Publications
Publications
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- All HBS Web
(2,608)
- Faculty Publications (789)
- 2023
- Working Paper
Channeled Attention and Stable Errors
By: Tristan Gagnon-Bartsch, Matthew Rabin and Joshua Schwartzstein
We develop a framework for assessing when somebody will eventually notice that she has
a misspecified model of the world, premised on the idea that she neglects information that
she deems—through the lens of her misconceptions—to be irrelevant. In doing so, we... View Details
- 2023
- Working Paper
How People Use Statistics
By: Pedro Bordalo, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer
We document two new facts about the distributions of answers in famous statistical problems: they are i) multi-modal and ii) unstable with respect to irrelevant changes in the problem. We offer a model in which, when solving a problem, people represent each hypothesis... View Details
- 2023
- Article
Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten
By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details
- July–August 2023
- Article
Accounting for Carbon Offsets
By: Robert S. Kaplan, Karthik Ramanna and Marc Roston
Markets for carbon trading function poorly, and many traded offsets do not actually perform as promised. Without robust protocols for monitoring offsets and in the absence of proper accounting mechanisms, market-based approaches to reducing atmospheric GHG will be... View Details
- 2023
- Chapter
Inflation and Misallocation in New Keynesian Models
By: Alberto Cavallo, Francesco Lippi and Ken Miyahara
The New Keynesian framework implies that sluggish price adjustment results in a distorted allocation of resources. We use a simple model to quantify these unobservable distortions, using data that depict the price-setting behavior of firms, specifically the frequency... View Details
- 2023
- Working Paper
The Complexity of Economic Decisions
By: Xavier Gabaix and Thomas Graeber
We propose a theory of the complexity of economic decisions. Leveraging a macroeconomic framework of production functions, we conceptualize the mind as a cognitive economy, where a task’s complexity is determined by its composition of cognitive operations. Complexity... View Details
- 2023
- Working Paper
Auditing Predictive Models for Intersectional Biases
By: Kate S. Boxer, Edward McFowland III and Daniel B. Neill
Predictive models that satisfy group fairness criteria in aggregate for members of a protected class, but do not guarantee subgroup fairness, could produce biased predictions for individuals at the intersection of two or more protected classes. To address this risk, we... View Details
- 2023
- Working Paper
ESG: From Process to Product
By: George Serafeim
ESG measurement, analysis, management, and communication is a process that the financial industry has turned into a product, resulting in many investment funds using the ESG label. This has caused confusion, generating demand for a framework that defines... View Details
- May 2023
- Article
Equilibrium Effects of Pay Transparency
By: Zoë B. Cullen and Bobak Pakzad-Hurson
The public discourse around pay transparency has focused on the direct effect: how workers seek
to rectify newly-disclosed pay inequities through renegotiations. The question of how wage-setting
and hiring practices of the firm respond in equilibrium has received... View Details
Keywords: Pay Transparency; Online Labor Market; Privacy; Wage Gap; Corporate Disclosure; Wages; Negotiation
- 2023
- Article
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju
As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means... View Details
- April 2023
- Technical Note
An Art & A Science: How to Apply Design Thinking to Data Science Challenges
By: Michael Parzen, Eddie Lin, Douglas Ng and Jessie Li
We hear it all the time as managers: “what is the data that backs up your decisions?” Even local mom-and-pop shops now have access to complex point-of-sale systems that can closely track sales and customer data. Social media influencers have turned into seven-figure... View Details
- 2023
- Case
Christiana Figueres and the Collaborative Approach to Negotiating Climate Action
By: James K. Sebenius, Laurence A. Green, Hannah Riley-Bowles, Lara SanPietro and Mina Subramanian
This case study centers on Harvard’s Program on Negotiation 2022 Great Negotiator, Christiana Figueres, and her efforts as Executive Secretary of the United Nations Framework Convention on Climate Change (UNFCCC) to build momentum for, and ultimately pass, the 2015... View Details
- March–April 2023
- Article
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in... View Details
- April 2023
- Article
The Subjective Expected Utility Approach and a Framework for Defining Project Risk in Terms of Novelty and Feasibility—A Response to Franzoni and Stephan (2023), ‘Uncertainty and Risk-Taking in Science’
In their Discussion Paper, Franzoni and Stephan (F&S, 2023) discuss the shortcomings of existing peer review models in shaping the funding of risky science. Their discussion offers a conceptual framework for incorporating risk into peer review models of research... View Details
- March 2023
- Background Note
A Primer on OKRs
By: Suraj Srinivasan and Li-Kuan (Jason) Ni
The OKR framework is a popular goal-setting and strategy execution tool that uses goal setting through “Objectives” and measuring performance using “Key Results” on a periodic basis to measure and drive performance. The OKR framework has been adopted and practiced at... View Details
Keywords: Business Organization; Talent and Talent Management; Framework; Corporate Governance; Goals and Objectives; Growth and Development; Growth and Development Strategy; Growth Management; Management Analysis, Tools, and Techniques; Management Practices and Processes; Management Skills; Management Systems; Measurement and Metrics; Outcome or Result; Performance Effectiveness; Performance Evaluation; Performance Expectations; Performance Productivity; Performance Efficiency
- March 2023 (Revised March 2025)
- Module Note
LCA Module Overview: Society
By: Nien-hê Hsieh
Leadership and Corporate and Accountability (LCA) is a required course in the first-year MBA curriculum at Harvard Business School to help managers determine and deliver on their economic, legal, and ethical responsibilities. This note summarizes the cases and outlines... View Details
- 2023
- Working Paper
Remote Work across Jobs, Companies, and Space
By: Stephen Hansen, Peter John Lambert, Nick Bloom, Steven J. Davis, Raffaella Sadun and Bledi Taska
The pandemic catalyzed an enduring shift to remote work. To measure and characterize
this shift, we examine more than 250 million job vacancy postings across five
English-speaking countries. Our measurements rely on a state-of-the-art language-processing
framework... View Details
- March–April 2023
- Article
Market Segmentation Trees
By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market... View Details
- March 2023
- Article
Reaching for Rigor and Relevance: Better Marketing Research for a Better World
By: Shilpa Madan, Gita Venkataramani Johar, Jonah Berger, Pierre Chandon, Rajesh Chandy, Rebecca Hamilton, Leslie John, Aparna Labroo, Peggy J. Liu, John G. Lynch, Nina Mazar, Nicole Mead, Vikas Mittal, Christine Moorman, Michael I. Norton, John Roberts, Dilip Soman, Madhu Viswanathan and Katherine White
Over the past several decades, scholars have highlighted the obligations and opportunities for marketing as a discipline to play a role in creating a better world — or risk becoming irrelevant for the largest problems facing consumers and society. Climate change,... View Details
- 2023
- Working Paper
Distributionally Robust Causal Inference with Observational Data
By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li
We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first... View Details