Browse or search publications from faculty affiliated with the lab.
Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations
When researchers develop new econometric methods it is common practice to compare the performance of the new methods to those of existing methods…
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.…
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…
Low-Intensity Fires Mitigate the Risk of High-Intensity Wildfires in California’s Forests
The increasing frequency of severe wildfires demands a shift in landscape management to mitigate their consequences. The role of managed, low-…
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…
Federated Causal Inference in Heterogeneous Observational Data
We are interested in estimating the effect of a treatment applied to individuals at multiple sites, where data is stored locally for each site.…
Machine-Learning-Based High-Benefit Approach versus Conventional High-Risk Approach in Blood Pressure Management
In medicine, clinicians treat individuals under an implicit assumption that high-risk patients would benefit most from the treatment (‘high-risk…
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…
The Heterogeneous Earnings Impact of Job Loss Across Workers, Establishments, and Markets
Using generalized random forests and rich Swedish administrative data, we show that the earnings effects of job displacement due to establishment…
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…
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…
Expanding Capacity for Vaccines against COVID-19 and Future Pandemics: A Review of Economic Issues
We review economic arguments for using public policy to accelerate vaccine supply during a pandemic. Rapidly vaccinating a large share of the…
Effective and Scalable Programs to Facilitate Labor Market Transitions for Women in Technology
We describe the design, implementation, and evaluation of a low-cost and scalable program that supports women in Poland in transitioning into jobs…
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…
Platform Annexation
The article offers information about the platform annexation, and the logic using basic principles from platform economics. It analyzes the…
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…
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,…
Uncovering Interpretable Potential Confounders in Electronic Medical Records
Randomized clinical trials (RCT) are the gold standard for informing treatment decisions. Observational studies are often plagued by selection…