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- Faculty Publications (568)
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- All HBS Web (618)
- Faculty Publications (568)
- 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.
- May 2017
- Article
Stable and Strategy-Proof Matching with Flexible Allotments
By: John William Hatfield, Scott Duke Kominers and Alexander Westkamp
We introduce a framework of matching with flexible allotments that can be used to model firms with cross-division hiring restrictions. Our framework also allows us to nest some prior models of matching with distributional constraints. Building upon our recent work on... View Details
Hatfield, John William, Scott Duke Kominers, and Alexander Westkamp. "Stable and Strategy-Proof Matching with Flexible Allotments." American Economic Review 107, no. 5 (May 2017): 214–219.
- July 1999
- Background Note
Note on Statistical Tests for a Randomized Matched Pair Experimental Design, A
By: Alvin J. Silk
Concerns understanding the conditions under which an experimental design that employs matching and randomization may result in gains in precision as compared to a design that utilizes randomization and independent samples--i.e., no matching. An empirical example is... View Details
- 1981
- Chapter
Sparsity and Piecewise Linearity in Large Portfolio Optimization Problems
By: André Perold and Harry M. Markowitz
- 18 Nov 2016
- Conference Presentation
Rawlsian Fairness for Machine Learning
By: Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel and Aaron Leon Roth
Motivated by concerns that automated decision-making procedures can unintentionally lead to discriminatory behavior, we study a technical definition of fairness modeled after John Rawls' notion of "fair equality of opportunity". In the context of a simple model of... View Details
Joseph, Matthew, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Leon Roth. "Rawlsian Fairness for Machine Learning." Paper presented at the 3rd Workshop on Fairness, Accountability, and Transparency in Machine Learning, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), November 18, 2016.
- 2008
- Chapter
Assessing Creativity and Its Antecedents: An Exploration of the Componential Theory of Creativity
By: T. M. Amabile and Jennifer Mueller
Amabile, T. M., and Jennifer Mueller. "Assessing Creativity and Its Antecedents: An Exploration of the Componential Theory of Creativity." In Handbook of Organizational Creativity, edited by Jing Zhou and Christina E. Shalley. Lawrence Erlbaum Associates, 2008.
- March 1999 (Revised December 2001)
- Background Note
Analyzing Consumer Preferences
By: Robert J. Dolan
Presents a non-traditional description of the conjoint analysis methodology. Discusses the process by which a study is done and cites areas of application. View Details
Dolan, Robert J. "Analyzing Consumer Preferences." Harvard Business School Background Note 599-112, March 1999. (Revised December 2001.)
- January 2008 (Revised April 2008)
- Teaching Note
Pilgrim Bank (B): Statistics Review with Data Desk
By: Frances X. Frei
Teaching Note for 602095. View Details
- September 1993 (Revised August 2011)
- Exercise
ExtendSim® Simulation Exercises in Process Analysis (B)
By: Roy D. Shapiro
Second set of exercises meant to be used with ExtendSim, a simulation package created by Imagine That, Inc. of San Jose, California, that allows students to investigate the impact of adding buffers to simple in-line processes with uncertain processing times. View Details
Shapiro, Roy D. "ExtendSim® Simulation Exercises in Process Analysis (B)." Harvard Business School Exercise 694-040, September 1993. (Revised August 2011.)
- 2006
- Chapter
Interorganizational Cooperation between Not-for-profit Organizations: A Relational Analysis
By: Julie Battilana and Metin Sengul
Battilana, Julie, and Metin Sengul. "Interorganizational Cooperation between Not-for-profit Organizations: A Relational Analysis." In Relational Perspectives in Organization Studies: A Research Companion, edited by Olympia Kyriakidou and Mustafa F. Özbilgin, 197–220. Cheltenham, U.K.: Edward Elgar Publishing, 2006.
- Article
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses
By: Kaivalya Rawal and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision-making, there has been a lot of interest in developing algorithms which can provide recourses to affected individuals. While developing such tools is important, it is even more critical to... View Details
Rawal, Kaivalya, and Himabindu Lakkaraju. "Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses." Advances in Neural Information Processing Systems (NeurIPS) 33 (2020).