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Human Decisions and Machine Predictions

Citations

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography for Economics:
  1. > Econometrics > Big Data

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Cited by:

  1. Ghysels, Eric & Babii, Andrii & Chen, Xi & Kumar, Rohit, 2020. "Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice," CEPR Discussion Papers 15418, C.E.P.R. Discussion Papers.
  2. Sophie-Charlotte Klose & Johannes Lederer, 2020. "A Pipeline for Variable Selection and False Discovery Rate Control With an Application in Labor Economics," Papers 2006.12296, arXiv.org, revised Jun 2020.
  3. MIYAKAWA Daisuke, 2019. "Shocks to Supply Chain Networks and Firm Dynamics: An Application of Double Machine Learning," Discussion papers 19100, Research Institute of Economy, Trade and Industry (RIETI).
  4. Richard Berk, 2019. "Accuracy and Fairness for Juvenile Justice Risk Assessments," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 16(1), pages 175-194, March.
  5. Achten, Sandra & Lessmann, Christian, 2020. "Spatial inequality, geography and economic activity," World Development, Elsevier, vol. 136(C).
  6. Peter Leopold S. Bergman & Elizabeth Kopko & Julio Rodriguez, 2021. "Using Predictive Analytics to Track Students: Evidence from a Seven-College Experiment," CESifo Working Paper Series 9157, CESifo.
  7. Bauer, Kevin & Gill, Andrej, 2021. "Mirror, mirror on the wall: Machine predictions and self-fulfilling prophecies," SAFE Working Paper Series 313, Leibniz Institute for Financial Research SAFE.
  8. McKenzie, David & Sansone, Dario, 2019. "Predicting entrepreneurial success is hard: Evidence from a business plan competition in Nigeria," Journal of Development Economics, Elsevier, vol. 141(C).
  9. Khudri, Md Mohsan & Hussey, Andrew, 2024. "Breastfeeding and Child Development Outcomes across Early Childhood and Adolescence: Doubly Robust Estimation with Machine Learning," IZA Discussion Papers 17080, Institute of Labor Economics (IZA).
  10. Liyang Tang, 2020. "Application of Nonlinear Autoregressive with Exogenous Input (NARX) neural network in macroeconomic forecasting, national goal setting and global competitiveness assessment," Papers 2005.08735, arXiv.org.
  11. Ivan A Canay & Magne Mogstad & Jack Mount, 2024. "On the Use of Outcome Tests for Detecting Bias in Decision Making," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(4), pages 2135-2167.
  12. Ajay Agrawal & Joshua S. Gans & Avi Goldfarb, 2019. "Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 31-50, Spring.
  13. Maria De‐Arteaga & Stefan Feuerriegel & Maytal Saar‐Tsechansky, 2022. "Algorithmic fairness in business analytics: Directions for research and practice," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3749-3770, October.
  14. Valerio Capraro & Roberto Di Paolo & Veronica Pizziol, 2023. "Assessing Large Language Models' ability to predict how humans balance self-interest and the interest of others," Papers 2307.12776, arXiv.org, revised Feb 2024.
  15. Gambardella, Alfonso, 2023. "Private and social functions of patents: Innovation, markets, and new firms," Research Policy, Elsevier, vol. 52(7).
  16. Laura Toschi & Elisa Ughetto & Andrea Fronzetti Colladon, 2023. "The identity of social impact venture capitalists: exploring social linguistic positioning and linguistic distinctiveness through text mining," Small Business Economics, Springer, vol. 60(3), pages 1249-1280, March.
  17. Elliott Ash & Claudia Marangon, 2024. "Judging disparities: Recidivism risk, image motives and in-group bias on Wisconsin criminal courts," Discussion Papers 2024-03, Nottingham Interdisciplinary Centre for Economic and Political Research (NICEP).
  18. Andini, Monica & Ciani, Emanuele & de Blasio, Guido & D'Ignazio, Alessio & Salvestrini, Viola, 2018. "Targeting with machine learning: An application to a tax rebate program in Italy," Journal of Economic Behavior & Organization, Elsevier, vol. 156(C), pages 86-102.
  19. Yoan Hermstrüwer & Pascal Langenbach, 2022. "Fair Governance with Humans and Machines," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2022_04, Max Planck Institute for Research on Collective Goods, revised 01 Mar 2023.
  20. Kristian Lum & David B. Dunson & James Johndrow, 2022. "Closer than they appear: A Bayesian perspective on individual‐level heterogeneity in risk assessment," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(2), pages 588-614, April.
  21. Shroff, Ravi & Vamvourellis, Konstantinos, 2022. "Pretrial release judgments and decision fatigue," LSE Research Online Documents on Economics 117579, London School of Economics and Political Science, LSE Library.
  22. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  23. Aliprantis, Dionissi & Martin, Hal & Tauber, Kristen, 2024. "What determines the success of housing mobility programs?," Journal of Housing Economics, Elsevier, vol. 65(C).
  24. Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan, 2021. "Preventing rather than punishing: An early warning model of malfeasance in public procurement," International Journal of Forecasting, Elsevier, vol. 37(1), pages 360-377.
  25. Leib, Margarita & Köbis, Nils & Rilke, Rainer Michael & Hagens, Marloes & Irlenbusch, Bernd, 2023. "Corrupted by Algorithms? How AI-Generated and Human-Written Advice Shape (Dis)Honesty," IZA Discussion Papers 16293, Institute of Labor Economics (IZA).
  26. Daniela Sele & Marina Chugunova, 2023. "Putting a Human in the Loop: Increasing Uptake, but Decreasing Accuracy of Automated Decision-Making," Rationality and Competition Discussion Paper Series 438, CRC TRR 190 Rationality and Competition.
  27. Susan Athey & Stefan Wager, 2021. "Policy Learning With Observational Data," Econometrica, Econometric Society, vol. 89(1), pages 133-161, January.
  28. Beth Coulthard & John Mallett & Brian Taylor, 2020. "Better Decisions for Children with “Big Data”: Can Algorithms Promote Fairness, Transparency and Parental Engagement?," Societies, MDPI, vol. 10(4), pages 1-16, December.
  29. Charles Hoffreumon & Chris Forman & Nicolas van Zeebroeck, 2024. "Make or buy your artificial intelligence? Complementarities in technology sourcing," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 452-479, March.
  30. Bo Cowgill, 2019. "Bias and Productivity in Humans and Machines," Upjohn Working Papers 19-309, W.E. Upjohn Institute for Employment Research.
  31. Jeffrey Penney & Steven Lehrer & Emilia Galan, 2024. "Mandatory minimum sentencing and its effect on sentencing distributions: Evidence from Canada," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 57(1), pages 55-77, February.
  32. Jean-Marie John-Mathews & Dominique Cardon & Christine Balagué, 2022. "From Reality to World. A Critical Perspective on AI Fairness," Journal of Business Ethics, Springer, vol. 178(4), pages 945-959, July.
  33. Will Dobbie & Andres Liberman & Daniel Paravisini & Vikram Pathania, 2021. "Measuring Bias in Consumer Lending [Loan Prospecting and the Loss of Soft Information]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(6), pages 2799-2832.
  34. Nathalie de Marcellis-Warin & Frédéric Marty & Eva Thelisson & Thierry Warin, 2020. "Artificial Intelligence and Market Manipulations: Ex-ante Evaluation in the Regulator's Arsenal," CIRANO Working Papers 2020s-64, CIRANO.
  35. Klockmann, Victor & von Schenk, Alicia & Villeval, Marie Claire, 2022. "Artificial intelligence, ethics, and intergenerational responsibility," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 284-317.
  36. Runshan Fu & Ginger Zhe Jin & Meng Liu, 2022. "Does Human-algorithm Feedback Loop Lead to Error Propagation? Evidence from Zillow’s Zestimate," NBER Working Papers 29880, National Bureau of Economic Research, Inc.
  37. Roshni Sahoo & Stefan Wager, 2022. "Policy Learning with Competing Agents," Papers 2204.01884, arXiv.org, revised Apr 2024.
  38. Andres, Antonio Rodriguez & Otero, Abraham & Amavilah, Voxi Heinrich, 2021. "Using Deep Learning Neural Networks to Predict the Knowledge Economy Index for Developing and Emerging Economies," MPRA Paper 109137, University Library of Munich, Germany.
  39. Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," CESifo Working Paper Series 8702, CESifo.
  40. Jella Pfeiffer & Julia Gutschow & Christian Haas & Florian Möslein & Oliver Maspfuhl & Frederik Borgers & Suzana Alpsancar, 2023. "Algorithmic Fairness in AI," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(2), pages 209-222, April.
  41. Michael Allan Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Papers 1906.03044, arXiv.org.
  42. Adam Altmejd & Anna Dreber & Eskil Forsell & Juergen Huber & Taisuke Imai & Magnus Johannesson & Michael Kirchler & Gideon Nave & Colin Camerer, 2019. "Predicting the replicability of social science lab experiments," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-18, December.
  43. Daníelsson, Jón & Macrae, Robert & Uthemann, Andreas, 2022. "Artificial intelligence and systemic risk," Journal of Banking & Finance, Elsevier, vol. 140(C).
  44. Monica Andini & Emanuele Ciani & Guido de Blasio & Alessio D'Ignazio & Viola Salvestrini, 2017. "Targeting policy-compliers with machine learning: an application to a tax rebate programme in Italy," Temi di discussione (Economic working papers) 1158, Bank of Italy, Economic Research and International Relations Area.
  45. Tamer Boyaci, & Caner Canyakmaz, & Francis de Véricourt,, 2020. "Human and machine: The impact of machine input on decision-making under cognitive limitations," ESMT Research Working Papers ESMT-20-02, ESMT European School of Management and Technology.
  46. Yucheng Yang & Zhong Zheng & Weinan E, 2020. "Interpretable Neural Networks for Panel Data Analysis in Economics," Papers 2010.05311, arXiv.org, revised Nov 2020.
  47. Brendan O'Flaherty & Rajiv Sethi & Morgan Williams, 2024. "The nature, detection, and avoidance of harmful discrimination in criminal justice," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 43(1), pages 289-320, January.
  48. Daniel Carter & Amelia Acker & Dan Sholler, 2021. "Investigative approaches to researching information technology companies," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(6), pages 655-666, June.
  49. Margarita Leib & Nils Kobis & Rainer Michael Rilke & Marloes Hagens & Bernd Irlenbusch, 2023. "Corrupted by Algorithms? How AI-generated and Human-written Advice Shape (Dis)honesty," Papers 2301.01954, arXiv.org.
  50. Anja Lambrecht & Catherine Tucker, 2019. "Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads," Management Science, INFORMS, vol. 65(7), pages 2966-2981, July.
  51. Robert John Zagar & James Garbarino & Brad Randmark & Ishup Singh & Joseph Kovach & Emma Cenzon & Michael Benko & Steve Tippins & Kenneth G. Busch, 2022. "Study 1: 630 Domestic-Terrorist, Mass-Murdering, Spree-Shooters Differ from 623 Controls and Study 2: 15 Domestic-Terrorist, Mass-Murdering, Spree-Shooters Differ From 23 Homicidal and 36 Controls on ," Review of European Studies, Canadian Center of Science and Education, vol. 14(1), pages 1-54, March.
  52. Jorge Mejia & Shawn Mankad & Anandasivam Gopal, 2019. "A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections," Information Systems Research, INFORMS, vol. 30(4), pages 1363-1386, December.
  53. Alexander Erlei & Lukas Meub, 2024. "Technological Shocks and Algorithmic Decision Aids in Credence Goods Markets," Papers 2401.17929, arXiv.org, revised Apr 2024.
  54. Zhao, Shuping & Xu, Kai & Wang, Zhao & Liang, Changyong & Lu, Wenxing & Chen, Bo, 2022. "Financial distress prediction by combining sentiment tone features," Economic Modelling, Elsevier, vol. 106(C).
  55. Margarita Leib & Nils Köbis & Rainer Michael Rilke & Marloes Hagens & Bernd Irlenbusch, 2023. "Corrupted by Algorithms? How AI-generated and Human-written Advice Shape (Dis)honesty," ECONtribute Discussion Papers Series 251, University of Bonn and University of Cologne, Germany.
  56. Escobar, Maria A. & Tobón, Santiago & Vanegas-Arias, Martín, 2023. "Production and persistence of criminal skills: Evidence from a high-crime context," Journal of Development Economics, Elsevier, vol. 160(C).
  57. 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).
  58. Jongbin Jung & Connor Concannon & Ravi Shroff & Sharad Goel & Daniel G. Goldstein, 2020. "Simple rules to guide expert classifications," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 771-800, June.
  59. Dargnies, Marie-Pierre & Hakimov, Rustamdjan & Kübler, Dorothea, 2022. "Aversion to hiring algorithms: Transparency, gender profiling, and self-confidence," Discussion Papers, Research Unit: Market Behavior SP II 2022-202, WZB Berlin Social Science Center.
  60. D'Acunto, Francesco & Ghosh, Pulak & Jain, Rajiv & Rossi, Alberto G., 2022. "How costly are cultural biases?," LawFin Working Paper Series 34, Goethe University, Center for Advanced Studies on the Foundations of Law and Finance (LawFin).
  61. Chen, S. & Doerr, S. & Frost, J. & Gambacorta, L. & Shin, H.S., 2023. "The fintech gender gap," Journal of Financial Intermediation, Elsevier, vol. 54(C).
  62. Jesse Rothstein & Albert Yoon, 2024. "Rankings without U.S. News: A revealed preference approach to evaluating law schools," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 21(2), pages 279-336, June.
  63. Maude Lavanchy & Patrick Reichert & Jayanth Narayanan & Krishna Savani, 2023. "Applicants’ Fairness Perceptions of Algorithm-Driven Hiring Procedures," Journal of Business Ethics, Springer, vol. 188(1), pages 125-150, November.
  64. Khoa Hoang & Robert Faff, 2021. "Is the ex‐ante equity risk premium always positive? Evidence from a new conditional expectations model," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 95-124, March.
  65. Jon Kleinberg & Sendhil Mullainathan, 2019. "Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability," NBER Working Papers 25854, National Bureau of Economic Research, Inc.
  66. Delogu, Marco & Lagravinese, Raffaele & Paolini, Dimitri & Resce, Giuliano, 2024. "Predicting dropout from higher education: Evidence from Italy," Economic Modelling, Elsevier, vol. 130(C).
  67. Wencheng Lu, 2024. "Inevitable challenges of autonomy: ethical concerns in personalized algorithmic decision-making," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-9, December.
  68. Alex James & Jeanette McLeod & Shaun Hendy & Kip Marks & Delia Rusu & Syen Nik & Michael J Plank, 2019. "Using family network data in child protection services," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-14, October.
  69. Chugunova, Marina & Sele, Daniela, 2022. "We and It: An interdisciplinary review of the experimental evidence on how humans interact with machines," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 99(C).
  70. 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.
  71. Ratzanyel Rincón, 2023. "Quarterly multidimensional poverty estimates in Mexico using machine learning algorithms/Estimaciones trimestrales de pobreza multidimensional en México mediante algoritmos de aprendizaje de máquina," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 38(1), pages 3-68.
  72. S. Mills & S. Costa & C. R. Sunstein, 2023. "AI, Behavioural Science, and Consumer Welfare," Journal of Consumer Policy, Springer, vol. 46(3), pages 387-400, September.
  73. Yael Karlinsky-Shichor & Oded Netzer, 2024. "Automating the B2B Salesperson Pricing Decisions: A Human-Machine Hybrid Approach," Marketing Science, INFORMS, vol. 43(1), pages 138-157, January.
  74. Guido de Blasio & Alessio D'Ignazio & Marco Letta, 2020. "Predicting Corruption Crimes with Machine Learning. A Study for the Italian Municipalities," Working Papers 16/20, Sapienza University of Rome, DISS.
  75. Huijian Han & Zhiming Li & Zongwei Li, 2023. "Using Machine Learning Methods to Predict Consumer Confidence from Search Engine Data," Sustainability, MDPI, vol. 15(4), pages 1-12, February.
  76. Fernandez, Marcelo Ariel & Mayskaya, Tatiana & Nikandrova, Arina, 2024. "Imposing commitment to rein in overconfidence in learning," Games and Economic Behavior, Elsevier, vol. 144(C), pages 29-48.
  77. Eyke Hüllermeier & Roman Słowiński, 2024. "Preference learning and multiple criteria decision aiding: differences, commonalities, and synergies—part II," 4OR, Springer, vol. 22(3), pages 313-349, September.
  78. Said Kaawach & Oskar Kowalewski & Oleksandr Talavera, 2023. "Automatic vs Manual Investing: Role of Past Performance," Discussion Papers 23-04, Department of Economics, University of Birmingham.
  79. Ian Lundberg & Arvind Narayanan & Karen Levy & Matthew Salganik, 2018. "Privacy, ethics, and data access: A case study of the Fragile Families Challenge," Working Papers wp18-09-ff, Princeton University, School of Public and International Affairs, Center for Research on Child Wellbeing..
  80. Vitezslav Titl & Deni Mazrekaj & Fritz Schiltz, 2024. "Identifying Politically Connected Firms: A Machine Learning Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(1), pages 137-155, February.
  81. Prithwiraj Choudhury & Evan Starr & Rajshree Agarwal, 2020. "Machine learning and human capital complementarities: Experimental evidence on bias mitigation," Strategic Management Journal, Wiley Blackwell, vol. 41(8), pages 1381-1411, August.
  82. Emilio Carrizosa & Cristina Molero-Río & Dolores Romero Morales, 2021. "Mathematical optimization in classification and regression trees," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 5-33, April.
  83. Ostheimer, Julia & Chowdhury, Soumitra & Iqbal, Sarfraz, 2021. "An alliance of humans and machines for machine learning: Hybrid intelligent systems and their design principles," Technology in Society, Elsevier, vol. 66(C).
  84. Jeremy Bertomeu & Edwige Cheynel & Eric Floyd & Wenqiang Pan, 2021. "Using machine learning to detect misstatements," Review of Accounting Studies, Springer, vol. 26(2), pages 468-519, June.
  85. Isil Erel & Léa H Stern & Chenhao Tan & Michael S Weisbach, 2021. "Selecting Directors Using Machine Learning," NBER Chapters, in: Big Data: Long-Term Implications for Financial Markets and Firms, pages 3226-3264, National Bureau of Economic Research, Inc.
  86. Drew Fudenberg & Jon Kleinberg & Annie Liang & Sendhil Mullainathan, 2019. "Measuring the Completeness of Theories," Papers 1910.07022, arXiv.org.
  87. Ali Shirali & Rediet Abebe & Moritz Hardt, 2024. "Allocation Requires Prediction Only if Inequality Is Low," Papers 2406.13882, arXiv.org.
  88. Shan Huang & Michael Allan Ribers & Hannes Ullrich, 2021. "The Value of Data for Prediction Policy Problems: Evidence from Antibiotic Prescribing," Discussion Papers of DIW Berlin 1939, DIW Berlin, German Institute for Economic Research.
  89. Antulov-Fantulin, Nino & Lagravinese, Raffaele & Resce, Giuliano, 2021. "Predicting bankruptcy of local government: A machine learning approach," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 681-699.
  90. Juan Carlos Perdomo, 2023. "The Relative Value of Prediction in Algorithmic Decision Making," Papers 2312.08511, arXiv.org, revised May 2024.
  91. Ali Bakdur & Fumito Masui & Michal Ptaszynski, 2021. "Predicting Increase in Demand for Public Buses in University Students Daily Life Needs: Case Study Based on a City in Japan," Sustainability, MDPI, vol. 13(9), pages 1-28, May.
  92. Zhang, Han, 2021. "How Using Machine Learning Classification as a Variable in Regression Leads to Attenuation Bias and What to Do About It," SocArXiv 453jk, Center for Open Science.
  93. Yusuke Narita & Kohei Yata, 2021. "Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules," Working Papers 2021-022, Human Capital and Economic Opportunity Working Group.
  94. Gert Bijnens & Shyngys Karimov & Jozef Konings, 2023. "Does Automatic Wage Indexation Destroy Jobs? A Machine Learning Approach," De Economist, Springer, vol. 171(1), pages 85-117, March.
  95. Colak, Gonul & Fu, Mengchuan & Hasan, Iftekhar, 2022. "On modeling IPO failure risk," Economic Modelling, Elsevier, vol. 109(C).
  96. Jing Wu & Zhaocheng Zhang & Sean X. Zhou, 2022. "Credit Rating Prediction Through Supply Chains: A Machine Learning Approach," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1613-1629, April.
  97. Colak, Gonul & Fu, Mengchuan & Hasan, Iftekhar, 2020. "Why are some Chinese firms failing in the US capital markets? A machine learning approach," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
  98. Manav Raj & Robert Seamans, 2019. "Primer on artificial intelligence and robotics," Journal of Organization Design, Springer;Organizational Design Community, vol. 8(1), pages 1-14, December.
  99. David Almog & Romain Gauriot & Lionel Page & Daniel Martin, 2024. "AI Oversight and Human Mistakes: Evidence from Centre Court," Papers 2401.16754, arXiv.org, revised Feb 2024.
  100. Bharti, Nitin Kumar & Roy, Sutanuka, 2023. "The early origins of judicial stringency in bail decisions: Evidence from early childhood exposure to Hindu-Muslim riots in India," Journal of Public Economics, Elsevier, vol. 221(C).
  101. Matthew Harding & Gabriel F. R. Vasconcelos, 2022. "Managers versus Machines: Do Algorithms Replicate Human Intuition in Credit Ratings?," Papers 2202.04218, arXiv.org.
  102. Ola G. El‐Taliawi & Nihit Goyal & Michael Howlett, 2021. "Holding out the promise of Lasswell's dream: Big data analytics in public policy research and teaching," Review of Policy Research, Policy Studies Organization, vol. 38(6), pages 640-660, November.
  103. Valerio Capraro & Roberto Di Paolo & Matjaz Perc & Veronica Pizziol, 2024. "Language-based game theory in the age of artificial intelligence," Papers 2403.08944, arXiv.org.
  104. Daniel Bjorkegren & Joshua E. Blumenstock & Samsun Knight, 2020. "Manipulation-Proof Machine Learning," Papers 2004.03865, arXiv.org.
  105. Christoph Engel, 2018. "Empirical Methods for the Law," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 174(1), pages 5-23, March.
  106. Carrizosa, Emilio & Kurishchenko, Kseniia & Marín, Alfredo & Romero Morales, Dolores, 2022. "Interpreting clusters via prototype optimization," Omega, Elsevier, vol. 107(C).
  107. Ismail, I. & Stam, P.J.A. & Portrait, F.R.M. & van Witteloostuijn, A. & Koolman, X., 2024. "Addressing unanticipated interactions in risk equalization: A machine learning approach to modeling medical expenditure risk," Economic Modelling, Elsevier, vol. 130(C).
  108. Walter, Johannes & Biermann, Jan & Horton, John, 2024. "Advised by an Algorithm: Learning with Different Informational Resources," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302407, Verein für Socialpolitik / German Economic Association.
  109. Prithwiraj Choudhury & Dan Wang & Natalie A. Carlson & Tarun Khanna, 2019. "Machine learning approaches to facial and text analysis: Discovering CEO oral communication styles," Strategic Management Journal, Wiley Blackwell, vol. 40(11), pages 1705-1732, November.
  110. Pedro Bordalo & John Conlon & Nicola Gennaioli & Spencer Kwon & Andrei Shleifer, 2023. "How People Use Statistics," Working Papers 699, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  111. Fumagalli, Elena & Rezaei, Sarah & Salomons, Anna, 2022. "OK computer: Worker perceptions of algorithmic recruitment," Research Policy, Elsevier, vol. 51(2).
  112. Pinelopi K. Goldberg & Tristan Reed, 2020. "Demand-Side Constraints in Development: The Role of Market Size, Trade, and (In)Equality," NBER Working Papers 27286, National Bureau of Economic Research, Inc.
  113. Goldberg,Pinelopi Koujianou & Reed,Tristan, 2020. "Income Distribution, International Integration and Sustained Poverty Reduction," Policy Research Working Paper Series 9342, The World Bank.
  114. Liwei Chen & J. J. Po-An Hsieh & Arun Rai, 2022. "How Does Intelligent System Knowledge Empowerment Yield Payoffs? Uncovering the Adaptation Mechanisms and Contingency Role of Work Experience," Information Systems Research, INFORMS, vol. 33(3), pages 1042-1071, September.
  115. Ginevra Buratti & Alessio D'Ignazio, 2023. "Improving the effectiveness of financial education programs. A targeting approach," Questioni di Economia e Finanza (Occasional Papers) 765, Bank of Italy, Economic Research and International Relations Area.
  116. Talia Gillis & Bryce McLaughlin & Jann Spiess, 2021. "On the Fairness of Machine-Assisted Human Decisions," Papers 2110.15310, arXiv.org, revised Sep 2023.
  117. Zeyang Chen & Yu-Jane Liu & Juanjuan Meng & Zeng Wang, 2023. "What’s in a Face? An Experiment on Facial Information and Loan-Approval Decision," Management Science, INFORMS, vol. 69(4), pages 2263-2283, April.
  118. He, Yunwen, 2021. "Using your regular contacts as collateral: The information value of call logs," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
  119. Bhattacharya, D. & Shvets, J., 2022. "Inferring the Performance Diversity Trade-Off in University Admissions: Evidence from Cambridge," Cambridge Working Papers in Economics 2238, Faculty of Economics, University of Cambridge.
  120. Eli Ben-Michael & D. James Greiner & Melody Huang & Kosuke Imai & Zhichao Jiang & Sooahn Shin, 2024. "Does AI help humans make better decisions? A statistical evaluation framework for experimental and observational studies," Papers 2403.12108, arXiv.org, revised Oct 2024.
  121. Anthony Niblett, 2018. "Regulatory Reform in Ontario: Machine Learning and Regulation," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 507, March.
  122. McKenzie, David & Sansone, Dario, 2017. "Man vs. Machine in Predicting Successful Entrepreneurs: Evidence from a Business Plan Competition in Nigeria," CEPR Discussion Papers 12523, C.E.P.R. Discussion Papers.
  123. Arthur Charpentier, 2022. "Quantifying fairness and discrimination in predictive models," Papers 2212.09868, arXiv.org.
  124. 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.
  125. Philine Widmer & Sergio Galletta & Elliott Ash, 2022. "Media Slant is Contagious," Papers 2202.07269, arXiv.org, revised Apr 2023.
  126. Gorny, Paul M. & Groos, Eva & Strobel, Christina, 2024. "Do Personalized AI Predictions Change Subsequent Decision-Outcomes? The Impact of Human Oversight," MPRA Paper 121065, University Library of Munich, Germany.
  127. Jean-Marie John-Mathews, 2022. "Some critical and ethical perspectives on the empirical turn of AI interpretability," Post-Print hal-03395823, HAL.
  128. Alessandra Garbero & Marco Letta, 2022. "Predicting household resilience with machine learning: preliminary cross-country tests," Empirical Economics, Springer, vol. 63(4), pages 2057-2070, October.
  129. Ekaterina Jussupow & Kai Spohrer & Armin Heinzl & Joshua Gawlitza, 2021. "Augmenting Medical Diagnosis Decisions? An Investigation into Physicians’ Decision-Making Process with Artificial Intelligence," Information Systems Research, INFORMS, vol. 32(3), pages 713-735, September.
  130. Battiston, Pietro & Gamba, Simona & Santoro, Alessandro, 2024. "Machine learning and the optimization of prediction-based policies," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
  131. John-Mathews, Jean-Marie, 2022. "Some critical and ethical perspectives on the empirical turn of AI interpretability," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
  132. Bas Scheer & Brinn Hekkelman & Mark Kattenberg, 2024. "The Costs of Affirmative Action: Evidence from a Medical School Lottery," CPB Discussion Paper 455, CPB Netherlands Bureau for Economic Policy Analysis.
  133. Tanvir Ahmed Khan, 2023. "Can Unbiased Predictive AI Amplify Bias?," Working Paper 1510, Economics Department, Queen's University.
  134. Bauer, Kevin & von Zahn, Moritz & Hinz, Oliver, 2022. "Expl(AI)ned: The impact of explainable Artificial Intelligence on cognitive processes," SAFE Working Paper Series 315, Leibniz Institute for Financial Research SAFE, revised 2022.
  135. Jason Anastasopoulos & George J. Borjas & Gavin G. Cook & Michael Lachanski, 2018. "Job Vacancies, the Beveridge Curve, and Supply Shocks: The Frequency and Content of Help-Wanted Ads in Pre- and Post-Mariel Miami," NBER Working Papers 24580, National Bureau of Economic Research, Inc.
  136. Wumi AJAYI & Adekoya Damola Felix & Ojarikre Oghenenerowho Princewill & Fajuyigbe Gbenga Joseph, 2024. "Software Engineering’s Key Role in AI Content Trustworthiness," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 11(4), pages 183-201, April.
  137. de Blasio, Guido & D'Ignazio, Alessio & Letta, Marco, 2022. "Gotham city. Predicting ‘corrupted’ municipalities with machine learning," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
  138. Paola Bertoli & Veronica Grembi, 2018. "Courts, scheduled damages, and medical malpractice insurance," Empirical Economics, Springer, vol. 55(2), pages 831-854, September.
  139. Jermain C. Kaminski & Christian Hopp, 2020. "Predicting outcomes in crowdfunding campaigns with textual, visual, and linguistic signals," Small Business Economics, Springer, vol. 55(3), pages 627-649, October.
  140. Keding, Christoph & Meissner, Philip, 2021. "Managerial overreliance on AI-augmented decision-making processes: How the use of AI-based advisory systems shapes choice behavior in R&D investment decisions," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
  141. Andreas Fuster & Paul Goldsmith‐Pinkham & Tarun Ramadorai & Ansgar Walther, 2022. "Predictably Unequal? The Effects of Machine Learning on Credit Markets," Journal of Finance, American Finance Association, vol. 77(1), pages 5-47, February.
  142. Yidi Liu & Xin Li & Zhiqiang (Eric) Zheng, 2024. "Smart Natural Disaster Relief: Assisting Victims with Artificial Intelligence in Lending," Information Systems Research, INFORMS, vol. 35(2), pages 489-504, June.
  143. Huang, Ming-Hui & Rust, Roland T., 2022. "A Framework for Collaborative Artificial Intelligence in Marketing," Journal of Retailing, Elsevier, vol. 98(2), pages 209-223.
  144. Tzai-Shuen Chen, 2018. "Evaluating Conditional Cash Transfer Policies with Machine Learning Methods," Papers 1803.06401, arXiv.org.
  145. Joshua Grossman & Julian Nyarko & Sharad Goel, 2023. "Racial bias as a multi‐stage, multi‐actor problem: An analysis of pretrial detention," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 20(1), pages 86-133, March.
  146. Elliott Ash & Sergio Galletta & Tommaso Giommoni, 2021. "A Machine Learning Approach to Analyze and Support Anti-Corruption Policy," CESifo Working Paper Series 9015, CESifo.
  147. Ballestar, María Teresa & Doncel, Luis Miguel & Sainz, Jorge & Ortigosa-Blanch, Arturo, 2019. "A novel machine learning approach for evaluation of public policies: An application in relation to the performance of university researchers," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
  148. Ajit Desai, 2023. "Machine Learning for Economics Research: When What and How?," Papers 2304.00086, arXiv.org, revised Apr 2023.
  149. Danielle Li & Lindsey R. Raymond & Peter Bergman, 2020. "Hiring as Exploration," NBER Working Papers 27736, National Bureau of Economic Research, Inc.
  150. Lily Davies & Mark Kattenberg & Benedikt Vogt, 2023. "Predicting Firm Exits with Machine Learning: Implications for Selection into COVID-19 Support and Productivity Growth," CPB Discussion Paper 444, CPB Netherlands Bureau for Economic Policy Analysis.
  151. Jianghong Xu & Chenguang Wang & Xukang Yin & Weixin Wang, 2024. "Digital economy and rural household resilience: Evidence from China," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 70(5), pages 244-263.
  152. Huang, Shan & Ribers, Michael Allan & Ullrich, Hannes, 2022. "Assessing the value of data for prediction policies: The case of antibiotic prescribing," Economics Letters, Elsevier, vol. 213(C).
  153. Hannes Ullrich & Michael Allan Ribers, 2023. "Machine predictions and human decisions with variation in payoffs and skill: the case of antibiotic prescribing," Berlin School of Economics Discussion Papers 0027, Berlin School of Economics.
  154. Andini, Monica & Boldrini, Michela & Ciani, Emanuele & de Blasio, Guido & D'Ignazio, Alessio & Paladini, Andrea, 2022. "Machine learning in the service of policy targeting: The case of public credit guarantees," Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 434-475.
  155. Anja Garbely & Elias Steiner, 2023. "Understanding compliance with voluntary sustainability standards: a machine learning approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(10), pages 11209-11239, October.
  156. Ginther, Donna K. & Heggeness, Misty L., 2020. "Administrative discretion in scientific funding: Evidence from a prestigious postdoctoral training program✰," Research Policy, Elsevier, vol. 49(4).
  157. Martin B. Schmidt, 2024. "On the Incentive Structure of Tournaments: Evidence from the National Basketball Association’s Draft Lottery," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 50(3), pages 400-429, June.
  158. Saravanan Kesavan & Tarun Kushwaha, 2020. "Field Experiment on the Profit Implications of Merchants’ Discretionary Power to Override Data-Driven Decision-Making Tools," Management Science, INFORMS, vol. 66(11), pages 5182-5190, November.
  159. Sloan, Carly Will & Naufal, George S & Caspers, Heather, 2018. "The Effect of Risk Assessment Scores on Judicial Behavior and Defendant Outcomes," IZA Discussion Papers 11948, Institute of Labor Economics (IZA).
  160. Sarah Spiekermann & Hanna Krasnova & Oliver Hinz & Annika Baumann & Alexander Benlian & Henner Gimpel & Irina Heimbach & Antonia Köster & Alexander Maedche & Björn Niehaves & Marten Risius & Manuel Tr, 2022. "Values and Ethics in Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(2), pages 247-264, April.
  161. Scott Schanke & Gordon Burtch & Gautam Ray, 2021. "Estimating the Impact of “Humanizing” Customer Service Chatbots," Information Systems Research, INFORMS, vol. 32(3), pages 736-751, September.
  162. Körtner, John & Bonoli, Giuliano, 2021. "Predictive Algorithms in the Delivery of Public Employment Services," SocArXiv j7r8y, Center for Open Science.
  163. Runshan Fu & Yan Huang & Param Vir Singh, 2020. "Crowd, Lending, Machine, and Bias," Papers 2008.04068, arXiv.org.
  164. Strittmatter, Anthony, 2023. "What is the value added by using causal machine learning methods in a welfare experiment evaluation?," Labour Economics, Elsevier, vol. 84(C).
  165. Jeanine Miklós-Thal & Catherine Tucker, 2019. "Collusion by Algorithm: Does Better Demand Prediction Facilitate Coordination Between Sellers?," Management Science, INFORMS, vol. 65(4), pages 1552-1561, April.
  166. Kevin Bauer & Andrej Gill, 2024. "Mirror, Mirror on the Wall: Algorithmic Assessments, Transparency, and Self-Fulfilling Prophecies," Information Systems Research, INFORMS, vol. 35(1), pages 226-248, March.
  167. Rebitschek, Felix G. & Gigerenzer, Gerd & Wagner, Gert G., 2021. "People underestimate the errors made by algorithms for credit scoring and recidivism prediction but accept even fewer errors," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11, pages 1-11.
  168. Bansak, Kirk & Paulson, Elisabeth, 2023. "Public Opinion on Fairness and Efficiency for Algorithmic and Human Decision-Makers," OSF Preprints pghmx, Center for Open Science.
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