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Publications

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      • Faculty Publications  (104)

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      • 2023
      • Working Paper

      Summarizing the Mental Customer Journey

      By: Julian De Freitas, Ahmet Uğuralp, Zeliha Uğuralp, Pechthida Kim and Tomer Ullman
      How do consumers summarize and act on their experiences, as when deciding whether an interaction with a firm was satisfying and whether to buy from it? Previous work on the summary of continuous experiences has tended to focus on a handful of experience patterns and...  View Details
      Keywords: Customer Experience; Customer Journey; Natural Language Processing; Summarization; Customer Satisfaction; Outcome or Result; Decision Choices and Conditions
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      De Freitas, Julian, Ahmet Uğuralp, Zeliha Uğuralp, Pechthida Kim, and Tomer Ullman. "Summarizing the Mental Customer Journey." Harvard Business School Working Paper, No. 23-038, January 2023.
      • 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.
      • Article

      Expected Stock Returns Worldwide: A Log-Linear Present-Value Approach

      By: Akash Chattopadhyay, Matthew R. Lyle and Charles C.Y. Wang
      This study provides the first large-scale study of the performance of expected-return proxies (ERPs) internationally. Analyst-forecast-based ICCs are sparsely populated and not robustly associated with future returns. Earnings-model-forecast-based ICCs are...  View Details
      Keywords: Expected Returns; Discount Rates; Fundamental Valuation; Implied Cost Of Capital; International Equity Markets; Present Value; Investment Return; Equity; Markets; Global Range
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      Chattopadhyay, Akash, Matthew R. Lyle, and Charles C.Y. Wang. "Expected Stock Returns Worldwide: A Log-Linear Present-Value Approach." Accounting Review 97, no. 2 (March 2022): 107–133.
      • March 2022
      • Article

      Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field

      By: Reshmaan Hussam, Natalia Rigol and Benjamin N. Roth
      Identifying high-growth microentrepreneurs in low-income countries remains a challenge due to a scarcity of verifiable information. With a cash grant experiment in India we demonstrate that community knowledge can help target high-growth microentrepreneurs; while the...  View Details
      Keywords: Microentrepreneurs; Community Information; Field Experiment; Loans; Entrepreneurship; Developing Countries and Economies; Financing and Loans; Information; Mathematical Methods; India
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      Hussam, Reshmaan, Natalia Rigol, and Benjamin N. Roth. "Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field." American Economic Review 112, no. 3 (March 2022): 861–898.
      • 2022
      • Working Paper

      What Triggers National Stock Market Jumps?

      By: Scott R. Baker, Nicholas Bloom, Steven J. Davis and Marco Sammon
      We examine newspapers the day after major stock-market jumps to evaluate the proximate cause, geographic source, and clarity of these events from 1900 in the US, 1930 in the UK and 1980 in 12 other countries. We find four main results. First, the United States plays an...  View Details
      Keywords: Uncertainty; Policy Uncertainty; Stock Market; Financial Markets; Volatility; Risk and Uncertainty; Policy; Newspapers
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      Baker, Scott R., Nicholas Bloom, Steven J. Davis, and Marco Sammon. "What Triggers National Stock Market Jumps?" Working Paper, February 2022.
      • January 2022
      • Article

      Rational Habit Formation: Experimental Evidence from Handwashing in India

      By: Reshmaan Hussam, Atonu Rabbani, Giovanni Reggiani and Natalia Rigol
      We test the predictions of the rational addiction model, reconceptualized as rational habit formation, in the context of handwashing in rural India. To track handwashing, we design soap dispensers with timed sensors. We test for rational habit formation by informing...  View Details
      Keywords: Handwashing; Habit; Monitoring; Behavior; Health; Motivation and Incentives
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      Hussam, Reshmaan, Atonu Rabbani, Giovanni Reggiani, and Natalia Rigol. "Rational Habit Formation: Experimental Evidence from Handwashing in India." American Economic Journal: Applied Economics 14, no. 1 (January 2022): 1–41. (Lead Article.)
      • January 2022
      • Article

      Why Is Corporate Virtue in the Eye of the Beholder? The Case of ESG Ratings

      By: Dane Christensen, George Serafeim and Anywhere Sikochi
      Despite the rising use of environmental, social, and governance (ESG) ratings, there is substantial disagreement across rating agencies regarding what rating to give to individual firms. As what drives this disagreement is unclear, we examine whether a firm’s ESG...  View Details
      Keywords: ESG Ratings; Rating Agency Disagreement; ESG Disclosure; Corporate Social Responsibility; Sustainability; Corporate Social Responsibility and Impact; Environmental Sustainability; Corporate Disclosure
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      Christensen, Dane, George Serafeim, and Anywhere Sikochi. "Why Is Corporate Virtue in the Eye of the Beholder? The Case of ESG Ratings." Accounting Review 97, no. 1 (January 2022): 147–175.
      • Article

      Megastudies Improve the Impact of Applied Behavioural Science

      By: Katherine L. Milkman, Dena Gromet, Hung Ho, Joseph S. Kay, Timothy W. Lee, Pepi Pandiloski, Yeji Park, Aneesh Rai, Max Bazerman, John Beshears, Lauri Bonacorsi, Colin Camerer, Edward Chang, Gretchen Chapman, Robert Cialdini, Hengchen Dai, Lauren Eskreis-Winkler, Ayelet Fishbach, James J. Gross, Samantha Horn, Alexa Hubbard, Steven J. Jones, Dean Karlan, Tim Kautz, Erika Kirgios, Joowon Klusowski, Ariella Kristal, Rahul Ladhania, Jens Ludwig, George Loewenstein, Barbara Mellers, Sendhil Mullainathan, Silvia Saccardo, Jann Spiess, Gaurav Suri, Joachim H. Talloen, Jamie Taxer, Yaacov Trope, Lyle Ungar, Kevin G. Volpp, Ashley Whillans, Jonathan Zinman and Angela L. Duckworth
      Policy-makers are increasingly turning to behavioural science for insights about how to improve citizens’ decisions and outcomes. Typically, different scientists test different intervention ideas in different samples using different outcomes over different time...  View Details
      Keywords: Policy Making; Behavioral Science; Behavior; Change; Decision Making; Policy
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      Milkman, Katherine L., Dena Gromet, Hung Ho, Joseph S. Kay, Timothy W. Lee, Pepi Pandiloski, Yeji Park, Aneesh Rai, Max Bazerman, John Beshears, Lauri Bonacorsi, Colin Camerer, Edward Chang, Gretchen Chapman, Robert Cialdini, Hengchen Dai, Lauren Eskreis-Winkler, Ayelet Fishbach, James J. Gross, Samantha Horn, Alexa Hubbard, Steven J. Jones, Dean Karlan, Tim Kautz, Erika Kirgios, Joowon Klusowski, Ariella Kristal, Rahul Ladhania, Jens Ludwig, George Loewenstein, Barbara Mellers, Sendhil Mullainathan, Silvia Saccardo, Jann Spiess, Gaurav Suri, Joachim H. Talloen, Jamie Taxer, Yaacov Trope, Lyle Ungar, Kevin G. Volpp, Ashley Whillans, Jonathan Zinman, and Angela L. Duckworth. "Megastudies Improve the Impact of Applied Behavioural Science." Nature 600, no. 7889 (December 16, 2021): 478–483.
      • 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.
      • July–August 2021
      • Article

      Why You Aren't Getting More from Your Marketing AI

      By: Eva Ascarza, Michael Ross and Bruce G.S. Hardie
      Fewer than 40% of companies that invest in AI see gains from it, usually because of one or more of these errors: (1) They don’t ask the right question, and end up directing AI to solve the wrong problem. (2) They don’t recognize the differences between the value of...  View Details
      Keywords: Artificial Intelligence; Marketing; Decision Making; Communication; Framework; AI and Machine Learning
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      Ascarza, Eva, Michael Ross, and Bruce G.S. Hardie. "Why You Aren't Getting More from Your Marketing AI." Harvard Business Review 99, no. 4 (July–August 2021): 48–54.
      • January–February 2021
      • Article

      Cross‐firm Return Predictability and Accounting Quality

      By: Wen Chen, Mozaffar Khan, Leonid Kogan and George Serafeim
      We test the hypothesis that if poor accounting quality (AQ) is associated with poor investor understanding of firms’ revenue and cost structures, then poor AQ stocks likely respond more slowly than good AQ stocks to new non‐idiosyncratic information that affects both...  View Details
      Keywords: Accounting Quality; Earnings Quality; Stock Returns; Investment Strategy; Accounting; Business Earnings; Quality; Investment Return; Investment; Strategy
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      Chen, Wen, Mozaffar Khan, Leonid Kogan, and George Serafeim. "Cross‐firm Return Predictability and Accounting Quality." Journal of Business Finance & Accounting 48, nos. 1-2 (January–February 2021): 70–101.
      • January 2021
      • Case

      The FIRE Savings Calculator

      By: Michael Parzen and Paul Hamilton
      This case follows Carol Muñoz, a member of the Financial Independence, Retire Early (FIRE) lifestyle movement. At the age of 45, Carol is considering retiring and living off the $1 million she has accumulated. Using Monte Carlo simulation, Carol forecasts the...  View Details
      Keywords: Analysis; Forecasting and Prediction; Financial Strategy; Investment Portfolio; Investment Return; Personal Finance; Saving; Risk and Uncertainty; Diversification; Theory; Personal Development and Career; Financial Services Industry
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      Parzen, Michael, and Paul Hamilton. "The FIRE Savings Calculator." Harvard Business School Case 621-087, January 2021.
      • January 2021
      • Article

      A Model of Relative Thinking

      By: Benjamin Bushong, Matthew Rabin and Joshua Schwartzstein
      Fixed differences loom smaller when compared to large differences. We propose a model of relative thinking where a person weighs a given change along a consumption dimension by less when it is compared to bigger changes along that dimension. In deterministic settings,...  View Details
      Keywords: Relative Thinking; Econometric Models; Behavior; Cognition and Thinking
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      Bushong, Benjamin, Matthew Rabin, and Joshua Schwartzstein. "A Model of Relative Thinking." Review of Economic Studies 88, no. 1 (January 2021): 162–191.
      • December 2020
      • Article

      Monetary Policy and Global Banking

      By: Falk Bräuning and Victoria Ivashina
      When central banks adjust interest rates, the opportunity cost of lending in local currency changes, but—in absence of frictions—there is no spillover effect to lending in other currencies. However, when equity capital is limited, global banks must benchmark domestic...  View Details
      Keywords: Global Banks; Monetary Policy Transmission; Cross-border Lending; Banks and Banking; Financial Markets; Global Range
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      Bräuning, Falk, and Victoria Ivashina. "Monetary Policy and Global Banking." Journal of Finance 75, no. 6 (December 2020): 3055–3095.
      • October 2020
      • Article

      IQ from IP: Simplifying Search in Portfolio Choice

      By: Huaizhi Chen, Lauren Cohen, Umit Gurun, Dong Lou and Christopher J. Malloy
      Using a novel database that tracks web traffic on the SEC’s EDGAR servers between 2004 and 2015, we show that mutual fund managers gather information on a very particular subset of firms and insiders, and their surveillance is very persistent over time. This tracking...  View Details
      Keywords: Tracked Trades; Return Predictability; Institutional Trading; Insider Trading; Institutional Investing; Information; Investment Portfolio; Decisions; Management
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      Chen, Huaizhi, Lauren Cohen, Umit Gurun, Dong Lou, and Christopher J. Malloy. "IQ from IP: Simplifying Search in Portfolio Choice." Journal of Financial Economics 138, no. 1 (October 2020): 118–137. (Winner of the First Prize, Crowell Memorial Award for Best Paper in Quantitative Investments, PanAgora Asset Management, 2019.)
      • 2020
      • Working Paper

      Aggregate and Firm-Level Stock Returns During Pandemics, in Real Time

      By: Laura Alfaro, Anusha Chari, Andrew Greenland and Peter K. Schott
      We show that unexpected changes in the trajectory of COVID-19 infections predict U.S. stock returns, in real time. Parameter estimates indicate that an unanticipated doubling (halving) of projected infections forecasts next-day decreases (increases) in aggregate U.S....  View Details
      Keywords: COVID-19; Stock Returns; Health Pandemics; Stocks; Investment Return; Forecasting and Prediction
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      Alfaro, Laura, Anusha Chari, Andrew Greenland, and Peter K. Schott. "Aggregate and Firm-Level Stock Returns During Pandemics, in Real Time." NBER Working Paper Series, No. 26950, April 2020. (Revised May 2020.)
      • Fall 2019
      • Article

      Endogenous Productivity of Demand-Induced R&D: Evidence from Pharmaceuticals

      By: Kyle Myers and Mark Pauly
      We examine trends in the productivity of the pharmaceutical sector over the past three decades. Motivated by Ricardo’s insight that productivity and rents are endogenous to demand when inputs are scarce, we examine the industry’s aggregate R&D production function....  View Details
      Keywords: Innovation; Productivity; Pharmaceuticals; Innovation and Invention; Performance Productivity; Pharmaceutical Industry
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      Myers, Kyle, and Mark Pauly. "Endogenous Productivity of Demand-Induced R&D: Evidence from Pharmaceuticals." RAND Journal of Economics 50, no. 3 (Fall 2019): 591–614.
      • 2019
      • Working Paper

      Reflexivity in Credit Markets

      By: Robin Greenwood, Samuel G. Hanson and Lawrence J. Jin
      Reflexivity is the idea that investors' biased beliefs affect market outcomes, and that market outcomes in turn affect investors' beliefs. We develop a behavioral model of the credit cycle featuring such a two-way feedback loop. In our model, investors form beliefs...  View Details
      Keywords: Reflexivity; Attitudes; Financial Markets; Forecasting and Prediction; Investment; Credit
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      Greenwood, Robin, Samuel G. Hanson, and Lawrence J. Jin. "Reflexivity in Credit Markets." NBER Working Paper Series, No. 25747, April 2019.
      • March 2019 (Revised May 2019)
      • Case

      Growth Investing at Totem Point

      By: Suraj Srinivasan, Charles C.Y. Wang and Jonah Goldberg
      The case describes the investment of hedge fund, Totem Point Management in Analog Semiconductors (ADI) as a way to discuss forecasting and valuation in growth companies. In June 2016, hedge fund Totem Point invested in ADI at around $55 a share. In general, Totem Point...  View Details
      Keywords: Growth Investing; Investment; Strategy; Forecasting and Prediction; Valuation
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      Srinivasan, Suraj, Charles C.Y. Wang, and Jonah Goldberg. "Growth Investing at Totem Point." Harvard Business School Case 119-091, March 2019. (Revised May 2019.)
      • 2020
      • Working Paper

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

      By: 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; Customer Value and Value Chain; Consumer Behavior; Analytics and Data Science; Mathematical Methods; Retail Industry
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      Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Harvard Business School Working Paper, No. 19-091, February 2019. (Revised May 2020. Accepted at the Journal of Marketing Research.)
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