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- All HBS Web (618)
- Faculty Publications (568)
Show Results For
- All HBS Web (618)
- Faculty Publications (568)
- 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
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).
- 2020
- Working Paper
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
Bojinov, Iavor I., David Simchi-Levi, and Jinglong Zhao. "Design and Analysis of Switchback Experiments." Harvard Business School Working Paper, No. 21-034, September 2020.
- October 1992
- Case
Charles River Jazz Festival
Charles River Jazz Festival must decide whether to press a compact disk (CD) of Friday's jazz performance for sale on Saturday and Sunday. The idea to press CDs is novel, so there is considerable uncertainty about how receptive customers will be. The festival must... View Details
Wu, George. "Charles River Jazz Festival." Harvard Business School Case 893-004, October 1992.
- January 1982
- Background Note
Sharing Costs: Internal Telephone Billing Rates
By: Elon Kohlberg
Kohlberg, Elon. "Sharing Costs: Internal Telephone Billing Rates." Harvard Business School Background Note 182-109, January 1982.
- 2002
- Chapter
Future Possibilities in Finance Theory and Finance Practice
By: Robert C. Merton
Merton, Robert C. "Future Possibilities in Finance Theory and Finance Practice." In Mathematical Finance - Bachelier Congress 2000, edited by H. Geman, D. Madan, S. Pliska, and T. Vorst. Berlin: Springer-Verlag, 2002. (Was HBS Working Paper 01-030.)
- September 1976 (Revised June 1977)
- Background Note
Assessing Certainty Equivalents by Assessing Preference for Consequences
By: Paul A. Vatter
Vatter, Paul A. "Assessing Certainty Equivalents by Assessing Preference for Consequences." Harvard Business School Background Note 177-038, September 1976. (Revised June 1977.)
- 1981
- Chapter
Risk Aversion and Solutions to Nash's Bargaining Problem
By: R. Kihlstrom, A. E. Roth and D. Schmeidler
- May 2020
- Article
Inventory Auditing and Replenishment Using Point-of-Sales Data
By: Achal Bassamboo, Antonio Moreno and Ioannis Stamatopoulos
Spoilage, expiration, damage due to employee/customer handling, employee theft, and customer shoplifting usually are not reflected in inventory records. As a result, records often report phantom inventory, i.e., units of good not available for sale. We derive an... View Details
Keywords: Shelf Availability; Inventory Record Inaccuracy; Optimal Replenishment; Retail Analytics; Performance Effectiveness; Analysis; Mathematical Methods
Bassamboo, Achal, Antonio Moreno, and Ioannis Stamatopoulos. "Inventory Auditing and Replenishment Using Point-of-Sales Data." Production and Operations Management 29, no. 5 (May 2020): 1219–1231.
- April 1979
- Article
Statistical Models of Bond Ratings: A Methodological Inquiry
By: Robert S. Kaplan and Gabriel Urwitz
Kaplan, Robert S., and Gabriel Urwitz. "Statistical Models of Bond Ratings: A Methodological Inquiry." Journal of Business (April 1979): 231–261.
- 2024
- Working Paper
Winner Take All: Exploiting Asymmetry in Factorial Designs
By: Matthew DosSantos DiSorbo, Iavor I. Bojinov and Fiammetta Menchetti
Researchers and practitioners have embraced factorial experiments to simultaneously test multiple treatments, each with different levels. With the rise of technologies like Generative AI, factorial experimentation has become even more accessible: it is easier than ever... View Details
Keywords: Factorial Designs; Fisher Randomizations; Rank Estimators; Employer Interventions; Causal Inference; Mathematical Methods; Performance Improvement
DosSantos DiSorbo, Matthew, Iavor I. Bojinov, and Fiammetta Menchetti. "Winner Take All: Exploiting Asymmetry in Factorial Designs." Harvard Business School Working Paper, No. 24-075, June 2024.
- September 2021
- Article
Diagnostic Bubbles
By: Pedro Bordalo, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer
We introduce diagnostic expectations into a standard setting of price formation in which investors learn about the fundamental value of an asset and trade it. We study the interaction of diagnostic expectations with two well-known mechanisms: learning from prices and... View Details
Bordalo, Pedro, Nicola Gennaioli, Spencer Yongwook Kwon, and Andrei Shleifer. "Diagnostic Bubbles." Journal of Financial Economics 141, no. 3 (September 2021).
- 14 Aug 2017
- Conference Presentation
A Convex Framework for Fair Regression
By: Richard Berk, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel and Aaron Roth
We introduce a flexible family of fairness regularizers for (linear and logistic) regression problems. These regularizers all enjoy convexity, permitting fast optimization, and they span the range from notions of group fairness to strong individual fairness. By varying... View Details
Berk, Richard, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Roth. "A Convex Framework for Fair Regression." Paper presented at the 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), August 14, 2017.
- Article
A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects
By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public... View Details
Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods
McFowland III, Edward, Sandeep Gangarapu, Ravi Bapna, and Tianshu Sun. "A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects." MIS Quarterly 45, no. 4 (December 2021): 1807–1832.
- 1995
- Chapter
Dynamic General Equilibrium Models with Imperfectly Competitive Product Markets
By: Julio J. Rotemberg and Michael Woodford
- December 2019
- Article
Costly Concessions: An Empirical Framework for Matching with Imperfectly Transferable Utility
By: Alfred Galichon, Scott Duke Kominers and Simon Weber
We introduce an empirical framework for models of matching with imperfectly transferable utility and unobserved heterogeneity in tastes. Our framework allows us to characterize matching equilibrium in a flexible way that includes as special cases the classic fully- and... View Details
Keywords: Sorting; Matching; Marriage Market; Intrahousehold Allocation; Imperfectly Transferable Utility; Marketplace Matching; Mathematical Methods
Galichon, Alfred, Scott Duke Kominers, and Simon Weber. "Costly Concessions: An Empirical Framework for Matching with Imperfectly Transferable Utility." Journal of Political Economy 127, no. 6 (December 2019): 2875–2925.
- Article
Games of Threats
By: Elon Kohlberg and Abraham Neyman
A game of threats on a finite set of players, N, is a function d that assigns a real number to any coalition, S ⊆ N, such that d(S) = -d(N\S). A game of threats is not necessarily a coalitional game as it may fail to satisfy the condition d(Ø) = 0. We show that analogs... View Details
Kohlberg, Elon, and Abraham Neyman. "Games of Threats." Games and Economic Behavior 108 (March 2018): 139–145.
- 2005
- Chapter
A Revised Model of the Resource Allocation Process
By: J. L. Bower and Clark Gilbert
Bower, J. L., and Clark Gilbert. "A Revised Model of the Resource Allocation Process." In From Resource Allocation to Strategy, edited by Joseph L. Bower and Clark Gilbert. U.K.: Oxford University Press, 2005.
- 2005
- Chapter
Anomaly Seeking Research: Thirty Years of Development in Resource Allocation Theory
By: Clark Gilbert and Clayton M. Christensen
Gilbert, Clark, and Clayton M. Christensen. "Anomaly Seeking Research: Thirty Years of Development in Resource Allocation Theory." In From Resource Allocation to Strategy, edited by Joseph L. Bower and Clark Gilbert. U.K.: Oxford University Press, 2005.
- March 1992 (Revised June 1992)
- Background Note
Strategic Industry Model: Emergent Technologies
By: Robert J. Dolan
Describes computer model and output from conjoint analysis and perceptual mapping for product line planning. View Details
Dolan, Robert J. "Strategic Industry Model: Emergent Technologies." Harvard Business School Background Note 592-086, March 1992. (Revised June 1992.)