Research for Business, Government, and Society

The rise of marketplaces for goods and services has led to changes in the mechanisms used to ensure high quality. We analyze this phenomenon in the Uber market, where the system of pre-screening that prevailed in the taxi industry has been…

In a wide variety of applications, including healthcare, bidding in first price auctions, digital recommendations, and online education, it can be beneficial to learn a policy that assigns treatments to individuals based on their characteristics…

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…

When choosing whether and how much to donate, potential donors often observe a set of default donation amounts known as an “ask string.” In an experiment with more than 400,000 PayPal users, we replace a relatively unused donation amount ($75) on…

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…

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…

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…

We conducted two experiments on PayPal’s Give at Checkout feature to learn about the effect of 1) information about charity outcomes on donations, and 2) exposure to these point-of-sale microgiving requests on subsequent giving. In this “…

In this paper, we study the design and analysis of experiments conducted on a set of units over multiple time periods where the starting time of the treatment may vary by unit. The design problem involves selecting an initial treatment time for…

The increasing frequency of severe wildfires demands a shift in landscape management to mitigate their consequences. The role of managed, low-intensity fire as a driver of beneficial fuel treatment in fire-adapted ecosystems has drawn interest in…

The rapid development of generative AI technology is transforming the political landscape, presenting both challenges and opportunities for the 2024 US election. This document provides a research-based overview of the potential impact of…

How can we democratically govern the AI, social media, and online platforms of the future? Today, low participation is a major barrier to community governance online. We leverage a digital quasi-experiment that allows us to study the links…

This paper analyzes a randomized controlled trial of a personalized digital counseling intervention addressing informational constraints and choice architecture, cross-randomized with discounts for long-acting reversible contraceptives (LARCs),…

In many settings, interventions may be more effective for some individuals than others, so that targeting interventions may be beneficial. We analyze the value of targeting in the context of a large-scale field experiment with over 53,000 college…

We are interested in estimating the effect of a treatment applied to individuals at multiple sites, where data is stored locally for each site. Due to privacy constraints, individual-level data cannot be shared across sites; the sites may also…

In medicine, clinicians treat individuals under an implicit assumption that high-risk patients would benefit most from the treatment (‘high-risk approach’). However, treating individuals with the highest estimated benefit using a novel machine-…

Using generalized random forests and rich Swedish administrative data, we show that the earnings effects of job displacement due to establishment closures are extremely heterogeneous across workers, establishments, and markets. The decile of…

Framework agreements (FAs) are procurement mechanisms used in private and public organizations by which a central procurement agency selects an assortment of products, typically through auctions, and then affiliated organizations can purchase…

This paper studies the stochastic linear bandit problem, where a decision-maker chooses actions from possibly time-dependent sets of vectors in ℝd and receives noisy rewards. The objective is to minimize regret, the difference between the…

In this Closer Look, we consider current trends in shareholder activism and their potential impact. We examine the introduction of universal proxies, the increase in “activism experience” among directors, and the changing strategies of activists…

Problem definition: We consider the mechanism design problem of finding an optimal pay-as-bid mechanism in which the platform chooses an assortment of suppliers in order to balance the trade-off between two objectives: providing enough variety to…

Franz Edelman Award 2022, Winning Project

During the COVID-19 crisis, the Chilean Ministry of Health and the Ministry of Sciences, Technology, Knowledge and Innovation partnered with the Instituto Sistemas Complejos de Ingeniería…

During a global pandemic, how can we best prompt social media users to demonstrate discernment in sharing information online? We ran a contextual adaptive experiment on Facebook Messenger with users in Kenya and Nigeria and tested 40 combinations…

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…