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- April 2024
- Article
A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification
By: Hsin-Hsiao Scott Wang, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow and Caleb Nelson
Backgrounds: Urinary Tract Dilation (UTD) classification has been designed to be a more objective grading system to evaluate antenatal and post-natal UTD. Due to unclear association between UTD classifications to specific anomalies such as vesico-ureteral reflux (VUR),...
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Wang, Hsin-Hsiao Scott, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow, and Caleb Nelson. "A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification." Journal of Pediatric Urology 20, no. 2 (April 2024): 271–278.
- 2024
- Working Paper
Product Liability Litigation and Innovation: Evidence from Medical Devices
By: Alberto Galasso and Hong Luo
We examine the relationship between product liability litigation and innovation by systematically
combining data on product liability lawsuits with data on new product introductions in a panel dataset of
leading medical device firms. We first document a decline in...
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Keywords:
Lawsuits and Litigation;
Product Development;
Technological Innovation;
Safety;
Governing Rules, Regulations, and Reforms;
Medical Devices and Supplies Industry
Galasso, Alberto, and Hong Luo. "Product Liability Litigation and Innovation: Evidence from Medical Devices." Harvard Business School Working Paper, No. 24-063, March 2024.
- Working Paper
Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application
By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely...
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Keywords:
Peer-to-peer Markets;
Marketplace Matching;
AI and Machine Learning;
Demand and Consumers;
Digital Platforms;
Marketing
Feng, Flora, Charis Li, and Shunyuan Zhang. "Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application." SSRN Working Paper Series, No. 4665286, February 2024.
- November 2023
- Article
Algorithmic Mechanism Design with Investment
By: Mohammad Akbarpour, Scott Duke Kominers, Kevin Michael Li, Shengwu Li and Paul Milgrom
We study the investment incentives created by truthful mechanisms that allocate resources using approximation algorithms. Some approximation algorithms guarantee nearly 100% of the optimal welfare, but have only a zero guarantee when one bidder can invest before...
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Akbarpour, Mohammad, Scott Duke Kominers, Kevin Michael Li, Shengwu Li, and Paul Milgrom. "Algorithmic Mechanism Design with Investment." Econometrica 91, no. 6 (November 2023): 1969–2003.
- 2023
- Article
Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause...
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Srinivas, Suraj, Sebastian Bordt, and Himabindu Lakkaraju. "Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- October, 2023
- Article
Cleaning Up the Great Lakes: Housing Market Impacts of Removing Legacy Pollutants
By: Alecia Cassidy, Robyn C. Meeks and Michale R. Moore
The Great Lakes and their tributaries make up the largest freshwater system on the planet, providing drinking water and recreational value to millions of people. Yet manufacturing plants left a legacy of toxic pollutants in the region, tarnishing it as part of the...
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Keywords:
Valuation Of Environmental Effects;
Housing Demand;
Water Pollution;
Water Quality;
Infrastructure;
Pollution;
Consumer Behavior
Cassidy, Alecia, Robyn C. Meeks, and Michale R. Moore. "Cleaning Up the Great Lakes: Housing Market Impacts of Removing Legacy Pollutants." Journal of Public Economics 226 (October, 2023).
- 2023
- Working Paper
Words Can Hurt: How Political Communication Can Change the Pace of an Epidemic
By: Jessica Gagete-Miranda, Lucas Argentieri Mariani and Paula Rettl
While elite-cue effects on public opinion are well-documented, questions remain as
to when and why voters use elite cues to inform their opinions and behaviors. Using
experimental and observational data from Brazil during the COVID-19 pandemic, we
study how leader...
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Keywords:
Elites;
Public Engagement;
Politics;
Political Affiliation;
Political Campaigns;
Political Influence;
Political Leadership;
Political Economy;
Survey Research;
COVID-19;
COVID-19 Pandemic;
COVID;
Cognitive Psychology;
Cognitive Biases;
Political Elections;
Voting;
Power and Influence;
Identity;
Behavior;
Latin America;
Brazil
Gagete-Miranda, Jessica, Lucas Argentieri Mariani, and Paula Rettl. "Words Can Hurt: How Political Communication Can Change the Pace of an Epidemic." Harvard Business School Working Paper, No. 24-022, October 2023.
- August 2023
- Article
Formal Employment and Organized Crime: Regression Discontinuity Evidence from Colombia
By: Gaurav Khanna, Carlos Medina, Anant Nyshadham, Jorge Tamayo and Nicolas Torres
Safety net programs, common in settings with high informality like Latin America, often use a means test to establish eligibility. We ask: in settings in which organised crime provides lucrative opportunities in the informal market, will discouraging formal employment...
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Khanna, Gaurav, Carlos Medina, Anant Nyshadham, Jorge Tamayo, and Nicolas Torres. "Formal Employment and Organized Crime: Regression Discontinuity Evidence from Colombia." Economic Journal 133 (August 2023): 2427–2448.
- 2023
- Working Paper
How People Use Statistics
By: Pedro Bordalo, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer
We document two new facts about the distributions of answers in famous statistical problems: they are i) multi-modal and ii) unstable with respect to irrelevant changes in the problem. We offer a model in which, when solving a problem, people represent each hypothesis...
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Bordalo, Pedro, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon, and Andrei Shleifer. "How People Use Statistics." NBER Working Paper Series, No. 31631, August 2023.
- 2023
- Working Paper
The Complexity of Economic Decisions
By: Xavier Gabaix and Thomas Graeber
We propose a theory of the complexity of economic decisions. Leveraging a macroeconomic framework of production functions, we conceptualize the mind as a cognitive economy, where a task’s complexity is determined by its composition of cognitive operations. Complexity...
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Gabaix, Xavier, and Thomas Graeber. "The Complexity of Economic Decisions." Harvard Business School Working Paper, No. 24-049, February 2024.
- February 2023
- Article
Disruption and Credit Markets
By: Bo Becker and Victoria Ivashina
We show that over the past half century innovative disruptions were central to understanding corporate defaults. In a given year, industries experiencing abnormally high VC or IPO activity subsequently see higher default rates, higher segment exits by conglomerates,...
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Becker, Bo, and Victoria Ivashina. "Disruption and Credit Markets." Journal of Finance 78, no. 1 (February 2023): 105–139.
- 2024
- Working Paper
Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence
By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
Even if algorithms make better predictions than humans on average, humans may sometimes have private information
which an algorithm does not have access to that can improve performance. How can we help humans effectively use
and adjust recommendations made by...
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Keywords:
Cognitive Biases;
Algorithm Transparency;
Forecasting and Prediction;
Behavior;
AI and Machine Learning;
Analytics and Data Science;
Cognition and Thinking
Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence." Working Paper, February 2024.
- 2022
- Article
The Pricing and Ownership of U.S. Green Bonds
By: Malcolm Baker, Daniel Bergstresser, George Serafeim and Jeffrey Wurgler
We study green bonds, which are bonds whose proceeds are used for environmentally sensitive purposes. After an overview of the U.S. corporate and municipal green bonds markets, we study pricing and ownership patterns using a simple framework that incorporates assets...
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Keywords:
Green Bond;
Pricing;
Climate Finance;
ESG;
SRI;
Sustainable;
Municipal;
Bonds;
Environmental Sustainability;
Financial Markets;
Price;
Ownership;
United States
Baker, Malcolm, Daniel Bergstresser, George Serafeim, and Jeffrey Wurgler. "The Pricing and Ownership of U.S. Green Bonds." Annual Review of Financial Economics 14 (2022): 415–437.
- 2022
- Working Paper
Banking on Transparency for the Poor: Experimental Evidence from India
By: Erica M. Field, Natalia Rigol, Charity M. Troyer Moore, Rohini Pande and Simone G. Schaner
Do information frictions limit the benefits of financial inclusion drives for the rural poor? We evaluate an experimental intervention among recently banked poor Indian women receiving government cash transfers via direct deposit. Treated women were provided automated...
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Field, Erica M., Natalia Rigol, Charity M. Troyer Moore, Rohini Pande, and Simone G. Schaner. "Banking on Transparency for the Poor: Experimental Evidence from India." NBER Working Paper Series, No. 30289, July 2022.
- 2022
- Working Paper
Retail Investors’ Contrarian Behavior Around News, Attention, and the Momentum Effect
By: Cheng (Patrick) Luo, Enrichetta Ravina, Marco Sammon and Luis M. Viceira
Using a large panel of U.S. brokerage accounts trades and positions, we show that a large fraction of retail investors trade as contrarians after large earnings surprises, especially for loser stocks, and that such contrarian trading contributes to post earnings...
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Keywords:
Retail Investors;
Post Earnings Announcement Drift;
Price Momentum;
Behavioral Finance;
Investment;
Demographics
Luo, Cheng (Patrick), Enrichetta Ravina, Marco Sammon, and Luis M. Viceira. "Retail Investors’ Contrarian Behavior Around News, Attention, and the Momentum Effect." Working Paper, June 2022.
- Article
Act Like a Scientist: Great Leaders Challenge Assumptions, Run Experiments, and Follow the Evidence
By: Stefan Thomke and Gary W. Loveman
Though they’ve been warned for decades about the dangers of overrelying on gut instinct and personal experience, managers keep failing to critically examine—much less challenge—the ideas their decisions are based on. To correct this problem they need to think and act...
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Thomke, Stefan, and Gary W. Loveman. "Act Like a Scientist: Great Leaders Challenge Assumptions, Run Experiments, and Follow the Evidence." Harvard Business Review 100, no. 3 (May–June 2022): 120–129.
- 2022
- Working Paper
THEMIS: A Framework for Cost-Benefit Analysis of COVID-19 Non-Pharmaceutical Interventions
By: Dimitris Bertsimas, Michael Lingzhi Li and Saksham Soni
Since December 2019, the world has been ravaged by the COVID-19 pandemic, with over 150 million confirmed cases and 3 million confirmed deaths worldwide. To combat the spread of COVID-19, governments have issued unprecedented non-pharmaceutical interventions (NPIs),...
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Keywords:
COVID-19;
Health Pandemics;
Policy;
Framework;
Cost vs Benefits;
Outcome or Result;
United States;
Germany;
Brazil;
Singapore;
Spain
Bertsimas, Dimitris, Michael Lingzhi Li, and Saksham Soni. "THEMIS: A Framework for Cost-Benefit Analysis of COVID-19 Non-Pharmaceutical Interventions." Working Paper, April 2022.
- January–February 2022
- Article
Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion
By: Ryan Allen and Prithwiraj Choudhury
How does a knowledge worker’s level of domain experience affect their algorithm-augmented work performance? We propose and test theoretical predictions that domain experience has countervailing effects on algorithm-augmented performance: on one hand, domain experience...
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Keywords:
Automation;
Domain Experience;
Algorithmic Aversion;
Experts;
Algorithms;
Machine Learning;
Future Of Work;
Employees;
Experience and Expertise;
Decision Making;
Performance
Allen, Ryan, and Prithwiraj Choudhury. "Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion." Organization Science 33, no. 1 (January–February 2022): 149–169. ("Best PhD Student Paper" at SMS conference 2020.)
- January 10, 2022
- Article
The Secret Ingredient of Thriving Companies? Human Magic
By: Hubert Joly
The traditional corporate approach to motivating people has been a combination of carrots and sticks: a system of financial incentives designed to mobilize everyone around a plan designed by a few smart people at the top. Multiple studies have confirmed that, for any...
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Keywords:
Meaning;
Purpose;
Organizational Culture;
Employees;
Motivation and Incentives;
Performance
Joly, Hubert. "The Secret Ingredient of Thriving Companies? Human Magic." Harvard Business Review (website) (January 10, 2022).
- Article
Complementarity between Audited Financial Reporting and Voluntary Disclosure: The Case of Former Andersen Clients
By: Richard Frankel, Alon Kalay, Gil Sadka and Yuan Zou
Prior literature presents various perspectives on the role of financial reporting. One view is that mandatory periodic reporting disciplines managers and encourages timely voluntary disclosure. We examine this "confirmation hypothesis" using the shock to financial...
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Keywords:
Financial Disclosure;
Mandatory Reporting;
Reliability;
Voluntary Disclosure;
Financial Reporting;
Quality;
Corporate Disclosure
Frankel, Richard, Alon Kalay, Gil Sadka, and Yuan Zou. "Complementarity between Audited Financial Reporting and Voluntary Disclosure: The Case of Former Andersen Clients." Accounting Review 96, no. 6 (November 2021): 215–238.