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Publications

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      • Faculty Publications  (147)

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      • 2023
      • Working Paper

      Feature Importance Disparities for Data Bias Investigations

      By: Peter W. Chang, Leor Fishman and Seth Neel
      It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection... View Details
      Keywords: AI and Machine Learning; Analytics and Data Science; Prejudice and Bias
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      Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
      • 2023
      • Working Paper

      The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities

      By: David S. Scharfstein and Sergey Chernenko
      We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement bias in... View Details
      Keywords: Racial Disparity; Paycheck Protection Program; Measurement Error; AI and Machine Learning; Race; Measurement and Metrics; Equality and Inequality; Prejudice and Bias; Forecasting and Prediction; Outcome or Result
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      Scharfstein, David S., and Sergey Chernenko. "The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities." Working Paper, April 2023.
      • 2024
      • Working Paper

      Everyone Steps Back?: The Widespread Retraction of Crowd-Funding Support for Minority Creators When Migration Fear Is High

      By: John (Jianqui) Bai, William R. Kerr, Chi Wan and Alptug Yorulmaz
      We study racial biases on Kickstarter across multiple ethnic groups from 2009-2021. Scaling the concept of racially salient events, we quantify the close co-movement of minority funding gaps to inflamed political rhetoric surrounding migration. The racial funding gap... View Details
      Keywords: Crowdfunding; Prejudice and Bias; Race; Immigration; Public Opinion
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      Bai, John (Jianqui), William R. Kerr, Chi Wan, and Alptug Yorulmaz. "Everyone Steps Back? The Widespread Retraction of Crowd-Funding Support for Minority Creators When Migration Fear Is High." Harvard Business School Working Paper, No. 23-046, January 2023. (Revised February 2024.)
      • September 16, 2022
      • Article

      3 Workplace Biases that Derail Mid-Career Women

      By: Colleen Ammerman and Boris Groysberg
      Mid-career women are often surprised by the levels of bias and discrimination they encounter in the workplace, especially if they’ve successfully avoided it earlier in their careers. After speaking to 100 senior women executives, the authors identified three distinct... View Details
      Keywords: Personal Development and Career; Prejudice and Bias; Gender
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      Ammerman, Colleen, and Boris Groysberg. "3 Workplace Biases that Derail Mid-Career Women." Harvard Business Review (website) (September 16, 2022).
      • 2022
      • Working Paper

      Confidence, Self-Selection and Bias in the Aggregate

      By: Benjamin Enke, Thomas Graeber and Ryan Oprea
      The influence of behavioral biases on aggregate outcomes like prices and allocations depends in part on self-selection: whether rational people opt more strongly into aggregate interactions than biased individuals. We conduct a series of betting market, auction and... View Details
      Keywords: Prejudice and Bias; Cognition and Thinking; Markets; Price
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      Enke, Benjamin, Thomas Graeber, and Ryan Oprea. "Confidence, Self-Selection and Bias in the Aggregate." NBER Working Paper Series, No. 30262, July 2022.
      • 2022
      • Chapter

      Redirecting Rawlsian Reasoning Toward the Greater Good

      By: Joshua D. Greene, Karen Huang and Max Bazerman
      In A Theory of Justice, John Rawls employed the ‘veil of Ignorance’ as a moral reasoning device designed to promote impartial thinking. By imagining the choices of decision-makers who are blind to biasing information, one might see more clearly the organizing... View Details
      Keywords: Moral Sensibility; Judgments; Prejudice and Bias; Decision Making
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      Greene, Joshua D., Karen Huang, and Max Bazerman. "Redirecting Rawlsian Reasoning Toward the Greater Good." Chap. 15 in The Oxford Handbook of Moral Psychology, edited by Manuel Vargas and John M. Doris, 246–261. Oxford, UK: Oxford University Press, 2022.
      • June 2022
      • Article

      The Use and Misuse of Patent Data: Issues for Finance and Beyond

      By: Josh Lerner and Amit Seru
      Patents and citations are powerful tools for understanding innovation increasingly used in financial economics (and management research more broadly). Biases may result, however, from the interactions between the truncation of patents and citations and the changing... View Details
      Keywords: Patents; Analytics and Data Science; Corporate Finance; Research
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      Lerner, Josh, and Amit Seru. "The Use and Misuse of Patent Data: Issues for Finance and Beyond." Review of Financial Studies 35, no. 6 (June 2022): 2667–2704.
      • May 2022 (Revised June 2024)
      • Case

      LOOP: Driving Change in Auto Insurance Pricing

      By: Elie Ofek and Alicia Dadlani
      John Henry and Carey Anne Nadeau, co-founders and co-CEOs of LOOP, an insurtech startup based in Austin, Texas, were on a mission to modernize the archaic $250 billion automobile insurance market. They sought to create equitably priced insurance by eliminating pricing... View Details
      Keywords: AI and Machine Learning; Technological Innovation; Equality and Inequality; Prejudice and Bias; Growth and Development Strategy; Customer Relationship Management; Price; Insurance Industry; Financial Services Industry
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      Ofek, Elie, and Alicia Dadlani. "LOOP: Driving Change in Auto Insurance Pricing." Harvard Business School Case 522-073, May 2022. (Revised June 2024.)
      • Article

      How Much Should We Trust Staggered Difference-In-Differences Estimates?

      By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
      We explain when and how staggered difference-in-differences regression estimators, commonly applied to assess the impact of policy changes, are biased. These biases are likely to be relevant for a large portion of research settings in finance, accounting, and law that... View Details
      Keywords: Difference In Differences; Staggered Difference-in-differences Designs; Generalized Difference-in-differences; Dynamic Treatment Effects; Mathematical Methods
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      Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" Journal of Financial Economics 144, no. 2 (May 2022): 370–395. (Editor's Choice, May 2022; Jensen Prize, First Place, June 2023.)
      • November 12, 2021
      • Editorial

      The Psychology Behind Meeting Overload

      By: A.V. Whillans, Dave Feldman and Damian Wisniewski
      Bad meetings are the bane of the corporate world — and yet despite what appears to be an overwhelming consensus that they’re often unnecessary and unproductive, many workplaces continue to struggle to avoid them. In this piece, the authors discuss the psychological... View Details
      Keywords: Meetings; Collaboration; Psychology; Time Management; Communication
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      Whillans, A.V., Dave Feldman, and Damian Wisniewski. "The Psychology Behind Meeting Overload." Harvard Business Review (website) (November 12, 2021).
      • Article

      Fighting Bias on the Front Lines

      By: Alexandra C. Feldberg and Tami Kim
      Most companies aim for exceptional customer service, but too few are attentive to the subtle discrimination by frontline employees that can alienate customers, lead to lawsuits, or even cause lasting brand damage by going viral.
      This article presents research... View Details
      Keywords: Customer Service; Customer Focus and Relationships; Service Delivery; Diversity; Prejudice and Bias; Organizational Change and Adaptation
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      Feldberg, Alexandra C., and Tami Kim. "Fighting Bias on the Front Lines." Harvard Business Review 99, no. 6 (November–December 2021): 90–98.
      • October 2021
      • Article

      Changing Gambling Behavior through Experiential Learning

      By: Shawn A. Cole, Martin Abel and Bilal Zia
      This paper tests experiential learning as a debiasing tool to reduce gambling in South Africa, through a randomized field experiment. The study implements a simple, interactive game that simulates the odds of winning the national lottery through dice rolling.... View Details
      Keywords: Debiasing; Experiential Learning; Behavioral Economics; Financial Education; Learning; Games, Gaming, and Gambling; Behavior; Decision Making
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      Cole, Shawn A., Martin Abel, and Bilal Zia. "Changing Gambling Behavior through Experiential Learning." World Bank Economic Review 35, no. 3 (October 2021): 745–763.
      • September 2021
      • Article

      Gender Stereotypes in Deliberation and Team Decisions

      By: Katherine B. Coffman, Clio Bryant Flikkema and Olga Shurchkov
      We explore how groups deliberate and decide on ideas in an experiment with communication. We find that gender biases play a significant role in which group members are chosen to answer on behalf of the group. Conditional on the quality of their ideas, individuals are... View Details
      Keywords: Gender Differences; Stereotypes; Teams; Economic Experiments; Gender; Prejudice and Bias; Groups and Teams; Perception
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      Coffman, Katherine B., Clio Bryant Flikkema, and Olga Shurchkov. "Gender Stereotypes in Deliberation and Team Decisions." Games and Economic Behavior 129 (September 2021): 329–349.
      • Summer 2021
      • Article

      Predictable Country-level Bias in the Reporting of COVID-19 Deaths

      By: Botir Kobilov, Ethan Rouen and George Serafeim
      We examine whether a country’s management of the COVID-19 pandemic relate to the downward biasing of the number of reported deaths from COVID-19. Using deviations from historical averages of the total number of monthly deaths within a country, we find that the... View Details
      Keywords: COVID-19; Deaths; Reporting; Incentives; Government Policy; Health Pandemics; Health Care and Treatment; Country; Crisis Management; Outcome or Result; Reports; Policy
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      Kobilov, Botir, Ethan Rouen, and George Serafeim. "Predictable Country-level Bias in the Reporting of COVID-19 Deaths." Journal of Government and Economics 2 (Summer 2021).
      • June 2021
      • Case

      Bozoma Saint John: Leading with Authenticity and Urgency

      By: Francesca Gino and Frances X. Frei
      In this multimedia case, Bozoma Saint John recounts numerous defining moments from her childhood and work experiences. We learn what empowered and inspired her to be her authentic self, to be vulnerable and open to new experiences, to find commonality with others, to... View Details
      Keywords: Biases; Personal Development and Career; Identity; Interests; Ethics; Values and Beliefs; Opportunities; Leadership Style; Diversity
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      Gino, Francesca, and Frances X. Frei. "Bozoma Saint John: Leading with Authenticity and Urgency." Harvard Business School Multimedia/Video Case 921-708, June 2021.
      • May 2021
      • Article

      Ideology and Composition Among an Online Crowd: Evidence From Wikipedians

      By: Shane Greenstein, Grace Gu and Feng Zhu
      Online communities bring together participants from diverse backgrounds and often face challenges in aggregating their opinions. We infer lessons from the experience of individual contributors to Wikipedia articles about U.S. politics. We identify two factors that... View Details
      Keywords: User Segregation; Online Community; Contested Knowledge; Collective Intelligence; Ideology; Bias; Wikipedia; Knowledge Sharing; Perspective; Government and Politics
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      Greenstein, Shane, Grace Gu, and Feng Zhu. "Ideology and Composition Among an Online Crowd: Evidence From Wikipedians." Management Science 67, no. 5 (May 2021): 3067–3086.
      • Article

      Missing the Near Miss: Recognizing Valuable Learning Opportunities in Radiation Oncology

      By: Palak Kundu, Olivia Jung, Luca F. Valle, Amy C. Edmondson, Nzhde Agazaryan, John Hegde, Michael Steinberg and Ann Raldow
      “Near miss” events are valuable low-cost learning opportunities in radiation oncology as they do not result in patient harm and are more pervasive than adverse events that do. Near misses vary depending on the presence of a latent error of behavior or process, and the... View Details
      Keywords: Radiation Oncology; Cognitive Biases; Health Care and Treatment; Learning
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      Kundu, Palak, Olivia Jung, Luca F. Valle, Amy C. Edmondson, Nzhde Agazaryan, John Hegde, Michael Steinberg, and Ann Raldow. "Missing the Near Miss: Recognizing Valuable Learning Opportunities in Radiation Oncology." Practical Radiation Oncology 11, no. 3 (May 2021): e256–e262.
      • 2021
      • Article

      Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring

      By: Tom Sühr, Sophie Hilgard and Himabindu Lakkaraju
      Ranking algorithms are being widely employed in various online hiring platforms including LinkedIn, TaskRabbit, and Fiverr. Prior research has demonstrated that ranking algorithms employed by these platforms are prone to a variety of undesirable biases, leading to the... View Details
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      Sühr, Tom, Sophie Hilgard, and Himabindu Lakkaraju. "Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society 4th (2021).
      • 2021
      • Working Paper

      Cognitive Biases: Mistakes or Missing Stakes?

      By: Benjamin Enke, Uri Gneezy, Brian Hall, David Martin, Vadim Nelidov, Theo Offerman and Jeroen van de Ven
      Despite decades of research on heuristics and biases, empirical evidence on the effect of large incentives—as present in relevant economic decisions—on cognitive biases is scant. This paper tests the effect of incentives on four widely documented biases: base rate... View Details
      Keywords: Cognitive Biases; Incentives; Motivation and Incentives; Decision Making; Performance
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      Enke, Benjamin, Uri Gneezy, Brian Hall, David Martin, Vadim Nelidov, Theo Offerman, and Jeroen van de Ven. "Cognitive Biases: Mistakes or Missing Stakes?" Harvard Business School Working Paper, No. 21-102, March 2021.
      • March 2021
      • Teaching Plan

      The Black New Venture Competition

      By: Karen G. Mills, Jeffrey J. Bussgang, Martin A. Sinozich and Gabriella Elanbeck
      Black entrepreneurs encounter many unique obstacles when raising capital to start and grow a business, some stemming from deep systemic discrimination. During their second year at Harvard Business School (HBS), MBA students Kimberly Foster and Tyler Simpson decided to... View Details
      Keywords: Analytics; Startup; Start-up; Startup Financing; Financing; Startups; Start-ups; Business And Community; Business And Society; Business Growth; Discrimination; Women; Women-owned Businesses; African Americans; African-american Entrepreneurs; African-american Investors; African-American Protagonist; African-American Women; Early Stage Funding; Early Stage; Innovation & Entrepreneurship; Innovation Competitions; Entrepreneurial Financing; Business Plan; Business Startups; Diversity; Gender; Race; Entrepreneurship; Venture Capital; Small Business; Leadership; Information Technology; Competition
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      Mills, Karen G., Jeffrey J. Bussgang, Martin A. Sinozich, and Gabriella Elanbeck. "The Black New Venture Competition." Harvard Business School Teaching Plan 821-094, March 2021.
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