Browse or search publications from faculty affiliated with the lab.
Presidential Address: The Economist as Designer in the Innovation Process for Socially Impactful Digital Products
This paper provides an economic perspective on data-driven innovation in digital products, focusing on the role of complex experiments in measuring and improving social impact. The discussion highlights how tools and insights from economics…
Service Quality on Online Platforms: Empirical Evidence about Driving Quality at Uber
Online marketplaces have adopted new quality control mechanisms that can accommodate a flexible pool of providers. In the context of ride-hailing, we measure the effectiveness of these mechanisms, which include ratings, incentives, and behavioral…
Estimating Wage Disparities Using Foundation Models
One thread of empirical work in social science focuses on decomposing group differences in outcomes into unexplained components and components explained by observable factors. In this paper, we study gender wage decompositions, which require…
LABOR-LLM: Language-Based Occupational Representations with Large Language Models
Many empirical studies of labor market questions rely on estimating relatively simple predictive models using small, carefully constructed longitudinal survey datasets based on hand-engineered features. Large Language Models (LLMs), trained on…
The Value of Non-traditional Credentials in the Labor Market
This study investigates the labor market value of credentials obtained from Massive Open Online Courses (MOOCs) and shared on business networking platforms. We conducted a randomized experiment involving more than 800,000 learners, primarily from…
CAREER: A Foundation Model for Labor Sequence Data
Labor economists regularly analyze employment data by fitting predictive models to small, carefully constructed longitudinal survey datasets. Although machine learning methods offer promise for such problems, these survey datasets are too small…
Digital Interventions and Habit Formation in Educational Technology
We evaluate a contest-based intervention intended to increase the usage of an educational app that helps children in India learn to read English. The evaluation included approximately 10,000 children, of whom about half were randomly selected to…
Targeting, Personalization, and Engagement in an Agricultural Advisory Service
ICT is increasingly used to deliver customized information in developing countries. We examine whether individually targeting the timing of automated voice calls meaningfully increases engagement in an agricultural advisory service. We define,…
Decomposing Changes in the Gender Wage Gap over Worker Careers
A large literature in labor economics seeks to decompose observed gender wage gaps (GWGs) into different sources, including portions explained by cross-gender differences in education, occupation, and experience. This paper provides new methods…
Digital Public Health Interventions at Scale: The Impact of Social Media Advertising on Beliefs and Outcomes Related to COVID Vaccines
Public health organizations increasingly use social media advertising campaigns in pursuit of public health goals. In this paper, we evaluate the impact of about $40 million of social media advertisements that were run and experimentally tested…
Personalized Recommendations in EdTech: Evidence from a Randomized Controlled Trial
We study the impact of personalized content recommendations on the usage of an educational app for children. In a randomized controlled trial, we show that the introduction of personalized recommendations increases the consumption of content in…
Emotion- Versus Reasoning-Based Drivers of Misinformation Sharing: A Field Experiment Using Text Message Courses in Kenya
Two leading hypotheses for why individuals unintentionally share misinformation are that 1) they are unable to recognize that a post contains misinformation, and 2) they make impulsive, emotional sharing decisions without thinking about whether a…
Policy Learning with Adaptively Collected Data
Learning optimal policies from historical data enables the gains from personalization to be realized in a wide variety of applications. The growing policy learning literature focuses on a setting where the treatment assignment policy does not…
Semiparametric Estimation of Treatment Effects in Randomized Experiments
We develop new semiparametric methods for estimating treatment effects. We focus on a setting where the outcome distributions may be thick tailed, where treatment effects are small, where sample sizes are large and where assignment is completely…