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- Faculty Publications (568)
Show Results For
- All HBS Web (618)
- Faculty Publications (568)
- January 2010
- Journal Article
A Choice Prediction Competition: Choices from Experience and from Description
By: Ido Erev, Eyal Ert, Alvin E. Roth, Ernan E. Haruvy, Stefan Herzog, Robin Hau, Ralph Hertwig, Terrence Steward, Robert West and Christian Lebiere
Erev, Ert, and Roth organized three choice prediction competitions focused on three related choice tasks: one-shot decisions from description (decisions under risk), one-shot decisions from experience, and repeated decisions from experience. Each competition was based... View Details
Keywords: Experience and Expertise; Decision Choices and Conditions; Forecasting and Prediction; Mathematical Methods; Risk and Uncertainty; Competition
Erev, Ido, Eyal Ert, Alvin E. Roth, Ernan E. Haruvy, Stefan Herzog, Robin Hau, Ralph Hertwig, Terrence Steward, Robert West, and Christian Lebiere. "A Choice Prediction Competition: Choices from Experience and from Description." Special Issue on Decisions from Experience. Journal of Behavioral Decision Making 23, no. 1 (January 2010).
- Web
PhD Programs - Doctoral
requirements and curriculum, read student profiles as well as student research , and placement information. The PhD in Business Administration grounds students in the disciplinary theories and research methods that form the foundation of... View Details
- 2022
- Article
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.
By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a... View Details
Keywords: Machine Learning Models; Counterfactual Explanations; Adversarial Examples; Mathematical Methods
Pawelczyk, Martin, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, and Himabindu Lakkaraju. "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
- September–October 2023
- Article
Interpretable Matrix Completion: A Discrete Optimization Approach
By: Dimitris Bertsimas and Michael Lingzhi Li
We consider the problem of matrix completion on an n × m matrix. We introduce the problem of interpretable matrix completion that aims to provide meaningful insights for the low-rank matrix using side information. We show that the problem can be... View Details
Keywords: Mathematical Methods
Bertsimas, Dimitris, and Michael Lingzhi Li. "Interpretable Matrix Completion: A Discrete Optimization Approach." INFORMS Journal on Computing 35, no. 5 (September–October 2023): 952–965.
- November 2021
- Article
Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective
By: Iavor Bojinov, Ashesh Rambachan and Neil Shephard
In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative... View Details
Keywords: Panel Data; Dynamic Causal Effects; Potential Outcomes; Finite Population; Nonparametric; Mathematical Methods
Bojinov, Iavor, Ashesh Rambachan, and Neil Shephard. "Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective." Quantitative Economics 12, no. 4 (November 2021): 1171–1196.
- 2021
- Working Paper
How Much Should We Trust Staggered Difference-In-Differences Estimates?
By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
Difference-in-differences analysis with staggered treatment timing is frequently used to assess the impact of policy changes on corporate outcomes in academic research. However, recent advances in econometric theory show that such designs are likely to be biased in the... View Details
Keywords: Difference In Differences; Staggered Difference-in-differences Designs; Generalized Difference-in-differences; Dynamic Treatment Effects; Mathematical Methods
Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" European Corporate Governance Institute Finance Working Paper, No. 736/2021, February 2021. (Harvard Business School Working Paper, No. 21-112, April 2021.)
- 2023
- Working Paper
PRIMO: Private Regression in Multiple Outcomes
By: Seth Neel
We introduce a new differentially private regression setting we call Private Regression in Multiple Outcomes (PRIMO), inspired the common situation where a data analyst wants to perform a set of l regressions while preserving privacy, where the covariates... View Details
Neel, Seth. "PRIMO: Private Regression in Multiple Outcomes." Working Paper, March 2023.
- April 2021
- Article
A Model of Multi-Pass Search: Price Search Across Stores and Time
By: Navid Mojir and K. Sudhir
In retail settings with price promotions, consumers often search across stores and time. However, the search literature typically only models one pass search across stores, ignoring revisits to stores; the choice literature using scanner data has modeled search across... View Details
Keywords: Consumer Search; Multi-pass Search; Price Search; Store Search; Spatial Search; Temporal Search; Spatiotemporal Search; Dynamic Structural Models; MPEC; Price Promotions; Store Loyalty; Consumer Behavior; Price; Spending; Marketing; Mathematical Methods
Mojir, Navid, and K. Sudhir. "A Model of Multi-Pass Search: Price Search Across Stores and Time." Management Science 67, no. 4 (April 2021): 2126–2150.
- Article
Wealth-Making in Nineteenth and Early Twentieth Century Britain: Industry v. Commerce and Finance
By: Tom Nicholas
This paper refutes the hypothesis put forward by W.D. Rubinstein that a disproportionately large share of Britain's wealth makers were active in commercial and financial trades in London. We use a data set of businessmen active in nineteenth- and early... View Details
Keywords: Trade; Finance; Commercialization; Mathematical Methods; Wealth and Poverty; Great Britain; London
Nicholas, Tom. "Wealth-Making in Nineteenth and Early Twentieth Century Britain: Industry v. Commerce and Finance." Business History 41, no. 1 (January 1999).
- 2019
- Article
Time Series Experiments and Causal Estimands: Exact Randomization Tests and Trading
By: Iavor I Bojinov and Neil Shephard
We define causal estimands for experiments on single time series, extending the potential outcome framework to dealing with temporal data. Our approach allows the estimation of a broad class of these estimands and exact randomization based p-values for testing causal... View Details
Bojinov, Iavor I., and Neil Shephard. "Time Series Experiments and Causal Estimands: Exact Randomization Tests and Trading." Journal of the American Statistical Association 114, no. 528 (2019): 1665–1682.
- May 2017
- Article
Agent-based Modeling: A Guide for Social Psychologists
By: Joshua Conrad Jackson, David Rand, Kevin Lewis, Michael I. Norton and Kurt Gray
Agent-based modeling is a longstanding but underused method that allows researchers to simulate artificial worlds for hypothesis testing and theory building. Agent-based models (ABMs) offer unprecedented control and statistical power by allowing researchers to... View Details
Jackson, Joshua Conrad, David Rand, Kevin Lewis, Michael I. Norton, and Kurt Gray. "Agent-based Modeling: A Guide for Social Psychologists." Social Psychological & Personality Science 8, no. 4 (May 2017): 387–395.
- 2010
- Other Unpublished Work
Modeling Passenger Travel and Delays in the National Air Transportation System
Many of the existing methods for evaluating an airline's on-time performance are based on flight-centric measures of delay. However, recent research has demonstrated that passenger delays depend on many factors in addition to flight delays. For instance,... View Details
- 2024
- Working Paper
Modest Victims: Victims Who Decline to Broadcast Their Victimization Are Seen As Morally Virtuous
By: Nathan Dhaliwal, Jillian J. Jordan and Pat Barclay
What do people think of victims who conceal their victimhood? We propose that the decision to not broadcast that one has been victimized serves as a costly act of modesty—in doing so, one is potentially forgoing social support and compensation from one’s community. We... View Details
Dhaliwal, Nathan, Jillian J. Jordan, and Pat Barclay. "Modest Victims: Victims Who Decline to Broadcast Their Victimization Are Seen As Morally Virtuous." Working Paper, August 2024.
- January 2008
- Background Note
Equity Options
By: Joshua Coval and Erik Stafford
The goal of this simulation is to understand the reliance of option values on volatility. When an investor trades an option, they are essentially trading volatility. Therefore, much of the focus in this lesson is on forecasting volatility. Students are able to use two... View Details
Keywords: Volatility; Forecasting and Prediction; Stock Options; Investment Return; Price; Market Transactions; Mathematical Methods; Value
Coval, Joshua, and Erik Stafford. "Equity Options." Harvard Business School Background Note 208-118, January 2008.
- 2014
- Working Paper
Search-Based Peer Firms: Aggregating Investor Perceptions Through Internet Co-Searches
By: Charles M.C. Lee, Paul Ma and Charles C.Y. Wang
Applying a "co-search" algorithm to Internet traffic at the SEC's EDGAR web-site, we develop a novel method for identifying economically-related peer firms and for measuring their relative importance. Our results show that firms appearing in chronologically adjacent... View Details
Keywords: Peer Firm; EDGAR Search Traffic; Revealed Preference; Co-search; Industry Classification; Analytics and Data Science; Internet and the Web; Mathematical Methods; Corporate Finance
Lee, Charles M.C., Paul Ma, and Charles C.Y. Wang. "Search-Based Peer Firms: Aggregating Investor Perceptions Through Internet Co-Searches." Harvard Business School Working Paper, No. 13-048, November 2012. (Revised September 2013, March 2014, June 2014, July 2014.)
- August 2019
- Article
When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation
By: Yicheng Song, Nachiketa Sahoo and Elie Ofek
Sometimes we desire change, a break from the same or an opportunity to fulfill different aspects of our needs. Noting that consumers seek variety, several approaches have been developed to diversify items recommended by personalized recommender systems. However,... View Details
Keywords: Recommender Systems; Personalization; Recommendation Diversity; Variety Seeking; Collaborative Filtering; Consumer Utility Models; Digital Media; Clickstream Analysis; Learning-to-rank; Consumer Behavior; Media; Customization and Personalization; Strategy; Mathematical Methods
Song, Yicheng, Nachiketa Sahoo, and Elie Ofek. "When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation." Management Science 65, no. 8 (August 2019): 3737–3757.
- 2016
- Article
Penalized Fast Subset Scanning
By: Skyler Speakman, Sriram Somanchi, Edward McFowland III and Daniel B. Neill
We present the penalized fast subset scan (PFSS), a new and general framework for scalable and accurate pattern detection. PFSS enables exact and efficient identification of the most anomalous subsets of the data, as measured by a likelihood ratio scan statistic.... View Details
Keywords: Disease Surveillance; Likelihood Ratio Statistic; Pattern Detection; Scan Statistic; Mathematical Methods
Speakman, Skyler, Sriram Somanchi, Edward McFowland III, and Daniel B. Neill. "Penalized Fast Subset Scanning." Journal of Computational and Graphical Statistics 25, no. 2 (2016): 382–404. (Selected for “Best of JCGS” invited session by the journal’s editor in chief.)
- Forthcoming
- Article
Slowly Varying Regression Under Sparsity
By: Dimitris Bertsimas, Vassilis Digalakis Jr, Michael Lingzhi Li and Omar Skali Lami
We consider the problem of parameter estimation in slowly varying regression models with sparsity constraints. We formulate the problem as a mixed integer optimization problem and demonstrate that it can be reformulated exactly as a binary convex optimization problem... View Details
Bertsimas, Dimitris, Vassilis Digalakis Jr, Michael Lingzhi Li, and Omar Skali Lami. "Slowly Varying Regression Under Sparsity." Operations Research (forthcoming). (Pre-published online March 27, 2024.)
- 2010
- Working Paper
Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans
By: Doug J. Chung, Thomas J. Steenburgh and K. Sudhir
We estimate a dynamic structural model of sales force response to a bonus based compensation plan. The paper has two main methodological innovations: First, we implement empirically the method proposed by Arcidiacono and Miller (2010) to accommodate unobserved latent... View Details
Keywords: Compensation and Benefits; Performance Productivity; Mathematical Methods; Salesforce Management; Motivation and Incentives
Chung, Doug J., Thomas J. Steenburgh, and K. Sudhir. "Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans." Harvard Business School Working Paper, No. 11-041, October 2010.
- 12 Mar 2008
- Working Paper Summaries
Allocating Marketing Resources
Keywords: by Sunil Gupta & Thomas J. Steenburgh