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- 2025
- Working Paper
Extractive Taxation and the French Revolution
By: Tommaso Giommoni, Gabriel Loumeau and Marco Tabellini
We study the fiscal determinants of the French Revolution, exploiting plausibly exogenous variation in the salt tax—a large source of royal revenues and one of the most extractive forms of taxation of the Ancien Régime. Implementing a Regression Discontinuity... View Details
Keywords: Extractive Taxation; Regime Change; French Revolution; State Capacity; Taxation; History; Government Administration; Attitudes; Public Opinion
Giommoni, Tommaso, Gabriel Loumeau, and Marco Tabellini. "Extractive Taxation and the French Revolution." Harvard Business School Working Paper, No. 25-047, April 2025. (Featured at VoxEU.)
- February 2025
- Article
Variation in Batch Ordering of Imaging Tests in the Emergency Department and the Impact on Care Delivery
By: Jacob C. Jameson, Soroush Saghafian, Robert S. Huckman and Nicole Hodgson
Objectives: To examine heterogeneity in physician batch ordering practices and measure the impact of a physician's tendency to batch order imaging tests on patient outcomes and resource utilization.
Study Setting and Design: In this retrospective study, we used... View Details
Study Setting and Design: In this retrospective study, we used... View Details
Keywords: Health Care; Operations Management; Productivity; Health Care and Treatment; Operations; Outcome or Result; Resource Allocation; Health Industry; United States
Jameson, Jacob C., Soroush Saghafian, Robert S. Huckman, and Nicole Hodgson. "Variation in Batch Ordering of Imaging Tests in the Emergency Department and the Impact on Care Delivery." Health Services Research 60, no. 1 (February 2025).
- 2024
- Working Paper
Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions
By: Caleb Kwon, Ananth Raman and Jorge Tamayo
We investigate whether corporate officers should grant managers discretion to override AI-driven demand forecasts and labor scheduling tools. Analyzing five years of administrative data from a large grocery retailer using such an AI tool, encompassing over 500 stores,... View Details
Keywords: AI and Machine Learning; Forecasting and Prediction; Working Conditions; Performance Productivity
Kwon, Caleb, Ananth Raman, and Jorge Tamayo. "Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions." Working Paper, April 2024.
- 2024
- Working Paper
Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference
By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov
Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to... View Details
Lindon, Michael, Dae Woong Ham, Martin Tingley, and Iavor I. Bojinov. "Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference." Harvard Business School Working Paper, No. 24-060, March 2024.
- February 2024
- Teaching Note
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
Teaching Note for HBS Case No. 224-029. Levi Strauss & Co. (“Levi Strauss”) partnered with the IT services company Wipro to incorporate more sophisticated methods, such as machine learning, into their financial forecasting process starting in 2018. The decision to... View Details
- February 2024
- Article
Fifty Shades of QE: Robust Evidence
By: Brian Fabo, Marina Jančoková, Elisabeth Kempf and Ľuboš Pástor
Fabo et al. (2021) show that papers written by central bank researchers find quantitative easing (QE) to be more effective than papers written by academics. Weale and Wieladek (2022) show that a subset of these results lose statistical significance when OLS regressions... View Details
Keywords: Quantitative Easing; Research; Mathematical Methods; Perception; Banks and Banking; Body of Literature
Fabo, Brian, Marina Jančoková, Elisabeth Kempf, and Ľuboš Pástor. "Fifty Shades of QE: Robust Evidence." Art. 107065. Journal of Banking & Finance 159 (February 2024).
- December 2023
- Article
Association of Hospital System Affiliation with COVID-19 Capacity Burden
By: Zachary Levin, Pinar Karaca-Mandic, Richard J. Boxer and Regina E. Herzlinger
What is the message? The COVID-19 pandemic exposed the highly variable and uncoordinated responses by hospitals. The authors found that while the non-top ten system affiliated hospitals had a larger COVID-19 share index relative to independent hospitals, top-ten system... View Details
Keywords: COVID-19 Pandemic; Resource Allocation; Health Pandemics; Demographics; Health Care and Treatment; Health Industry
Levin, Zachary, Pinar Karaca-Mandic, Richard J. Boxer, and Regina E. Herzlinger. "Association of Hospital System Affiliation with COVID-19 Capacity Burden." Health Management, Policy and Innovation 8, no. 3 (December 2023).
- October 2023
- Article
Coordination and Bandwagon Effects: How Past Rankings Shape the Behavior of Voters and Candidates
By: Riako Granzier, Vincent Pons and Clémence Tricaud
Candidates’ placements in polls or past elections can be powerful coordination devices for both parties and voters. Using a regression discontinuity design in French elections, we show that candidates who place first by only a small margin in the first round are more... View Details
Keywords: Strategic Voting; Coordination; Bandwagon Effect; Regression Discontinuity Design; French Elections; Voting; Political Elections; Behavior; France
Granzier, Riako, Vincent Pons, and Clémence Tricaud. "Coordination and Bandwagon Effects: How Past Rankings Shape the Behavior of Voters and Candidates." American Economic Journal: Applied Economics 15, no. 4 (October 2023): 177–217.
- August 2023 (Revised March 2024)
- Case
Arla Foods: Data-Driven Decarbonization (A)
By: Michael Parzen, Michael W. Toffel, Susan Pinckney and Amram Migdal
The case describes Arla’s history, in particular its climate change mitigation efforts, and how it implemented a price incentive system to motivate individual farms to implement scope 1 greenhouse gas emissions mitigation measures and receive a higher milk price. The... View Details
Keywords: Dairy Industry; Business Earnings; Agribusiness; Animal-Based Agribusiness; Acquisition; Mergers and Acquisitions; Decision Making; Decisions; Voting; Environmental Management; Climate Change; Environmental Regulation; Environmental Sustainability; Green Technology; Pollution; Moral Sensibility; Values and Beliefs; Financial Strategy; Price; Profit; Revenue; Food; Geopolitical Units; Global Strategy; Ownership Type; Cooperative Ownership; Performance Efficiency; Performance Evaluation; Problems and Challenges; Natural Environment; Science-Based Business; Business Strategy; Commercialization; Cooperation; Corporate Strategy; Food and Beverage Industry; Agriculture and Agribusiness Industry; Europe; United Kingdom; European Union; Germany; Denmark; Sweden; Luxembourg; Belgium
Parzen, Michael, Michael W. Toffel, Susan Pinckney, and Amram Migdal. "Arla Foods: Data-Driven Decarbonization (A)." Harvard Business School Case 624-003, August 2023. (Revised March 2024.)
- August 2023 (Revised January 2024)
- Supplement
Arla Foods: Data-Driven Decarbonization (B)
By: Michael Parzen, Michael W. Toffel, Susan Pinckney and Amram Migdal
The case describes Arla’s history, in particular its climate change mitigation efforts, and how it implemented a price incentive system to motivate individual farms to implement scope 1 greenhouse gas emissions mitigation measures and receive a higher milk price. The... View Details
Keywords: Dairy Industry; Earnings Management; Environmental Accounting; Animal-Based Agribusiness; Mergers and Acquisitions; Decisions; Voting; Climate Change; Environmental Regulation; Environmental Sustainability; Green Technology; Pollution; Moral Sensibility; Values and Beliefs; Financial Strategy; Price; Profit; Revenue; Food; Geopolitical Units; Cross-Cultural and Cross-Border Issues; Global Strategy; Cooperative Ownership; Performance Efficiency; Performance Evaluation; Problems and Challenges; Natural Environment; Science-Based Business; Business Strategy; Commercial Banking; Cooperation; Corporate Strategy; Motivation and Incentives; Food and Beverage Industry; Agriculture and Agribusiness Industry; Europe; United Kingdom; European Union; Denmark; Sweden; Luxembourg; Belgium
Parzen, Michael, Michael W. Toffel, Susan Pinckney, and Amram Migdal. "Arla Foods: Data-Driven Decarbonization (B)." Harvard Business School Supplement 624-036, August 2023. (Revised January 2024.)
- August 2023
- Article
Formal Employment and Organized Crime: Regression Discontinuity Evidence from Colombia
By: Gaurav Khanna, Carlos Medina, Anant Nyshadham, Jorge Tamayo and Nicolas Torres
Safety net programs, common in settings with high informality like Latin America, often use a means test to establish eligibility. We ask: in settings in which organised crime provides lucrative opportunities in the informal market, will discouraging formal employment... View Details
Khanna, Gaurav, Carlos Medina, Anant Nyshadham, Jorge Tamayo, and Nicolas Torres. "Formal Employment and Organized Crime: Regression Discontinuity Evidence from Colombia." Economic Journal 133 (August 2023): 2427–2448.
- 2023
- Working Paper
Keep Your Enemies Closer: Strategic Platform Adjustments during U.S. and French Elections
By: Rafael Di Tella, Randy Kotti, Caroline Le Pennec and Vincent Pons
A key tenet of representative democracy is that politicians' discourse and policies should follow voters' preferences. In the median voter theorem, this outcome emerges as candidates strategically adjust their platform to get closer to their opponent. Despite its... View Details
Di Tella, Rafael, Randy Kotti, Caroline Le Pennec, and Vincent Pons. "Keep Your Enemies Closer: Strategic Platform Adjustments during U.S. and French Elections." NBER Working Paper Series, No. 31503, July 2023.
- May 2023
- Case
CMA CGM: Reducing the Carbon Footprint of Container Shipping
By: Willy C. Shih and Emilie Billaud
Marine transport is the most cost-effective way to move large volumes over long distances, and container shipping is the backbone of international trade in goods. Yet shipping contributed 3% of worldwide greenhouse gas emissions, and the deep-sea segment, which... View Details
Keywords: Container Shipping; Logistic Regression; Trade Links; Decarbonization; Environmental Strategies; Environmental Impact; Globalization; Trade; Environmental Regulation; Logistics; Supply Chain; Governance Compliance; Shipping Industry; European Union; Asia; North America
Shih, Willy C., and Emilie Billaud. "CMA CGM: Reducing the Carbon Footprint of Container Shipping." Harvard Business School Case 623-006, May 2023.
- 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.
- May–June 2023
- Article
Need for Speed: The Impact of In-Process Delays on Customer Behavior in Online Retail
By: Santiago Gallino, Nil Karacaoglu and Antonio Moreno
The impact of delays has been widely studied in various offline services. The focus of this study is online services, and we explore the impact of in-process delays—measured by website speed—on customer behavior. We leverage novel retail and website speed data to... View Details
Keywords: Online Retail; Quasi-experiments; Abandonment; Synthetic Control; E-commerce; Internet and the Web; Consumer Behavior; Policy; Retail Industry
Gallino, Santiago, Nil Karacaoglu, and Antonio Moreno. "Need for Speed: The Impact of In-Process Delays on Customer Behavior in Online Retail." Operations Research 71, no. 3 (May–June 2023): 876–894.
- 2023
- Working Paper
PRIMO: Private Regression in Multiple Outcomes
By: Seth Neel
We introduce a new differentially private regression setting we call Private Regression in Multiple Outcomes (PRIMO), inspired the common situation where a data analyst wants to perform a set of l regressions while preserving privacy, where the covariates... View Details
Neel, Seth. "PRIMO: Private Regression in Multiple Outcomes." Working Paper, March 2023.
- March–April 2023
- Article
Market Segmentation Trees
By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market... View Details
Keywords: Decision Trees; Computational Advertising; Market Segmentation; Analytics and Data Science; E-commerce; Consumer Behavior; Marketplace Matching; Marketing Channels; Digital Marketing
Aouad, Ali, Adam Elmachtoub, Kris J. Ferreira, and Ryan McNellis. "Market Segmentation Trees." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 648–667.
- 2022
- Article
Becoming a Learning Organization While Enhancing Performance: The Case of LEGO
By: Thomas Borup Kristensen, Henrik Saabye and Amy Edmondson
Purpose - The purpose of this study is to empirically test how problem-solving lean practices, along with
leaders as learning facilitators in an action learning approach, can be transferred from a production context to a
knowledge work context for the purpose... View Details
Kristensen, Thomas Borup, Henrik Saabye, and Amy Edmondson. "Becoming a Learning Organization While Enhancing Performance: The Case of LEGO." International Journal of Operations & Production Management 42, no. 13 (2022): 438–481.
- 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
Keywords: Political Parties; Incumbent Politicians; Democracy; Political Elections; Competitive Advantage
Dano, Kevin, Francesco Ferlenga, Vincenzo Galasso, Caroline Le Pennec, and Vincent Pons. "Coordination and Incumbency Advantage in Multi-Party Systems: Evidence from French Elections." NBER Working Paper Series, No. 30541, October 2022.
- 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
Tan, Alyssa J., Vincent Mancini, James J. Gross, Amit Goldenberg, Johanna C. Badcock, Michelle H. Lim, Rodrigo Becerra, Ben Jackson, and David A. Preece. "Loneliness Versus Distress: A Comparison of Emotion Regulation Profiles." Behaviour Change 39, no. 3 (September 2022): 180–190.