UC Santa Cruz

This dissertation presents three experimental studies with an emphasis on the influence of information and innovation on digital markets including financial exchanges and online marketplaces. The first chapter focuses on the experimental evaluation of a new financial market design. The second and third chapters focus on how access to information affects people's behavior in the online marketplaces.

The first chapter provides a laboratory study of a newly proposed Flow Market format as a response to the design weaknesses of the continuous double auction used in most financial markets worldwide.We designed and deployed a laboratory experiment that compares the Flow Market and the CDA using several fundamental metrics. We find evidence that the flow market changes traders’ behavior relative to CDA, allowing them to shred orders more effectively: compared to the CDA, the Flow market exhibits fewer and larger orders. We also find both formats perform similarly in terms of price and allocative efficiency. However, the Flow Market leads to lower price volatility. Interestingly, the total traded volume is lower under the Flow Market than under CDA. Still, this difference decreases with traders’ experience, i.e., as they learn the mechanics of the Flow format. Our findings provide initial insights regarding the feasibility of the Flow trade format and its potential to promote financial market stability and fairness.

The second chapter modifies the traditional sequential search models to consider the ex post uncertainty in which the uncertainty cannot be fully eliminated by the search. We derived players' optimal search strategy given their risk attitudes. We also test our theory in a laboratory experiment with a search game to track subjects' behavior and use a multiple price list and a bomb risk elicitation task to elicit subjects' risk preferences. We find that, in this scenario, risk-averse players tend to increase their reservation value and extend their search duration.

The last chapter investigates the informational barrier problem in the online marketplaces. We design a sequential game to study how informational barrier is formed due to the reputation system and propose a fractional searching mechanism to enable the entry by reliable firms. The model predicts the optimal behaviors of the firms and shows that the fractional searching enables cost-effective firms with no reputation to enter the market more easily. Additionally, we test our theory in a laboratory experiment using an interactive market game to track subjects' behaviors with a simplified reputation system. The experimental results indicate that fractional searching effectively alleviates the entry problem of new firms with superior quality.