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- 2025
- Working Paper
Crossing the Design-Use Divide: How Process Manipulation Shapes the Design and Use of AI
By: Rebecca Karp
Existing literature often separates research on the design of innovations from their implementation and use, neglecting the role of selection—how organizations choose which innovations to implement. Although scholars suggest scientific approaches for selecting novel... View Details
Keywords: Decision Choices and Conditions; Technology Adoption; Groups and Teams; Prejudice and Bias
Karp, Rebecca. "Crossing the Design-Use Divide: How Process Manipulation Shapes the Design and Use of AI." Harvard Business School Working Paper, No. 25-034, January 2025.
- 2025
- Working Paper
Home Sweet Home: How Much Do Employees Value Remote Work?
By: Zoë B. Cullen, Bobak Pakzad-Hurson and Ricardo Perez-Truglia
We estimate the value employees place on remote work using revealed preferences in a high-stakes, real-world context, focusing on U.S. tech workers. On average, employees are willing to accept a 25% pay cut for partly or fully remote roles. Our estimates are three to... View Details
Cullen, Zoë B., Bobak Pakzad-Hurson, and Ricardo Perez-Truglia. "Home Sweet Home: How Much Do Employees Value Remote Work?" NBER Working Paper Series, No. 33383, January 2025.
- 2025
- Article
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics 43, no. 1 (2025): 256–268.
- December 5, 2024
- Article
A Consensus Definition of Creativity in Surgery: A Delphi Study Protocol
By: Alex Thabane, Tyler McKechnie, Phillip Staibano, Vikram Arora, Goran Calic, Jason W. Busse, Sameer Parpia and Mohit Bhandari
Introduction
Clear definitions are essential in science, particularly in the study of abstract phenomena like creativity. Due to its inherent complexity and domain-specific nature, the study of creativity has been complicated, as evidenced by the various... View Details
Clear definitions are essential in science, particularly in the study of abstract phenomena like creativity. Due to its inherent complexity and domain-specific nature, the study of creativity has been complicated, as evidenced by the various... View Details
Thabane, Alex, Tyler McKechnie, Phillip Staibano, Vikram Arora, Goran Calic, Jason W. Busse, Sameer Parpia, and Mohit Bhandari. "A Consensus Definition of Creativity in Surgery: A Delphi Study Protocol." PLoS ONE 19, no. 12 (December 5, 2024).
- December 2024
- Article
Respect for Improvements and Comparative Statics in Matching Markets
One of the oldest results in the theory of two-sided matching is the entry comparative static, which shows that under the Gale–Shapley deferred acceptance algorithm, adding a new agent to one side of the market makes all the agents on the other side weakly... View Details
Kominers, Scott Duke. "Respect for Improvements and Comparative Statics in Matching Markets." Journal of Mechanism and Institution Design 9, no. 1 (December 2024): 83–104.
- November 2024
- Article
Preference Externality Estimators: A Comparison of Border Approaches and IVs
By: Xi Ling, Wesley R. Hartmann and Tomomichi Amano
This paper compares two estimators—the Border Approach and an Instrumental Variable (IV) estimator—using a unified framework where identifying variation arises from “preference externalities,” following the intuition in Waldfogel (2003). We highlight two dimensions in... View Details
Ling, Xi, Wesley R. Hartmann, and Tomomichi Amano. "Preference Externality Estimators: A Comparison of Border Approaches and IVs." Management Science 70, no. 11 (November 2024): 7892–7910.
- 2024
- Working Paper
Pitfalls of Demographic Forecasts of U.S. Elections
By: Richard Calvo, Vincent Pons and Jesse M. Shapiro
Many observers have forecast large partisan shifts in the US electorate based on demographic trends. Such forecasts are appealing because demographic trends are often predictable even over long horizons. We backtest demographic forecasts using data on US elections... View Details
Keywords: Mathematical Methods; Voting; Political Elections; Trends; Forecasting and Prediction; Demographics
Calvo, Richard, Vincent Pons, and Jesse M. Shapiro. "Pitfalls of Demographic Forecasts of U.S. Elections." NBER Working Paper Series, No. 33016, October 2024.
- 2024
- Working Paper
Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python
By: Melissa Ouellet and Michael W. Toffel
This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in... View Details
Keywords: Empirical Methods; Empirical Operations; Statistical Methods And Machine Learning; Statistical Interferences; Research Analysts; Analytics and Data Science; Mathematical Methods
Ouellet, Melissa, and Michael W. Toffel. "Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python." Harvard Business School Working Paper, No. 25-010, August 2024.
- 2024
- Working Paper
The New Digital Divide
By: Mayana Pereira, Shane Greenstein, Raffaella Sadun, Prasanna Tambe, Lucia Ronchi Darre, Tammy Glazer, Allen Kim, Rahul Dodhia and Juan Lavista Ferres
We build and analyze new metrics of digital usage that leverage telemetry data collected by Microsoft during operating system updates across forty million Windows devices in U.S. households. These measures of US household digital usage are much more comprehensive than... View Details
Keywords: Mathematical Methods; Measurement and Metrics; Geographic Location; Behavior; Technology Adoption; Demographics
Pereira, Mayana, Shane Greenstein, Raffaella Sadun, Prasanna Tambe, Lucia Ronchi Darre, Tammy Glazer, Allen Kim, Rahul Dodhia, and Juan Lavista Ferres. "The New Digital Divide." NBER Working Paper Series, No. 32932, September 2024.
- 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.
- 2024
- Working Paper
People, Practices, and Productivity: A Review of New Advances in Personnel Economics
By: Mitchell Hoffman and Christopher T. Stanton
This chapter surveys recent advances in personnel economics. We begin by presenting evidence showing substantial and persistent productivity variation among workers in the same roles. We discuss new research on incentives and compensation; hiring practices; the... View Details
Hoffman, Mitchell, and Christopher T. Stanton. "People, Practices, and Productivity: A Review of New Advances in Personnel Economics." NBER Working Paper Series, No. 32849, August 2024.
- 2024
- Working Paper
Winner Take All: Exploiting Asymmetry in Factorial Designs
By: Matthew DosSantos DiSorbo, Iavor I. Bojinov and Fiammetta Menchetti
Researchers and practitioners have embraced factorial experiments to simultaneously test multiple treatments, each with different levels. With the rise of technologies like Generative AI, factorial experimentation has become even more accessible: it is easier than ever... View Details
Keywords: Factorial Designs; Fisher Randomizations; Rank Estimators; Employer Interventions; Causal Inference; Mathematical Methods; Performance Improvement
DosSantos DiSorbo, Matthew, Iavor I. Bojinov, and Fiammetta Menchetti. "Winner Take All: Exploiting Asymmetry in Factorial Designs." Harvard Business School Working Paper, No. 24-075, June 2024.
- 2024
- Article
A Universal In-Place Reconfiguration Algorithm for Sliding Cube-Shaped Robots in Quadratic Time
By: Zachary Abel, Hugo A. Akitaya, Scott Duke Kominers, Matias Korman and Frederick Stock
In the modular robot reconfiguration problem we are given n cube-shaped modules (or "robots") as well as two configurations, i.e., placements of the n modules so that their union is face-connected. The goal is to find a sequence of moves that reconfigures the modules... View Details
Abel, Zachary, Hugo A. Akitaya, Scott Duke Kominers, Matias Korman, and Frederick Stock. "A Universal In-Place Reconfiguration Algorithm for Sliding Cube-Shaped Robots in Quadratic Time." Proceedings of the International Symposium on Computational Geometry (SoCG) 40th (2024): 1:1–1:14.
- June 2024
- Article
Redistributive Allocation Mechanisms
By: Mohammad Akbarpour, Piotr Dworczak and Scott Duke Kominers
Many scarce public resources are allocated at below-market-clearing prices, and sometimes for free. Such "non-market" mechanisms sacrifice some surplus, yet they can potentially improve equity. We develop a model of mechanism design with redistributive concerns. Agents... View Details
Akbarpour, Mohammad, Piotr Dworczak, and Scott Duke Kominers. "Redistributive Allocation Mechanisms." Journal of Political Economy 132, no. 6 (June 2024): 1831–1875. (Authors' names are in certified random order.)
- 2024
- Working Paper
What Is Newsworthy? Theory and Evidence
By: Luis Armona, Matthew Gentzkow, Emir Kamenica and Jesse M. Shapiro
We study newsworthiness in theory and practice. We focus on situations in which a news outlet observes the realization of a state of the world and must decide whether to report the realization to a consumer who pays an opportunity cost to consume the report. The... View Details
Armona, Luis, Matthew Gentzkow, Emir Kamenica, and Jesse M. Shapiro. "What Is Newsworthy? Theory and Evidence." NBER Working Paper Series, No. 32512, May 2024.
- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I. Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details
Liang, Biyonka, and Iavor I. Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
- 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
- Working Paper
Design-Based Inference for Multi-arm Bandits
By: Dae Woong Ham, Iavor I. Bojinov, Michael Lindon and Martin Tingley
Multi-arm bandits are gaining popularity as they enable real-world sequential decision-making across application areas, including clinical trials, recommender systems, and online decision-making. Consequently, there is an increased desire to use the available... View Details
Ham, Dae Woong, Iavor I. Bojinov, Michael Lindon, and Martin Tingley. "Design-Based Inference for Multi-arm Bandits." Harvard Business School Working Paper, No. 24-056, March 2024.
- February 2024
- Article
Fifty Shades of QE: Robust Evidence
By: Brian Fabo, Marina Jančoková, Elisabeth Kempf and Ľuboš Pástor
Fabo et al. (2021) show that papers written by central bank researchers find quantitative easing (QE) to be more effective than papers written by academics. Weale and Wieladek (2022) show that a subset of these results lose statistical significance when OLS regressions... View Details
Keywords: Quantitative Easing; Research; Mathematical Methods; Perception; Banks and Banking; Body of Literature
Fabo, Brian, Marina Jančoková, Elisabeth Kempf, and Ľuboš Pástor. "Fifty Shades of QE: Robust Evidence." Art. 107065. Journal of Banking & Finance 159 (February 2024).
- 2024
- Working Paper
Bootstrap Diagnostics for Irregular Estimators
By: Isaiah Andrews and Jesse M. Shapiro
Empirical researchers frequently rely on normal approximations in order to summarize and communicate uncertainty about their findings to their scientific audience. When such approximations are unreliable, they can lead the audience to make misguided decisions. We... View Details
Andrews, Isaiah, and Jesse M. Shapiro. "Bootstrap Diagnostics for Irregular Estimators." NBER Working Paper Series, No. 32038, January 2024.