Publications
Publications
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- All HBS Web
(944)
- Faculty Publications (245)
- July 2023
- Article
So, Who Likes You? Evidence from a Randomized Field Experiment
By: Ravi Bapna, Edward McFowland III, Probal Mojumder, Jui Ramaprasad and Akhmed Umyarov
With one-third of marriages in the United States beginning online, online dating platforms have become important curators of the modern social fabric. Prior work on online dating has elicited two critical frictions in the heterosexual dating market. Women, governed by... View Details
- June 2023
- Simulation
Artea Dashboard and Targeting Policy Evaluation
By: Ayelet Israeli and Eva Ascarza
Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea... View Details
Keywords: Algorithm Bias; Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; United States
- June 2023
- Article
Do Job Seekers Value Diversity Information? Evidence from a Field Experiment and Human Capital Disclosures
By: Jung Ho Choi, Joseph Pacelli, Kristina M. Rennekamp and Sorabh Tomar
We examine how information about the diversity of a potential employer's workforce affects individuals’ job-seeking behavior. We embed a field experiment in job recommendation emails from a leading career advice agency in the U.S. The experimental treatment involves... View Details
- 2023
- Article
Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators
By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details
- May 2023 (Revised June 2023)
- Case
Novartis (A): Reimagining Medicine
By: Ramon Casadesus-Masanell, Claudio Feser, Karolin Frankenberger and David Redaschi
This case unfolds around the first-ever approved personalized cancer treatment, how Novartis wrapped it into a new business model design, and how Novartis scaled it. Novartis — one of the largest pharmaceutical companies in the world — is, among other ventures,... View Details
- May 2023 (Revised June 2023)
- Supplement
Novartis (B): Reimagining Medicine
By: Ramon Casadesus-Masanell, Claudio Feser, Karolin Frankenberger and David Redaschi
This case unfolds around the first-ever approved personalized cancer treatment, how Novartis wrapped it into a new business model design, and how Novartis scaled it. Novartis — one of the largest pharmaceutical companies in the world — is, among other ventures,... View Details
- May 2023 (Revised June 2023)
- Supplement
Novartis (C): Reimagining Medicine
By: Ramon Casadesus-Masanell, Claudio Feser, Karolin Frankenberger and David Redaschi
This case unfolds around the first-ever approved personalized cancer treatment, how Novartis wrapped it into a new business model design, and how Novartis scaled it. Novartis — one of the largest pharmaceutical companies in the world — is, among other ventures,... View Details
- March–April 2023
- Article
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in... View Details
- 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
- February 2023
- Article
OTC Intermediaries
By: Andrea L. Eisfeldt, Bernard Herskovic, Sriram Rajan and Emil Siriwardane
We study the effect of dealer exit on prices and quantities in a model of an over-the-counter (OTC) market featuring a core-periphery network with bilateral trading costs. The model is calibrated using regulatory data on the entire U.S. credit default swap (CDS) market... View Details
- 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
- September 2022
- Technical Note
Addressing Social Determinants of Health in the American Landscape
By: Susanna Gallani and Jacob Riegler
Social determinants of health (SDOH) have gained significant attention in recent years. A growing body of research shows that a person’s health is influenced by a large number of non-genetic factors, most of which operate outside the realm of health care and are... View Details
- September 2022
- Article
Giving a Buck or Making a Buck? Donations by Pharmaceutical Manufacturers to Independent Patient Assistance Charities
By: Leemore Dafny, Christopher Ody and Teresa Rokos
The federal Anti-Kickback Statute prohibits biopharmaceutical manufacturers from directly covering Medicare enrollees’ out-of-pocket spending for the drugs they manufacture, but manufacturers may donate to independent patient assistance charities and earmark donations... View Details
- September 2022
- Article
The Impact of Financial Assistance Programs on Health Care Utilization: Evidence from Kaiser Permanente
By: Alyce S. Adams, Raymond Kluender, Neale Mahoney, Jinglin Wang, Francis Wong and Wesley Yin
Most hospitals have financial assistance programs for low-income patients. We use administrative data from Kaiser Permanente to study the effects of financial assistance on health care utilization. Using a regression discontinuity design based on an income threshold... View Details
- 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... View Details
- July 2022
- Article
The Passionate Pygmalion Effect: Passionate Employees Attain Better Outcomes in Part Because of More Preferential Treatment by Others
By: Ke Wang, Erica R. Bailey and Jon M. Jachimowicz
Employees are increasingly exhorted to “pursue their passion” at work. Inherent in this call is the belief that passion will produce higher performance because it promotes intrapersonal processes that propel employees forward. Here, we suggest that the pervasiveness of... View Details
- 2022
- Working Paper
Causal Inference During A Pandemic: Evidence on the Effectiveness of Nebulized Ibuprofen as an Unproven Treatment for COVID-19 in Argentina
By: Sebastian Calonico, Rafael Di Tella and Juan Cruz Lopez Del Valle
Many medical decisions during the pandemic were made without the support of causal evidence obtained in clinical trials. We study the case of nebulized ibuprofen (NaIHS), a drug that was extensively used on COVID-19 patients in Argentina amidst wild claims about its... View Details
- Article
How Much Should We Trust Staggered Difference-In-Differences Estimates?
By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
We explain when and how staggered difference-in-differences regression estimators, commonly applied to assess the impact of policy changes, are biased. These biases are likely to be relevant for a large portion of research settings in finance, accounting, and law that... View Details
- 2022
- Working Paper
A Linear Panel Model with Heterogeneous Coefficients and Variation in Exposure
By: Jesse M. Shapiro and Liyang Sun
Linear panel models featuring unit and time fixed effects appear in many areas of empirical economics. An active literature studies the interpretation of the ordinary least squares estimator of the model, commonly called the two-way fixed effects (TWFE) estimator, in... View Details
- April–June 2022
- Other Article
Commentary on 'Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters'
There has been a substantial discussion in various methodological and applied literatures around causal inference; especially in the use of machine learning and statistical models to understand heterogeneity in treatment effects and to make optimal decision... View Details