Shaofei Jiang. (2020). Equilibrium refinement in finite evidence games.
Abstract: Evidence games study situations where a sender persuades a receiver by selectively disclosing hard evidence about an unknown state of the world. Evidence games often have multiple equilibria. Hart et al. (2017) propose to focus on truth-leaning equilibria, i.e., perfect Bayesian equilibria where the sender prefers disclosing truthfully when indifferent, and the receiver takes off-path disclosure at face value. They show that a truth-leaning equilibrium is an equilibrium of a perturbed game where the sender has an infinitesimal reward for truth-telling. We show that, when the receiver's action space is finite, truth-leaning equilibrium may fail to exist, and it is not equivalent to equilibrium of the perturbed game. To restore existence, we introduce a disturbed game with a small uncertainty about the receiver's payoff. A purifiable equilibrium is a truth-leaning equilibrium in an infinitesimally disturbed game. It exists and features a simple characterization. A truth-leaning equilibrium that is also purifiable is an equilibrium of the perturbed game.
Shaofei Jiang. (2019). Disclosure games with large evidence spaces.
Abstract: This paper studies disclosure games, allowing for large evidence spaces and general disclosure rules. A sender observes a piece of evidence about an unknown state and tries to influence the posterior belief of a receiver by disclosing evidence with possible omission. We focus on truth-leaning equilibria, where the sender discloses truthfully when doing so is optimal, and the receiver does not discount off-path messages. We show that, given any disclosure rule, all equilibria are payoff equivalent and characterize the unique equilibrium value function of the sender. We also propose a method to construct equilibria for a broad class of games. Applying these results, we study left-censored disclosure, where evidence is a sequence of signals, and the sender can truncate evidence from the left. In equilibrium, seemingly sub-optimal messages are disclosed, and the sender's disclosure contains the longest truncation that yields the maximal difference between the number of favorable and unfavorable signals.
Shaofei Jiang. (2018). Advertisement and investment in quality.
Abstract: I study a model of firm dynamics where a firm can invest in product quality and exert efforts to obtain good publicities. The market learns from good publicities without directly observing quality, investment, or efforts. I analyze the relationship between the firm's advertisement and investment incentives. I show that any equilibrium has a threshold structure: the firm invests and advertises when the market belief is low, only advertises for a range of intermediate beliefs, and does neither when the belief is high. I further study whether increased frequency of publicity opportunities will lead to increased investment, and how these results differ when the market learns from bad news.
Shaofei Jiang, Xuezheng Qin. (2019). The inequality of nutrition intake among adults in China. Journal of Chinese Economic and Business Studies, 17(1), 65-89.
As teaching assistant:
Microeconomics II (PhD), for Prof. Caroline Thomas, UT Austin (2018-20) | Select TA session notes
Math for Economists (PhD), for Prof. Maxwell Stinchcombe, UT Austin (2019)
Probability & Statistics (PhD), for Prof. Maxwell Stinchcombe & Haiqing Xu, UT Austin (2017-18)
Macroeconomic Theory, for Prof. Felipe Schwartzman, UT Austin (2017)
Introduction to Microeconomics, for Prof. Thomas Wiseman, UT Austin (2016)
Applied Econometrics, for Prof. Wanchuan Lin, Peking University (2016)