PhD Thesis Defense, Fan Wang, Economics and Decision Sciences

Congratulations to Dr Fan Wang, Economics and Decision Sciences, who successfully defended his Doctoral thesis at HEC Paris, on July 13, 2020. Fan will join the ESSEC Business School - Singapore as assistant professor.

Thesis Topic: Essays in Decision Theory and Behavioral Economics

Supervisors:  Professor Itzhak Gilboa, HEC Paris and Professor Mohammed Abdellaoui, HEC Paris

Jury members:    
Antoine Billot, Professor, University of Paris II Panthéon-Assas 
Jean-Philippe LeFort,  Associate Professor, University Paris Dauphine-PSL 
Tomasz Michalski, Associate Professor, HEC Paris                            
Jean-Marc Tallon, Professor, Paris School of Economics 

Itzhak Gilboa, Professor, HEC Paris, Supervisor
Mohammed Abdellaoui, Professor, HEC Paris, Co-Supervisor

Abstract: 
In this thesis, I propose new measurement and models of ambiguity aversion and status quo bias. The first two chapters utilize an agent’s attitude towards well-defined uncertainty (i.e., risk), which is better understood in the literature, to measure that of less well-defined uncertainty (i.e., ambiguity) and other components of decision making (e.g., utility function). This approach presents at least two advantages. First, it leads to an easily implementable tool for comparing ambiguity attitude across agents without requiring them to have the same risk attitude, as argued in Chapter 1. Second, it unveils a rich notion of trade-offs in the risk domain, through which popular decision-theoretic axioms can be reformulated to embed rank-dependent utility over risk into models of decision under uncertainty, as shown in Chapter 2. In the last Chapter, status quo bias is shown, under fairly general conditions, to be compatible with a rational decision model where the agent compares the likelihood of a status quo theory and various alternative theories, similar to statistical hypothesis testing. Taken together, the thesis provides new theoretical accounts of economic behavior that are amenable to formal analysis and empirical test.