Giovanni Compiani’s work primarily focuses on industrial organization and quantitative marketing, with an emphasis on applying frontier econometric methods to analyze markets and inform policy. Recently, he has focused on three major lines of inquiry. The first concerns methods to estimate consumer preferences that relax restrictive assumptions on what consumers know and how they operate when facing a choice problem. The second is a study of patterns of consumer search over multiple product attributes, with the goal of understanding what we can learn about consumer preferences from observed choice outcomes. The third involves the development of methods to analyze dynamic decisions by economic agents, allowing for variables that are observed by the agents (but not the researcher) and are correlated over time.
His research has appeared in Econometrics Journal and is forthcoming at Journal of Political Economy. He was a joint recipient of a 2018 Berkeley Haas Blockchain Initiative grant.
Compiani earned PhD, MPhil, and MA degrees in economics from Yale University, and holds MSc and BSc degrees cum laude in economics from Bocconi University. He was previously an assistant professor at Haas School of Business at the University of California, Berkeley.