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Publications

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    • All HBS Web  (462)
      • Faculty Publications  (165)

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      • 2025
      • Working Paper

      Discrimination, Rejection, and Job Search

      By: Anne Boring, Katherine Coffman, Dylan Glover and María José González-Fuentes
      We investigate how candidates’ willingness to apply responds to (potential) discrimination and rejection using a simulated labor market. Past work has shown that “blinding” job applications reduces discrimination and increases the rate at which women are hired. Our... View Details
      Keywords: Job Search; Prejudice and Bias; Selection and Staffing; Demographics
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      Boring, Anne, Katherine Coffman, Dylan Glover, and María José González-Fuentes. "Discrimination, Rejection, and Job Search." Working Paper, February 2025.
      • 2025
      • Working Paper

      Tax Planning, Illiquidity, and Credit Risks: Evidence from DeFi Lending

      By: Lisa De Simone, Peiyi Jin and Daniel Rabetti
      This study establishes a plausible causal link between tax-planning-induced illiquidity and credit risks in lending markets. Exploiting an exogenous tax shock imposed by the Internal Revenue Service (IRS) on cryptocurrency gains, along with millions of transactions in... View Details
      Keywords: Cryptocurrency; Taxation; Financial Liquidity; Credit; Financing and Loans; Financial Markets
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      De Simone, Lisa, Peiyi Jin, and Daniel Rabetti. "Tax Planning, Illiquidity, and Credit Risks: Evidence from DeFi Lending." Working Paper, February 2025.
      • 2025
      • Article

      Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments

      By: Kosuke Imai and Michael Lingzhi Li
      Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
      Keywords: AI and Machine Learning; Mathematical Methods; Analytics and Data Science
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      Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics 43, no. 1 (2025): 256–268.
      • 2024
      • Working Paper

      A Gender Backlash: Does Exposure to Female Labor Market Participation Fuel Gender Conservatism?

      By: Paula Rettl, Diane Bolet, Catherine E. De Vries, Simone Cremaschi, Tarik Abou-Chadi and Sergi Pardos-Prado
      The growing participation of women in the labor market has marked a significant societal transformation, coinciding with the rise of gender conservatism and far-right support. We study whether the economic consequences of labor market feminization and gender backlash... View Details
      Keywords: Gender Bias; Gender Equality; Gender Inclusivity; Politics; Political Backlash; Political Culture; Conservatism; Gender; Government and Politics; Equality and Inequality; Prejudice and Bias; Labor
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      Rettl, Paula, Diane Bolet, Catherine E. De Vries, Simone Cremaschi, Tarik Abou-Chadi, and Sergi Pardos-Prado. "A Gender Backlash: Does Exposure to Female Labor Market Participation Fuel Gender Conservatism?" Harvard Business School Working Paper, No. 25-022, November 2024.
      • 2024
      • Working Paper

      Does Private Equity Have Any Business Being in the Health Care Business?

      By: Nori Gerardo Lietz and Zirui Song
      Private Equity (“PE”) has come under increased scrutiny by the press, academics, and policymakers, as well as the public, for its investments in health care delivery. This scrutiny has been exacerbated by recent high profile hospital bankruptcies following PE... View Details
      Keywords: Private Equity; Government Administration; Acquisition; Health Industry
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      Lietz, Nori Gerardo, and Zirui Song. "Does Private Equity Have Any Business Being in the Health Care Business?" Harvard Business School Working Paper, No. 25-012, September 2024.
      • 2024
      • Working Paper

      Patent Hunters

      By: Lauren Cohen, Umit Gurun, Katie Moon and Paula Suh
      Analyzing millions of patents granted by the USPTO between 1976 and 2020, we find a pattern where specific patents only rise to prominence after considerable time has passed. Amongst these late-blooming influential patents, we show that there are key players (patent... View Details
      Keywords: Patents; Product Launch; Product; Innovation and Invention
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      Cohen, Lauren, Umit Gurun, Katie Moon, and Paula Suh. "Patent Hunters." NBER Working Paper Series, No. 32965, September 2024.
      • 2024
      • Working Paper

      The Wade Test: Generative AI and CEO Communication

      By: Prithwiraj Choudhury, Bart S. Vanneste and Amirhossein Zohrehvand
      Can generative artificial intelligence (AI) transform the role of the CEO by effectively automating CEO communication? This study investigates whether AI can mimic a human CEO and whether employees’ perception of the communication’s source matter. In a field... View Details
      Keywords: Business or Company Management; AI and Machine Learning; Perception; Communication
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      Choudhury, Prithwiraj, Bart S. Vanneste, and Amirhossein Zohrehvand. "The Wade Test: Generative AI and CEO Communication." Harvard Business School Working Paper, No. 25-008, August 2024.
      • August 2024
      • Article

      How Do Copayment Coupons Affect Branded Drug Prices and Quantities Purchased?

      By: Leemore S. Dafny, Kate Ho and Edward Kong
      Drug copayment coupons to reduce patient cost-sharing have become nearly ubiquitous for high-priced brand-name prescription drugs. Medicare bans such coupons on the grounds that they are kickbacks that induce utilization, but they are commonly used by... View Details
      Keywords: Prescription Drugs; Coupons; Impact; Health Care and Treatment; Markets; Price; Spending; Pharmaceutical Industry; United States
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      Dafny, Leemore S., Kate Ho, and Edward Kong. "How Do Copayment Coupons Affect Branded Drug Prices and Quantities Purchased?" American Economic Journal: Economic Policy 16, no. 3 (August 2024): 314–346.
      • 2024
      • Article

      Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules

      By: Michael Lingzhi Li and Kosuke Imai
      A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today’s scientists across... View Details
      Keywords: AI and Machine Learning; Research
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      Li, Michael Lingzhi, and Kosuke Imai. "Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules." Journal of Causal Inference 12, no. 1 (2024).
      • July–August 2024
      • Article

      Disclosing Downstream Emissions

      By: Robert S. Kaplan and Karthik Ramanna
      An increasing number of companies are using the E-liability carbon-accounting method as an important tool for tracking progress toward reducing global emissions in their supply chains. The system does not require formal accounting for downstream emissions—those... View Details
      Keywords: Carbon Emissions; Environmental Accounting; Corporate Accountability; Corporate Social Responsibility and Impact; Corporate Disclosure; Environmental Sustainability
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      Kaplan, Robert S., and Karthik Ramanna. "Disclosing Downstream Emissions." Harvard Business Review 102, no. 4 (July–August 2024): 124–133.
      • 2024
      • Working Paper

      Navigating Software Vulnerabilities: Eighteen Years of Evidence from Medium and Large U.S. Organizations

      By: Raviv Murciano-Goroff, Ran Zhuo and Shane Greenstein
      How prevalent are severe software vulnerabilities, how fast do software users respond to the availability of secure versions, and what determines the variance in the installation distribution? Using the largest dataset ever assembled on user updates, tracking server... View Details
      Keywords: Cybersecurity; Applications and Software; Technology Adoption; Consumer Behavior
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      Murciano-Goroff, Raviv, Ran Zhuo, and Shane Greenstein. "Navigating Software Vulnerabilities: Eighteen Years of Evidence from Medium and Large U.S. Organizations." NBER Working Paper Series, No. 32696, July 2024.
      • 2024
      • Working Paper

      Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization

      By: Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
      This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
      Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
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      Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.
      • 2024
      • Working Paper

      Winner Take All: Exploiting Asymmetry in Factorial Designs

      By: Matthew DosSantos DiSorbo, Iavor I. Bojinov and Fiammetta Menchetti
      Researchers and practitioners have embraced factorial experiments to simultaneously test multiple treatments, each with different levels. With the rise of technologies like Generative AI, factorial experimentation has become even more accessible: it is easier than ever... View Details
      Keywords: Factorial Designs; Fisher Randomizations; Rank Estimators; Employer Interventions; Causal Inference; Mathematical Methods; Performance Improvement
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      DosSantos DiSorbo, Matthew, Iavor I. Bojinov, and Fiammetta Menchetti. "Winner Take All: Exploiting Asymmetry in Factorial Designs." Harvard Business School Working Paper, No. 24-075, June 2024.
      • 2024
      • Working Paper

      Advancing Personalization: How to Experiment, Learn & Optimize

      By: Aurelie Lemmens, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela and Oded Netzer
      Personalization has become the heartbeat of modern marketing. Advances in causal inference and machine learning enable companies to understand how the same marketing action can impact the choices of individual customers differently. This article provides an academic... View Details
      Keywords: Personalization; Targeting; Experiments; Observational Studies; Policy Implementation; Policy Evaluation; Customization and Personalization; Marketing Strategy; AI and Machine Learning
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      Lemmens, Aurelie, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela, and Oded Netzer. "Advancing Personalization: How to Experiment, Learn & Optimize." Working Paper, July 2024. (Revised March 2025.)
      • May 2024
      • Article

      Relational Attributions for One’s Own Resilience Predict Compassion for Others

      By: Rachel Ruttan, Ting Zhang, Sivahn Barli and Katherine DeCelles
      Existing work on attribution theory distinguishes between external and internal attributions (i.e., “I overcame adversity due to luck” vs. “my own effort”). We introduce the construct of relational resilience attributions (i.e., “due to help from other people”) as a... View Details
      Keywords: Personal Characteristics; Forecasting and Prediction; Attitudes; Behavior
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      Ruttan, Rachel, Ting Zhang, Sivahn Barli, and Katherine DeCelles. "Relational Attributions for One’s Own Resilience Predict Compassion for Others." Journal of Personality and Social Psychology 126, no. 5 (May 2024): 818–840.
      • 2023
      • Working Paper

      An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits

      By: Biyonka Liang and Iavor I. Bojinov
      Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details
      Keywords: Analytics and Data Science; AI and Machine Learning; Mathematical Methods
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      Liang, Biyonka, and Iavor I. Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
      • 2024
      • Working Paper

      Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference

      By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov
      Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to... View Details
      Keywords: Mathematical Methods; Analytics and Data Science
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      Lindon, Michael, Dae Woong Ham, Martin Tingley, and Iavor I. Bojinov. "Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference." Harvard Business School Working Paper, No. 24-060, March 2024.
      • March 2024
      • Article

      How Foes Become Allies: The Shifting Role of Business in Climate Politics

      By: Irja Vormedal and Jonas Meckling
      Firms often oppose costly public policy reforms—but under what conditions may they come to support such reforms? Previous scholarship has taken a predominantly static approach to the analysis of business positions. Here, we advance a dynamic theory of change in... View Details
      Keywords: Policy; Environmental Regulation; Business and Government Relations
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      Vormedal, Irja, and Jonas Meckling. "How Foes Become Allies: The Shifting Role of Business in Climate Politics." Policy Sciences 57, no. 1 (March 2024): 101–124.
      • March 2024
      • Article

      Human Capital Affects Religious Identity: Causal Evidence from Kenya

      By: Livia Alfonsi, Michal Bauer, Julie Chytilová and Edward Miguel
      We study how human capital and economic conditions causally affect the choice of religious denomination. We utilize a longitudinal dataset monitoring the religious history of more than 5,000 Kenyans over 20 years, in tandem with a randomized experiment (deworming) that... View Details
      Keywords: Religion; Human Capital; Developing Countries and Economies; Welfare; Kenya
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      Alfonsi, Livia, Michal Bauer, Julie Chytilová, and Edward Miguel. "Human Capital Affects Religious Identity: Causal Evidence from Kenya." Art. 103215. Journal of Development Economics 167 (March 2024).
      • 2024
      • Book

      When Democracy Breaks: Studies in Democratic Erosion and Collapse, from Ancient Athens to the Present Day

      By: Archon Fung, David Moss and Odd Arne Westad
      Democracy is often described in two opposite ways, as either wonderfully resilient or dangerously fragile. Curiously, both characterizations can be correct, depending on the context. When Democracy Breaks aims to deepen our understanding of what separates democratic... View Details
      Keywords: Government and Politics; History; Culture; Failure
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      Fung, Archon, David Moss, and Odd Arne Westad, eds. When Democracy Breaks: Studies in Democratic Erosion and Collapse, from Ancient Athens to the Present Day. Oxford University Press, 2024.
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