Browse or search publications from faculty affiliated with the lab.
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.…
Impact Matters for Giving at Checkout
We conducted two experiments on PayPal’s Give at Checkout feature to learn about the effect of 1) information about charity outcomes on donations…
Optimal Experimental Design for Staggered Rollouts
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…
Can Personalized Digital Counseling Improve Consumer Search for Modern Contraceptive Methods?
This paper analyzes a randomized controlled trial of a personalized digital counseling intervention addressing informational constraints and…
Machine Learning Who to Nudge: Causal vs Predictive Targeting in a Field Experiment on Student Financial Aid Renewal
In many settings, interventions may be more effective for some individuals than others, so that targeting interventions may be beneficial. We…
Policy Learning with Adaptively Collected Data
In a wide variety of applications, including healthcare, bidding in first price auctions, digital recommendations, and online education, it can be…
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…
Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracles
Contextual bandit algorithms often estimate reward models to inform decision-making. However, true rewards can contain action-independent…
Battling the Coronavirus Infodemic Among Social Media Users in Africa
During a global pandemic, how can we best prompt social media users to demonstrate discernment in sharing information online? We ran a contextual…
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…
Smiles in Profiles: Improving Fairness and Efficiency Using Estimates of User Preferences in Online Marketplaces
Online platforms often face challenges being both fair (i.e., non-discriminatory) and efficient (i.e., maximizing revenue). Using computer vision…
PayPal Giving Experiments
This report describes insights gleaned from the Data Fellows collaboration among PayPal, Northwestern University’s Kellogg School of Management,…
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…
Shared Decision-Making: Can Improved Counseling Increase Willingness to Pay for Modern Contraceptives?
Long-acting reversible contraceptives are highly effective in preventing unintended pregnancies, but take-up remains low. This paper analyzes a…
Off-Policy Evaluation via Adaptive Weighting with Data from Contextual Bandits
It has become increasingly common for data to be collected adaptively, for example using contextual bandits. Historical data of this type can be…
Confidence Intervals for Policy Evaluation in Adaptive Experiments
Adaptive experiment designs can dramatically improve statistical efficiency in randomized trials, but they also complicate statistical inference.…
Tractable Contextual Bandits Beyond Realizability
Tractable contextual bandit algorithms often rely on the realizability assumption — i.e., that the true expected reward model belongs to a known…
Practitioner’s Guide: Designing Adaptive Experiments
Adaptive experiments present a unique opportunity to more rapidly learn which of many treatments work best, evaluate multiple hypotheses, and…
Adapting to Misspecification in Contextual Bandits with Offline Regression Oracles
Computationally efficient contextual bandits are often based on estimating a predictive model of rewards given contexts and arms using past data.…
Optimal Policies to Battle the Coronavirus “Infodemic” Among Social Media Users in Sub-Saharan Africa: Pre-analysis Plan
Alongside the outbreak of the novel coronavirus, an “infodemic” of myths and hoax cures is spreading over online media outlets and social media…
Survey Bandits with Regret Guarantees
We consider a variant of the contextual bandit problem. In standard contextual bandits, when a user arrives we get the user’s complete…
The Surrogate Index: Combining Short-Term Proxies to Estimate Long-Term Treatment Effects More Rapidly and Precisely
A common challenge in estimating the long-term impacts of treatments (e.g., job training programs) is that the outcomes of interest (e.g.,…
Estimation Considerations in Contextual Bandits
Contextual bandit algorithms are sensitive to the estimation method of the outcome model as well as the exploration method used,…