Dissertation Defense: Shan Gui

Three Essays on Dynamic Mechanism Design

Wednesday, March 20, 2024 9:30 AM to 11:30 AM EDT
Vernon Smith Hall (formerly Metropolitan Building), 5075 (ICES Classroom)


The College of Humanities and Social Sciences is pleased to announce the following dissertation defense:

Shan Gui
Advisor: Dr. Daniel E Houser

Three Essays on Dynamic Mechanism Design

Wednesday, March 20, 2024
09:30 AM - 11:30 AM
George Mason University, Arlington Campus
Vernon Smith Hall (formerly Metropolitan Building), Room 5075


The dissertation focuses on exploring theory and experiments in dynamic mechanism design, aiming to provide helpful guidance for dynamic mechanism design in natural environments. 

The first chapter, co-authored with Daniel Houser, compares the experimental revenue of the “optimal non-clairvoyant dynamic mechanism” with its theoretical prediction, thereby emphasizing the practical value of this novel mechanism. Dynamic mechanisms provide a powerful means for optimizing the revenue and efficiency of repeated auctions. However, implementing them is complicated due to a number of conditions that are difficult to satisfy in practice. These include the fact that the auction designer must be clairvoyant, in the sense that they must have reliable forecasts of participants’ valuation distributions in all future periods. Recently, Mirrokni et al. (2020) introduced a non-clairvoyant dynamic mechanism and showed that it is optimal within the class of dynamic mechanisms that do not rely on strong assumptions regarding knowledge about the future. We showed, however, that an optimal static mechanism (a Myerson auction) can under certain conditions outperform their dynamic mechanism. Here, we report data from an experiment designed to test the performance of the Mirrokni et al. (2020) mechanism in relation to the Myerson auction. Our results support the theory: the optimal non-clairvoyant dynamic mechanism either outperforms or underperforms the repeat static Myerson according to theory predictions. Our results highlight the practical importance of non-clairvoyant mechanisms as implementable approaches to dynamic auction design. 

The second chapter, co-authored with Daniel Houser, investigates the decision-making processes of human sellers when selecting dynamic mechanisms. We propose an experimental design to investigate how human sellers choose between two easily-conducted dynamic mechanisms: the optimal non-clairvoyant dynamic mechanism (NC) (Mirrokni et al., 2020) and the optimal repeated static mechanism (RS) (Myerson, 1981). Our results indicate that human sellers can harness their experience in an environment to choose the optimal mechanism later in the experiment. In addition, sellers tend to adjust their choice of mechanism based on past revenue. We further find that: (i) sellers generally overprice; and (ii) buyers participate less in NC due to the greater-than-suggested upfront fee, leading to the theoretical-experimental revenue gap. Our results shed light on how sellers choose dynamic mechanisms and can potentially help improve mechanism design. 

The third chapter, co-authored with Jingnan Chen, Erte Xiao, and Daniel Houser, shifts the focus to gender inequality in leadership positions within the workplace. Employing an online experiment, we scrutinize the efficacy of an easily implementable default (opt-out) approach in mitigating the gender disparity in willingness to contribute ideas. Our investigation encompasses two types of defaults: non-merit-based defaults, where individuals are randomly assigned to a leadership position for contributions (with the option to opt out), and merit-based defaults, where individuals are placed in their default position based on their skills and abilities. Our findings reveal that defaults wield significant effects on mitigating the gender gap in willingness to contribute ideas. We find little evidence, however, that defaults mitigate stereotype bias in the willingness to contribute. Notably, both the random default and the merit-based default yield equivalent results in narrowing this gap. This study highlights the practical significance of the default option in fostering a more equitable working environment for women. 

All members of the George Mason University community are invited to attend.


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