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Publications
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- August 5, 2025
- Article
Data-driven Equation Discovery Reveals Nonlinear Reinforcement Learning in Humans
By: Kyle J. LaFollette, Janni Yuval, Roey Schurr, David Melnikoff and Amit Goldenberg
Computational models of reinforcement learning (RL) have significantly contributed to our understanding of human behavior and decision-making. Traditional RL models, however, often adopt a linear approach to updating reward expectations, potentially oversimplifying the... View Details
- 2025
- Working Paper
Productivity Beliefs and Efficiency in Science
By: Fabio Bertolotti, Kyle R. Myers and Wei Yang Tham
We develop a method to estimate producers’ productivity beliefs in settings where output quantities and input prices are unobservable, and we use it to evaluate allocative efficiency in the market for science. Our model of researchers’ labor supply shows that their... View Details
- May 2025
- Article
Imagining the Future: Memory, Simulation and Beliefs
By: Pedro Bordalo, Giovanni Burro, Katherine B. Coffman, Nicola Gennaioli and Andrei Shleifer
How do people form beliefs about novel risks, with which they have little or no experience? Motivated by survey data on beliefs about Covid we collected in 2020, we build a model based on the psychology of selective memory. When a person thinks about an event,... View Details
- May–June 2025
- Article
Slowly Varying Regression Under Sparsity
By: Dimitris Bertsimas, Vassilis Digalakis Jr, Michael Lingzhi Li and Omar Skali Lami
We consider the problem of parameter estimation in slowly varying regression models with sparsity constraints. We formulate the problem as a mixed integer optimization problem and demonstrate that it can be reformulated exactly as a binary convex optimization problem... View Details
- April 2025 (Revised May 2025)
- Background Note
Customer Acquisition and the Cash Flow Trap
By: E. Ofek, Barak Libai and Eitan Muller
Startups as well as existing firms recognize the need to invest in order to acquire customers for their new ventures. And as each customer is expected at some point to have generated sufficient gross margins to cover their CAC, management expects that, soon enough, the... View Details
- March 2025
- Case
The Changing Climate on Wall Street
By: Clayton S. Rose, Maxim Pike Harrell and Michael Norris
Increasing and conflicting regulatory requirements and political pressures regarding climate change tested the leaders of U.S. financial institutions, as they struggled to determine how best to comply while managing their business and its risks.
In October 2024,... View Details
In October 2024,... View Details
Keywords: Competency and Skills; Decision Making; Cost vs Benefits; Ethics; Corporate Accountability; Leadership; Management; Risk Management; Corporate Social Responsibility and Impact; Mission and Purpose; Organizational Change and Adaptation; Organizational Culture; Civil Society or Community; Social Issues; Adaptation; Risk and Uncertainty; Insurance; Climate Change; Change Management; Banking Industry; Financial Services Industry; Insurance Industry; United States; Europe
- 2025
- Working Paper
Incentive-Compatible Recovery from Manipulated Signals, with Applications to Decentralized Physical Infrastructure
By: Jason Milionis, Jens Ernstberger, Joseph Bonneau, Scott Duke Kominers and Tim Roughgarden
We introduce the first formal model capturing the elicitation of unverifiable information from a party (the "source") with implicit signals derived by other players (the "observers"). Our model is motivated in part by applications in decentralized physical... View Details
- February 2025
- Tutorial
Preparing Business Leaders for an Era of Climate Instability: Understanding and Managing Physical Climate Risk
By: Michael W. Toffel and Spencer Glendon
In this compelling video, Spencer Glendon, founder of Probable Futures and Executive Fellow at Harvard Business School, describes the profound implications of climate change for businesses, the economy, and societies around the world. Drawing from his background in... View Details
- 2025
- Working Paper
Is Love Blind? AI-Powered Trading with Emotional Dividends
By: De-Rong Kong and Daniel Rabetti
We leverage the non-fungible tokens (NFTs) setting to assess the valuation of emotional dividends (LOVE), a long-standing empirical challenge in private-value markets such as art, antiques, and collectibles. Having created and validated our proxy, we use deep learning... View Details
- 2025
- Working Paper
Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning
Reinforcement learning (RL) offers potential for optimizing sequences of customer interactions by modeling the relationships
between customer states, company actions, and long-term value. However, its practical implementation often faces significant
challenges.... View Details
- January 2025
- Technical Note
AI vs Human: Analyzing Acceptable Error Rates Using the Confusion Matrix
By: Tsedal Neeley and Tim Englehart
This technical note introduces the confusion matrix as a foundational tool in artificial intelligence (AI) and large language models (LLMs) for assessing the performance of classification models, focusing on their reliability for decision-making. A confusion matrix... View Details
- January 2025
- Supplement
Hippo: Weathering the Storm of the Home Insurance Crisis (B)
By: Lauren Cohen, Grace Headinger and Sophia Pan
Rick McCathron, CEO of Hippo, was optimistic about the InsurTech's path to profitability after navigating the financial uncertainties of 2022. By bundling their home insurance services with third-parties and established insurance incumbents, Hippo was adopting a... View Details
Keywords: Fintech; Underwriters; Big Data; Homeowners' Insurance; Catastrophe Risk; Global Warming; Environment; Business Economics; Vertical Specialization; Bundling; Economies Of Scale; Business Model; Forecasting and Prediction; Climate Change; Environmental Sustainability; Green Technology; Technological Innovation; Natural Environment; Natural Disasters; Weather; Business Strategy; Competitive Advantage; Business Earnings; Insurance; Social Issues; Profit; Growth and Development Strategy; Insurance Industry; California; United States
- January 2025
- Case
AI Meets VC: The Data-Driven Revolution at Quantum Light Capital
By: Lauren Cohen, Grace Headinger and Sophia Pan
Ilya Kondrashov, CEO of Quantum Light Capital, was driven to harness AI for identifying high-potential scale-ups. Collaborating with Nik Storonsky, founder of Revolut, the duo observed that most venture capital (VC) decisions were heavily influenced by emotion, with... View Details
Keywords: Artificial Intelligence; Business Finance; Data Analysis; Angel Investors; Cognitive Biases; Scale; Venture Capital; Investment; Business Model; Forecasting and Prediction; Technological Innovation; Innovation Strategy; Behavior; Cognition and Thinking; Public Opinion; Private Sector; Business Strategy; Competitive Advantage; Business Earnings; Behavioral Finance; AI and Machine Learning; Analytics and Data Science; Business Startups; Financial Services Industry; London; United Kingdom
- 2025
- Working Paper
Combining Complements: Theory and Evidence from Cancer Treatment Innovation
By: Rebekah Dix and Todd A. Lensman
Innovations often combine several components to achieve outcomes greater than the
“sum of the parts.” We argue that such combination innovations can introduce an understudied
inefficiency—a positive market expansion externality that benefits the owners of
the... View Details
- November 2024
- Supplement
AlphaGo (C): Birth of a New Intelligence
By: Shikhar Ghosh and Shweta Bagai
This case, the final of a three-part series, explores DeepMind's pivotal transition from mastering games to solving real-world scientific challenges. In December 2020, DeepMind's AI system AlphaFold 2 achieved a breakthrough by solving protein folding—a 50-year-old... View Details
Keywords: Autonomy; Deep Learning; Drug Discovery; Healthcare Innovation; Neural Networks; Scientific Research; Technology Startup; AI and Machine Learning; Technological Innovation; Research and Development; Business Model; Business Strategy; Open Source Distribution; Technology Industry; United States
- 2024
- Working Paper
Scaling Core Earnings Measurement with Large Language Models
By: Matthew Shaffer and Charles CY Wang
We study the application of large language models (LLMs) to the estimation of core earnings, i.e., a firm's persistent profitability from its core business activities. This construct is central to investors' assessments of economic performance and valuations. However,... View Details
- November 2024
- Article
Perceptions About Monetary Policy
By: Michael D. Bauer, Carolin Pflueger and Adi Sunderam
We estimate perceptions about the Federal Reserve’s monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions varies substantially over time,... View Details
- October 2024
- Article
Canary Categories
By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that... View Details
- 2024
- Working Paper
Pitfalls of Demographic Forecasts of U.S. Elections
By: Richard Calvo, Vincent Pons and Jesse M. Shapiro
Many observers have forecast large partisan shifts in the US electorate based on demographic trends. Such forecasts are appealing because demographic trends are often predictable even over long horizons. We backtest demographic forecasts using data on US elections... View Details
- 2024
- Article
Learning Under Random Distributional Shifts
By: Kirk Bansak, Elisabeth Paulson and Dominik Rothenhäusler
Algorithmic assignment of refugees and asylum seekers to locations within host
countries has gained attention in recent years, with implementations in the U.S.
and Switzerland. These approaches use data on past arrivals to generate machine
learning models that can... View Details