Recently, the co-authored paper Evaluating Non-Clairvoyant Dynamic Mechanisms: Theory and Experiment by Assistant Professor Gui Shan from the Department of Microeconomics, School of Economics, Shanghai University of Finance and Economics (SUFE), has been formally published in Games and Economic Behavior, a top-tier international economics journal.
Abstract
We study dynamic mechanism design in non-clairvoyant environments, where sellers cannot forecast future demand and buyers hold private information. Using two laboratory experiments, we evaluate two non-clairvoyant mechanisms: the dynamic maximin-optimal non-clairvoyant mechanism (DM, Mirrokni et al. (2020)) and the repeated static optimal mechanism (RS, Myerson (1981)). Experiment 1 compares DM and RS across demand-distribution scenarios and shows that non-clairvoyant mechanisms perform as intended: DM either outperforms or underperforms RS depending on the scenario, consistent with theory. Building on these results, Experiment 2 examines the optimal clairvoyant mechanism (OC) and an alternative implementation of DM. In a striking departure from theoretical predictions, OC with full information performs no better than the non-clairvoyant mechanisms, while DM delivers stable performance across different implementations. Our findings underscore the practical value of non-clairvoyant mechanisms as feasible solutions for dynamic auction design amid market uncertainty.
Gui Shan is Assistant Professor at the School of Economics, SUFE. She received her PhD in Economics from George Mason University in the United States. Her research focuses on behavioral and experimental economics. Her works have appeared in journals including Games and Economic Behavior and American Journal of Economics and Sociology. She is the principal investigator of a Young Scientists Fund project of the National Natural Science Foundation of China.
