Welcome to Linchen Zhang (张林辰)’s website!
I am an Economics Ph.D. student at University of California San Diego (Cohort 2021).
My research interests are microeconomics theory and behavioral economics, with a focus on robust mechanism design.
You can find my detailed CV here.
Happy browsing!
Working Papers
- Participation-Adaptive Pricing
- with Benjamin Brooks and Songzi Du
- Abstract: A large number of buyers with single unit demand have a common value for the good being sold. We describe a new class of mechanisms, which we refer to as participationadaptive pricing: Each prospective buyer indicates whether or not they want to buy a good, available goods are rationed among those who wish to purchase, and the market price is an increasing function of the number of buyers who wish to purchase. We characterize a class of pricing rules for which, as the number of buyers grows large, the expected market price converges to the expected value, regardless of the buyers’ information and equilibrium strategies.
- Presented at: Triangle micro conference 2024^, Texas A&M^
- ^: presented by a co-author
Work in Progress
- Revenue Guarantee across Bayes Coarse Correlated Equilibria (preliminary draft)
- Abstract: A single unit item owner sells the good to buyers through an auction design. We study the revenue guarantee (the lowest expected revenue amount that the seller can get) across all Bayes coarse correlated equilibria (BCCE, a weaker and inclusive equilibrium concept than Bayes correlated equilibrium, or BCE), starting with analysis in a first-price auction and a common value setting. We first show that it suffices to only examine identical-play equilibria, where all buyers follow exactly the same actions. Based on this simplification, we give characteristic functions for the revenue guarantee assuming a continuous value distribution. Revenue guarantee under BCCE converges to that under BCE when the market goes large. We also extend the model to allow for discrete distributions, other standard auctions, and symmetric prior environments.
- Presented at: UCSD TBE workshop, GAIMSS’24 (Flash talk and poster), ACM EC24 (poster), 35th Stony Brook Game Theory Conference