Publications
Publications
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- All HBS Web
(721)
- Faculty Publications (191)
- March 2024
- Article
Medicare Price Negotiation and Pharmaceutical Innovation Following the Inflation Reduction Act
By: Matthew Vogel, Pragya Kakani, Amitabh Chandra and Rena M. Conti
The Inflation Reduction Act (IRA) requires Medicare to negotiate lower prices for some medicines with high Medicare spending. Using historical data from public and proprietary sources to apply the IRA's negotiation criteria retrospectively, we identify all drugs that... View Details
- 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
- January 2024
- Article
Population Interference in Panel Experiments
By: Kevin Wu Han, Guillaume Basse and Iavor Bojinov
The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit’s outcome, has received considerable attention in standard randomized experiments. The complications produced by population interference in... View Details
- 2023
- Working Paper
Money, Time, and Grant Design
By: Kyle Myers and Wei Yang Tham
The design of research grants has been hypothesized to be a useful tool for
influencing researchers and their science. We test this by conducting two thought
experiments in a nationally representative survey of academic researchers. First,
we offer participants a... View Details
- December 2023
- Teaching Note
Buurtzorg
By: Ethan Bernstein and Tatiana Sandino
Teaching Note for HBS Case No. 122-101. As co-founders of home nursing company Buurtzorg, Jos de Blok and Gonnie Kronenberg prized both self-management and organizational learning. Buurtzorg’s 10,000 nurses across 950 neighborhood nursing teams in the Netherlands were... View Details
- 2025
- Working Paper
Enhancing Treatment Effect Prediction on Privacy-Protected Data: An Honest Post-Processing Approach
By: Ta-Wei Huang and Eva Ascarza
As firms increasingly rely on customer data for personalization, concerns over privacy and regulatory compliance have grown. Local Differential Privacy (LDP) offers strong individual-level protection by injecting noise into data before collection. While... View Details
- 2023
- Article
Balancing Risk and Reward: An Automated Phased Release Strategy
By: Yufan Li, Jialiang Mao and Iavor Bojinov
Phased releases are a common strategy in the technology industry for gradually releasing new products or updates through a sequence of A/B tests in which the number of treated units gradually grows until full deployment or deprecation. Performing phased releases in a... View Details
- 2024
- Working Paper
The Uneven Impact of Generative AI on Entrepreneurial Performance
By: Nicholas G. Otis, Rowan Clarke, Solène Delecourt, David Holtz and Rembrand Koning
Scalable and low-cost AI assistance has the potential to improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it difficult to know whether recent AI advances can help business owners make... View Details
- 2023
- Working Paper
Are Hospital Quality Indicators Causal?
By: Amitabh Chandra, Maurice Dalton and Douglas O. Staiger
Hospitals play a key role in patient outcomes and spending, but efforts to improve their quality are hindered because we do not know whether hospital quality indicators are causal or biased. We evaluate the validity of commonly used quality indicators, such as... View Details
- October 2023
- Article
What Does the Inflation Reduction Act Mean for Patients and Physicians?
By: Amitabh Chandra and Benedic Ippolito
The debate around prescription drug measures in the recently passed U.S. Inflation Reduction Act (IRA), which limit some patients’ out-of-pocket costs, has not fully addressed their effect on physicians and patients via their effect on payers. Reducing patients’ costs... View Details
- July 2023
- Article
Before or After? The Effects of Payment Decision Timing in Pay-What-You-Want Contexts
By: Raghabendra P. KC, Vincent Mak and Elie Ofek
We study how payment decision timing—before versus after product delivery—influences consumer payment under pay-what-you-want pricing. We focus on situations where there is minimal change in consumer uncertainty regarding the product before versus after receiving it.... View Details
- 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
- 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
- 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