Publications
Publications
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- All HBS Web
(2,936)
- Faculty Publications (976)
- July 2023
- Article
Takahashi-Alexander Revisited: Modeling Private Equity Portfolio Outcomes Using Historical Simulations
By: Dawson Beutler, Alex Billias, Sam Holt, Josh Lerner and TzuHwan Seet
In 2001, Dean Takahashi and Seth Alexander of the Yale University Investments Office developed a deterministic model for estimating future cash flows and valuations for the Yale endowment’s private equity portfolio. Their model, which is simple and intuitive, is still... 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
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details
- June 2023
- Case
Tractor Supply Co
By: David L. Ager and Michael A. Roberto
In February 2023, Hal Lawton, CEO of Tractor Supply Co, the largest farm and ranch retailer in the United States reflected on the company’s 70% growth between 2019 and 2022. Economists had begun to predict an economic downturn and experts were predicting softening... View Details
- 2023
- Working Paper
Evaluation and Learning in R&D Investment
By: Alexander P. Frankel, Joshua L. Krieger, Danielle Li and Dimitris Papanikolaou
We examine the role of spillover learning in shaping the value of exploratory versus incremental
R&D. Using data from drug development, we show that novel drug candidates generate more
knowledge spillovers than incremental ones. Despite being less likely to reach... View Details
- June 2023
- Case
Accounting for Loan Losses at JPMorgan Chase: Predicting Credit Costs
By: Jonas Heese, Jung Koo Kang and James Weber
The case examines the accounting for loan losses at a large bank, how a bank sets its Allowance for Loan and Lease Losses (ALLL) on its financial statements. ALLL, and the rules that set them, determine when banks would and would not extend loans, which significantly... 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
- Article
Provable Detection of Propagating Sampling Bias in Prediction Models
By: Pavan Ravishankar, Qingyu Mo, Edward McFowland III and Daniel B. Neill
With an increased focus on incorporating fairness in machine learning models, it becomes imperative not only to assess and mitigate bias at each stage of the machine learning pipeline but also to understand the downstream impacts of bias across stages. Here we consider... View Details
- June 2023
- Article
When Does Uncertainty Matter? Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making
By: Sean McGrath, Parth Mehta, Alexandra Zytek, Isaac Lage and Himabindu Lakkaraju
As machine learning (ML) models are increasingly being employed to assist human decision
makers, it becomes critical to provide these decision makers with relevant inputs which can
help them decide if and how to incorporate model predictions into their decision... View Details
- May 2023 (Revised November 2023)
- Case
Arcos Dorados: Decarbonizing McDonald's in Latin America
By: George Serafeim, Michael W. Toffel, Jenyfeer Martinez Buitrago and Mariana Cal
This case describes the decarbonization strategy of Arcos Dorados—McDonald’s largest independent franchisee, operating in 20 countries and territories in Latin America and the Caribbean—and how the company measured its greenhouse gas (GHG) emissions, including those... View Details
Keywords: Environmental Accounting; Animal-Based Agribusiness; Plant-Based Agribusiness; Change Management; Forecasting and Prediction; Environmental Sustainability; Food; Growth Management; Supply Chain; Corporate Social Responsibility and Impact; Strategy; Agriculture and Agribusiness Industry; Food and Beverage Industry; Green Technology Industry; Consumer Products Industry; Latin America; North and Central America; South America
- May 11, 2020
- Article
Steer Your Family Businesses Through an Unplanned Transition
By: Josh Baron and Nick Di Loreto
In a perfect world, family businesses will transition leadership from one generation to the next along a predictable and well-planned process — whether that’s determined within the business, the ownership group, or the family itself — passing the baton after years of... View Details
- 2023
- Article
Conduit Incentives: Eliciting Cooperation from Workers Outside of Managers' Control
By: Susanna Gallani
Can managers use monetary incentives to elicit cooperation from workers they cannot reward for their efforts? I study “conduit incentives,” an innovative incentive design, whereby managers influence bonus-ineligible workers’ effort by offering bonus-eligible employees... View Details
Keywords: Organizational Behavior Modification; Peer Monitoring; Persistence Of Performance Improvements; Crowding Out; Implicit Incentives; Compensation; Healthcare; Social Pressure; Image Motivation; Incentives; Motivation; Performance; Behavior; Motivation and Incentives; Compensation and Benefits; Governing Rules, Regulations, and Reforms; Organizational Culture; Health Industry; California
- 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
- May 2023
- Article
Incentive Effects of Subjective Allocations of Rewards and Penalties
By: Wei Cai, Susanna Gallani and Jee-Eun Shin
We examine the incentive effects of subjectivity in allocating tournament-based rewards and punishments. We use data from a company where reward and punishment decisions are based on a combination of objective metrics and subjective performance assessments. Rankings... View Details
- 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 21, 2023
- Article
When Scenario Planning Fails
By: Kalle Heikkinen, William R. Kerr, Mika Malin, Panu Routila and Eemil Rupponen
How can organizations perform scenario planning when they are hit by shocks outside of leaders’ field of vision? Interviews with Nordic executives, who experienced both the Covid-19 pandemic and were in close proximity to Russia as the country invaded Ukraine, can... View Details
- April 12, 2023
- Article
Using AI to Adjust Your Marketing and Sales in a Volatile World
By: Das Narayandas and Arijit Sengupta
Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer... View Details
- 2023
- Working Paper
Feature Importance Disparities for Data Bias Investigations
By: Peter W. Chang, Leor Fishman and Seth Neel
It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection... View Details
- April 2023
- Article
Learning Down to Train Up: Mentors Are More Effective When They Value Insights from Below
By: Ting Zhang, Dan Wang and Adam D. Galinsky
Although mentorship is vital for individual success, potential mentors often view it as a costly burden. To understand what motivates mentors to overcome this barrier and more fully engage with their mentees, we introduce a new construct, learning direction, which... View Details
- April 2023
- Article
On the Privacy Risks of Algorithmic Recourse
By: Martin Pawelczyk, Himabindu Lakkaraju and Seth Neel
As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely beneficial to affected... View Details