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- Faculty Publications (187)
- 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; Jensen Prize, First Place, June 2023.)
- 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 March 2024)
- 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 March 2024.)
- 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.
- 2022
- Working Paper
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Working Paper, March 2022.
- March 2022
- Article
Where to Locate COVID-19 Mass Vaccination Facilities?
By: Dimitris Bertsimas, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li and Alessandro Previero
The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new... View Details
Keywords: Vaccines; COVID-19; Health Care and Treatment; Health Pandemics; Performance Effectiveness; Analytics and Data Science; Mathematical Methods
Bertsimas, Dimitris, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li, and Alessandro Previero. "Where to Locate COVID-19 Mass Vaccination Facilities?" Naval Research Logistics Quarterly 69, no. 2 (March 2022): 179–200.
- 24 Feb 2022
- Other Presentation
The Fearless ICU
By: Amy C. Edmondson
The last 24 months have pushed ICU teams around the world to their limits. As we move forward, we need to heal and rebuild our critical care teams. Healthcare more than ever will require ICU teams to perform at the highest levels and to continuously innovate to deliver... View Details
Keywords: Psychological Safety; Teams; Critical Care; Health Care and Treatment; Groups and Teams; Performance Effectiveness
"The Fearless ICU." Critical Matters (podcast), Sound Physicians, February 24, 2022.
- February 2022
- Case
Cleveland Clinic Abu Dhabi
By: Linda A. Hill and Emily Tedards
In 2006, the Cleveland Clinic and Mubadala Investment Company partnered with a bold ambition to deliver world class healthcare in the United Arab Emirates. In 2015, after nearly a decade of planning and construction, Cleveland Clinic Abu Dhabi opened its doors. By... View Details
Keywords: Organizational Behavior; Culture; Alignment; Organizational Effectiveness; Purpose; Impact; Leadership Development; Diversity; Collaboration; Co-creation; Learning Organizations; Empowerment; Teams; Team Dynamics; Teamwork; Team Effectiveness; Trust; Talent; Talent Development And Retention; Psychological Safety; Organizational Evolution; Coaching; Board; Analytics; Innovation; Data; Data Visualization; Digital Technology; Digital; Customer Experience; Experimentation; Change Management; Data-driven Decision-making; Debates; Ecosystem; Partnership; Telemedicine; Sustainability; Global Organizations; Local; Hospital; Healthcare; United Arab Emirates; Health Care and Treatment; Partners and Partnerships; Globalization; Quality; Organizational Culture; Mission and Purpose; Innovation and Management; Information Technology; Joint Ventures; Leadership; Performance Effectiveness; Abu Dhabi; United Arab Emirates
Hill, Linda A., and Emily Tedards. "Cleveland Clinic Abu Dhabi." Harvard Business School Case 422-058, February 2022.
- February 2022
- Case
Cleveland Clinic Abu Dhabi (Abridged)
By: Linda A. Hill and Emily Tedards
In 2006, the Cleveland Clinic and Mubadala Investment Company partnered with a bold ambition to deliver world class healthcare in the United Arab Emirates. In 2015, after nearly a decade of planning and construction, Cleveland Clinic Abu Dhabi opened its doors. By... View Details
Keywords: Organization Behavior; Culture; Alignment; Organizational Effectiveness; Purpose; Impact; Leadership Development; Diversity; Collaboration; Co-creation; Learning Organizations; Empowerment; Teams; Team Dynamics; Teamwork; Team Effectiveness; Trust; Talent; Talent Development And Retention; Psychological Safety; Organizational Evolution; Coaching; Board; Analytics; Innovation; Data; Data Visualization; Digital Technology; Digital; Customer Experience; Experimentation; Change Management; Data-driven Decision-making; Debates; Ecosystem; Partnership; Telemedicine; Sustainability; Global Organizations; Local; Hospital; Healthcare; United Arab Emirates; Health Care and Treatment; Partners and Partnerships; Globalization; Quality; Organizational Culture; Mission and Purpose; Innovation and Management; Information Technology; Joint Ventures; Leadership; Performance Effectiveness; Abu Dhabi; United Arab Emirates
Hill, Linda A., and Emily Tedards. "Cleveland Clinic Abu Dhabi (Abridged)." Harvard Business School Case 422-056, February 2022.
- February 2022
- Case
Cleveland Clinic Abu Dhabi: Leading Through the Fog of the COVID-19 Pandemic
By: Linda A. Hill and Emily Tedards
As COVID-19 began to take lives, destroy healthcare systems, and shut down economies across the globe, Dr. Rakesh Suri, Chief Executive Officer of Cleveland Clinic Abu Dhabi, and his executive team adapted their leadership to instill the new levels of agility and... View Details
Keywords: Organizational Behavior; Culture; Organizational Culture; Organizational Adaptation; Organizational Effectiveness; Alignment; Leadership; Innovation; Diversity; Collaboration; Co-creation; Learning Organizations; Empowerment; Teamwork; Ecosystem; Agility; Partnerships; Data-driven Decision-making; Operating Model; Risk Management; Virtual Work; Team Dynamics; Telemedicine; Metrics; Globalization; Pandemic; COVID-19; Hospital; Healthcare; United Arab Emirates; Middle East; Health Care and Treatment; Health Pandemics; Organizational Change and Adaptation; Crisis Management; Leading Change; Leadership Style; Digital Transformation; United Arab Emirates; Middle East
Hill, Linda A., and Emily Tedards. "Cleveland Clinic Abu Dhabi: Leading Through the Fog of the COVID-19 Pandemic." Harvard Business School Case 422-057, February 2022.
- February 2022
- Case
Leading The UK Vaccine Task Force
By: Amy C. Edmondson and Claudia Pienica
This case describes the first six months of the UK Vaccine Taskforce, under the leadership of Kate Bingham. With a career spent in the private sector as a biotech investor, Bingham’s appointment within the government was considered unusual. The overarching brief given... View Details
Keywords: COVID-19; Vaccine; Government; Health Pandemics; Health Care and Treatment; Science; Innovation and Invention; Groups and Teams; Leadership; Decision Making; Government and Politics; Health; Innovation and Management; Governance; Change; Government Administration; Health Industry; Financial Services Industry; Public Administration Industry; Europe; United Kingdom
Edmondson, Amy C., and Claudia Pienica. "Leading The UK Vaccine Task Force." Harvard Business School Case 622-079, February 2022.
- 2022
- Article
Alleviating Time Poverty Among the Working Poor: A Pre-Registered Longitudinal Field Experiment
By: A.V. Whillans and Colin West
Poverty entails more than a scarcity of material resources—it also involves a shortage of time. To examine the causal benefits of reducing time poverty, we conducted a longitudinal feld experiment over six consecutive weeks in an urban slum in Kenya with a sample of... View Details
Keywords: Time; Subjective Well Being; Administrative Costs; Friction; Poverty; Well-being; Money; Perception; Kenya
Whillans, A.V., and Colin West. "Alleviating Time Poverty Among the Working Poor: A Pre-Registered Longitudinal Field Experiment." Art. 719. Scientific Reports 12 (2022).
- Article
A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects
By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public... View Details
Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods
McFowland III, Edward, Sandeep Gangarapu, Ravi Bapna, and Tianshu Sun. "A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects." MIS Quarterly 45, no. 4 (December 2021): 1807–1832.
- Article
Social Technology: An Interdisciplinary Approach to Improving Care for Older Adults
By: Arthur Kleinman, Hongtu Chen, Sue E. Levkoff, Ann Forsyth, David E. Bloom, Winnie Yip, Tarun Khanna, Conor J. Walsh, David Perry, Ellen W. Seely, Anne S. Kleinman, Yan Zhang, Yuan Wang, Jun Jing, Tianshu Pan, Ning An, Zhenggang Bai, Jiexiu Wang, Qing Liu and Fawwaz Habbal
Population aging is a defining demographic reality of our era. It is associated with an increase in the societal burden of delivering care to older adults with chronic conditions or frailty. How to integrate global population aging and technology development to help... View Details
Keywords: Health Care and Treatment; Age; Service Delivery; Information Technology; Collaborative Innovation and Invention
Kleinman, Arthur, Hongtu Chen, Sue E. Levkoff, Ann Forsyth, David E. Bloom, Winnie Yip, Tarun Khanna, Conor J. Walsh, David Perry, Ellen W. Seely, Anne S. Kleinman, Yan Zhang, Yuan Wang, Jun Jing, Tianshu Pan, Ning An, Zhenggang Bai, Jiexiu Wang, Qing Liu, and Fawwaz Habbal. "Social Technology: An Interdisciplinary Approach to Improving Care for Older Adults." Art. 729149. Frontiers in Public Health 9 (2021).
- December 2021
- Article
Trade Policy Uncertainty and Stock Returns
By: Marcelo Bianconi, Federico Esposito and Marco Sammon
A recent literature has documented large real effects of trade policy uncertainty (TPU) on trade, employment, and investment, but there is little evidence that investors are compensated for bearing such risk. To quantify the risk premium associated with TPU, we exploit... View Details
Keywords: Trade Policy; Uncertainty; Stock Returns; Risk Premium; Tariff Rates; Portfolio Analysis; Trade; Policy; Risk and Uncertainty; Stocks; Investment Return
Bianconi, Marcelo, Federico Esposito, and Marco Sammon. "Trade Policy Uncertainty and Stock Returns." Art. 102492. Journal of International Money and Finance 119 (December 2021).
- November 2021
- Article
Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective
By: Iavor Bojinov, Ashesh Rambachan and Neil Shephard
In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative... View Details
Keywords: Panel Data; Dynamic Causal Effects; Potential Outcomes; Finite Population; Nonparametric; Mathematical Methods
Bojinov, Iavor, Ashesh Rambachan, and Neil Shephard. "Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective." Quantitative Economics 12, no. 4 (November 2021): 1171–1196.
- 2021
- Article
Don't Get It or Don't Spread It: Comparing Self-interested versus Prosocial Motivations for COVID-19 Prevention Behaviors
By: Jillian J. Jordan, Erez Yoeli and David Rand
COVID-19 prevention behaviors may be seen as self-interested or prosocial. Using American samples from MTurk and Prolific (total n = 6,850), we investigated which framing is more effective—and motivation is stronger—for fostering prevention behavior intentions. We... View Details
Keywords: COVID-19; Prevention; Prosocial Motivation; Health Pandemics; Behavior; Motivation and Incentives
Jordan, Jillian J., Erez Yoeli, and David Rand. "Don't Get It or Don't Spread It: Comparing Self-interested versus Prosocial Motivations for COVID-19 Prevention Behaviors." Art. 20222. Scientific Reports 11 (2021).
- 2021
- Working Paper
The Luck of the Draw: The Causal Effect of Physicians on Birth Outcomes
By: Arlen Guarin, Christian Posso, Estefania Saravia and Jorge Tamayo
Identifying the effect of physicians’ skills on health outcomes is a challenging task due to the nonrandom sorting between physicians and hospitals. We overcome this challenge by exploiting a Colombian government program that randomly assigned 2,126 physicians to 618... View Details
Keywords: Physicians' Health Skills; Health Birth Outcomes; Birthing Outcomes; Experimental Evidence; Health Care and Treatment; Competency and Skills; Outcome or Result; Health Industry; Colombia
Guarin, Arlen, Christian Posso, Estefania Saravia, and Jorge Tamayo. "The Luck of the Draw: The Causal Effect of Physicians on Birth Outcomes." Harvard Business School Working Paper, No. 22-015, February 2021. (R&R American Economic Journal.)
- Article
Supporting Value-Based Health Care—Aligning Financial and Legal Accountability
By: Mark M. Zaki, Anupam B. Jena and Amitabh Chandra
U.S. health care payment and delivery-system reforms have focused on improving care by making organizations accountable for outcomes, quality, and costs. Payers have supported the implementation of accountable care organizations (ACOs), bundled-payment models, and... View Details
Zaki, Mark M., Anupam B. Jena, and Amitabh Chandra. "Supporting Value-Based Health Care—Aligning Financial and Legal Accountability." New England Journal of Medicine 385, no. 11 (September 9, 2021): 965–967.