Essays on time preference and combinatorial auctions.

Abstract

This dissertation consists of three essays in experimental economics. The first essay analyzes the time preference and intertemporal choice behavior of human subjects. The second essay studies a new combinatorial auction mechanism in a laboratory setting. In the last essay, we compare several combinatorial auction mechanisms to solve scheduling problems. The first essay presents a laboratory experiment on time preferences to deepen our understanding. Specifically I propose a new experimental design and test its implications. Unlike existing designs, my unique experimental design does not impose any parametric assumptions on the utility function, which allows me to identify the time discount function independently of the form of the utility function. My generalized model successfully shows that subjects exhibit increasing impatience over time. This observation has not been reported in previous studies, which estimate only decreasing impatience. The main findings of my study are: (1) about two-thirds of subjects exhibit future bias and (2) the time discount function is an inverse S-curve, suggesting an expanded notion of the present. In the second essay, we study two package auction mechanisms in a laboratory setting, a sealed bid Vickrey auction and an ascending version of Vickrey, the iBEA auction. Unlike the single-unit Vickrey auction, where bidders tend to overbid in the laboratory, most of our bidders either underbid or bid their true values. Furthermore, at the aggregate level, Vickrey generates significantly higher revenue and efficiency than iBEA. We also find that human bidders learn from their robot opponents when robot strategies are myopic best responses. In the third essay, we explore the possibility of auction mechanisms, applying them to a scheduling problem. We apply concepts from mechanism design to compare different resource allocation schemes in a laboratory. The findings illustrate the utility of economic approaches in understanding issues that emerge in large-scale collaborations, such as entire scientific and engineering communities.