Filter Results
:
(239)
Show Results For
-
All HBS Web
(816)
- Faculty Publications (239)
Show Results For
-
All HBS Web
(816)
- Faculty Publications (239)
Page 1 of
239
Results
→
- March–April 2024
- Article
How Companies Should Weigh in on a Controversy: A Better Approach to Stakeholder Management
By: David M. Bersoff, Sandra J. Sucher and Peter Tufano
Executives need guidance about managing their organizations’ engagement with societal issues—including hot-button topics such as gender, climate, and racial discrimination. Success in this realm does not mean avoiding public controversy or achieving unanimous support...
View Details
Keywords:
Values and Beliefs;
Social Issues;
Business and Stakeholder Relations;
Judgments;
Management Practices and Processes
Bersoff, David M., Sandra J. Sucher, and Peter Tufano. "How Companies Should Weigh in on a Controversy: A Better Approach to Stakeholder Management." Harvard Business Review 102, no. 2 (March–April 2024): 108–119.
- 2023
- Working Paper
'De Gustibus' and Disputes about Reference Dependence
By: Thomas Graeber, Pol Campos-Mercade, Lorenz Goette, Alexandre Kellogg and Charles Sprenger
Existing tests of reference-dependent preferences assume universal loss aversion. This paper examines the implications of heterogeneity in gain-loss attitudes for such tests. In experiments on labor supply and exchange behavior we measure gain-loss attitudes and then...
View Details
Graeber, Thomas, Pol Campos-Mercade, Lorenz Goette, Alexandre Kellogg, and Charles Sprenger. "'De Gustibus' and Disputes about Reference Dependence." Harvard Business School Working Paper, No. 24-046, January 2024.
- 2023
- Working Paper
Estimating Productivity in the Presence of Spillovers: Firm-Level Evidence from the U.S. Production Network
By: Ebehi Iyoha
This paper examines the extent to which productivity gains are transmitted across U.S. firms through buyer-supplier relationships. Many empirical studies measure firm-to-firm spillovers using firm-level productivity estimates derived from control function approaches....
View Details
Iyoha, Ebehi. "Estimating Productivity in the Presence of Spillovers: Firm-Level Evidence from the U.S. Production Network." Harvard Business School Working Paper, No. 24-033, December 2023. (Winner of the Young Economists' Essay Award at the 2021 Annual Conference of the European Association for Research in Industrial Economics (EARIE))
- December 12, 2023
- Article
Prices for Common Services at Quaternary vs Nonquaternary Hospitals
By: Brandon W. Yan, Maximilian J. Pany and Leemore S. Dafny
Using commercial health insurance claims data from 2017-2019, we assessed whether quaternary hospitals charged higher prices for common, unspecialized services also offered by nonquaternary hospitals. We found quaternary-hospital price premiums of 8.2 percent, on...
View Details
Yan, Brandon W., Maximilian J. Pany, and Leemore S. Dafny. "Prices for Common Services at Quaternary vs Nonquaternary Hospitals." JAMA, the Journal of the American Medical Association 330, no. 22 (December 12, 2023): 2211–2213.
- November 2023
- Article
Effects of Remote Patient Monitoring Use on Care Outcomes Among Medicare Patients with Hypertension
By: Mitchell Tang, Carter Nakamoto, Ariel Dora Stern, Jose Zubizarreta, Felippe Marcondes, Lori Uscher-Pines, Lee Schwamm and Ateev Mehrotra
Background: Remote patient monitoring (RPM) is a promising tool for improving chronic disease management. Use of RPM for hypertension monitoring is growing rapidly, raising concerns about increased spending. However, the effects of RPM are still...
View Details
Tang, Mitchell, Carter Nakamoto, Ariel Dora Stern, Jose Zubizarreta, Felippe Marcondes, Lori Uscher-Pines, Lee Schwamm, and Ateev Mehrotra. "Effects of Remote Patient Monitoring Use on Care Outcomes Among Medicare Patients with Hypertension." Annals of Internal Medicine 176, no. 11 (November 2023): 1465–1475.
- 2023
- Article
Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten
By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an...
View Details
Keywords:
Analytics and Data Science;
AI and Machine Learning;
Decision Making;
Governing Rules, Regulations, and Reforms
Lakkaraju, Himabindu, Satyapriya Krishna, and Jiaqi Ma. "Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 17808–17826.
- July 2023
- Article
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted...
View Details
Bojinov, Iavor I., David Simchi-Levi, and Jinglong Zhao. "Design and Analysis of Switchback Experiments." Management Science 69, no. 7 (July 2023): 3759–3777.
- 2023
- Working Paper
The Market for Sharing Interest Rate Risk: Quantities and Asset Prices
By: Umang Khetan, Jane Li, Ioana Neamtu and Ishita Sen
We study the extent of interest rate risk sharing across the financial system using granular positions and transactions data in interest rate swaps. We show that pension and insurance (PF&I) sector emerges as a natural counterparty to banks and corporations: overall,...
View Details
Keywords:
Interest Rates;
Investment Funds;
Banks and Banking;
Insurance;
Investment Banking;
Risk and Uncertainty
Khetan, Umang, Jane Li, Ioana Neamtu, and Ishita Sen. "The Market for Sharing Interest Rate Risk: Quantities and Asset Prices." Harvard Business School Working Paper, No. 24-052, February 2024.
- June 2023
- Case
Investing in the Climate Transition at Neuberger Berman
By: George Serafeim and Benjamin Maletta
By mid-2023, Neuberger Berman (NB), an active asset manager, had grown its assets under management to about half a trillion dollars and took pride in its client centricity and innovative spirit. Responding to client demand for investment products that integrated...
View Details
Keywords:
Carbon Emissions;
Sustainability;
Decarbonization;
Performance;
Risk Assessment;
Opportunities;
Environmental Sustainability;
Carbon Footprint;
Business Analysis;
Investing;
Regulation;
Asset Management;
Investment Strategy;
Climate Change;
Transition;
Analysis;
Product Positioning;
Strategy;
Investment Portfolio;
Financial Services Industry;
Energy Industry
- June 2023
- Article
Regulatory Limits to Risk Management
By: Ishita Sen
Variable annuities, the largest liability of U.S. life insurers, are investment products containing long-dated minimum return guarantees. I show that guarantees with similar economic risks are treated differently by regulation and these differences impact insurers’...
View Details
Keywords:
Interest Rate Risk;
Variable Annuities;
Capital Regulation;
Reinsurance;
Derivatives;
Risk Management;
Interest Rates;
Governing Rules, Regulations, and Reforms
Sen, Ishita. "Regulatory Limits to Risk Management." Review of Financial Studies 36, no. 6 (June 2023): 2175–2223.
- 2023
- Working Paper
The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities
By: David S. Scharfstein and Sergey Chernenko
We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement bias in...
View Details
Keywords:
Racial Disparity;
Paycheck Protection Program;
Measurement Error;
AI and Machine Learning;
Race;
Measurement and Metrics;
Equality and Inequality;
Prejudice and Bias;
Forecasting and Prediction;
Outcome or Result
Scharfstein, David S., and Sergey Chernenko. "The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities." Working Paper, April 2023.
- 2023
- Working Paper
A Welfare Analysis of Gambling in Video Games
By: Tomomichi Amano and Andrey Simonov
In 2020, gamers worldwide spent more than $15 billion on loot boxes, a lottery of virtual items built into video games. Loot boxes are contentious, as regulators worry that they constitute gambling. In contrast, video game companies maintain that loot boxes are...
View Details
Keywords:
Consumer Behavior;
Policy;
Games, Gaming, and Gambling;
Product Design;
Video Game Industry
Amano, Tomomichi, and Andrey Simonov. "A Welfare Analysis of Gambling in Video Games." Harvard Business School Working Paper, No. 23-052, February 2023.
- 2023
- Working Paper
Distributionally Robust Causal Inference with Observational Data
By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li
We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first...
View Details
Bertsimas, Dimitris, Kosuke Imai, and Michael Lingzhi Li. "Distributionally Robust Causal Inference with Observational Data." Working Paper, February 2023.
- January 23, 2023
- Article
Digital Public Health Interventions at Scale: The Impact of Social Media Advertising on Beliefs and Outcomes Related to COVID Vaccines
By: Susan Athey, Kristen Grabarz, Michael Luca and Nils Wernerfelt
Public health organizations increasingly use social media advertising campaigns in pursuit of public health goals. In this paper, we evaluate the impact of about $40 million of social media advertisements that were run and experimentally tested on Facebook and...
View Details
Keywords:
COVID-19 Pandemic;
Public Health;
Vaccines;
Social Media;
Advertising;
Power and Influence;
Health Care and Treatment
Athey, Susan, Kristen Grabarz, Michael Luca, and Nils Wernerfelt. "Digital Public Health Interventions at Scale: The Impact of Social Media Advertising on Beliefs and Outcomes Related to COVID Vaccines." e2208110120. Proceedings of the National Academy of Sciences 120, no. 5 (January 23, 2023).
- 2023
- Article
Experimental Evaluation of Individualized Treatment Rules
By: Kosuke Imai and Michael Lingzhi Li
The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a...
View Details
Keywords:
Causal Inference;
Heterogeneous Treatment Effects;
Precision Medicine;
Uplift Modeling;
Analytics and Data Science;
AI and Machine Learning
Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
- 2022
- Book
Private Equity
By: Paul A. Gompers and Steven N. Kaplan
This Advanced Introduction provides an illustrative guide to private equity, integrating insights from academic research with examples to derive practical recommendations. Paul Gompers and Steven Kaplan begin by reviewing the history of private equity then exploring...
View Details
Gompers, Paul A., and Steven N. Kaplan. Private Equity. Elgar Advanced Introductions. London: Edward Elgar Publishing, 2022.
- 2022
- Article
The Ordinary Concept of a Meaningful Life: The Role of Subjective and Objective Factors in Third-Person Attributions of Meaning
By: Michael Prinzing, Julian De Freitas and Barbara L. Fredrickson
The desire for a meaningful life is ubiquitous, yet the ordinary concept of a meaningful life is poorly understood. Across six experiments (total N = 2,539), we investigated whether third-person attributions of meaning depend on the psychological states an agent...
View Details
Keywords:
Experimental Philosophy;
Folk Theories;
Meaning In Life;
Moral Psychology;
Positive Psychology;
Moral Sensibility;
Satisfaction
Prinzing, Michael, Julian De Freitas, and Barbara L. Fredrickson. "The Ordinary Concept of a Meaningful Life: The Role of Subjective and Objective Factors in Third-Person Attributions of Meaning." Journal of Positive Psychology 17, no. 5 (2022): 639–654.
- 2022
- Article
Data Poisoning Attacks on Off-Policy Evaluation Methods
By: Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expensive. However, the extent to which such methods can be trusted under adversarial threats...
View Details
Lobo, Elita, Harvineet Singh, Marek Petrik, Cynthia Rudin, and Himabindu Lakkaraju. "Data Poisoning Attacks on Off-Policy Evaluation Methods." Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI) 38th (2022): 1264–1274.
- 2022
- Working Paper
Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments
By: Fanglin Chen, Xiao Liu, Davide Proserpio and Isamar Troncoso
We propose a method, Product2Vec, based on representation learning, that can automatically learn latent product attributes that drive consumer choices, to study product-level competition when the number of products is large. We demonstrate Product2Vec’s...
View Details
Chen, Fanglin, Xiao Liu, Davide Proserpio, and Isamar Troncoso. "Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments." NYU Stern School of Business Research Paper Series, July 2022.
- 2022
- Conference Presentation
Towards the Unification and Robustness of Post hoc Explanation Methods
By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two...
View Details
Keywords:
AI and Machine Learning
Agarwal, Sushant, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, and Himabindu Lakkaraju. "Towards the Unification and Robustness of Post hoc Explanation Methods." Paper presented at the 3rd Symposium on Foundations of Responsible Computing (FORC), 2022.