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- Faculty Publications (117)
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- All HBS Web (339)
- Faculty Publications (117)
- 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 2010 (Revised March 2016)
- Background Note
Marketing Analysis Toolkit: Break-even Analysis
By: Thomas J. Steenburgh and Jill Avery
Marketing managers are often called upon to make recommendations for or against programs that cost money to implement. Before expenditures are made, managers want to be sure that they will be getting a return on their investment. One way of assessing this is by... View Details
Keywords: Decision Making; Investment Return; Spending; Management Analysis, Tools, and Techniques; Marketing Strategy; Strategic Planning; Mathematical Methods
Steenburgh, Thomas J., and Jill Avery. "Marketing Analysis Toolkit: Break-even Analysis." Harvard Business School Background Note 510-080, February 2010. (Revised March 2016.)
- 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.
- Article
Two-Sided Platforms: Product Variety and Pricing Structures
By: Andrei Hagiu
This paper provides a new modeling framework to analyze two-sided platforms connecting producers and consumers. In contrast to the existing literature, indirect network effects are determined endogenously, through consumers' taste for variety and producer competition.... View Details
Keywords: Pricing Structure; Indirect Network Effects; Product Variety; Price; Network Effects; Two-Sided Platforms; Product; Renting or Rental; Competition
Hagiu, Andrei. "Two-Sided Platforms: Product Variety and Pricing Structures ." Journal of Economics & Management Strategy 18, no. 4 (Winter 2009).
- 2007
- Other Unpublished Work
Implementing Technology
By: Diego Comin and Bart Hobijn
We introduce a tractable model of endogenous growth in which the returns to innovation are determined by the technology adoption decisions of the users of new technologies. Technology adoption involves an implementation investment that determines the initial... View Details
Keywords: Learning; Investment; Investment Return; Innovation and Invention; Growth and Development Strategy; Performance Productivity; Technology Adoption
Comin, Diego, and Bart Hobijn. "Implementing Technology." November 2007. (Revise and resubmit at the Journal of Economic Theory.)
- 2020
- Working Paper
Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective
We provide a comprehensive examination of whether, to what extent, and which accounting variables are useful for improving the predictive accuracy of GDP growth forecasts. We leverage statistical models that accommodate a broad set of (341) variables—outnumbering the... View Details
Keywords: Big Data; Elastic Net; GDP Growth; Machine Learning; Macro Forecasting; Short Fat Data; Accounting; Economic Growth; Forecasting and Prediction; Analytics and Data Science
Datar, Srikant, Apurv Jain, Charles C.Y. Wang, and Siyu Zhang. "Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective." Harvard Business School Working Paper, No. 21-113, December 2020.
- May 2010
- Supplement
Tim Westergren of Pandora Radio
By: Willy C. Shih and Halle Alicia Tecco
Pandora Radio is at a crossroads. Founder Tim Westergren has just been told by a well known VC to get rid of his unprofitable customers in order to get his costs down, but Westergren is not sure that such actions are consistent with his company's business model.... View Details
Keywords: History; Business Model; Customers; Venture Capital; Internet and the Web; Cost Management; Outcome or Result; Customization and Personalization; Growth and Development Strategy; Music Industry
Shih, Willy C., and Halle Alicia Tecco. "Tim Westergren of Pandora Radio." Harvard Business School Video Supplement 610-714, May 2010.
- July 2022
- Article
What Do I Make of the Rest of My Life? Global and Quotidian Life Construal across the Retirement Transition
By: Jeff Steiner and Teresa M. Amabile
Retirement means relinquishing the daily structure that work provides and the career-dependent meanings that it offers life narratives. The retirement transition can therefore involve contemplating both how to spend newly-freed daily time and the implications of... View Details
Keywords: Retirement Transition; Life Narrative; Construal Level Theory; Global Construal; Quotidian Construal; Meanings Of Work And Retirement; Retirement; Transition; Perspective
Steiner, Jeff, and Teresa M. Amabile. "What Do I Make of the Rest of My Life? Global and Quotidian Life Construal across the Retirement Transition." Art. 104137. Organizational Behavior and Human Decision Processes 171 (July 2022).
- September 2018
- Article
Discretionary Task Ordering: Queue Management in Radiological Services
By: Maria Ibanez, Jonathan R. Clark, Robert S. Huckman and Bradley R. Staats
Work-scheduling research typically prescribes task sequences implemented by managers. Yet employees often have discretion to deviate from their prescribed sequence. Using data from 2.4 million radiological diagnoses, we find that doctors prioritize similar tasks... View Details
Keywords: Discretion; Scheduling; Queue; Healthcare; Learning; Experience; Decentralization; Operations; Service Operations; Service Delivery; Performance; Performance Effectiveness; Performance Efficiency; Performance Improvement; Performance Productivity; Decisions; Time Management; Cost vs Benefits; Health Industry
Ibanez, Maria, Jonathan R. Clark, Robert S. Huckman, and Bradley R. Staats. "Discretionary Task Ordering: Queue Management in Radiological Services." Management Science 64, no. 9 (September 2018): 4389–4407. (Working paper available here. Winner of the 2017 Best Paper Competition of the POMS College of Healthcare Operations Management. Featured in Forbes, Quartz, and Inc.)
- 2017
- Working Paper
Discretionary Task Ordering: Queue Management in Radiological Services
By: Maria Ibanez, Jonathan R. Clark, Robert S. Huckman and Bradley R. Staats
Work scheduling research typically prescribes task sequences implemented by managers. Yet employees often have discretion to deviate from their prescribed sequence. Using data from 2.4 million radiological diagnoses, we find that doctors prioritize similar tasks... View Details
Keywords: Discretion; Scheduling; Queue; Healthcare; Learning; Experience; Decentralization; Delegation; Behavioral Operations; Operations; Service Operations; Service Delivery; Performance; Performance Effectiveness; Performance Efficiency; Performance Improvement; Performance Productivity; Decisions; Time Management; Cost vs Benefits; Health Industry
Ibanez, Maria, Jonathan R. Clark, Robert S. Huckman, and Bradley R. Staats. "Discretionary Task Ordering: Queue Management in Radiological Services." Harvard Business School Working Paper, No. 16-051, October 2015. (Revised March 2017.)
- 2016
- Working Paper
Meet the Oligarchs: Business Legitimacy, State Capacity and Taxation
By: Rafael Di Tella, Juan Dubra and Alejandro Lagomarsino
We analyze the role of people’s beliefs about the rich in the determination of public policy in the context of a randomized online survey experiment. A question we study is the desirability of government-private sector meetings, a variable we argue is connected to... View Details
Keywords: Business Legitimacy; State Capacity; Meetings; Taxes; Top 1%; Regulation; Prejudice and Bias; Values and Beliefs; Taxation; Business and Government Relations
Di Tella, Rafael, Juan Dubra, and Alejandro Lagomarsino. "Meet the Oligarchs: Business Legitimacy, State Capacity and Taxation." Harvard Business School Working Paper, No. 17-046, December 2016.
The Magic That Makes Customer Experiences Stick
The field of customer experience (CX) design — which aims to ensure that customers have positive touch points with companies while buying and consuming their products and services — has grown quickly in recent years. Research has shown that memorable experiences,... 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
Keywords: Targeted Intervention; Conditional Average Treatment Effect Estimation; Differential Privacy; Honest Estimation; Post-processing; Analytics and Data Science; Consumer Behavior; Marketing
Huang, Ta-Wei, and Eva Ascarza. "Enhancing Treatment Effect Prediction on Privacy-Protected Data: An Honest Post-Processing Approach." Harvard Business School Working Paper, No. 24-034, December 2023. (Revised March 2025.)
- 2023
- Working Paper
When Should Public Programs Be Privately Administered? Theory and Evidence from the Paycheck Protection Program
By: Alexander Bartik, Zoë B. Cullen, Edward L. Glaeser, Michael Luca, Christopher Stanton and Adi Sunderam
What happens when public resources are allocated by private companies whose objectives may be
imperfectly aligned with policy goals? We study this question in the context of the Paycheck
Protection Program (PPP), which relied on private banks to disburse aid to small... View Details
Keywords: Paycheck Protection Program; Targeting; Impact; Entrepreneurship; Health Pandemics; Small Business; Financing and Loans; Outcome or Result; United States
Bartik, Alexander, Zoë B. Cullen, Edward L. Glaeser, Michael Luca, Christopher Stanton, and Adi Sunderam. "When Should Public Programs Be Privately Administered? Theory and Evidence from the Paycheck Protection Program." Harvard Business School Working Paper, No. 21-021, August 2020. (Revised July 2023. Accepted at The Review of Economics and Statistics.)
- Forthcoming
- Article
When Should Public Programs Be Privately Administered? Theory and Evidence from the Paycheck Protection Program
By: Alexander W. Bartik, Zoë Cullen, Edward L. Glaeser, Michael Luca, Christopher Stanton and Adi Sunderam
What happens when public resources are allocated by private companies whose objectives may be
imperfectly aligned with policy goals? We study this question in the context of the Paycheck
Protection Program (PPP), which relied on private banks to disburse aid to small... View Details
Keywords: Paycheck Protection Program; Targeting; Impact; Entrepreneurship; Health Pandemics; Small Business; Financing and Loans; Outcome or Result; United States
Bartik, Alexander W., Zoë Cullen, Edward L. Glaeser, Michael Luca, Christopher Stanton, and Adi Sunderam. "When Should Public Programs Be Privately Administered? Theory and Evidence from the Paycheck Protection Program." Review of Economics and Statistics (forthcoming).
- November 2024
- Article
Preference Externality Estimators: A Comparison of Border Approaches and IVs
By: Xi Ling, Wesley R. Hartmann and Tomomichi Amano
This paper compares two estimators—the Border Approach and an Instrumental Variable (IV) estimator—using a unified framework where identifying variation arises from “preference externalities,” following the intuition in Waldfogel (2003). We highlight two dimensions in... View Details
Ling, Xi, Wesley R. Hartmann, and Tomomichi Amano. "Preference Externality Estimators: A Comparison of Border Approaches and IVs." Management Science 70, no. 11 (November 2024): 7892–7910.
- March 2020
- Article
Diagnosing Missing Always at Random in Multivariate Data
By: Iavor I. Bojinov, Natesh S. Pillai and Donald B. Rubin
Models for analyzing multivariate data sets with missing values require strong, often assessable, assumptions. The most common of these is that the mechanism that created the missing data is ignorable—a twofold assumption dependent on the mode of inference. The first... View Details
Keywords: Missing Data; Diagnostic Tools; Sensitivity Analysis; Hypothesis Testing; Missing At Random; Row Exchangeability; Analytics and Data Science; Mathematical Methods
Bojinov, Iavor I., Natesh S. Pillai, and Donald B. Rubin. "Diagnosing Missing Always at Random in Multivariate Data." Biometrika 107, no. 1 (March 2020): 246–253.
- Research Summary
Estimating Demand Uncertainty Using Judgmental Forecasts
Measuring demand uncertainty is a key activity in supply chain planning, but is difficult when demand history is unavailable such as for new products. One method that can be applied in such cases uses dispersion among forecasting experts as a measure of demand... View Details
- 28 Jul 2008
- Research & Ideas
Making the Decision to Franchise (or not)
customer-facing operating environment affects organizational design choices such as control systems, incentives, performance measurement, and ownership structures," explains Campbell. "Even firms that have very standardized business View Details
- July–August 2024
- Article
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 Strategy
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.