Publications
Publications
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- All HBS Web
(299)
- Faculty Publications (111)
- 2022
- Working Paper
Coordination and Incumbency Advantage in Multi-Party Systems: Evidence from French Elections
By: Kevin Dano, Francesco Ferlenga, Vincenzo Galasso, Caroline Le Pennec and Vincent Pons
In theory, free and fair elections can improve the selection of politicians and incentivize them to exert effort. In practice, incumbency advantage and coordination issues may lead to the (re)election of bad politicians. We ask whether these two forces compound each... View Details
- September 2022
- Article
Loneliness Versus Distress: A Comparison of Emotion Regulation Profiles
By: Alyssa J. Tan, Vincent Mancini, James J. Gross, Amit Goldenberg, Johanna C. Badcock, Michelle H. Lim, Rodrigo Becerra, Ben Jackson and David A. Preece
Loneliness, a negative emotion stemming from the perception of unmet social needs, is a major public health concern. Current interventions often target social domains but produce small effects and are not as effective as established emotion regulation (ER)-based... View Details
Keywords: Emotions
- 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
- Article
Nonparametric Subset Scanning for Detection of Heteroscedasticity
By: Charles R. Doss and Edward McFowland III
We propose Heteroscedastic Subset Scan (HSS), a novel method for identifying covariates that are responsible for violations of the homoscedasticity assumption in regression settings. Viewing the problem as one of anomalous pattern detection, we use subset scanning... View Details
- 2022
- Working Paper
Innovation on Wings: Nonstop Flights and Firm Innovation in the Global Context
By: Dany Bahar, Prithwiraj Choudhury, Do Yoon Kim and Wesley W. Koo
We study whether, when, and how better connectivity through nonstop flights leads to positive innovation outcomes for firms in the global context. Using unique data of all flights emanating from 5,015 airports around the globe from 2005 to 2015 and exploiting a... View Details
- 2022
- Working Paper
Machine Learning Models for Prediction of Scope 3 Carbon Emissions
By: George Serafeim and Gladys Vélez Caicedo
For most organizations, the vast amount of carbon emissions occur in their supply chain and in the post-sale processing, usage, and end of life treatment of a product, collectively labelled scope 3 emissions. In this paper, we train machine learning algorithms on 15... 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
- March 2022 (Revised January 2025)
- Technical Note
Linear Regression
This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to... View Details
- March 2022 (Revised January 2025)
- Technical Note
Prediction & Machine Learning
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
- March 2022
- Article
Assessing the Impact of the COVID-19 Pandemic on Clinician Ambulatory Electronic Health Record Use
By: A Jay Holmgren, Lance Downing, Mitchell Tang, Christopher Sharp, Christopher Longhurst and Robert S. Huckman
Objective: The COVID-19 pandemic changed clinician electronic health record (EHR) work in a multitude of ways. To evaluate how, we measure ambulatory clinician EHR use in the United States throughout the COVID-19 pandemic.
Materials and Methods: We use EHR... View Details
Materials and Methods: We use EHR... View Details
- 2022
- Working Paper
Electoral Turnovers
By: Benjamin Marx, Vincent Pons and Vincent Rollet
In most national elections, voters face a key choice between continuity and change. Electoral turnovers occur when the incumbent candidate or party fails to win reelection. To understand how turnovers affect national outcomes, we study the universe of presidential and... View Details
- February 2022
- Article
Sugar-sweetened Beverage Purchases and Intake at Event Arenas with and without a Portion Size Cap
By: Sheri Volger, James Scott Parrott, Brian Elbel, Leslie K. John, Jason P. Block, Pamela Rothpletz-Puglia and Christina A. Roberto
This is the first real-world study to examine the association between a voluntary 16-ounce (oz.) portion-size cap on sugar-sweetened beverages (SSB) at a sporting arena on volume of SSBs and food calories purchased and consumed during basketball games. Cross-sectional... View Details
- 2022
- Working Paper
The Impact of Campaign Finance Rules on Candidate Selection and Electoral Outcomes: Evidence from France
By: Nikolaj Broberg, Vincent Pons and Clémence Tricaud
This paper investigates the effects of campaign finance rules on electoral outcomes. In French departmental and municipal elections, candidates competing in districts above 9,000 inhabitants face spending limits and are eligible for public reimbursement if they obtain... View Details
- January–February 2022
- Article
Operational Disruptions, Firm Risk, and Control Systems
By: William Schmidt and Ananth Raman
Operational disruptions can impact a firm's risk, which manifests in a host of operational issues, including a higher holding cost for inventory, a higher financing cost for capacity expansion, and a higher perception of the firm's risk among its supply chain partners.... View Details
- August 2021
- Case
Precision Paint Co.
Describes a marketing director about to launch a new process for demand forecasting. Provides data that allow students to do a multivariable regression analysis. A rewritten version of an earlier case. View Details
- June 2021
- Technical Note
Introduction to Linear Regression
By: Michael Parzen and Paul Hamilton
This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical... View Details
- May 2021
- Article
Choice Architecture in Physician–patient Communication: A Mixed-methods Assessment of Physicians' Competency
By: J. Hart, K. Yadav, S. Szymanski, A. Summer, A. Tannenbaum, J. Zlatev, D. Daniels and S.D. Halpern
Background: Clinicians’ use of choice architecture, or how they present options, systematically influences the choices made by patients and their surrogate decision makers. However, clinicians may incompletely understand this influence.... View Details
- January 2021
- Article
Machine Learning for Pattern Discovery in Management Research
By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details