Mike Vo
I am a Postdoctoral Research Associate in Applied Economics & Data Science at the University of Connecticut. I received my Ph.D. in Economics from the University of California, Irvine in 2023.
My research interests include economics of technology, industrial organization, and microeconomic theory, with recent projects on consumer protection policy, product design and versioning, collusion, and the use of large-scale human mobility data in applied economics.
Here is my CV and feel free to reach out at mike.vo@uconn.edu.
Research
Publications
NewDo Unconditional Full Refunds Benefit Consumers?
Accepted
NewEvaluating Precision, Differential Privacy, and Representation with Cell Phone Mobility Data: Evidence from Recreational Demand for Cape Cod Beaches
Forthcoming
Harnessing Human Mobility Data for Applied Economic Research: Current Knowledge, Challenges, and Emerging Opportunities
When to degrade a product: The utility-to-cost ratio rule
Working Papers
Price-Directed Search, Consumer Stickiness, and the Sustainability of Collusion
Directed Search, Frictions, and Tacit Collusion: A Computational Experiment
The Impact of Texas Senate Bill 8 on Family Care Utilization: Evidence from Large-Scale Mobility Data
Selected Work in Progress
Estimating Structural Models with Privacy-Protected Data: A Mean Bayesian Correction for Large-Scale Mobility Data
Beyond Supermarkets: Measuring the Impact of Food Environment on Healthy Store Utilization
Teaching
University of California, Irvine
Principles of Microeconomics
Graduate Microeconomic Theory II (PhD Core), Industrial Organization III, Money and Banking, Managerial Economics, Intermediate Microeconomics
★ Outstanding Teaching Assistant Award
Truman State University
Econometrics, International Trade
Asymptotica
I am building Asymptotica to connect the mathematical foundations of asymptotic theory with its practical application. It is designed to help PhD students, advanced undergraduates, and practitioners strengthen their grasp of asymptotic inference, making empirical research easier to both execute and interpret.
Visit Asymptotica.com →