I study the economics of data in the context of mass digitization, market failure, imperfect competition, and behavioral individuals.


Conceptually, I focus on information generation in the private sector: how firms collect and use consumer data, as well as its dynamic implications on consumer behaviors, pricing/markups, search frictions, and market competitiveness.

Empirically, I focus on applications in consumer finance, transportation, and e-commerce retail industries, making use of large datasets often obtained from independent collaborations with firms. I specialize in developing and estimating formal analytical models that account for empirically important features of consumer demand and firm conduct.

My primary field is industrial organization. My research sits at the intersection of IO, marketing, strategy, development, and finance.


Firms in many markets directly elicit large amounts of data from consumers. The data is used to mitigate information problems, to gain competitive advantages, and to extract rents from consumers. We develop an equilibrium framework to account for these countervailing forces and understand and decompose the value of data.


What kind of firms collect what types of data? Can such data facilitate growth? If so, through what channels? We analyze  the adoption and effect of analytics tools by firms on an e-commerce platform.

Is Growth-Hacking Feasible?

A Training Experiment on 2  million Online Stores (w/ Zhengyun Sun)

Is customizable business training online useful? Why? What kinds of firms participate? How are consumers influenced? We conducted a training experiment that influenced 2 million merchants on an e-commerce platform.

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?

©2020 by Yizhou Jin.