©2018 by Yizhou Jin.


My research lies in the intersection of industrial organization, quantitative marketing, and digitization.

I study how firms collect and use data and its implication on consumer behavior, pricing and competition, and privacy regulations. I focus on large and imperfectly competitive markets with information and incentive problems, such as U.S. auto insurance and Chinese retail e-commerce.


In my research, I combine economic theory with econometric techniques to extract insights from large datasets, often obtained from independent collaborations with firms. I specialize in developing formal analytical models to quantify complex but empirically important features of consumer demand and firm conduct.


How to quantify the economic impact of direct transactions of consumer data? More data can mitigate information and incentive problems, but consumers must self-select into providing data, and proprietary data may also increase future markups.


What kind of firms collect what types of data? Can such data facilitate growth? If so, through what channels?

Training and Selection among Small and Young Firms: Evidence from An E-commerce Experiment 

(w/ Zhengyun Sun)

Can business training facilitate growth among small and young firms? If so, what kinds of training are most useful for what types of firms? Can firm behavior during training be informative of potential managerial ability?

Incentivized Behavioral Modification and Learning in Auto Insurance (w/ Shosh Vasserman)

How does driving behavior respond to monetary incentives? Can short-term incentivized safe driving lead to persistent improvements in driving ability?