Filter Results
:
(221)
Show Results For
-
All HBS Web
(844)
- Faculty Publications (221)
Show Results For
-
All HBS Web
(844)
- Faculty Publications (221)
Page 1 of
221
Results
→
- 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
Jakubowski, Benjamin, Siram Somanchi, Edward McFowland III, and Daniel B. Neill. "Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators." Journal of Machine Learning Research 24, no. 133 (2023): 1–57.
- 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
Keywords:
OTC Markets;
Intermediaries;
Dealers;
Credit Default Swaps;
Risk Sharing;
Financial Markets;
Networks;
Price;
Risk and Uncertainty
Eisfeldt, Andrea L., Bernard Herskovic, Sriram Rajan, and Emil Siriwardane. "OTC Intermediaries." Review of Financial Studies 36, no. 2 (February 2023): 615–677.
- 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.
- 2023
- Working Paper
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to...
View Details
Keywords:
Long-run Targeting;
Heterogeneous Treatment Effect;
Statistical Surrogacy;
Customer Churn;
Field Experiments;
Consumer Behavior;
Customer Focus and Relationships;
AI and Machine Learning;
Marketing
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Harvard Business School Working Paper, No. 23-023, October 2022. (Revised April 2023.)
- 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
Keywords:
Socioeconomic Determinants Of Health;
Social Determinants Of Health;
Population Health;
Health;
Health Care and Treatment;
Social Issues;
Health Industry;
Insurance Industry;
Medical Devices and Supplies Industry;
United States
Gallani, Susanna, and Jacob Riegler. "Addressing Social Determinants of Health in the American Landscape." Harvard Business School Technical Note 123-023, September 2022.
- 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
Keywords:
Cost Sharing;
Prescription Drugs;
Drug Spending;
Medicare;
Dual Eligibility;
Cost;
Health Care and Treatment;
Philanthropy and Charitable Giving;
Pharmaceutical Industry
Dafny, Leemore, Christopher Ody, and Teresa Rokos. "Giving a Buck or Making a Buck? Donations by Pharmaceutical Manufacturers to Independent Patient Assistance Charities." Health Affairs 41, no. 9 (September 2022).
- 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
Keywords:
Healthcare;
Utilization;
Financial Assistance;
Health Care and Treatment;
Social Issues;
Poverty;
Health Industry
Adams, Alyce S., Raymond Kluender, Neale Mahoney, Jinglin Wang, Francis Wong, and Wesley Yin. "The Impact of Financial Assistance Programs on Health Care Utilization: Evidence from Kaiser Permanente." American Economic Review: Insights 4, no. 3 (September 2022): 389–407.
- 2022
- Working Paper
Can Finance Save the World? Measurement and Effects of Coal Divestment Policies by Banks
By: Daniel Green and Boris Vallée
We study whether divestment policies are an effective tool to address climate change, using coal lending bans by banks around the world as a laboratory. In contrast to theories arguing divestment is ineffective because capital is highly subsitutable, we find large...
View Details
Keywords:
Coal Power;
Climate Change;
Investment;
Environmental Sustainability;
Policy;
Financing and Loans;
Energy Industry;
Banking Industry
Green, Daniel, and Boris Vallée. "Can Finance Save the World? Measurement and Effects of Coal Divestment Policies by Banks." Working Paper, August 2022.
- 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
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.
- 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
Keywords:
Passion;
Self-fufilling Prophecy;
Lay Beliefs;
Interpersonal Processes;
Employees;
Performance;
Attitudes;
Organizational Culture;
Social Psychology
Wang, Ke, Erica R. Bailey, and Jon M. Jachimowicz. "The Passionate Pygmalion Effect: Passionate Employees Attain Better Outcomes in Part Because of More Preferential Treatment by Others." Journal of Experimental Social Psychology 101 (July 2022).
- 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
Keywords:
COVID-19;
Drug Treatment;
Health Pandemics;
Health Care and Treatment;
Decision Making;
Outcome or Result;
Argentina
Calonico, Sebastian, Rafael Di Tella, and Juan Cruz Lopez Del Valle. "Causal Inference During A Pandemic: Evidence on the Effectiveness of Nebulized Ibuprofen as an Unproven Treatment for COVID-19 in Argentina." NBER Working Paper Series, No. 30084, May 2022.
- 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
Keywords:
Difference In Differences;
Staggered Difference-in-differences Designs;
Generalized Difference-in-differences;
Dynamic Treatment Effects;
Mathematical Methods
Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" Journal of Financial Economics 144, no. 2 (May 2022): 370–395. (Editor's Choice, May 2022.)
- 2022
- Working Paper
Reputation Burning: Analyzing the Impact of Brand Sponsorship on Social Influencers
By: Magie Cheng and Shunyuan Zhang
The growth of the influencer marketing industry warrants an empirical examination of the effect of posting sponsored videos on an influencer’s reputation. We collect a novel dataset of user-generated YouTube videos created by prominent English-speaking influencers in...
View Details
Keywords:
Influencer Marketing;
Social Influencers;
Brand;
Sponsorship;
Video Analytics;
Marketing;
Brands and Branding;
Media;
Reputation
Cheng, Magie, and Shunyuan Zhang. "Reputation Burning: Analyzing the Impact of Brand Sponsorship on Social Influencers." Harvard Business School Working Paper, No. 22-067, April 2022.
- April 18, 2022
- Article
Will mRNA Technology Companies Spawn Innovation Ecosystems?
By: Christoph Grimpe, Timo Minssen, W. Nicholson Price, II and Ariel Dora Stern
The mRNA technologies that helped rapidly create effective COVID-19 vaccines could become technology platform businesses, which has tremendous implications for players in the world of drug development. These platforms could attract other companies interested in...
View Details
Keywords:
Health Care;
Digital Health;
Technology;
Innovation;
Health Care and Treatment;
Technological Innovation;
Digital Transformation;
Health Industry;
United States
Grimpe, Christoph, Timo Minssen, W. Nicholson Price, II, and Ariel Dora Stern. "Will mRNA Technology Companies Spawn Innovation Ecosystems?" Harvard Business Review (website) (April 18, 2022).
- 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
Shapiro, Jesse M., and Liyang Sun. "A Linear Panel Model with Heterogeneous Coefficients and Variation in Exposure." NBER Working Paper Series, No. 29976, April 2022.
- 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
Keywords:
Causal Inference;
Treatment Effect Estimation;
Treatment Assignment Policy;
Human-in-the-loop;
Decision Making;
Fairness
McFowland III, Edward. "Commentary on 'Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters'." INFORMS Journal on Data Science 1, no. 1 (April–June 2022): 21–22.
- March 2022 (Revised August 2022)
- Case
DaVita Responds to COVID
By: Susanna Gallani and David Lane
Early in August 2021, DaVita CEO Javier Rodriguez was assessing the ongoing impact of the COVID-19 pandemic on his firm, which provided life-sustaining kidney dialysis to roughly 240,000 people. Effective infection control practices and information sharing had ensured...
View Details
Keywords:
COVID-19 Pandemic;
Change Management;
Communication;
Talent and Talent Management;
Fairness;
Values and Beliefs;
Corporate Accountability;
Health Care and Treatment;
Health Pandemics;
Human Resources;
Employee Relationship Management;
Retention;
Wages;
Working Conditions;
Leadership Style;
Crisis Management;
Organizational Culture;
Health Industry;
United States
Gallani, Susanna, and David Lane. "DaVita Responds to COVID." Harvard Business School Case 122-007, March 2022. (Revised August 2022.)
- March 2022
- Article
Estimating the Effectiveness of Permanent Price Reductions for Competing Products Using Multivariate Bayesian Structural Time Series Models
By: Fiammetta Menchetti and Iavor Bojinov
Researchers regularly use synthetic control methods for estimating causal effects when a sub-set of units receive a single persistent treatment, and the rest are unaffected by the change. In many applications, however, units not assigned to treatment are nevertheless...
View Details
Keywords:
Causal Inference;
Partial Interference;
Synthetic Controls;
Bayesian Structural Time Series;
Mathematical Methods
Menchetti, Fiammetta, and Iavor Bojinov. "Estimating the Effectiveness of Permanent Price Reductions for Competing Products Using Multivariate Bayesian Structural Time Series Models." Annals of Applied Statistics 16, no. 1 (March 2022): 414–435.
- Article
Health App Policy: International Comparison of Nine Countries' Approaches
By: Anna Essén, Ariel Dora Stern, Christoffer Bjerre Haase, Josip Car, Felix Greaves, Dragana Paparova, Steven Vandeput, Rik Wehrens and David W. Bates
An abundant and growing supply of digital health applications (apps) exists in the commercial tech-sector, which can be bewildering for clinicians, patients, and payers. A growing challenge for the health care system is therefore to facilitate the identification of...
View Details
Keywords:
Digital Health;
Apps;
Health Care and Treatment;
Internet and the Web;
Policy;
Global Range;
Applications and Software
Essén, Anna, Ariel Dora Stern, Christoffer Bjerre Haase, Josip Car, Felix Greaves, Dragana Paparova, Steven Vandeput, Rik Wehrens, and David W. Bates. "Health App Policy: International Comparison of Nine Countries' Approaches." npj Digital Medicine 5, no. 31 (2022).