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Publications

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    • All HBS Web  (943)
      • Faculty Publications  (176)

      Predictive Models Remove Predictive Models →

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      • 2022
      • Working Paper

      Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development

      By: Daniel Yue, Paul Hamilton and Iavor Bojinov
      Predictive model development is understudied despite its importance to modern businesses. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms) as the primary driver of model quality, the value of tools...  View Details
      Keywords: Analytics and Data Science
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      Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022.
      • 2022
      • Working Paper

      Demand-and-Supply Imbalance Risk and Long-Term Swap Spreads

      By: Samuel G. Hanson, Aytek Malkhozov and Gyuri Venter
      We develop and test a model in which swap spreads are determined by end users' demand for and constrained intermediaries' supply of long-term interest rate swaps. Swap spreads reflect compensation both for using scarce intermediary capital and for bearing convergence...  View Details
      Keywords: Swap Spreads; Risk and Uncertainty; Interest Rates; Financial Crisis; Financial Markets
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      Hanson, Samuel G., Aytek Malkhozov, and Gyuri Venter. "Demand-and-Supply Imbalance Risk and Long-Term Swap Spreads." Working Paper, December 2022.
      • Working Paper

      Representation and Extrapolation: Evidence from Clinical Trials

      By: Marcella Alsan, Maya Durvasula, Harsh Gupta, Joshua Schwartzstein and Heidi L. Williams
      This article examines the consequences and causes of low enrollment of Black patients in clinical trials. We develop a simple model of similarity-based extrapolation that predicts that evidence is more relevant for decision-making by physicians and patients when it...  View Details
      Keywords: Representation; Racial Disparity; Health Testing and Trials; Race; Equality and Inequality; Innovation and Invention; Pharmaceutical Industry
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      Alsan, Marcella, Maya Durvasula, Harsh Gupta, Joshua Schwartzstein, and Heidi L. Williams. "Representation and Extrapolation: Evidence from Clinical Trials." NBER Working Paper Series, No. 30575, October 2022. (Revise and resubmit, Quarterly Journal of Economics.)
      • 2022
      • Working Paper

      What's My Employee Worth? The Effects of Salary Benchmarking

      By: Zoë B. Cullen, Shengwu Li and Ricardo Perez-Truglia
      While U.S. legislation prohibits employers from sharing information about their employees’ compensation with each other, companies are still allowed to acquire and use more aggregated data provided by third parties. Most medium and large firms report using this type...  View Details
      Keywords: Information Sharing; Wages; Policy; Compensation and Benefits
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      Cullen, Zoë B., Shengwu Li, and Ricardo Perez-Truglia. "What's My Employee Worth? The Effects of Salary Benchmarking." NBER Working Paper Series, No. 30570, October 2022. (Revised January 2023.)
      • 2022
      • Working Paper

      Perceptions about Monetary Policy

      By: Michael D. Bauer, Carolin Pflueger and Adi Sunderam
      We estimate perceptions about the Fed's monetary policy rule from micro data on professional forecasters. The perceived rule varies significantly over time, with important consequences for monetary policy and bond markets. Over the monetary policy cycle, easings are...  View Details
      Keywords: Monetary Policy; Central Banking; Forecasting and Prediction; Policy; Interest Rates
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      Bauer, Michael D., Carolin Pflueger, and Adi Sunderam. "Perceptions about Monetary Policy." NBER Working Paper Series, No. 30480, September 2022.
      • 2022
      • Working Paper

      Imagining the Future: Memory, Simulation and Beliefs about COVID

      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? A 2020 U.S. survey of beliefs about the lethality of COVID reveals that the elderly underestimate, and the young overestimate, their own risks, and that people with more health...  View Details
      Keywords: Expectations; Memory; COVID-19 Pandemic; Perception; Behavior; Decision Choices and Conditions; Values and Beliefs
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      Bordalo, Pedro, Giovanni Burro, Katherine B. Coffman, Nicola Gennaioli, and Andrei Shleifer. "Imagining the Future: Memory, Simulation and Beliefs about COVID." NBER Working Paper Series, No. 30353, August 2022.
      • 2022
      • Working Paper

      Machine Learning Models for Prediction of Scope 3 Carbon Emissions

      By: George Serafeim and Gladys Vélez Caicedo
      For most organizations, the vast amount of carbon emissions occur in their supply chain and in the post-sale processing, usage, and end of life treatment of a product, collectively labelled scope 3 emissions. In this paper, we train machine learning algorithms on 15...  View Details
      Keywords: Carbon Emissions; Climate Change; Environment; Carbon Accounting; Machine Learning; Artificial Intelligence; Digital; Data Science; Environmental Sustainability; Environmental Management; Environmental Accounting
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      Serafeim, George, and Gladys Vélez Caicedo. "Machine Learning Models for Prediction of Scope 3 Carbon Emissions." Harvard Business School Working Paper, No. 22-080, June 2022.
      • March 2022 (Revised July 2022)
      • Module Note

      Prediction & Machine Learning

      By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
      This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional...  View Details
      Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation
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      Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Module Note 622-101, March 2022. (Revised July 2022.)
      • February 2022 (Revised September 2022)
      • Case

      Lilium: Preparing for Takeoff

      By: Navid Mojir, Vincent Dessain, Mette Fuglsang Hjortshoej and Emer Moloney
      Lilium is a German company focused on developing electric vertical takeoff and landing vehicles (eVTOLs) that can be used to offer air taxi services. The company went public in September 2021 through a special purpose acquisition company (SPAC) deal, raising more than...  View Details
      Keywords: SPACs; Business Model; Forecasting and Prediction; Green Technology; Capital Markets; Venture Capital; Initial Public Offering; Rural Scope; Urban Scope; City; Disruptive Innovation; Growth and Development Strategy; Technological Innovation; Demand and Consumers; Market Timing; Industry Growth; Infrastructure; Logistics; Product Design; Product Development; Production; Service Delivery; Service Operations; Strategic Planning; Partners and Partnerships; Risk and Uncertainty; Urban Development; Sustainable Cities; Business Strategy; Competitive Strategy; Competitive Advantage; Air Transportation; Aerospace Industry; Air Transportation Industry; Green Technology Industry; Transportation Industry; Travel Industry; Germany; Munich; Brazil; United States; Florida
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      Mojir, Navid, Vincent Dessain, Mette Fuglsang Hjortshoej, and Emer Moloney. "Lilium: Preparing for Takeoff." Harvard Business School Case 522-084, February 2022. (Revised September 2022.)
      • January 10, 2022
      • Article

      The Link Between Income, Income Inequality, and Prosocial Behavior Around the World: A Multiverse Approach

      By: Lucia Macchia and Ashley V. Whillans
      The questions of whether high-income individuals are more prosocial than low-income individuals and whether income inequality moderates this effect have received extensive attention. We shed new light on this topic by analyzing a large-scale dataset with a...  View Details
      Keywords: Prosocial Behavior; Income Inequality; Behavior; Philanthropy and Charitable Giving; Income
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      Macchia, Lucia, and Ashley V. Whillans. "The Link Between Income, Income Inequality, and Prosocial Behavior Around the World: A Multiverse Approach." Social Psychology (January 10, 2022): 375–386.
      • Article

      Counterfactual Explanations Can Be Manipulated

      By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh
      Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate...  View Details
      Keywords: Machine Learning Models; Counterfactual Explanations
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      Slack, Dylan, Sophie Hilgard, Himabindu Lakkaraju, and Sameer Singh. "Counterfactual Explanations Can Be Manipulated." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
      • Article

      Behavioral and Neural Representations en route to Intuitive Action Understanding

      By: Leyla Tarhan, Julian De Freitas and Talia Konkle
      When we observe another person’s actions, we process many kinds of information—from how their body moves to the intention behind their movements. What kinds of information underlie our intuitive understanding about how similar actions are to each other? To address this...  View Details
      Keywords: Action Perception; Intuitive Similarity; Multi-arrangement; fMRI; Representational Similarity Analysis; Behavior; Perception
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      Tarhan, Leyla, Julian De Freitas, and Talia Konkle. "Behavioral and Neural Representations en route to Intuitive Action Understanding." Neuropsychologia 163 (December 2021).
      • October 2021
      • Article

      Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach

      By: Nicolas Padilla and Eva Ascarza
      The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can...  View Details
      Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Programs; Consumer Behavior; Analysis
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      Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Journal of Marketing Research (JMR) 58, no. 5 (October 2021): 981–1006.
      • September 2021
      • Article

      Learning from Deregulation: The Asymmetric Impact of Lockdown and Reopening on Risky Behavior During COVID-19

      By: Edward L. Glaeser, Ginger Zhe Jin, Michael Luca and Benjamin T. Leyden
      During the COVID-19 pandemic, states issued and then rescinded stay-at-home orders that restricted mobility. We develop a model of learning by deregulation, which predicts that lifting stay-at-home orders can signal that going out has become safer. Using restaurant...  View Details
      Keywords: COVID-19; Lockdown; Reopening; Impact; Coronavirus; Public Health Measures; Mobility; Health Pandemics; Governing Rules, Regulations, and Reforms; Consumer Behavior
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      Glaeser, Edward L., Ginger Zhe Jin, Michael Luca, and Benjamin T. Leyden. "Learning from Deregulation: The Asymmetric Impact of Lockdown and Reopening on Risky Behavior During COVID-19." Special Issue on COVID-19 and Regional Economies. Journal of Regional Science 61, no. 4 (September 2021): 696–709.
      • 2021
      • Working Paper

      Salience

      By: Pedro Bordalo, Nicola Gennaioli and Andrei Shleifer
      We review the fast-growing work on salience and economic behavior. Psychological research shows that salient stimuli attract human attention “bottom up” due to their high contrast with surroundings, their surprising nature relative to recalled experiences, or their...  View Details
      Keywords: Salience; Economic Behavior; Bottom Up Attention; Microeconomics; Decision Making; Behavior
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      Bordalo, Pedro, Nicola Gennaioli, and Andrei Shleifer. "Salience." NBER Working Paper Series, No. 29274, September 2021.
      • August 2021
      • Supplement

      Coats: Supply Chain Challenges: Spreadsheet Supplement

      By: Willy C. Shih
      Coats, the largest thread maker in the world, transformed its business to digital colour measurement so that it could respond better to customer demand in the garment industry for rapid product cycles and more fragmented colour choices. Its embrace of digital colour...  View Details
      Keywords: Inventory Management; Supply Chain; Inventory; Supply Chain Management; Operations; Growth and Development Strategy; Forecasting and Prediction; Demand and Consumers; Consolidation; Apparel and Accessories Industry; Asia
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      Shih, Willy C. "Coats: Supply Chain Challenges: Spreadsheet Supplement." Harvard Business School Spreadsheet Supplement 622-702, August 2021.
      • 2021
      • Working Paper

      Multiple Team Membership, Turnover, and On-Time Delivery: Evidence from Construction Services

      By: Hise O. Gibson, Bradely R. Staats and Ananth Raman
      Firms who want to compete in dynamic markets are finding that they must build more agile operations to ensure success. One way for a firm to increase organizational agility is to allocate employees to multiple project teams, simultaneously—a practice known as multiple...  View Details
      Keywords: Multiple Team Membership; Turnover; Fluid Teams; Project Management; Groups and Teams; Projects; Management; Performance
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      Gibson, Hise O., Bradely R. Staats, and Ananth Raman. "Multiple Team Membership, Turnover, and On-Time Delivery: Evidence from Construction Services." Harvard Business School Working Paper, No. 22-004, July 2021.
      • Article

      Learning Models for Actionable Recourse

      By: Alexis Ross, Himabindu Lakkaraju and Osbert Bastani
      As machine learning models are increasingly deployed in high-stakes domains such as legal and financial decision-making, there has been growing interest in post-hoc methods for generating counterfactual explanations. Such explanations provide individuals adversely...  View Details
      Keywords: Machine Learning Models; Recourse; Algorithm; Mathematical Methods
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      Ross, Alexis, Himabindu Lakkaraju, and Osbert Bastani. "Learning Models for Actionable Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
      • June 2021
      • Technical Note

      Introduction to Linear Regression

      By: Michael Parzen and Paul Hamilton
      This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical...  View Details
      Keywords: Linear Regression; Regression; Analysis; Forecasting and Prediction; Risk and Uncertainty; Theory; Compensation and Benefits; Mathematical Methods; Analytics and Data Science
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      Parzen, Michael, and Paul Hamilton. "Introduction to Linear Regression." Harvard Business School Technical Note 621-086, June 2021.
      • 2021
      • Working Paper

      Equilibrium Effects of Pay Transparency

      By: Zoë B. Cullen and Bobak Pakzad-Hurson
      The public discourse around pay transparency has focused on the direct effect: how workers seek to rectify newly-disclosed pay inequities through renegotiations. The question of how wage-setting and hiring practices of the firm respond in equilibrium has received...  View Details
      Keywords: Pay Transparency; Online Labor Market; Privacy; Wage Gap; Negotiation; Corporate Disclosure; Compensation and Benefits; Gender
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      Cullen, Zoë B., and Bobak Pakzad-Hurson. "Equilibrium Effects of Pay Transparency." NBER Working Paper Series, No. 28903, June 2021. (Conditionally accepted at Econometrica.)
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