Publications
“Dynamic Survival Bias in Optimal Stopping Problems” ( Journal of Economic Theory)
This paper studies the optimal inference from observing an ongoing experiment. An experimenter sequentially chooses whether to continue with costly trials that yield random payoffs. The experimenter sees the full history of the trial results, while an outside observer sees only the recent trial results, not the earlier prehistory. I contrast the optimal sophisticated posterior of the observer based on a full Bayesian inference that accounts for the prehistory and the naive posterior based solely on the observed history. The resulting dynamic bias grows with longer prehistory if we see enough early successes. Observing more failures may increase the sophisticated posterior if they come early. Revealing a success (failure) in the prehistory always increases (lowers) the sophisticated posterior. Uncovering a more recent signal leads to a larger change than an older one. Seeing a future failure may increase the sophisticated posterior.
Working Papers
"Population Games with Strategic Substitution"
This paper studies a static population game with strategic substitutes. I assume one dimensional continuous action with heterogeneous action cost among players. I explore the diminishing cross effect condition on the payoff function, which delivers equilibrium uniqueness and several comparative statics results --- 1. The equilibrium distribution of actions level rises in the first order stochastic dominance order when the type distribution falls in the first order stochastic dominance order and the dispersion order. 2. The equilibrium distribution of actions rises when the own action effect is larger. My model has applications in games with a p2p network structure and other massive social interactions with a pairwise matching nature.
“Hospital Runs” (with Chao He)
Hospital runs are devastating when low-risk patients crowd out high-risk ones. This paper studies a rushing game among patients. We characterize the condition of runs. There exist self-fulfilling hospital runs because seeking care early grants patients the priority in receiving treatment when their condition deteriorates. Inefficient waiting can also happen as individuals ignore the social cost of future overload. With SIR dynamics, hospital runs are triggered long before the medical resources are insufficient for high-risk patients. Many countries encourage low-risk patients to stay at home to prevents the crowd-out but, this policy is domianted by giving priority to high-risk patients.
Work in Progress
“Dynamic Survival Bias in Optimal Stopping Problems” ( Journal of Economic Theory)
This paper studies the optimal inference from observing an ongoing experiment. An experimenter sequentially chooses whether to continue with costly trials that yield random payoffs. The experimenter sees the full history of the trial results, while an outside observer sees only the recent trial results, not the earlier prehistory. I contrast the optimal sophisticated posterior of the observer based on a full Bayesian inference that accounts for the prehistory and the naive posterior based solely on the observed history. The resulting dynamic bias grows with longer prehistory if we see enough early successes. Observing more failures may increase the sophisticated posterior if they come early. Revealing a success (failure) in the prehistory always increases (lowers) the sophisticated posterior. Uncovering a more recent signal leads to a larger change than an older one. Seeing a future failure may increase the sophisticated posterior.
Working Papers
"Population Games with Strategic Substitution"
This paper studies a static population game with strategic substitutes. I assume one dimensional continuous action with heterogeneous action cost among players. I explore the diminishing cross effect condition on the payoff function, which delivers equilibrium uniqueness and several comparative statics results --- 1. The equilibrium distribution of actions level rises in the first order stochastic dominance order when the type distribution falls in the first order stochastic dominance order and the dispersion order. 2. The equilibrium distribution of actions rises when the own action effect is larger. My model has applications in games with a p2p network structure and other massive social interactions with a pairwise matching nature.
“Hospital Runs” (with Chao He)
Hospital runs are devastating when low-risk patients crowd out high-risk ones. This paper studies a rushing game among patients. We characterize the condition of runs. There exist self-fulfilling hospital runs because seeking care early grants patients the priority in receiving treatment when their condition deteriorates. Inefficient waiting can also happen as individuals ignore the social cost of future overload. With SIR dynamics, hospital runs are triggered long before the medical resources are insufficient for high-risk patients. Many countries encourage low-risk patients to stay at home to prevents the crowd-out but, this policy is domianted by giving priority to high-risk patients.
Work in Progress
