare," Papers 2410.07443, arXiv.org, revised Oct 2024.
    13. Stoye, Jörg, 2012. "Minimax regret treatment choice with covariates or with limited validity of experiments," Journal of Econometrics, Elsevier, vol. 166(1), pages 138-156.
    14. Tetenov, Aleksey, 2012. "Statistical treatment choice based on asymmetric minimax regret criteria," Journal of Econometrics, Elsevier, vol. 166(1), pages 157-165.
    15. Vira Semenova, 2023. "Aggregated Intersection Bounds and Aggregated Minimax Values," Papers 2303.00982, arXiv.org, revised Jun 2024.
    16. Aleksey Tetenov, 2016. "An economic theory of statistical testing," CeMMAP working papers CWP50/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised May 2024.
    18. Yuchen Hu & Henry Zhu & Emma Brunskill & Stefan Wager, 2024. "Minimax-Regret Sample Selection in Randomized Experiments," Papers 2403.01386, arXiv.org, revised Jun 2024.
    19. Nathan Kallus & Angela Zhou, 2021. "Minimax-Optimal Policy Learning Under Unobserved Confounding," Management Science, INFORMS, vol. 67(5), pages 2870-2890, May.
    20. Iverson, Terrence, 2013. "Minimax regret discounting," Journal of Environmental Economics and Management, Elsevier, vol. 66(3), pages 598-608.
    21. Debopam Bhattacharya & Pascaline Dupas, 2008. "Inferring Welfare Maximizing Treatment Assignment under Budget Constraints," NBER Working Papers 14447, National Bureau of Economic Research, Inc.
    22. Charles F. Manski, 2019. "Econometrics For Decision Making: Building Foundations Sketched By Haavelmo And Wald," Papers 1912.08726, arXiv.org, revised Feb 2021.
    23. Charles F. Manski & Aleksey Tetenov, 2014. "The Quantile Performance of Statistical Treatment Rules Using Hypothesis Tests to Allocate a Population to Two Treatments," CeMMAP working papers 44/14, Institute for Fiscal Studies.
    24. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
    25. Anders Bredahl Kock & David Preinerstorfer, 2024. "Regularizing Discrimination in Optimal Policy Learning with Distributional Targets," Papers 2401.17909, arXiv.org.
    26. Juliano Assunção & Robert McMillan & Joshua Murphy & Eduardo Souza-Rodrigues, 2019. "Optimal Environmental Targeting in the Amazon Rainforest," NBER Working Papers 25636, National Bureau of Economic Research, Inc.
    27. Susan Athey & Stefan Wager, 2017. "Policy Learning with Observational Data," Papers 1702.02896, arXiv.org, revised Sep 2020.
    28. Maximilian Blesch & Philipp Eisenhauer, 2023. "Robust Decision-Making under Risk and Ambiguity," Rationality and Competition Discussion Paper Series 463, CRC TRR 190 Rationality and Competition.
    29. García-Pola, Bernardo, 2020. "Do people minimize regret in strategic situations? A level-k comparison," Games and Economic Behavior, Elsevier, vol. 124(C), pages 82-104.
    30. Charles F. Manski, 2019. "Statistical inference for statistical decisions," Papers 1909.06853, arXiv.org.
    31. Karl H. Schlag, 2007. "How to Attain Minimax Risk with Applications to Distribution-Free Nonparametric Estimation and Testing," Economics Working Papers ECO2007/04, European University Institute.
    32. Kitagawa, Toru & Wang, Guanyi, 2023. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," Journal of Econometrics, Elsevier, vol. 232(1), pages 109-131.
    33. Charles F. Manski, 2019. "Meta-Analysis for Medical Decisions," NBER Working Papers 25504, National Bureau of Economic Research, Inc.
    34. Evan Sadler, 2015. "Minimax and the value of information," Theory and Decision, Springer, vol. 78(4), pages 575-586, April.
    35. Daido Kido, 2022. "Distributionally Robust Policy Learning with Wasserstein Distance," Papers 2205.04637, arXiv.org, revised Aug 2022.
    36. Toru Kitagawa & Weining Wang & Mengshan Xu, 2022. "Policy Choice in Time Series by Empirical Welfare Maximization," Papers 2205.03970, arXiv.org, revised Dec 2024.
    37. Daido Kido, 2023. "Locally Asymptotically Minimax Statistical Treatment Rules Under Partial Identification," Papers 2311.08958, arXiv.org.
    38. Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev, 2022. "Functional Sequential Treatment Allocation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(539), pages 1311-1323, September.
    39. Masahiro Kato & Masaaki Imaizumi & Takuya Ishihara & Toru Kitagawa, 2023. "Asymptotically Optimal Fixed-Budget Best Arm Identification with Variance-Dependent Bounds," Papers 2302.02988, arXiv.org, revised Jul 2023.
    40. Achim Ahrens & Alessandra Stampi-Bombelli & Selina Kurer & Dominik Hangartner, 2023. "Optimal multi-action treatment allocation: A two-phase field experiment to boost immigrant naturalization," Papers 2305.00545, arXiv.org, revised Feb 2024.
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    Cited by:

    1. Stoye, Jörg, 2011. "Axioms for minimax regret choice correspondences," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2226-2251.
    2. Stoye, Jörg, 2012. "Minimax regret treatment choice with covariates or with limited validity of experiments," Journal of Econometrics, Elsevier, vol. 166(1), pages 138-156.
    3. Tetenov, Aleksey, 2012. "Statistical treatment choice based on asymmetric minimax regret criteria," Journal of Econometrics, Elsevier, vol. 166(1), pages 157-165.
    4. Iverson, Terrence, 2013. "Minimax regret discounting," Journal of Environmental Economics and Management, Elsevier, vol. 66(3), pages 598-608.
    5. Undral Byambadalai, 2022. "Identification and Inference for Welfare Gains without Unconfoundedness," Papers 2207.04314, arXiv.org.
    6. Stoye, Jörg, 2009. "Minimax regret treatment choice with finite samples," Journal of Econometrics, Elsevier, vol. 151(1), pages 70-81, July.

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