Wenji Xu

Assistant Professor, Department of Economics and Finance, City University of Hong Kong. 

Ph.D., University of Chicago, 2020. 

My research is on economic theory and industrial organization

Email: wenjixu@cityu.edu.hk

Curriculum Vitae

Working Papers

Informational Intermediation, Market Feedback, and Welfare Losses. (Online Appendix) with Kai Hao Yang

This paper examines the welfare implications of third-party informational intermediation. A seller sets the price of a product that is sold through an informational intermediary. The intermediary can disclose information about the product to consumers and earns a fixed percentage of sales revenue in each period. The intermediary's market base grows at a rate that increases with past consumer surplus. We characterize the stationary equilibria and the set of subgame perfect equilibrium payoffs. When market feedback (i.e., the extent to which past consumer surplus affects future market bases) increases, welfare may decrease in the Pareto sense.

Selling with Recommender Systems and Price Dynamics.  with Shuoguang Yang 

A long-lived seller sells a new product of unknown value through a recommender system that offers prices and recommends products to short-lived consumers in continuous time. The seller receives feedback about the product at a rate that increases with the instantaneous sales volume. The profit-maximizing selling mechanism features episodes of price discounts, during which the seller discontinuously lowers the price and selectively sends out unwarranted recommendations to consumers. The optimal price path may involve delayed discounts, below-cost pricing, and price cycles. 

Social Learning through Action-Signals.

This paper studies sequential social learning when people learn about others' actions through coarse signals. Agents arrive in cohorts sequentially. Each agent chooses an action upon observing a private "state-signal" about a payoff-relevant state of the world and "action-signals" that summarize previous cohorts' actions. I specify conditions under which adequate learning occurs, i.e., agents eventually learn the truth and take the correct actions. A necessary condition for adequate learning is that the state-signals can induce unbounded private likelihoods. When private likelihoods are unbounded, adequate learning occurs if and only if the information environment is separable. Separability is satisfied by doubly monotone partitional action-signals. 

Platform Design for Costly Learning

This paper studies the optimal design of a platform to incentivize its users to collectively acquire costly information about the quality of a product (or a service, an investment opportunity, etc.). Users arrive in discrete time. Each user observes information disclosed by the platform and may acquire a costly private signal about the product quality before making his purchase decision. The platform observes users' past purchase history and can disclose any information about past histories to subsequent users. It is shown that if the information environment features negative feedback, it is optimal for the platform to release no information early on to induce user exploration and publish a list of potentially good products at a later point in time, once and for all. On the other hand, if the information environment features positive feedback, it is optimal for the platform to continuously flag projects that are potentially good for an extended period of time right after the product is released. Welfare comparisons with different benchmarks are discussed. 

Social Learning under Information Control

The efficiency of market economies and democratic political system depends on the accuracy of individuals’ beliefs. However, centralized information control has, from time to time, hindered efficient societal information aggregation. In this paper, we study to what extent information aggregation in social learning environments is affected by centralized information control of a principal with a state-independent preference. We consider a population of agents who arrive sequentially and obtain information about the state of the world both from their private signals and by observing information about other agents’ actions either exogenously or through the principal. Contrary to the naïve intuition, information aggregation can be very resilient, rather than fragile, provided that the agents have access to some minimal amount of “expanding” observations of others’ actions that are outside of the principal’s control. In general, the learning outcome depends on whether and how the beliefs generated by the private signals are bounded, as well as the type of exogenous observations that agents have.