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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. 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 Jan 2024.
    2. Aibo Gong, 2021. "Bounds for Treatment Effects in the Presence of Anticipatory Behavior," Papers 2111.06573, arXiv.org, revised Dec 2022.
    3. Sokbae Lee & Martin Weidner, 2021. "Bounding Treatment Effects by Pooling Limited Information across Observations," Papers 2111.05243, arXiv.org, revised Dec 2023.

  2. 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. Filip Obradovi'c, 2022. "Measuring Diagnostic Test Performance Using Imperfect Reference Tests: A Partial Identification Approach," Papers 2204.00180, arXiv.org, revised Feb 2023.
    2. 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.
    3. Bollinger, Christopher R. & van Hasselt, Martijn, 2020. "Estimating the cumulative rate of SARS-CoV-2 infection," Economics Letters, Elsevier, vol. 197(C).

  3. 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. David Hardt & Markus Nagler & Johannes Rincke, 2022. "Tutoring in (Online) Higher Education: Experimental Evidence," CESifo Working Paper Series 9555, CESifo.
    2. 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.
    3. 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.
    4. 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).
    5. 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.
    6. Luis Ángel Monroy-Gómez-Franco, & Roberto Vélez Grajales & Luis Felipe López-Calva, 2021. "The potential effects of the COVID-19 pandemic on learning," Papers 2021_08, Centro de Estudios Espinosa Yglesias.
    7. Hardt, David & Nagler, Markus & Rincke, Johannes, 2022. "Can peer mentoring improve online teaching effectiveness? An RCT during the COVID-19 pandemic," Labour Economics, Elsevier, vol. 78(C).
    8. 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).
    9. 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.
    10. Maria De Paola & Francesca Gioia & Vincenzo Scoppa, 2022. "Online Teaching, Procrastination And Students’ Achievement: Evidence From Covid-19 Induced Remote Learning," Working Papers 202202, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    11. Bratti, Massimiliano & Lippo, Enrico, 2022. "COVID-19 and the Gender Gap in University Student Performance," IZA Discussion Papers 15456, Institute of Labor Economics (IZA).
    12. 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.
    13. 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).
    14. 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).
    15. 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.
    16. 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).
    17. 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.
    18. 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.

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

    Cited by:

    1. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confidence Intervals for Projections of Partially Identified Parameters," Papers 1601.00934, arXiv.org, revised Jun 2019.
    2. Gregory Cox, 2022. "A Generalized Argmax Theorem with Applications," Papers 2209.08793, arXiv.org.
    3. Isaiah Andrews & Jonathan Roth & Ariel Pakes, 2023. "Inference for Linear Conditional Moment Inequalities," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(6), pages 2763-2791.
    4. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    5. Thomas M. Russell, 2020. "Policy Transforms and Learning Optimal Policies," Papers 2012.11046, arXiv.org.

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

    Cited by:

    1. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    2. Bart Smeulders & Laurens Cherchye & Bram De Rock, 2021. "Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing," Econometrica, Econometric Society, vol. 89(1), pages 437-455, January.
    3. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.

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

    Cited by:

    1. Yuichi Kitamura & Jorg Stoye, 2019. "Nonparametric Counterfactuals in Random Utility Models," Papers 1902.08350, arXiv.org, revised May 2019.
    2. Christopher Turansick, 2023. "On Graphical Methods in Stochastic Choice," Papers 2303.14249, arXiv.org, revised Sep 2023.
    3. Mark Dean & Dilip Ravindran & Jorg Stoye, 2022. "A Better Test of Choice Overload," Papers 2212.03931, 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. 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. John K. -H. Quah & Gerelt Tserenjigmid, 2022. "Price Heterogeneity as a source of Heterogenous Demand," Papers 2201.03784, arXiv.org, revised Jan 2022.
    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. Natalia Lazzati & John K.-H. Quah & Koji Shirai, 2018. "Nonparametric analysis of monotone choice," Discussion Paper Series 184, School of Economics, Kwansei Gakuin University.

  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. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    2. 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.
    3. Nail Kashaev & Victor H. Aguiar, 2022. "Nonparametric Analysis of Dynamic Random Utility Models," Papers 2204.07220, arXiv.org.
    4. Victor H. Aguiar & Nail Kashaev, 2018. "Stochastic Revealed Preferences with Measurement Error," Papers 1810.05287, arXiv.org, revised Sep 2020.
    5. Bart Smeulders, 2018. "Column Generation Algorithms for Nonparametric Analysis of Random Utility Models," Papers 1812.01400, arXiv.org.
    6. 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.
    7. Bart Smeulders & Laurens Cherchye & Bram De Rock, 2021. "Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing," Econometrica, Econometric Society, vol. 89(1), pages 437-455, January.
    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. 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.
    10. Aguiar, Victor H. & Serrano, Roberto, 2021. "Cardinal revealed preference: Disentangling transitivity and consistent binary choice," Journal of Mathematical Economics, Elsevier, vol. 94(C).

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

    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. Sam Cosaert & Thomas Demuynck, 2018. "Nonparametric welfare and demand analysis with unobserved individual heterogeneity," ULB Institutional Repository 2013/251988, ULB -- Universite Libre de Bruxelles.
    3. 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.
    4. 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.
    5. 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.
    6. Matthew Kovach & Gerelt Tserenjigmid, 2023. "The Focal Quantal Response Equilibrium," Papers 2304.00438, arXiv.org.
    7. 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.
    8. Christopher Turansick, 2021. "Identification in the Random Utility Model," Papers 2102.05570, arXiv.org, revised May 2022.
    9. 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.
    10. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    11. Mira Frick & Ryota Iijima & Tomasz Strzalecki, 2017. "Dynamic Random Utility," Cowles Foundation Discussion Papers 2092, Cowles Foundation for Research in Economics, Yale University.
    12. 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.
    13. Victor H. Aguiar & Maria Jose Boccardi & Nail Kashaev & Jeongbin Kim, 2018. "Random Utility and Limited Consideration," Papers 1812.09619, arXiv.org, revised Jul 2022.
    14. Aguiar, Victor H. & Kimya, Mert, 2019. "Adaptive stochastic search," Journal of Mathematical Economics, Elsevier, vol. 81(C), pages 74-83.
    15. Im, Changkuk & Rehbeck, John, 2022. "Non-rationalizable individuals and stochastic rationalizability," Economics Letters, Elsevier, vol. 219(C).
    16. Adams-Prassl, Abigail, 2019. "Mutually Consistent Revealed Preference Demand Predictions," CEPR Discussion Papers 13580, C.E.P.R. Discussion Papers.
    17. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    18. Whitney Newey & Sami Stouli, 2018. "Control Variables, Discrete Instruments, and Identification of Structural Functions," Bristol Economics Discussion Papers 18/702, School of Economics, University of Bristol, UK.
    19. 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.
    20. Nail Kashaev & Victor H. Aguiar, 2022. "Nonparametric Analysis of Dynamic Random Utility Models," Papers 2204.07220, arXiv.org.
    21. Victor H. Aguiar & Nail Kashaev, 2018. "Stochastic Revealed Preferences with Measurement Error," Papers 1810.05287, arXiv.org, revised Sep 2020.
    22. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    23. 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.
    24. Debopam Bhattacharya, 2019. "The Empirical Content of Binary Choice Models," Papers 1902.11012, arXiv.org, revised Oct 2020.
    25. Kashaev, Nail & Aguiar, Victor H., 2022. "A random attention and utility model," Journal of Economic Theory, Elsevier, vol. 204(C).
    26. 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.
    27. Laurens Cherchye & Thomas Demuynck & Bram De Rock, 2017. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Working Papers of Department of Economics, Leuven 598907, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    28. 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.
    29. 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.
    30. Francesca Molinari, 2020. "Microeconometrics with Partial Identi?cation," CeMMAP working papers CWP15/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    31. 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.
    32. 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.
    33. 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.
    34. Bart Smeulders & Laurens Cherchye & Bram De Rock, 2021. "Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing," Econometrica, Econometric Society, vol. 89(1), pages 437-455, January.
    35. 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.
    36. Aguiar, Victor H. & Hjertstrand, Per & Serrano, Roberto, 2020. "A Rationalization of the Weak Axiom of Revealed Preference," Working Paper Series 1321, Research Institute of Industrial Economics.
    37. Arie Beresteanu, 2021. "Identification of Incomplete Preferences," Working Paper 7145, Department of Economics, University of Pittsburgh.
    38. 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.
    39. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    40. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    41. Stoye, Jörg, 2019. "Revealed Stochastic Preference: A one-paragraph proof and generalization," Economics Letters, Elsevier, vol. 177(C), pages 66-68.
    42. Ian Crawford, 2019. "Nonparametric Analysis of Labour Supply Using Random Fields," Economics Papers 2019-W06, Economics Group, Nuffield College, University of Oxford.
    43. Natalia Lazzati & John K.-H. Quah & Koji Shirai, 2018. "Nonparametric analysis of monotone choice," Discussion Paper Series 184, School of Economics, Kwansei Gakuin University.
    44. Christopher Turansick, 2023. "On Graphical Methods in Stochastic Choice," Papers 2303.14249, arXiv.org, revised Sep 2023.
    45. Demuynck, Thomas & Hjertstrand, Per, 2019. "Samuelson's Approach to Revealed Preference Theory: Some Recent Advances," Working Paper Series 1274, Research Institute of Industrial Economics.
    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. Charles F. Manski, 2012. "Identification of Preferences and Evaluation of Income Tax Policy," NBER Working Papers 17755, National Bureau of Economic Research, Inc.
    48. Mark Dean & Dilip Ravindran & Jorg Stoye, 2022. "A Better Test of Choice Overload," Papers 2212.03931, arXiv.org.
    49. 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.
    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.

  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. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2017. "Monte Carlo confidence sets for identified sets," CeMMAP working papers CWP43/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. 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.
    3. 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.
    4. Lafférs, Lukáš & Mellace, Giovanni, 2020. "Identification of the average treatment effect when SUTVA is violated," Discussion Papers on Economics 3/2020, University of Southern Denmark, Department of Economics.
    5. Xiaohong Chen & Timothy M. Christensen & Keith O'Hara & Elie Tamer, 2016. "MCMC confidence sets for identified sets," CeMMAP working papers CWP28/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. 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.
    7. 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.
    8. Khushboo Surana, 2022. "How different are we? Identifying the degree of revealed preference heterogeneity," Discussion Papers 22/09, Department of Economics, University of York.
    9. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    10. Pakes, Ariel, 2017. "Empirical tools and competition analysis: Past progress and current problems," Scholarly Articles 34710163, Harvard University Department of Economics.
    11. 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.
    12. Pakes, Ariel, 2017. "Empirical tools and competition analysis: Past progress and current problems," International Journal of Industrial Organization, Elsevier, vol. 53(C), pages 241-266.
    13. 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.
    14. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Aug 2023.
    15. 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.
    16. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2019. "Constraint Qualifications in Partial Identification," Papers 1908.09103, arXiv.org, revised Apr 2021.
    17. Zach Flynn, 2020. "Identifying productivity when it is a factor of production," RAND Journal of Economics, RAND Corporation, vol. 51(2), pages 496-530, June.
    18. Yuan Liao & Anna Simoni, 2019. "Bayesian inference for partially identified smooth convex models," Post-Print hal-03089881, HAL.
    19. 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.
    20. Arie Beresteanu, 2020. "Quantile Regression with Interval Data," Working Paper 6899, Department of Economics, University of Pittsburgh.
    21. Laurens Cherchye & Bram De Rock & Khushboo Surana & Frederic Vermeulen, 2016. "Marital matching, economies of scale and intrahousehold allocations," Working Papers of Department of Economics, Leuven 551159, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    22. 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.
    23. 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.
    24. Victor H. Aguiar & Nail Kashaev & Roy Allen, 2022. "Prices, Profits, Proxies, and Production," University of Western Ontario, Departmental Research Report Series 20226, University of Western Ontario, Department of Economics.
    25. Lee, Y-Y. & Bhattacharya, D., 2018. "Applied Welfare Analysis for Discrete Choice with Interval-data on Income," Cambridge Working Papers in Economics 1882, Faculty of Economics, University of Cambridge.
    26. Hiroaki Kaido & Francesca Molinari & Jorg Stoye & Matthew Thirkettle, 2017. "Calibrated Projection in MATLAB: Users' Manual," Papers 1710.09707, arXiv.org.
    27. 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.
    28. Paul S. Koh, 2022. "Estimating Discrete Games of Complete Information: Bringing Logit Back in the Game," Papers 2205.05002, arXiv.org, revised Jun 2022.
    29. Levon Barseghyan & Maura Coughlin & Francesca Molinari & Joshua C. Teitelbaum, 2021. "Heterogeneous Choice Sets and Preferences," Econometrica, Econometric Society, vol. 89(5), pages 2015-2048, September.
    30. Freyberger, Joachim & Rai, Yoshiyasu, 2018. "Uniform confidence bands: Characterization and optimality," Journal of Econometrics, Elsevier, vol. 204(1), pages 119-130.
    31. 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.
    32. Christian Bontemps & Thierry Magnac, 2017. "Set Identification, Moment Restrictions, and Inference," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 103-129, September.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. 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.
    39. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2017. "Monte Carlo confidence sets for identified sets," CeMMAP working papers 43/17, Institute for Fiscal Studies.
    40. 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.
    41. Hiroaki Kaido & Jiaxuan Li & Marc Rysman, 2018. "Moment Inequalities in the Context of Simulated and Predicted Variables," Papers 1804.03674, arXiv.org.
    42. Ganesh Karapakula, 2022. "An Axiomatic Framework for Cost-Benefit Analysis," Papers 2207.13033, arXiv.org.
    43. Panos Toulis, 2020. "Estimation of Covid-19 Prevalence from Serology Tests: A Partial Identification Approach," Papers 2006.16214, arXiv.org.
    44. 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.
    45. 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.
    46. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    47. Shuowen Chen & Hiroaki Kaido, 2022. "Robust Tests of Model Incompleteness in the Presence of Nuisance Parameters," Papers 2208.11281, arXiv.org, revised Sep 2023.
    48. 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. 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. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    3. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2013. "Specification tests for partially identified models defined by moment inequalities," CeMMAP working papers CWP01/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. 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.
    5. 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.
    6. 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.
    7. Mira Frick & Ryota Iijima & Tomasz Strzalecki, 2017. "Dynamic Random Utility," Cowles Foundation Discussion Papers 2092, Cowles Foundation for Research in Economics, Yale University.
    8. Cherchye, Laurens & Demuynck, Thomas & De Rock, Bram, 2018. "Transitivity of preferences: when does it matter?," Theoretical Economics, Econometric Society, vol. 13(3), September.
    9. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers 60/17, Institute for Fiscal Studies.
    10. 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.
    11. Alexander Torgovitsky, 2019. "Partial identification by extending subdistributions," Quantitative Economics, Econometric Society, vol. 10(1), pages 105-144, January.
    12. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    13. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    14. 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.
    15. 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.
    16. Yuichi Kitamura & Jorg Stoye, 2019. "Nonparametric Counterfactuals in Random Utility Models," Papers 1902.08350, arXiv.org, revised May 2019.
    17. Bart Smeulders, 2018. "Column Generation Algorithms for Nonparametric Analysis of Random Utility Models," Papers 1812.01400, arXiv.org.
    18. 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.
    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. Ian Crawford & Matthew Polisson, 2015. "Demand analysis with partially observed prices," IFS Working Papers W15/16, Institute for Fiscal Studies.
    21. Kawaguchi, Kohei, 2017. "Testing rationality without restricting heterogeneity," Journal of Econometrics, Elsevier, vol. 197(1), pages 153-171.
    22. Sokbae (Simon) Lee & Kyungchui (Kevin) Song & Yoon-Jae Whang, 2014. "Testing for a general class of functional inequalities," CeMMAP working papers 09/14, Institute for Fiscal Studies.

  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. 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. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    11. Cherchye, Laurens & Demuynck, Thomas & De Rock, Bram, 2018. "Transitivity of preferences: when does it matter?," Theoretical Economics, Econometric Society, vol. 13(3), September.
    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. Kobus, Martyna & Kurek, Radosław, 2018. "Copula-based measurement of interdependence for discrete distributions," Journal of Mathematical Economics, Elsevier, vol. 79(C), pages 27-39.
    15. Im, Changkuk & Rehbeck, John, 2022. "Non-rationalizable individuals and stochastic rationalizability," Economics Letters, Elsevier, vol. 219(C).
    16. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    17. Nail Kashaev & Victor H. Aguiar, 2022. "Nonparametric Analysis of Dynamic Random Utility Models," Papers 2204.07220, arXiv.org.
    18. 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.
    19. Ian Crawford & Bram De Rock, 2013. "Empirical Revealed Preference," Working Papers ECARES ECARES 2013-32, ULB -- Universite Libre de Bruxelles.
    20. Apostolos Serletis & Maksim Isakin, "undated". "Stochastic Volatility Demand Systems," Working Papers 2014-74, Department of Economics, University of Calgary, revised 29 Sep 2014.
    21. 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.
    22. Debopam Bhattacharya, 2019. "The Empirical Content of Binary Choice Models," Papers 1902.11012, arXiv.org, revised Oct 2020.
    23. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    24. 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.
    25. Laurens Cherchye & Thomas Demuynck & Bram De Rock, 2017. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Working Papers of Department of Economics, Leuven 598907, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    26. Sam Cosaert & Thomas Demuynck, 2015. "Revealed preference theory for finite choice sets," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 59(1), pages 169-200, May.
    27. Francesca Molinari, 2020. "Microeconometrics with Partial Identi?cation," CeMMAP working papers CWP15/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    28. 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.
    29. Bart Smeulders & Laurens Cherchye & Bram De Rock, 2021. "Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing," Econometrica, Econometric Society, vol. 89(1), pages 437-455, January.
    30. Aguiar, Victor H. & Hjertstrand, Per & Serrano, Roberto, 2020. "A Rationalization of the Weak Axiom of Revealed Preference," Working Paper Series 1321, Research Institute of Industrial Economics.
    31. 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.
    32. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    33. 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.
    34. Arman Bidarbakht Nia, 2017. "A generalization to QUAIDS," Empirical Economics, Springer, vol. 52(1), pages 393-410, February.
    35. 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.
    36. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    37. Mark Dean & Daniel Martin, 2011. "Testing for Rationality with Consumption Data: Demographics and Heterogeneity," Working Papers 2011-11, Brown University, Department of Economics.
    38. Ian Crawford & Matthew Polisson, 2015. "Demand analysis with partially observed prices," IFS Working Papers W15/16, Institute for Fiscal Studies.
    39. Jerry Hausman & Whitney K. Newey, 2013. "Individual heterogeneity and average welfare," CeMMAP working papers 34/13, Institute for Fiscal Studies.
    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. 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.
    42. 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.
    43. Jerry Hausman & Whitney K. Newey, 2014. "Individual Heterogeneity and Average Welfare," CeMMAP working papers 42/14, Institute for Fiscal Studies.
    44. 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. Christian Bontemps & Thierry Magnac & Eric Maurin, 2012. "Set Identified Linear Models," Econometrica, Econometric Society, vol. 80(3), pages 1129-1155, May.
    2. Sam Cosaert & Thomas Demuynck, 2018. "Nonparametric welfare and demand analysis with unobserved individual heterogeneity," ULB Institutional Repository 2013/251988, ULB -- Universite Libre de Bruxelles.
    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. 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. Karthik Muralidharan & Mauricio Romero & Kaspar Wüthrich, 2020. "Factorial Designs, Model Selection, and (Incorrect) Inference in Randomized Experiments," CESifo Working Paper Series 8137, CESifo.
    6. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2017. "Monte Carlo confidence sets for identified sets," CeMMAP working papers CWP43/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Wooyoung Kim & Koohyun Kwon & Soonwoo Kwon & Sokbae Lee, 2018. "The identification power of smoothness assumptions in models with counterfactual outcomes," Quantitative Economics, Econometric Society, vol. 9(2), pages 617-642, July.
    8. Xiaohong Chen & Timothy M. Christensen & Keith O'Hara & Elie Tamer, 2016. "MCMC confidence sets for identified sets," CeMMAP working papers CWP28/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2014. "Inference for functions of partially identified parameters in moment inequality models," CeMMAP working papers CWP05/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. 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.
    11. Yuan Liao & Anna Simoni, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," Papers 1212.3267, arXiv.org, revised Nov 2013.
    12. 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.
    13. Clément de Chaisemartin, 2012. "Fuzzy differences in differences," PSE Working Papers halshs-00671368, HAL.
    14. 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.
    15. 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.
    16. Armstrong, Timothy B., 2014. "Weighted KS statistics for inference on conditional moment inequalities," Journal of Econometrics, Elsevier, vol. 181(2), pages 92-116.
    17. 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.
    18. 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.
    19. Adam McCloskey, 2012. "Bonferroni-Based Size-Correction for Nonstandard Testing Problems," Working Papers 2012-16, Brown University, Department of Economics.
    20. Wang, Xintong & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2021. "The Effects of Vietnam-Era Military Service on the Long-Term Health of Veterans: A Bounds Analysis," GLO Discussion Paper Series 764, Global Labor Organization (GLO).
    21. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    22. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    23. Aviv Nevo & Adam Rosen, 2008. "Identification with imperfect instruments," CeMMAP working papers CWP16/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    24. de Chaisemartin, Clement & D'Haultfoeuille, Xavier, "undated". "Supplement to Fuzzy Differences-in-Differences," Economic Research Papers 270217, University of Warwick - Department of Economics.
    25. Freyberger, Joachim & Horowitz, Joel L., 2015. "Identification and shape restrictions in nonparametric instrumental variables estimation," Journal of Econometrics, Elsevier, vol. 189(1), pages 41-53.
    26. Le-Yu Chen & Jerzy Szroeter, 2012. "Testing multiple inequality hypotheses: a smoothed indicator approach," CeMMAP working papers 16/12, Institute for Fiscal Studies.
    27. Emla Fitzsimons & Bansi Malde, 2014. "Empirically probing the quantity–quality model," Journal of Population Economics, Springer;European Society for Population Economics, vol. 27(1), pages 33-68, January.
    28. Wooldridge, Jeffrey M. & Imbens, Guido, 2009. "Recent Developments in the Econometrics of Program Evaluation," Scholarly Articles 3043416, Harvard University Department of Economics.
    29. Hiroaki Kaido & Francesca Molinari & Jorg Stoye, 2016. "Confidence Intervals for Projections of Partially Identified Parameters," Papers 1601.00934, arXiv.org, revised Jun 2019.
    30. 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.
    31. Mikkel Plagborg-Møller & Christian K. Wolf, 2022. "Instrumental Variable Identification of Dynamic Variance Decompositions," Journal of Political Economy, University of Chicago Press, vol. 130(8), pages 2164-2202.
    32. 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.
    33. 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.
    34. 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.
    35. 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 Jan 2024.
    36. Grant, Charles & Padula, Mario, 2013. "Using bounds to investigate household debt repayment behaviour," Research in Economics, Elsevier, vol. 67(4), pages 336-354.
    37. Tetsuya Kaji & Jianfei Cao, 2023. "Assessing Heterogeneity of Treatment Effects," Papers 2306.15048, arXiv.org.
    38. Krauth Brian, 2016. "Bounding a Linear Causal Effect Using Relative Correlation Restrictions," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 117-141, January.
    39. 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.
    40. Yuan Liao & Anna Simoni, 2019. "Bayesian inference for partially identified smooth convex models," Post-Print hal-03089881, HAL.
    41. 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.
    42. 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.
    43. 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).
    44. 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.
    45. Rothe, Christoph, 2011. "Partial Distributional Policy Effects," IZA Discussion Papers 6076, Institute of Labor Economics (IZA).
    46. Allen, Roy, 2018. "Testing moment inequalities: Selection versus recentering," Economics Letters, Elsevier, vol. 162(C), pages 124-126.
    47. Arie Beresteanu & Ilya Molchanov & Francesca Molinari, 2010. "Partial identification using random set theory," CeMMAP working papers CWP40/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    48. Demuynck, Thomas, 2015. "Bounding average treatment effects: A linear programming approach," Economics Letters, Elsevier, vol. 137(C), pages 75-77.
    49. Victor Chernozhukov & Wooyoung Kim & Sokbae Lee & Adam M. Rosen, 2015. "Implementing intersection bounds in Stata," Stata Journal, StataCorp LP, vol. 15(1), pages 21-44, March.
    50. 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.
    51. 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.
    52. 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.
    53. Magnac, Thierry, 2014. "Identification partielle: méthodes et conséquences pour les applications empiriques," TSE Working Papers 14-458, Toulouse School of Economics (TSE).
    54. Donald W.K. Andrews, 2011. "Similar-on-the-Boundary Tests for Moment Inequalities Exist, But Have Poor Power," Cowles Foundation Discussion Papers 1815, Cowles Foundation for Research in Economics, Yale University.
    55. 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.
    56. 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.
    57. Gerard, François & Rokkanen, Miikka & Rothe, Christoph, 2016. "Identification and Inference in Regression Discontinuity Designs with a Manipulated Running Variable," CEPR Discussion Papers 11048, C.E.P.R. Discussion Papers.
    58. Lee, Y-Y. & Bhattacharya, D., 2018. "Applied Welfare Analysis for Discrete Choice with Interval-data on Income," Cambridge Working Papers in Economics 1882, Faculty of Economics, University of Cambridge.
    59. Holford, Angus J., 2016. "Youth Employment and Academic Performance: Production Functions and Policy Effects," IZA Discussion Papers 10009, Institute of Labor Economics (IZA).
    60. Sung Jae Jun & Sokbae (Simon) Lee, 2019. "Identifying the effect of persuasion," CeMMAP working papers CWP69/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    61. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
    62. Keisuke Hirano & Jack R. Porter, 2012. "Impossibility Results for Nondifferentiable Functionals," Econometrica, Econometric Society, vol. 80(4), pages 1769-1790, July.
    63. Laurens Cherchye & Thomas Demuynck & Bram De Rock, 2017. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Working Papers of Department of Economics, Leuven 598907, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    64. Vira Semenova, 2020. "Generalized Lee Bounds," Papers 2008.12720, arXiv.org, revised Feb 2023.
    65. Armstrong, Timothy B. & Chan, Hock Peng, 2016. "Multiscale adaptive inference on conditional moment inequalities," Journal of Econometrics, Elsevier, vol. 194(1), pages 24-43.
    66. J. Stoye, 2009. "Charles F. Manski, Identification for Prediction and Decision (Harvard University Press 2007)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 857-862.
    67. James L. Powell, 2017. "Identification and Asymptotic Approximations: Three Examples of Progress in Econometric Theory," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 107-124, Spring.
    68. Aibo Gong, 2021. "Bounds for Treatment Effects in the Presence of Anticipatory Behavior," Papers 2111.06573, arXiv.org, revised Dec 2022.
    69. Joachim Freyberger & Joel L. Horowitz, 2013. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers 31/13, Institute for Fiscal Studies.
    70. Christian Bontemps & Thierry Magnac, 2017. "Set Identification, Moment Restrictions, and Inference," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 103-129, September.
    71. Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2017. "Going beyond LATE: Bounding Average Treatment Effects of Job Corps Training," GLO Discussion Paper Series 93, Global Labor Organization (GLO).
    72. Li, Tong & Oka, Tatsushi, 2015. "Set identification of the censored quantile regression model for short panels with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 363-377.
    73. 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.
    74. Stefan Boes, 2009. "Bounds on Counterfactual Distributions Under Semi-Monotonicity Constraints," SOI - Working Papers 0920, Socioeconomic Institute - University of Zurich.
    75. Michael Lechner & Blaise Melly, 2010. "Partial Idendification of Wage Effects of Training Programs," Working Papers 2010-8, Brown University, Department of Economics.
    76. Wenlong Ji & Lihua Lei & Asher Spector, 2023. "Model-Agnostic Covariate-Assisted Inference on Partially Identified Causal Effects," Papers 2310.08115, arXiv.org.
    77. 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.
    78. Yiwei Sun, 2023. "Extrapolating Away from the Cutoff in Regression Discontinuity Designs," Papers 2311.18136, arXiv.org.
    79. 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.
    80. 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.
    81. 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.
    82. 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).
    83. Fan, Yanqin & Park, Sang Soo, 2012. "Confidence intervals for the quantile of treatment effects in randomized experiments," Journal of Econometrics, Elsevier, vol. 167(2), pages 330-344.
    84. Xiaohong Chen & Timothy M. Christensen & Elie Tamer, 2017. "Monte Carlo confidence sets for identified sets," CeMMAP working papers 43/17, Institute for Fiscal Studies.
    85. 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.
    86. Huber, Martin, 2012. "Statistical verification of a natural "natural experiment": Tests and sensitivity checks for the sibling sex ratio instrument," Economics Working Paper Series 1219, University of St. Gallen, School of Economics and Political Science.
    87. Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2021. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," Papers 2112.13398, arXiv.org, revised Nov 2023.
    88. Sung Jae Jun & Yoonseok Lee & Youngki Shin, 2016. "Treatment Effects With Unobserved Heterogeneity: A Set Identification Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 302-311, April.
    89. Panos Toulis, 2020. "Estimation of Covid-19 Prevalence from Serology Tests: A Partial Identification Approach," Papers 2006.16214, arXiv.org.
    90. Armstrong, Timothy B., 2015. "Asymptotically exact inference in conditional moment inequality models," Journal of Econometrics, Elsevier, vol. 186(1), pages 51-65.
    91. Bontemps, Christian & Gualdani, Cristina & Remmy, Kevin, 2023. "Price Competition and Endogenous Product Choice in Networks: Evidence from the US Airline Industry," TSE Working Papers 23-1415, Toulouse School of Economics (TSE).
    92. Jörg Stoye, 2022. "Bounding infection prevalence by bounding selectivity and accuracy of tests: with application to early COVID-19 [False-negative results of initial RT-PCR assays for COVID-19: a systematic review]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 1-14.
    93. 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.
    94. 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).
    95. Hübler, Olaf, 2013. "Methods in empirical economics - a selective review with applications," Hannover Economic Papers (HEP) dp-513, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    96. 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.
    97. 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.
    98. 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.
    99. 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.
    100. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    101. 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.
    102. 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.
    103. Juan Carlos Escanciano & Lin Zhu, 2013. "Set inferences and sensitivity analysis in semiparametric conditionally identified models," CeMMAP working papers CWP55/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    104. Olaf Hübler, 2014. "Estimation of standard errors and treatment effects in empirical economics—methods and applications [Schätzung von Standardfehlern und Kausaleffekten in der empirischen Wirtschaftsforschung – Metho," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 47(1), pages 43-62, March.
    105. Sokbae Lee & Martin Weidner, 2021. "Bounding Treatment Effects by Pooling Limited Information across Observations," Papers 2111.05243, arXiv.org, revised Dec 2023.
    106. Fan, Yanqin & Park, Sang Soo, 2010. "Confidence sets for some partially identified parameters," MPRA Paper 37149, University Library of Munich, Germany.
    107. Yuan Liao & Anna Simoni, 2016. "Bayesian Inference for Partially Identified Convex Models: Is it Valid for Frequentist Inference?," Departmental Working Papers 201607, Rutgers University, Department of Economics.
    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.
    109. 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.
    110. Sungwon Lee, 2024. "Partial identification and inference for conditional distributions of treatment effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 107-127, January.

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 [False-negative results of initial RT-PCR assays for COVID-19: a systematic review]," 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. "Towards Eliciting Weak or Incomplete Preferences in the Lab: A Model-Rich Approach," Papers 2111.14431, arXiv.org, revised Dec 2023.
    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. Changkuk Im & John Rehbeck, 2021. "Non-rationalizable Individuals, Stochastic Rationalizability, and Sampling," Papers 2102.03436, arXiv.org, revised Oct 2021.
    4. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    5. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers 60/17, Institute for Fiscal Studies.
    6. Im, Changkuk & Rehbeck, John, 2022. "Non-rationalizable individuals and stochastic rationalizability," Economics Letters, Elsevier, vol. 219(C).
    7. Adams-Prassl, Abigail, 2019. "Mutually Consistent Revealed Preference Demand Predictions," CEPR Discussion Papers 13580, C.E.P.R. Discussion Papers.
    8. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    9. 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.
    10. Sebastiaan Maes & Raghav Malhotra, 2023. "Robust Hicksian Welfare Analysis under Individual Heterogeneity," Papers 2303.01231, arXiv.org, revised Nov 2023.
    11. Yuichi Kitamura & Jorg Stoye, 2019. "Nonparametric Counterfactuals in Random Utility Models," Papers 1902.08350, arXiv.org, revised May 2019.
    12. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    13. Stoye, Jörg, 2019. "Revealed Stochastic Preference: A one-paragraph proof and generalization," Economics Letters, Elsevier, vol. 177(C), pages 66-68.
    14. Ian Crawford & Matthew Polisson, 2015. "Demand analysis with partially observed prices," IFS Working Papers W15/16, Institute for Fiscal Studies.
    15. 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.
    16. 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.
    17. 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. Yuan Liao & Anna Simoni, 2012. "Semi-parametric Bayesian Partially Identified Models based on Support Function," Papers 1212.3267, arXiv.org, revised Nov 2013.
    2. 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.
    3. Tamini, Lota D., 2012. "Optimal quality choice under uncertainty on market development," MPRA Paper 40845, University Library of Munich, Germany.
    4. Karun Adusumilli & Friedrich Geiecke & Claudio Schilter, 2019. "Dynamically Optimal Treatment Allocation using Reinforcement Learning," Papers 1904.01047, arXiv.org, revised May 2022.
    5. Isaiah Andrews & Jesse M. Shapiro, 2021. "A Model of Scientific Communication," Econometrica, Econometric Society, vol. 89(5), pages 2117-2142, September.
    6. 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).
    7. Stoye, Jörg, 2015. "Choice theory when agents can randomize," Journal of Economic Theory, Elsevier, vol. 155(C), pages 131-151.
    8. Jörg Stoye, 2022. "Bounding infection prevalence by bounding selectivity and accuracy of tests: with application to early COVID-19 [False-negative results of initial RT-PCR assays for COVID-19: a systematic review]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 1-14.
    9. Gabriel Carroll, 2015. "Robustness and Linear Contracts," American Economic Review, American Economic Association, vol. 105(2), pages 536-563, February.
    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, 2017. "Improving Clinical Guidelines and Decisions under Uncertainty," NBER Working Papers 23915, National Bureau of Economic Research, Inc.
    3. Nathan Kallus & Angela Zhou, 2021. "Minimax-Optimal Policy Learning Under Unobserved Confounding," Management Science, INFORMS, vol. 67(5), pages 2870-2890, May.
    4. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
    5. Susan Athey & Stefan Wager, 2017. "Policy Learning with Observational Data," Papers 1702.02896, arXiv.org, revised Sep 2020.
    6. 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 CWP44/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Charles F. Manski, 2019. "Statistical inference for statistical decisions," Papers 1909.06853, arXiv.org.
    8. Knaus, Michael C., 2020. "Double Machine Learning Based Program Evaluation under Unconfoundedness," IZA Discussion Papers 13051, Institute of Labor Economics (IZA).
    9. Daido Kido, 2023. "Locally Asymptotically Minimax Statistical Treatment Rules Under Partial Identification," Papers 2311.08958, arXiv.org.
    10. 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.
    11. Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev, 2018. "Functional Sequential Treatment Allocation," Papers 1812.09408, arXiv.org, revised Aug 2020.
    12. Eric Mbakop & Max Tabord‐Meehan, 2021. "Model Selection for Treatment Choice: Penalized Welfare Maximization," Econometrica, Econometric Society, vol. 89(2), pages 825-848, March.
    13. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    14. 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).
    15. Augustine Denteh & Helge Liebert, 2022. "Who Increases Emergency Department Use? New Insights from the Oregon Health Insurance Experiment," Working Papers 2201, Tulane University, Department of Economics.
    16. Chunrong Ai & Yue Fang & Haitian Xie, 2024. "Data-driven Policy Learning for a Continuous Treatment," Papers 2402.02535, arXiv.org.
    17. Charles F. Manski, 2020. "Towards Reasonable Patient Care Under Uncertainty," Contemporary Economic Policy, Western Economic Association International, vol. 38(2), pages 227-245, April.
    18. Alexei N. Parakhonyak & Anton Sobolev, 2014. "Non-Reservation Price Equilibria And Search Without Priors," HSE Working papers WP BRP 69/EC/2014, National Research University Higher School of Economics.
    19. Charles F. Manski & Aleksey Tetenov, 2023. "Statistical Decision Theory Respecting Stochastic Dominance," Papers 2308.05171, arXiv.org.
    20. Keisuke Hirano & Jack R. Porter, 2016. "Panel Asymptotics and Statistical Decision Theory," The Japanese Economic Review, Springer, vol. 67(1), pages 33-49, March.
    21. Toru Kitagawa & Sokbae Lee & Chen Qiu, 2022. "Treatment Choice with Nonlinear Regret," Papers 2205.08586, arXiv.org, revised Feb 2024.
    22. Davide Viviano & Jelena Bradic, 2020. "Fair Policy Targeting," Papers 2005.12395, arXiv.org, revised Jun 2022.
    23. Charles F. Manski & Aleksey Tetenov, 2015. "Clinical trial design enabling epsilon-optimal treatment rules," Carlo Alberto Notebooks 430, Collegio Carlo Alberto.
    24. Charles F. Manski, 2018. "Reasonable patient care under uncertainty," Health Economics, John Wiley & Sons, Ltd., vol. 27(10), pages 1397-1421, October.
    25. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised Dec 2023.
    26. Charles F. Manski, 2019. "Econometrics For Decision Making: Building Foundations Sketched By Haavelmo And Wald," Papers 1912.08726, arXiv.org, revised Feb 2021.
    27. Anders Bredahl Kock & David Preinerstorfer, 2024. "Regularizing Discrimination in Optimal Policy Learning with Distributional Targets," Papers 2401.17909, arXiv.org.
    28. 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.
    29. 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.
    30. Charles F. Manski, 2019. "Meta-Analysis for Medical Decisions," NBER Working Papers 25504, National Bureau of Economic Research, Inc.
    31. Evan Sadler, 2015. "Minimax and the value of information," Theory and Decision, Springer, vol. 78(4), pages 575-586, April.
    32. Kock, Anders Bredahl & Preinerstorfer, David & Veliyev, Bezirgen, 2023. "Treatment recommendation with distributional targets," Journal of Econometrics, Elsevier, vol. 234(2), pages 624-646.
    33. Christopher Adjaho & Timothy Christensen, 2022. "Externally Valid Policy Choice," Papers 2205.05561, arXiv.org, revised Jul 2023.
    34. 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.
    35. Haitian Xie, 2020. "Finite-Sample Average Bid Auction," Papers 2008.10217, arXiv.org, revised Feb 2022.
    36. Thomas M. Russell, 2020. "Policy Transforms and Learning Optimal Policies," Papers 2012.11046, arXiv.org.

  14. 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. Bernhard Kasberger & Kyle Woodward, 2021. "Bidding in Multi-Unit Auctions under Limited Information," Papers 2112.11320, arXiv.org, revised Apr 2023.
    5. René Caldentey & Ying Liu & Ilan Lobel, 2017. "Intertemporal Pricing Under Minimax Regret," Operations Research, INFORMS, vol. 65(1), pages 104-129, February.
    6. Benjamin R. Handel & Kanishka Misra, 2015. "Robust New Product Pricing," Marketing Science, INFORMS, vol. 34(6), pages 864-881, November.
    7. Xiaoyu Cheng, 2022. "Robust Data-Driven Decisions Under Model Uncertainty," Papers 2205.04573, arXiv.org.
    8. 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.
    9. Bergemann, Dirk & Schlag, Karl, 2011. "Robust monopoly pricing," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2527-2543.
    10. 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.
    11. 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.
    12. 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.
    13. Buturak, Gökhan & Evren, Özgür, 2017. "Choice overload and asymmetric regret," Theoretical Economics, Econometric Society, vol. 12(3), September.
    14. Jörg Stoye, 2011. "Statistical decisions under ambiguity," Theory and Decision, Springer, vol. 70(2), pages 129-148, February.
    15. Eddie Dekel & Barton L. Lipman, 2009. "How (Not) to Do Decision Theory," Levine's Working Paper Archive 814577000000000339, David K. Levine.
    16. Galeazzi, Paolo & Marti, Johannes, 2023. "Choice structures in games," Games and Economic Behavior, Elsevier, vol. 140(C), pages 431-455.
    17. Alexei N. Parakhonyak & Anton Sobolev, 2014. "Non-Reservation Price Equilibria And Search Without Priors," HSE Working papers WP BRP 69/EC/2014, National Research University Higher School of Economics.
    18. Stoye, Jörg, 2009. "Minimax regret treatment choice with finite samples," Journal of Econometrics, Elsevier, vol. 151(1), pages 70-81, July.
    19. 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.
    20. John D. Hey & Gianna Lotito & Anna Maffioletti, 2018. "The descriptive and predictive adequacy of theories of decision making under uncertainty/ambiguity," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 8, pages 189-219, World Scientific Publishing Co. Pte. Ltd..
    21. 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.
    22. Paolo Galeazzi & Johannes Marti, 2023. "Choice Structures in Games," Papers 2304.11575, arXiv.org.
    23. Joseph Y. Halpern & Samantha Leung, 2016. "Minimizing regret in dynamic decision problems," Theory and Decision, Springer, vol. 81(1), pages 123-151, June.
    24. Halpern, Joseph Y. & Pass, Rafael, 2012. "Iterated regret minimization: A new solution concept," Games and Economic Behavior, Elsevier, vol. 74(1), pages 184-207.
    25. Zhe Yang & Yong Pu, 2012. "Existence and stability of minimax regret equilibria," Journal of Global Optimization, Springer, vol. 54(1), pages 17-26, September.
    26. 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.
    27. 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.
    28. 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.
    29. Stoye, Jörg, 2015. "Choice theory when agents can randomize," Journal of Economic Theory, Elsevier, vol. 155(C), pages 131-151.
    30. Mass, Helene, 2018. "Strategies under strategic uncertainty," ZEW Discussion Papers 18-055, ZEW - Leibniz Centre for European Economic Research.
    31. Hayashi, Takashi, 2009. "Stopping with anticipated regret," Journal of Mathematical Economics, Elsevier, vol. 45(7-8), pages 479-490, July.
    32. Yingni Guo & Eran Shmaya, 2023. "Regret-Minimizing Project Choice," Papers 2309.00214, arXiv.org.
    33. 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.
    34. Wanchang Zhang, 2022. "Auctioning Multiple Goods without Priors," Papers 2204.13726, arXiv.org.
    35. René Caldentey & Ying Liu & Ilan Lobel, 2017. "Intertemporal Pricing Under Minimax Regret," Operations Research, INFORMS, vol. 65(1), pages 104-129, February.
    36. Yingni Guo & Eran Shmaya, 2023. "Regret‐Minimizing Project Choice," Econometrica, Econometric Society, vol. 91(5), pages 1567-1593, September.
    37. Daniele Pennesi, 2021. "Between Commitment and Flexibility: Revealing Anticipated Regret and Elation," Working papers 071, Department of Economics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.

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

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Tetenov, Aleksey, 2012. "Statistical treatment choice based on asymmetric minimax regret criteria," Journal of Econometrics, Elsevier, vol. 166(1), pages 157-165.
    5. Karl H. Schlag, 2007. "Distribution-Free Learning," Economics Working Papers ECO2007/01, European University Institute.
    6. Bergemann, Dirk & Schlag, Karl, 2011. "Robust monopoly pricing," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2527-2543.
    7. 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.
    8. Stoye, Jörg, 2012. "Dominance and admissibility without priors," Economics Letters, Elsevier, vol. 116(1), pages 118-120.
    9. Renou, Ludovic & Schlag, Karl H., 2011. "Implementation in minimax regret equilibrium," Games and Economic Behavior, Elsevier, vol. 71(2), pages 527-533, March.
    10. 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.
    11. 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.
    12. 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).
    13. 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.
    14. Fabian Herweg & Daniel Müller, 2019. "A Comparison of Regret Theory and Salience Theory for Decisions under Risk," CESifo Working Paper Series 7445, CESifo.
    15. Tamini, Lota D., 2012. "Optimal quality choice under uncertainty on market development," MPRA Paper 40845, University Library of Munich, Germany.
    16. Massimo Marinacci, 2015. "Model Uncertainty," Working Papers 553, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    17. Stoye, Jörg, 2009. "Minimax regret treatment choice with finite samples," Journal of Econometrics, Elsevier, vol. 151(1), pages 70-81, July.
    18. Di Bartolomeo Giovanni & Di Pietro Marco, 2015. "Optimal inflation targeting rule under positive hazard functions for price changes," wp.comunite 0116, Department of Communication, University of Teramo.
    19. Isaiah Andrews & Jesse M. Shapiro, 2021. "A Model of Scientific Communication," Econometrica, Econometric Society, vol. 89(5), pages 2117-2142, September.
    20. Stoye, Jörg, 2011. "Axioms for minimax regret choice correspondences," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2226-2251.
    21. Iverson, Terrence, 2013. "Minimax regret discounting," Journal of Environmental Economics and Management, Elsevier, vol. 66(3), pages 598-608.
    22. Zhe Yang & Yong Pu, 2012. "Existence and stability of minimax regret equilibria," Journal of Global Optimization, Springer, vol. 54(1), pages 17-26, September.
    23. 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.
    24. Evan Sadler, 2015. "Minimax and the value of information," Theory and Decision, Springer, vol. 78(4), pages 575-586, April.
    25. 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.
    26. 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.
    27. Stoye, Jörg, 2015. "Choice theory when agents can randomize," Journal of Economic Theory, Elsevier, vol. 155(C), pages 131-151.
    28. 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.
    29. Yihao Luo & Jinhui Pang & Weibin Han & Huafei Sun, 2021. "New Solution based on Hodge Decomposition for Abstract Games," Papers 2109.14539, arXiv.org, revised Jan 2024.
    30. Hayashi, Takashi, 2009. "Stopping with anticipated regret," Journal of Mathematical Economics, Elsevier, vol. 45(7-8), pages 479-490, July.
    31. 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.
    32. 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.
    33. Diecidue, Enrico & Somasundaram, Jeeva, 2017. "Regret theory: A new foundation," Journal of Economic Theory, Elsevier, vol. 172(C), pages 88-119.
    34. Thomas M. Russell, 2020. "Policy Transforms and Learning Optimal Policies," Papers 2012.11046, arXiv.org.

  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. 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. David M. Kaplan & Longhao Zhuo, 2019. "Comparing latent inequality with ordinal data," Working Papers 1909, Department of Economics, University of Missouri.
    4. Manski, Charles F., 2016. "Credible interval estimates for official statistics with survey nonresponse," Journal of Econometrics, Elsevier, vol. 191(2), pages 293-301.
    5. Vishal Kamat, 2017. "Identifying the Effects of a Program Offer with an Application to Head Start," Papers 1711.02048, arXiv.org, revised Aug 2023.
    6. Esther Mirjam Girsberger & Romuald Méango & Hillel Rapoport, 2020. "Regional migration and wage inequality in the West African economic and monetary union," PSE-Ecole d'économie de Paris (Postprint) halshs-02491701, HAL.
    7. 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.
    8. 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.
    9. Philip Marx, 2020. "Sharp Bounds in the Latent Index Selection Model," Papers 2012.02390, arXiv.org, revised Apr 2023.
    10. 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.
    11. Rothe, Christoph, 2011. "Partial Distributional Policy Effects," IZA Discussion Papers 6076, Institute of Labor Economics (IZA).
    12. 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.
    13. 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.
    14. Yuichi Kitamura & Jorg Stoye, 2019. "Nonparametric Counterfactuals in Random Utility Models," Papers 1902.08350, arXiv.org, revised May 2019.
    15. Luther Yap, 2022. "Sensitivity of Policy Relevant Treatment Parameters to Violations of Monotonicity," Working Papers 655, Princeton University, Department of Economics, Industrial Relations Section..
    16. Matthew Masten & Alexandre Poirier, 2016. "Partial independence in nonseparable models," CeMMAP working papers 26/16, Institute for Fiscal Studies.
    17. 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.
    18. 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.
    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. 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.
    21. 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.
    22. Matthew A. Masten & Alexandre Poirier, 2017. "Identification of Treatment Effects under Conditional Partial Independence," Papers 1707.09563, arXiv.org.
    23. Kock, Anders Bredahl & Preinerstorfer, David & Veliyev, Bezirgen, 2023. "Treatment recommendation with distributional targets," Journal of Econometrics, Elsevier, vol. 234(2), pages 624-646.

  17. Stoye, Jörg, 2009. "Minimax regret treatment choice with finite samples," Journal of Econometrics, Elsevier, vol. 151(1), pages 70-81, July.

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Toru Kitagawa & Aleksey Tetenov, 2018. "Equality-minded treatment choice," CeMMAP working papers CWP71/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. 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.
    6. Charles F. Manski, 2017. "Improving Clinical Guidelines and Decisions under Uncertainty," NBER Working Papers 23915, National Bureau of Economic Research, Inc.
    7. Karl Schlag, 2006. "ELEVEN - Tests needed for a Recommendation," Economics Working Papers ECO2006/2, European University Institute.
    8. Charles F. Manski, 2007. "Adaptive Minimax-Regret Treatment Choice, With Application To Drug Approval," NBER Working Papers 13312, National Bureau of Economic Research, Inc.
    9. 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.
    10. Tetenov, Aleksey, 2012. "Statistical treatment choice based on asymmetric minimax regret criteria," Journal of Econometrics, Elsevier, vol. 166(1), pages 157-165.
    11. Vira Semenova, 2023. "Adaptive Estimation of Intersection Bounds: a Classification Approach," Papers 2303.00982, arXiv.org.
    12. Nathan Kallus & Angela Zhou, 2021. "Minimax-Optimal Policy Learning Under Unobserved Confounding," Management Science, INFORMS, vol. 67(5), pages 2870-2890, May.
    13. Debopam Bhattacharya & Pascaline Dupas, 2008. "Inferring Welfare Maximizing Treatment Assignment under Budget Constraints," NBER Working Papers 14447, National Bureau of Economic Research, Inc.
    14. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
    15. Juliano Assunção & Robert McMillan & Joshua Murphy & Eduardo Souza-Rodrigues, 2019. "Optimal Environmental Targeting in the Amazon Rainforest," NBER Working Papers 25636, National Bureau of Economic Research, Inc.
    16. Susan Athey & Stefan Wager, 2017. "Policy Learning with Observational Data," Papers 1702.02896, arXiv.org, revised Sep 2020.
    17. 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 CWP44/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Charles F. Manski, 2019. "Statistical inference for statistical decisions," Papers 1909.06853, arXiv.org.
    19. 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.
    20. Daido Kido, 2023. "Locally Asymptotically Minimax Statistical Treatment Rules Under Partial Identification," Papers 2311.08958, arXiv.org.
    21. 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.
    22. 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.
    23. Takanori Ida & Takunori Ishihara & Koichiro Ito & Daido Kido & Toru Kitagawa & Shosei Sakaguchi & Shusaku Sasaki, 2022. "Choosing Who Chooses: Selection-Driven Targeting in Energy Rebate Programs," NBER Working Papers 30469, National Bureau of Economic Research, Inc.
    24. Anders Bredahl Kock & David Preinerstorfer & Bezirgen Veliyev, 2018. "Functional Sequential Treatment Allocation," Papers 1812.09408, arXiv.org, revised Aug 2020.
    25. Eric Mbakop & Max Tabord‐Meehan, 2021. "Model Selection for Treatment Choice: Penalized Welfare Maximization," Econometrica, Econometric Society, vol. 89(2), pages 825-848, March.
    26. Yuya Sasaki & Takuya Ura, 2020. "Welfare Analysis via Marginal Treatment Effects," Papers 2012.07624, arXiv.org.
    27. Takuya Ishihara & Toru Kitagawa, 2021. "Evidence Aggregation for Treatment Choice," Papers 2108.06473, arXiv.org.
    28. Keisuke Hirano, 2023. "A Comment on: “Invidious Comparisons: Ranking and Selection as Compound Decisions” by Jiaying Gu and Roger Koenker," Econometrica, Econometric Society, vol. 91(1), pages 43-46, January.
    29. 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).
    30. Shosei Sakaguchi, 2021. "Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraints," Papers 2106.05031, arXiv.org, revised Apr 2024.
    31. Debopam Bhattacharya & Pascaline Dupas & Shin Kanaya, 2013. "Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets," Economics Series Working Papers 646, University of Oxford, Department of Economics.
    32. Toru Kitagawa & Shosei Sakaguchi & Aleksey Tetenov, 2021. "Constrained Classification and Policy Learning," Papers 2106.12886, arXiv.org, revised Jul 2023.
    33. Anders Bredahl Kock & Martin Thyrsgaard, 2017. "Optimal sequential treatment allocation," Papers 1705.09952, arXiv.org, revised Aug 2018.
    34. Garbero, Alessandra & Sakos, Grayson & Cerulli, Giovanni, 2023. "Towards data-driven project design: Providing optimal treatment rules for development projects," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    35. Toru Kitagawa & Aleksey Tetenov, 2015. "Who should be treated? Empirical welfare maximization methods for treatment choice," CeMMAP working papers 10/15, Institute for Fiscal Studies.
    36. Augustine Denteh & Helge Liebert, 2022. "Who Increases Emergency Department Use? New Insights from the Oregon Health Insurance Experiment," Working Papers 2201, Tulane University, Department of Economics.
    37. Jörg Stoye, 2011. "Statistical decisions under ambiguity," Theory and Decision, Springer, vol. 70(2), pages 129-148, February.
    38. Henrika Langen & Martin Huber, 2022. "How causal machine learning can leverage marketing strategies: Assessing and improving the performance of a coupon campaign," Papers 2204.10820, arXiv.org, revised Jun 2022.
    39. Chunrong Ai & Yue Fang & Haitian Xie, 2024. "Data-driven Policy Learning for a Continuous Treatment," Papers 2402.02535, arXiv.org.
    40. Charles F. Manski & Aleksey Tetenov, 2020. "Statistical Decision Properties of Imprecise Trials Assessing COVID-19 Drugs," Papers 2006.00343, arXiv.org.
    41. Timothy B. Armstrong & Shu Shen, 2013. "Inference on Optimal Treatment Assignments," Cowles Foundation Discussion Papers 1927, Cowles Foundation for Research in Economics, Yale University.
    42. Iverson, Terrence, 2012. "Communicating Trade-offs amid Controversial Science: Decision Support for Climate Policy," Ecological Economics, Elsevier, vol. 77(C), pages 74-90.
    43. Toru Kitagawa & Aleksey Tetenov, 2017. "Equality-minded treatment choice," CeMMAP working papers 10/17, Institute for Fiscal Studies.
    44. Sergio Firpo & Antonio F. Galvao & Martyna Kobus & Thomas Parker & Pedro Rosa-Dias, 2020. "Loss aversion and the welfare ranking of policy interventions," Papers 2004.08468, arXiv.org, revised Sep 2023.
    45. Kohei Yata, 2021. "Optimal Decision Rules Under Partial Identification," Papers 2111.04926, arXiv.org, revised Aug 2023.
    46. 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.
    47. Karun Adusumilli & Friedrich Geiecke & Claudio Schilter, 2019. "Dynamically Optimal Treatment Allocation using Reinforcement Learning," Papers 1904.01047, arXiv.org, revised May 2022.
    48. Charles F. Manski, 2020. "Towards Reasonable Patient Care Under Uncertainty," Contemporary Economic Policy, Western Economic Association International, vol. 38(2), pages 227-245, April.
    49. Keisuke Hirano & Jack R. Porter, 2012. "Impossibility Results for Nondifferentiable Functionals," Econometrica, Econometric Society, vol. 80(4), pages 1769-1790, July.
    50. Toru Kitagawa & Guanyi Wang, 2020. "Who Should Get Vaccinated? Individualized Allocation of Vaccines Over SIR Network," Papers 2012.04055, arXiv.org, revised Jul 2021.
    51. Charles F. Manski & Aleksey Tetenov, 2023. "Statistical Decision Theory Respecting Stochastic Dominance," Papers 2308.05171, arXiv.org.
    52. Keisuke Hirano & Jack R. Porter, 2016. "Panel Asymptotics and Statistical Decision Theory," The Japanese Economic Review, Springer, vol. 67(1), pages 33-49, March.
    53. J. Stoye, 2009. "Charles F. Manski, Identification for Prediction and Decision (Harvard University Press 2007)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 857-862.
    54. Takanori Ida & Takunori Ishihara & Koichiro Ito & Daido Kido & Toru Kitagawa & Shosei Sakaguchi & Shusaku Sasaki, 2021. "Paternalism, Autonomy, or Both? Experimental Evidence from Energy Saving Programs," Papers 2112.09850, arXiv.org.
    55. Toru Kitagawa & Sokbae Lee & Chen Qiu, 2022. "Treatment Choice with Nonlinear Regret," Papers 2205.08586, arXiv.org, revised Feb 2024.
    56. Toru Kitagawa & Guanyi Wang, 2020. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers CWP59/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    57. Takuya Ishihara & Daisuke Kurisu, 2022. "Shrinkage Methods for Treatment Choice," Papers 2210.17063, arXiv.org.
    58. Isaiah Andrews & Jesse M. Shapiro, 2021. "A Model of Scientific Communication," Econometrica, Econometric Society, vol. 89(5), pages 2117-2142, September.
    59. Karl H. Schlag, 2006. "Designing Non-Parametric Estimates and Tests for Means," Economics Working Papers ECO2006/26, European University Institute.
    60. Charles F. Manski & Aleksey Tetenov, 2015. "Clinical trial design enabling epsilon-optimal treatment rules," Carlo Alberto Notebooks 430, Collegio Carlo Alberto.
    61. Stoye, Jörg, 2011. "Axioms for minimax regret choice correspondences," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2226-2251.
    62. Charles F. Manski, 2018. "Reasonable patient care under uncertainty," Health Economics, John Wiley & Sons, Ltd., vol. 27(10), pages 1397-1421, October.
    63. Aleksey Tetenov, 2016. "An economic theory of statistical testing," CeMMAP working papers CWP50/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    64. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised Dec 2023.
    65. Iverson, Terrence, 2013. "Minimax regret discounting," Journal of Environmental Economics and Management, Elsevier, vol. 66(3), pages 598-608.
    66. Charles F. Manski, 2019. "Econometrics For Decision Making: Building Foundations Sketched By Haavelmo And Wald," Papers 1912.08726, arXiv.org, revised Feb 2021.
    67. Anders Bredahl Kock & David Preinerstorfer, 2024. "Regularizing Discrimination in Optimal Policy Learning with Distributional Targets," Papers 2401.17909, arXiv.org.
    68. 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.
    69. 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.
    70. 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.
    71. Charles F. Manski, 2019. "Meta-Analysis for Medical Decisions," NBER Working Papers 25504, National Bureau of Economic Research, Inc.
    72. Evan Sadler, 2015. "Minimax and the value of information," Theory and Decision, Springer, vol. 78(4), pages 575-586, April.
    73. Daido Kido, 2022. "Distributionally Robust Policy Learning with Wasserstein Distance," Papers 2205.04637, arXiv.org, revised Aug 2022.
    74. Toru Kitagawa & Weining Wang & Mengshan Xu, 2022. "Policy Choice in Time Series by Empirical Welfare Maximization," Papers 2205.03970, arXiv.org, revised Jun 2023.
    75. Aleksey Tetenov, 2016. "An economic theory of statistical testing," CeMMAP working papers 50/16, Institute for Fiscal Studies.
    76. Toru Kitagawa & Hugo Lopez & Jeff Rowley, 2022. "Stochastic Treatment Choice with Empirical Welfare Updating," Papers 2211.01537, arXiv.org, revised Feb 2023.
    77. Ron Berman & Christophe Van den Bulte, 2022. "False Discovery in A/B Testing," Management Science, INFORMS, vol. 68(9), pages 6762-6782, September.
    78. Toru Kitagawa & Guanyi Wang, 2021. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers CWP28/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    79. Kock, Anders Bredahl & Preinerstorfer, David & Veliyev, Bezirgen, 2023. "Treatment recommendation with distributional targets," Journal of Econometrics, Elsevier, vol. 234(2), pages 624-646.
    80. Yu-Chang Chen & Haitian Xie, 2022. "Personalized Subsidy Rules," Papers 2202.13545, arXiv.org, revised Mar 2022.
    81. 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.
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  18. 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.
  19. Stoye, Jörg, 2007. "Minimax Regret Treatment Choice With Incomplete Data And Many Treatments," Econometric Theory, Cambridge University Press, vol. 23(1), pages 190-199, February.

    Cited by:

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

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