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(836)
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Show Results For
- All HBS Web
(836)
- News (79)
- Research (641)
- Events (14)
- Multimedia (4)
- Faculty Publications (634)
- 2021
- Working Paper
Impact Investing: A Theory of Financing Social Enterprises
By: Benjamin N. Roth
I present a model of financing social enterprises to delineate the role of impact investors relative to “pure” philanthropists. I characterize the optimal scale and structure of a social enterprise when financed by grants, and when financed by investments. Impact... View Details
Roth, Benjamin N. "Impact Investing: A Theory of Financing Social Enterprises." Harvard Business School Working Paper, No. 20-078, February 2020. (Revised June 2021.)
- Article
Quantile Evaluation, Sensitivity to Bracketing, and Sharing Business Payoffs
By: Y. Grushka-Cockayne, K. C. Lichtendahl, V.R.R. Jose and R.L. Winkler
From forecasting competitions to conditional value-at-risk requirements, the use of multiple quantile assessments is growing in practice. To evaluate them, we use a rule from the general class of proper scoring rules for a forecaster’s multiple quantiles of a single... View Details
Grushka-Cockayne, Y., K. C. Lichtendahl, V.R.R. Jose, and R.L. Winkler. "Quantile Evaluation, Sensitivity to Bracketing, and Sharing Business Payoffs." Operations Research 65, no. 3 (May–June 2017): 712–728.
- January 2000
- Article
Maxmin Expected Utility through Statewise Combinations
By: Ramon Casadesus-Masanell, Peter Klibanoff and Emre Ozdenoren
This paper provides an axiomatic foundation for a maxmin expected utility over a set of priors (MMEU) decision rule in an environment where the elements of choice are Savage acts. The key axioms are stated using statewise combinations as in Gul (1992). View Details
Casadesus-Masanell, Ramon, Peter Klibanoff, and Emre Ozdenoren. "Maxmin Expected Utility through Statewise Combinations." Economics Letters 66, no. 1 (January 2000): 49–54.
- March 2016 (Revised January 2020)
- Teaching Note
Behavioural Insights Team (A) and (B)
By: Michael Luca and Patrick Rooney
The Behavioural Insights Team case introduces students to the concept of choice architecture and the value of experimental methods (sometimes called A/B testing) within organizational contexts. The exercise provides an opportunity for students to apply these principles... View Details
- March 2011 (Revised April 2021)
- Case
The Whiz Kids
By: Tom Nicholas and David Chen
In October 1945, Henry Ford II received a telegram in his office at the Ford Motor Company in Dearborn, Michigan written by Charles "Tex" Thornton, a U.S. Air Force colonel. The telegram presented an opportunity for Ford to deploy a system of statistical control which... View Details
Keywords: Ford Motor Company; Statistical Control; Management Systems; Accounting; Operations; Strategy; Mathematical Methods; Auto Industry; United States
Nicholas, Tom, and David Chen. "The Whiz Kids." Harvard Business School Case 811-042, March 2011. (Revised April 2021.)
- 2021
- Article
Aggregate Advertising Expenditure in the U.S. Economy: Measurement and Growth Issues in the Digital Era
By: Alvin J. Silk and Ernst R. Berndt
The two components of the advertising industry—the creative sector that develops and produces messages, and the communications sector that transmits messages via various media—have each been greatly affected by advances in creative design and communications... View Details
Keywords: Industry Evolution; Advertising; Spending; Measurement and Metrics; Mathematical Methods; Media; Advertising Industry; United States
Silk, Alvin J., and Ernst R. Berndt. "Aggregate Advertising Expenditure in the U.S. Economy: Measurement and Growth Issues in the Digital Era." Foundations and Trends® in Marketing 15, no. 1 (2021): 1–85.
- Article
On Market Timing and Investment Performance Part II: Statistical Procedures for Evaluating Forecasting Skills
By: Robert C. Merton and Roy D. Henriksson
Merton, Robert C., and Roy D. Henriksson. "On Market Timing and Investment Performance Part II: Statistical Procedures for Evaluating Forecasting Skills." Journal of Business 54, no. 4 (October 1981): 513–533.
- November 2007
- Background Note
Bayesian Estimation & Black-Litterman
By: Joshua D. Coval and Erik Stafford
Describes a practical method for asset allocation that is more robust to estimation errors than the traditional implementation of mean-variance optimization with sample means and covariances. The Bayesian inspired Black-Litterman model is described after introducing... View Details
Coval, Joshua D., and Erik Stafford. "Bayesian Estimation & Black-Litterman." Harvard Business School Background Note 208-085, November 2007.
- 01 Mar 2016
- News
Faculty Q&A: Price Check
How did you come to focus on algorithmic pricing? In my doctoral work at MIT, I was studying optimization, probability, and machine learning, which are essentially mathematical tools that enable us to use data to make better decisions.... View Details
- 01 Oct 1999
- News
Eight Among Many: Nancy J. Karch
Nancy Karch admits that when she arrived at Soldiers Field she had "almost no understanding of business." While pursuing a doctorate in mathematics at Northeastern University, she "stumbled upon the idea of business school" when she... View Details
Keywords: Susan Young
- 1992
- Chapter
Thinking Coalitionally: Party Arithmetic, Process Opportunism, and Strategic Sequencing
By: James K. Sebenius and David Lax
- 2024
- Working Paper
Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference
By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov
Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to... View Details
Lindon, Michael, Dae Woong Ham, Martin Tingley, and Iavor I. Bojinov. "Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference." Harvard Business School Working Paper, No. 24-060, March 2024.
- 2023
- Article
Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability
By: Usha Bhalla, Suraj Srinivas and Himabindu Lakkaraju
With the increased deployment of machine learning models in various real-world applications, researchers and practitioners alike have emphasized the need for explanations of model behaviour. To this end, two broad strategies have been outlined in prior literature to... View Details
Bhalla, Usha, Suraj Srinivas, and Himabindu Lakkaraju. "Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- May 2020
- Article
Scalable Holistic Linear Regression
By: Dimitris Bertsimas and Michael Lingzhi Li
We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting... View Details
Bertsimas, Dimitris, and Michael Lingzhi Li. "Scalable Holistic Linear Regression." Operations Research Letters 48, no. 3 (May 2020): 203–208.
- March 2022
- Article
Sensitivity Analysis of Agent-based Models: A New Protocol
By: Emanuele Borgonovo, Marco Pangallo, Jan Rivkin, Leonardo Rizzo and Nicolaj Siggelkow
Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such... View Details
Keywords: Agent-based Modeling; Sensitivity Analysis; Design Of Experiments; Total Order Sensitivity Indices; Organizations; Behavior; Decision Making; Mathematical Methods
Borgonovo, Emanuele, Marco Pangallo, Jan Rivkin, Leonardo Rizzo, and Nicolaj Siggelkow. "Sensitivity Analysis of Agent-based Models: A New Protocol." Computational and Mathematical Organization Theory 28, no. 1 (March 2022): 52–94.
- November 1990 (Revised August 1996)
- Background Note
Sampling and Statistical Inference
An introduction to sampling and statistical inference that covers the main concepts (confidence intervals, tests of statistical significance, choice of sample size) that are needed in making inferences about a population mean or percent. Includes discussion of problems... View Details
Schleifer, Arthur, Jr. "Sampling and Statistical Inference." Harvard Business School Background Note 191-092, November 1990. (Revised August 1996.)
- January 2008 (Revised April 2008)
- Teaching Note
Pilgrim Bank (C): Statistics Review with Data Desk
By: Frances X. Frei
Teaching Note for [602103]. View Details
- 2008
- Working Paper
Unravelling in Two-Sided Matching Markets and Similarity of Preferences
By: Hanna Halaburda
This paper investigates the causes and welfare consequences of unravelling in two-sided matching markets. It shows that similarity of preferences is an important factor driving unravelling. In particular, it shows that under the ex-post stable mechanism (the mechanism... View Details
Halaburda, Hanna. "Unravelling in Two-Sided Matching Markets and Similarity of Preferences." Harvard Business School Working Paper, No. 09-068, November 2008.
- May 2007 (Revised March 2008)
- Background Note
Basic Techniques for the Analysis of Customer Information Using Excel 2003: A Step-by-Step Approach
By: Francisco de Asis Martinez-Jerez
Provides a set of easy, step-by-step guides for some analytical techniques that are useful in the analysis of cases discussed in the course "Competing and Winning Through Customer Information (CWCI)". The instructions that follow use datasets from three of the cases in... View Details
Martinez-Jerez, Francisco de Asis. "Basic Techniques for the Analysis of Customer Information Using Excel 2003: A Step-by-Step Approach." Harvard Business School Background Note 107-073, May 2007. (Revised March 2008.)