Does Machine Learning Automate Moral Hazard and Error?
Citations
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Cited by:
- Wayne Xinwei Wan & Thies Lindenthal, 2023. "Testing machine learning systems in real estate," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(3), pages 754-778, May.
- Persson, Petra & Qiu, Xinyao & Rossin-Slater, Maya, 2021. "Family Spillover Effects of Marginal Diagnoses: The Case of ADHD," IZA Discussion Papers 14020, IZA Network @ LISER.
- Persson, Petra & Qiu, Xinyao & Rossin-Slater, Maya, 2021. "Family Spillover Effects of Marginal Diagnoses: The Case of ADHD," CEPR Discussion Papers 15660, C.E.P.R. Discussion Papers.
- Ziyuan Wang, 2023. "Spatial Differentiation Characteristics of Rural Areas Based on Machine Learning and GIS Statistical Analysis—A Case Study of Yongtai County, Fuzhou City," Sustainability, MDPI, vol. 15(5), pages 1-18, March.
- Ashvin Gandhi & Maggie Shi, 2025. "Screening Through Soft Spending Limits: Evidence from the Medicare Therapy Cap," NBER Working Papers 33722, National Bureau of Economic Research, Inc.
- Daníelsson, Jón & Macrae, Robert & Uthemann, Andreas, 2022.
"Artificial intelligence and systemic risk,"
Journal of Banking & Finance, Elsevier, vol. 140(C).
- Danielsson, Jon & Macrae, Robert & Uthemann, Andreas, 2022. "Artificial intelligence and systemic risk," LSE Research Online Documents on Economics 111601, London School of Economics and Political Science, LSE Library.
- Scott Duke Kominers & Alexander Teytelboym & Vincent P Crawford, 2017.
"An invitation to market design,"
Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 541-571.
- Kominers, Scott Duke & Teytelboym, Alexander & Crawford, Vincent P, 2017. "An invitation to market design," University of California at San Diego, Economics Working Paper Series qt3xp2110t, Department of Economics, UC San Diego.
- Scott Kominers & Alexander Teytelboym & Vincent Crawford, 2017. "An Invitation to Market Design," Working Papers 2017-069, Human Capital and Economic Opportunity Working Group.
- Songul Tolan, 2018. "Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges," JRC Working Papers on Digital Economy 2018-10, Joint Research Centre.
- Markus Eyting, 2020. "A Random Forest a Day Keeps the Doctor Away," Working Papers 2026, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
- Yves Paul Vincent Mbous & Todd Brothers & Mohammad A. Al-Mamun, 2023. "Medication Regimen Complexity Index Score at Admission as a Predictor of Inpatient Outcomes: A Machine Learning Approach," IJERPH, MDPI, vol. 20(4), pages 1-16, February.
- Bo Cowgill, 2019. "Bias and Productivity in Humans and Machines," Upjohn Working Papers 19-309, W.E. Upjohn Institute for Employment Research.
- Bauer, Kevin & Pfeuffer, Nicolas & Abdel-Karim, Benjamin M. & Hinz, Oliver & Kosfeld, Michael, 2020. "The terminator of social welfare? The economic consequences of algorithmic discrimination," SAFE Working Paper Series 287, Leibniz Institute for Financial Research SAFE.
- David Bardey & Philippe de Donder & Marie-Louise Leroux, 2024.
"Incentivizing Physicians' Diagnostic Effort and Test with Moral Hazard and Adverse Selection,"
Working Papers
hal-04803393, HAL.
- David Bardey & Philippe De Donder & Marie-Louise Leroux, 2025. "Incentivizing Physicians’ Diagnostic Effort and Test with Moral Hazard and Adverse Selection," CESifo Working Paper Series 11686, CESifo.
- David Bardey & Philippe De Donder & Marie-Louise Leroux, 2025. "Incentivizing Physicians’ Diagnostic Effort and Test with Moral Hazard and Adverse Selection," CIRANO Working Papers 2025s-02, CIRANO.
- David Bardey & Philippe De Donder & Marie-Louise Leroux, 2025. "Incentivizing Physicians’ Diagnostic Effort and Test with Moral Hazard and Adverse Selection," Cahiers de recherche / Working Papers 2501, Chaire de recherche sur les enjeux économiques intergénérationnels / Research Chair in Intergenerational Economics.
- David Bardey & Philippe De Donder & Marie-Louise Leroux, 2024. "Incentivizing Physicians' Diagnostic Effort and Test with Moral Hazard and Adverse Selection," Documentos CEDE 21269, Universidad de los Andes, Facultad de Economía, CEDE.
- De Donder, Philippe & Bardey, David & Leroux, Marie-Louise, 2024. "Incentivizing Physicians' Diagnostic Effort and Test with Moral Hazard and Adverse Selection," TSE Working Papers 24-1595, Toulouse School of Economics (TSE), revised Feb 2026.
- Navitha Singh Sewpersadh, 2023. "Disruptive business value models in the digital era," Journal of Innovation and Entrepreneurship, Springer, vol. 12(1), pages 1-27, December.
- Sasja Maria Pedersen & Nicolai Damslund & Trine Kjær & Kim Rose Olsen, 2025. "Optimising test intervals for individuals with type 2 diabetes: A machine learning approach," PLOS ONE, Public Library of Science, vol. 20(2), pages 1-19, February.
- Maria De-Arteaga & Vincent Jeanselme & Artur Dubrawski & Alexandra Chouldechova, 2025. "Leveraging Expert Consistency to Improve Algorithmic Decision Support," Management Science, INFORMS, vol. 71(12), pages 10465-10485, December.
- Heirati, Nima & Pitardi, Valentina & Wirtz, Jochen & Jayawardhena, Chanaka & Kunz, Werner & Paluch, Stefanie, 2025. "Unintended consequences of service robots – Recent progress and future research directions," Journal of Business Research, Elsevier, vol. 194(C).
- Xinran Liu, 2026. "Recovering Counterfactual Distributions via Wasserstein GANs," Papers 2601.17296, arXiv.org.
- repec:plo:pone00:0204920 is not listed on IDEAS
- Laura Blattner & Scott Nelson & Jann Spiess, 2021. "Unpacking the Black Box: Regulating Algorithmic Decisions," Papers 2110.03443, arXiv.org, revised May 2024.
- Kan Xu & Hamsa Bastani, 2025. "Multitask Learning and Bandits via Robust Statistics," Management Science, INFORMS, vol. 71(9), pages 7752-7773, September.
- Sendhil Mullainathan & Ziad Obermeyer, 2023.
"Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care,"
The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(2), pages 679-727.
- Sendhil Mullainathan & Ziad Obermeyer, 2019. "Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care," NBER Working Papers 26168, National Bureau of Economic Research, Inc.
- van Giffen, Benjamin & Herhausen, Dennis & Fahse, Tobias, 2022. "Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods," Journal of Business Research, Elsevier, vol. 144(C), pages 93-106.
- Hamsa Bastani, 2021. "Predicting with Proxies: Transfer Learning in High Dimension," Management Science, INFORMS, vol. 67(5), pages 2964-2984, May.
- Lambin, Xavier & Raizonville, Adrien, 2025. "From black box to glass box: algorithmic explainability as a strategic decision," Information Economics and Policy, Elsevier, vol. 71(C).
- Jill Walker Rettberg, 2020. "Situated data analysis: a new method for analysing encoded power relationships in social media platforms and apps," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 7(1), pages 1-13, December.
- Wan, Wayne Xinwei & Lindenthal, Thies, 2022. "Towards accountability in machine learning applications: A system-testing approach," ZEW Discussion Papers 22-001, ZEW - Leibniz Centre for European Economic Research.
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