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(838)
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- Faculty Publications (632)
Show Results For
- All HBS Web
(838)
- News (79)
- Research (640)
- Events (14)
- Multimedia (4)
- Faculty Publications (632)
- 2006
- Chapter
Advanced Regression Models
By: Raghuram Iyengar and Sunil Gupta
Keywords: Mathematical Methods
- 1978
- Chapter
Matrix-Weighted Averages: Computation and Presentation
By: Dutch Leonard
Keywords: Mathematical Methods
Leonard, Dutch. "Matrix-Weighted Averages: Computation and Presentation." In Proceedings of the Eleventh Symposium on the Interface of Computers and Statistics, edited by Ronald A. Gallant and Thomas Michael Gerig. Raleigh, NC: North Carolina State University, Institute of Statistics, 1978.
- July 1982 (Revised March 1984)
- Background Note
Worked Examples in Dynamic Programming
By: David E. Bell
Keywords: Mathematical Methods
Bell, David E. "Worked Examples in Dynamic Programming." Harvard Business School Background Note 183-028, July 1982. (Revised March 1984.)
- 06 Apr 2020
- Working Paper Summaries
A General Theory of Identification
Keywords: by Iavor Bojinov and Guillaume Basse
- 2006
- Book
Service Productivity Management: Improving Service Performance Using Data Envelopment Analysis
By: H. David Sherman and Joe Zhu
Here is an in-depth guide to the most powerful available benchmarking technique for improving service organization performance—Data Envelopment Analysis (DEA). The book outlines DEA as a benchmarking technique, identifies high cost service units, isolates specific... View Details
Sherman, H. David, and Joe Zhu. Service Productivity Management: Improving Service Performance Using Data Envelopment Analysis. Boston, MA: Springer, 2006.
- 1991
- Chapter
An Economic Approach to the Study of Bargaining
By: A. E. Roth
Roth, A. E. "An Economic Approach to the Study of Bargaining." In Handbook of Negotiation Research. Vol. 3, edited by M. H. Bazerman, R. J. Lewicki, and B. H. Sheppard, 35–67. Research on Negotiation in Organizations. JAI Press, 1991.
- July 1982 (Revised March 1984)
- Background Note
Why Preference Curves are Useful for Risky Decisions
By: David E. Bell
Bell, David E. "Why Preference Curves are Useful for Risky Decisions." Harvard Business School Background Note 183-030, July 1982. (Revised March 1984.)
- 01 Mar 2005
- News
Robert Buzzell Remembered
wholesale distribution; strategic planning; and the application of mathematical and statistical methods to marketing issues. A member of the HBS faculty from 1961 to 1993 and chair of the Marketing faculty from 1972 to 1977, he taught... View Details
- Alumni WDYDWYD
Margaret Regan
education was definitely emphasized by my dad as a vehicle to growth and expanding my horizons. I got a BS in Mathematics and then worked in computer programming before managing the computer facility at a major company. That sounds like... View Details
- Web
Rhea Acharya | MBA
Rhea Acharya Applied Mathematics Eliot 2025 Cohort 7 Living through this unprecedented period of technological growth has presented us with both ground-breaking solutions and new challenges. As we navigate these unknowns, we must turn to... View Details
- 22 Oct 2020
- Working Paper Summaries
Estimating Causal Effects in the Presence of Partial Interference Using Multivariate Bayesian Structural Time Series Models
Keywords: by Fiammetta Menchetti and Iavor Bojinov
- 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.)
- 2018
- Working Paper
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." NBER Working Paper Series, No. 25399, December 2018.
- 1994
- Dissertation
Borderline Personality Disorder: Dimension or Category? A Maximum Covariance Analysis
By: William B. Simpson
- 2025
- Working Paper
Evaluations Amid Measurement Error: Determining the Optimal Timing for Workplace Interventions
By: Matthew DosSantos DiSorbo, Iavor I. Bojinov and Fiammetta Menchetti
Researchers have embraced factorial experiments to simultaneously evaluate multiple treatments, each with different levels. Typically, in large-scale factorial experiments, the primary objective is identifying the treatment with the largest causal effect, especially... 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. "Evaluations Amid Measurement Error: Determining the Optimal Timing for Workplace Interventions." Harvard Business School Working Paper, No. 24-075, June 2024. (Revised May 2025.)
- 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