Linchen Zhang 张林辰
Ph.D. Candidate in Economics, UC San Diego
On the 2026–27 academic job market
I am a Ph.D. candidate in Economics at the University of California, San Diego, expecting to graduate in Spring 2027. I am very fortunate to be advised by Songzi Du.
My research interests are microeconomic theory and behavioral economics, with a focus on simplicity and robustness.
Before UC San Diego, I received a B.A. in Computer Science, Economics (magna cum laude), and Mathematics from Cornell University in 2021.
Job Market Paper
Recognizing Dominance through Local Improvement
Strategy-proofness is the traditional standard for predictable behavior, yet participants often fail to play dominant strategies. Most existing simplicity concepts attribute these failures to the cost of contingent reasoning, which they lower by comparing the worst case of the dominant strategy with the best case of an alternative. I argue that there is another approach, one that makes more use of the structure of the strategy set, which I formalize as a neighbor relation. Comparing neighboring strategies can reduce the need for contingent reasoning, and, even with a single contingency, it can simplify the search through the strategy set. I introduce a new simplicity criterion: a mechanism is local improvement solvable under a neighbor relation if repeatedly moving to an improving neighbor always reaches a dominant strategy. Strategy-proofness is the criterion under the coarsest relation, and many classical mechanisms satisfy it under finer ones. In extensive-form mechanisms without duplicate dominant strategies, the criterion under one-situation neighbors is strict action-proofness, which is distinct from obvious strategy-proofness. Among local improvement solvable mechanisms that implement the same outcomes, the criterion predicts more dominant-strategy play where the local comparison is salient.
UCSD TBE Seminar; UCSD TBE Workshop
Working Papers
Coarse Revenue Guarantee in First Price Auction and Beyond
I study the coarse revenue guarantee (CRG) of the single-unit first-price auction with common values. The CRG is the minimum expected revenue over all information structures and all Bayes coarse correlated equilibria (BCCE), the equilibrium notion to which no-regret learning leads. Identical play, in which all bidders submit the same bid, attains the worst-case revenue, and this reduction yields a closed-form characterization. The coarse guarantee is positive and increases with the number of bidders $N$. It lies strictly below the revenue guarantee of Bergemann, Brooks and Morris (2017) at every finite $N$, and the gap between the two closes at rate $\log N/N$. I extend the analysis to reserve prices, symmetric and asymmetric priors, other standard auctions, and an unknown value distribution.
UCSD TBE Workshop; GAIMSS 2024 (flash talk and poster); ACM EC 2024 (poster); Stony Brook Game Theory Conference 2024; Caltech Student Theory Conference 2025; Southwest Economics Theory Conference 2026; Econometric Society Asian-China Meeting 2026
Market Order Mechanisms
A homogeneous good is for sale to a large number of buyers with multi-unit demand. There are both common and idiosyncratic components to preferences. Trade occurs via a market order mechanism: Each buyer places an order for a number of units; the orders are filled in a random sequence; and buyers pay a price per unit that is a function of the aggregate order. We study the limit of such economies as the numbers of buyers and units grows large. If the pricing rules have vanishing price impact and span, then regardless of the sequence of information structures and equilibria, the limiting market outcome is guaranteed to be competitive: The goods are sold to the buyers with the highest values, at an expected price that is equal to the expected marginal value for the good. It is impossible to achieve similar guarantees for information aggregation.
Stony Brook Game Theory Conference 2025; 2026 Asian School in Theory
By co-authors: Triangle Micro Conference 2024; UChicago; Yale; Cambridge; UCL; UC Berkeley; Stanford; NBER Decentralization Conference 2026; Penn State; UPenn; HKU; NUS; HKUST; CUHK Shenzhen; SMU
Work in Progress
Conditional Dominance and Rationalizability with Information-Based Continuation Reasoning
UCLA Student Theory Conference 2026
Strategic Obliviousness
We study strategic obliviousness, the failure to account for publicly observable, payoff-relevant information about one’s opponents. In a laboratory experiment, a substantial share of participants behave as if others’ strategies do not depend on this information, revealing an incorrect mental model of others’ strategic reasoning. While participants condition on this information when choosing themselves, they do not anticipate that their opponents condition on it too.
By co-authors: LMU Munich; UCL
References
- Professor Songzi Du (Chair) Department of Economics, UC San Diego sodu@ucsd.edu
- Professor Aram Grigoryan Department of Economics, UC San Diego a2grigoryan@ucsd.edu
- Professor Joel Watson Department of Economics, UC San Diego jwatson@ucsd.edu
- Professor Emanuel Vespa Department of Economics, UC San Diego evespa@ucsd.edu