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(1,103)
- People (1)
- News (174)
- Research (619)
- Events (17)
- Multimedia (5)
- Faculty Publications (375)
Show Results For
- All HBS Web
(1,103)
- People (1)
- News (174)
- Research (619)
- Events (17)
- Multimedia (5)
- Faculty Publications (375)
- 2014
- Working Paper
De Gustibus non est Taxandum: Heterogeneity in Preferences and Optimal Redistribution
By: Benjamin B Lockwood and Matthew Weinzierl
The prominent but unproven intuition that preference heterogeneity reduces redistribution in a standard optimal tax model is shown to hold under the plausible condition that the distribution of preferences for consumption relative to leisure rises, in terms of... View Details
Lockwood, Benjamin B., and Matthew Weinzierl. "De Gustibus non est Taxandum: Heterogeneity in Preferences and Optimal Redistribution." Harvard Business School Working Paper, No. 12-063, January 2012. (Updated September 2014. NBER Working Paper Series, No. 17784. Published in Journal of Public Economics.)
- January 2018 (Revised February 2018)
- Technical Note
The Scope of Business at the Base of the Pyramid: Poverty in the U.S. and Other OECD Countries
By: V. Kasturi Rangan and Tricia Gregg
Using data from U.S. Census and OECD, this note defines poverty as those populations who fall below 50% of that country’s median per capita income. It then provides a brief statistical tour of six key challenges facing such populations: Income and Jobs, Healthcare,... View Details
Rangan, V. Kasturi, and Tricia Gregg. "The Scope of Business at the Base of the Pyramid: Poverty in the U.S. and Other OECD Countries." Harvard Business School Technical Note 518-037, January 2018. (Revised February 2018.)
- 05 Jun 2014
- Video
Career & Professional Development Overview
- January 1982 (Revised December 1997)
- Background Note
Note on the New Deal: From the First to the Second ""Hundred Days""
A brief summary of Franklin D. Roosevelt's New Deal policies between 1933 and 1935. Contains three statistical tables that supplement Selected U.S. Statistics: Part I and Selected U.S. Statistics: Part II. View Details
McCraw, Thomas K. Note on the New Deal: From the First to the Second ""Hundred Days"". Harvard Business School Background Note 382-115, January 1982. (Revised December 1997.)
- 2020
- Working Paper
A General Theory of Identification
By: Iavor Bojinov and Guillaume Basse
What does it mean to say that a quantity is identifiable from the data? Statisticians seem to agree
on a definition in the context of parametric statistical models — roughly, a parameter θ in a model
P = {Pθ : θ ∈ Θ} is identifiable if the mapping θ 7→ Pθ is injective.... View Details
Bojinov, Iavor, and Guillaume Basse. "A General Theory of Identification." Harvard Business School Working Paper, No. 20-086, February 2020.
- February 2021
- Tutorial
What is AI?
By: Tsedal Neeley
This video explores the elements that constitute artificial intelligence (AI). From its mathematical basis to current advances in AI, this video introduces students to data, tools, and statistical models that make a computer 'intelligent.' Through an explanation of... View Details
- Article
De Gustibus non est Taxandum: Heterogeneity in Preferences and Optimal Redistribution
By: Benjamin B Lockwood and Matthew Weinzierl
The prominent but unproven intuition that preference heterogeneity reduces redistribution in a standard optimal tax model is shown to hold under the plausible condition that the distribution of preferences for consumption relative to leisure rises, in terms of... View Details
Keywords: Motivation and Incentives; Income; Decision Choices and Conditions; Consumer Behavior; Taxation; Microeconomics; Macroeconomics
Lockwood, Benjamin B., and Matthew Weinzierl. "De Gustibus non est Taxandum: Heterogeneity in Preferences and Optimal Redistribution." Journal of Public Economics 124 (April 2015): 74–80. (Also NBER Working Paper Series, No. 17784, September 2014 and Harvard Business School Working Paper, No. 12-063, January 2012.)
- 2024
- Working Paper
Incorporating Micro Data into Differentiated Products Demand Estimation with PyBLP
We delineate a general framework for incorporating many types of micro data from summary statistics to full surveys of selected consumers into Berry, Levinsohn, and Pakes (1995) style estimates of differentiated products demand systems. We extend recommended practices... View Details
Conlon, Chris, and Jeff Gortmaker. "Incorporating Micro Data into Differentiated Products Demand Estimation with PyBLP." Working Paper, September 2024.
- January 1996 (Revised April 1997)
- Case
Deutsche Allgemeinversicherung
Describes the application of statistical process control in a service industry. In this case, Annette Kluck must decide how to adopt manufacturing-based principles to a service process ranging from customer account setup to legal services. View Details
Upton, David M. "Deutsche Allgemeinversicherung." Harvard Business School Case 696-084, January 1996. (Revised April 1997.)
Jeremy Yang
Jeremy Yang is an Assistant Professor of Business Administration in the Marketing Unit at Harvard Business School. He teaches Marketing in the MBA required curriculum. He develops data products for... View Details
- November 1989 (Revised June 1991)
- Background Note
Facts and Figures on Defense Procurement: The Department of Defense and Defense Procurement, An Overview
By: Robert L. Simons
Provides statistics and other factual information on the Department of Defense procurement process, DOD expenditures, market share segmentation, the variety of contract types, and the role of the Defense Contract Audit Agency. View Details
Keywords: National Security
Simons, Robert L. "Facts and Figures on Defense Procurement: The Department of Defense and Defense Procurement, An Overview." Harvard Business School Background Note 190-060, November 1989. (Revised June 1991.)
- 27 Jul 2016
- News
Airbnb's data shows that Airbnb helps the middle class. But does it?
V.G. Narayanan
Professor Narayanan is the Thomas D. Casserly, Jr. Professor of Business Administration, and Senior Associate Dean of Executive Education and HBS Online. His research focuses on management accounting with an interest in performance evaluation and incentives... View Details
- Article
Beyond Statistics: The Economic Content of Risk Scores
By: Liran Einav, Amy Finkelstein, Raymond Kluender and Paul Schrimpf
"Big data" and statistical techniques to score potential transactions have transformed insurance and credit markets. In this paper, we observe that these widely-used statistical scores summarize a much richer heterogeneity, and may be endogenous to the context in which... View Details
Einav, Liran, Amy Finkelstein, Raymond Kluender, and Paul Schrimpf. "Beyond Statistics: The Economic Content of Risk Scores." American Economic Journal: Applied Economics 8, no. 2 (April 2016): 195–224.
- 25 Oct 2018
- HBS Seminar
Fanyin Zheng, Columbia University
Miaomiao Zhang
Miaomiao Zhang is a doctoral candidate at the Technology & Operations Management Unit at Harvard Business School. Miaomiao received a B.S. in Applied Mathematics & Statistics and Economics from Emory University. She worked at the Strategy Unit at Harvard... View Details
- 20 Aug 2020
- Working Paper Summaries
Best Ideas
- September 2017 (Revised July 2023)
- Case
Adaptive Platform Trials: The Clinical Trial of the Future?
By: Ariel D. Stern and Sarah Mehta
In July 2017, Dr. Brian M. Alexander, president and CEO of the AGILE Research Foundation, was preparing to launch a new type of clinical trial—an adaptive platform trial—to study potential therapies for glioblastoma (GBM), an aggressive form of brain cancer.... View Details
Keywords: Clinical Trials; Cancer; Adaptive Platform Trials; Platform Trials; Adaptive Trials; Glioblastoma; Health; Health Care and Treatment; Health Testing and Trials; Business Strategy; Innovation Strategy; Health Industry; United States
Stern, Ariel D., and Sarah Mehta. "Adaptive Platform Trials: The Clinical Trial of the Future?" Harvard Business School Case 618-025, September 2017. (Revised July 2023.)
- TeachingInterests
Leading with People Analytics; HBS MBA Elective; 2021
- Teaching fellow for course on using data science to make decisions about people, such as hiring, firing, promotion, team composition, etc.
- Led weekly student review sessions teaching statistics and the R... View Details