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- 2024
- Article
Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
By: Michael Lingzhi Li and Kosuke Imai
A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today’s scientists across... View Details
- 2024
- Working Paper
AI Companions Reduce Loneliness
By: Julian De Freitas, Ahmet K Uguralp, Zeliha O Uguralp and Puntoni Stefano
Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications are... View Details
- June 2024
- Article
Oral History and Business History in Emerging Markets
By: Geoffrey Jones
This article describes the motivation, structure and use of the Creating Emerging Markets (CEM) oral history-based project at the Harvard Business School. The project consists of lengthy interviews with business leaders from emerging markets. By June 2024 183... View Details
- June 2024
- Article
Valuing the Societal Impact of Medicines and Other Health Technologies: A User Guide to Current Best Practices
By: Jason Shafrin, Jaehong Kim, Joshua T. Cohen, Louis P. Garrison, Dana A. Goldman, Jalpa A. Doshi, Joshua Krieger, Darius N. Lakdawalla, Peter J. Neumann, Charles E. Phelps, Melanie D. Whittington and Richard Willke
This study argues that value assessment conducted from a societal perspective should rely on the Generalized Cost-Effectiveness Analysis (GCEA) framework proposed herein. Recently developed value assessment inventories—such as the Second Panel on Cost-Effectiveness’s... View Details
- 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
- Working Paper
Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application
By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely... View Details
- November 2023 (Revised November 2024)
- Case
Decarbonizing Shipping at A.P. Møller-Maersk (A)
By: Willy Shih, Michael W. Toffel and Kelsey Carter
Container shipping was responsible for moving more than 80% of globally traded goods, and almost 3% of global greenhouse gas emissions. A.P. Møller-Maersk, one of the top three container lines, conducted an extensive lifecycle assessment (LCA) of alternative fuels,... View Details
- November–December 2023
- Article
Iterative Coordination and Innovation: Prioritizing Value over Novelty
By: Sourobh Ghosh and Andy Wu
An innovating organization faces the challenge of how to prioritize distinct goals of novelty and value, both of which underlie innovation. Popular practitioner frameworks like Agile management suggest that organizations can adopt an iterative approach of frequent... View Details
- October 2023
- Case
Prime Coalition: Estimating Climate Impact
A case on CRANE, a tool to help investors and green technology companies estimate the future climate impact of new technologies and products, called emissions reduction potential (ERP). The case includes material on CRANE’s methodology for estimating future carbon... View Details
- September–October 2023
- Article
Prospective Evaluation of the Cost of Performing Breast Imaging Examinations Using Time-Driven Activity-Based Costing Method: A Single Center Study
By: Aamir Ali, Jordana Phillips, Damir Ljuboja, Syed S. Shehab, Etta D. Pisano, Robert S. Kaplan and Ammar Sarwar
We use time-driven activity-based costing (TDABC) to measure the cost of performing breast imaging using different modalities: full-field digital mammography (FFDM), digital breast tomosynthesis (DBT), contrast-enhanced mammography (CEM), US and MRI exams, and... View Details
- 2024
- Working Paper
Anti-Political-Establishment Citizens: An In-Depth Study from Two Latin American Countries
By: Loreto Cox and Natalia Garbiras-Diaz
Building on citizens’ animosity towards politicians, anti-establishment parties and
candidates have achieved significant electoral success. While recent studies examine
the supply-side, we know little about what drives citizens’ anti-establishment sentiments and how... 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
- June 2023
- Case
Barton Malow: Building From the Top-Down
By: Hise O. Gibson and Alicia Dadlani
In 2023, Detroit-based Barton Malow completed the first high-rise building in the U.S. built from the top-down using LIFTbuild, a patented methodology that aimed to make construction safer and more efficient. By completing building work at ground level and then... 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
Teams in the Digital Workplace: Technology's Role for Communication, Collaboration, and Performance
By: Jacqueline N. Lane, Paul Leonardi, Noshir Contractor and Leslie DeChurch
This paper addresses the need for theoretical advancements in understanding team processes and the impact of technology on teams. Specifically, it examines the use of digital collaboration technologies by organizational teams and their effect on team communication and... View Details
- 2023
- Working Paper
The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities
By: David S. Scharfstein and Sergey Chernenko
We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement bias in... View Details
- April 2023
- Article
The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences
By: Armin Falk, Anke Becker, Thomas Dohmen, David B. Huffman and Uwe Sunde
Incentivized choice experiments are a key approach to measuring preferences in economics but are also costly. Survey measures are a low-cost alternative but can suffer from additional forms of measurement error due to their hypothetical nature. This paper seeks to... 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
- February 2023
- Article
Climate Solutions Investments
By: Alex Cheema-Fox, George Serafeim and Hui (Stacie) Wang
An increasing number of companies are providing products and services that help reduce carbon emissions in the economy. We develop a methodology to identify those companies and create a sample of publicly listed climate solutions companies allowing us to study their... View Details
- 2023
- Article
Experimental Evaluation of Individualized Treatment Rules
By: Kosuke Imai and Michael Lingzhi Li
The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a... View Details