I’m a research scientist on the Core Data Science team at Facebook, where I manage the Economics, Algorithms and Optimization group. I’m interested in causal inference broadly, in both large-scale experimental and observational settings, and using insights from economic theory to inform strategy and decision-making. My research has included work on empirical Bayesian shrinkage estimators and experiment splitting, imperfect treatment assignment, experimentation in markets, and the empirical analysis of auctions.
Discounts and Deadlines in Consumer Search
Dominic Coey, Bradley Larsen, Brennan Platt. American Economic Review, 2020.
Top Challenges from the first Practical Online Controlled Experiments Summit
Many co-authors. KDD Explorations, 2019.
Improving Treatment Effect Estimators Through Experiment Splitting
Dominic Coey, Tom Cunningham. The Web Conference (previously WWW), 2019.
The Bidder Exclusion Effect
Dominic Coey, Bradley Larsen, Kane Sweeney. RAND Journal of Economics, 2019.
Ascending Auctions with Bidder Asymmetries
Dominic Coey, Bradley Larsen, Kane Sweeney, Caio Waisman. Quantitative Economics, 2017.
People and Cookies: Imperfect Treatment Assignment in Online Experiments
Dominic Coey, Michael Bailey. WWW, 2016.
The Effect of Medicaid on Health Care Consumption of Young Adults
Dominic Coey. Health Economics, 2015.
Physicians’ Financial Incentives and Treatment Choices in Heart Attack Management
Dominic Coey. Quantitative Economics, 2014.
Why Marketplace Experimentation Is Harder Than It Seems: The Role of Test-Control Interference
Thomas Blake, Dominic Coey. EC, 2014.
Set-Asides and Subsidies in Auctions
Susan Athey, Dominic Coey, and Jonathan Levin. AEJ: Microeconomics 2013.
2014 American Economic Association Award for Best Paper in AEJ: Microeconomics.
The Simple Empirics of Optimal Online Auctions
Dominic Coey, Bradley Larsen, Kane Sweeney, Caio Waisman. Revise and resubmit, Marketing Science.