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  • All HBS Web  (1,107)
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  • All HBS Web  (1,107)
    • People  (1)
    • News  (177)
    • Research  (621)
    • Events  (18)
    • Multimedia  (5)
  • Faculty Publications  (376)
← Page 7 of 1,107 Results →
  • 05 Jun 2014
  • Video

Career & Professional Development Overview

  • 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
Keywords: Spending; Policy; Taxation; Theory; United States
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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.)
  • 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
Keywords: Identification; Econometric Models; Analytics and Data Science; Theory
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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
Keywords: Artificial Intelligence; Digital; Technological Innovation; Leadership; AI and Machine Learning; Mathematical Methods
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Neeley, Tsedal. What is AI? Harvard Business School Tutorial 421-713, February 2021. (https://hbsp.harvard.edu/product/421713-HTM-ENG?Ntt=tsedal%20neeley%20what%20is%20ai.)
  • 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
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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
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Conlon, Chris, and Jeff Gortmaker. "Incorporating Micro Data into Differentiated Products Demand Estimation with PyBLP." Working Paper, September 2024.
  • September 1974 (Revised April 1975)
  • Case

Ocean Spray Cranberries, Inc. (A)

At the conclusion of a small-scale pilot survey, management must decide whether to invest in a larger survey or terminate the project. The objective of the study is to use psychographic measurement techniques to study the alternative positions of cranberry sauce.... View Details
Keywords: Surveys; Product Positioning; Mathematical Methods; Agriculture and Agribusiness Industry; Food and Beverage Industry
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DeBruicker, F., and Jan-Erik Modig. "Ocean Spray Cranberries, Inc. (A)." Harvard Business School Case 575-039, September 1974. (Revised April 1975.)
  • 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
Keywords: Quality; Analysis; Service Operations; Business Strategy; Service Industry
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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
    Keywords: advertising; media; entertainment; information; consumer products
    • 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
    Keywords: Poverty; Social Issues; Problems and Challenges; Global Range
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    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.)
    • 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
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    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.)
    • 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
    Keywords: History; Mathematical Methods; Policy; Public Administration Industry; United States
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    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.)
    • 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
    Keywords: Analytics and Data Science; Risk and Uncertainty; Insurance Industry
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    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

    • 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

      Keywords: accounting industry; banking; service industry; telecommunications; health care
      • 20 Aug 2020
      • Working Paper Summaries

      Best Ideas

      Keywords: by Miguel Antón, Randolph B. Cohen, and Christopher Polk; Financial Services

        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
        • 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
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        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.)
        • Article

        Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

        By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
        The most prevalent notions of fairness in machine learning are statistical definitions: they fix a small collection of pre-defined groups, and then ask for parity of some statistic of the classifier (like classification rate or false positive rate) across these groups.... View Details
        Keywords: Machine Learning; Algorithms; Fairness; Mathematical Methods
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        Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
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