In three distinct, yet interrelated, essays I examine the effects of asymmetric information and imperfect information on economic decision makers' incentives and behaviour. To do so I employ, and modify, the methodology of Bayesian games.In chapter one, I analyse an unconventional contest inspired by the real world.In this contest, players are ranked by a scoring rule based on both their realised performance and how close this performance is to a target set before the contest,which is private information. I elucidate and analyse the incentive properties of these rules then characterise the equilibrium behaviour of the players.In chapter two, I integrate aspects from adverse selection and moral hazard models to provide a unied theory of securitisation under asymmetric information.I show that introducing skin in the game increases signalling costs for originators who performed sufficient due-diligence yet still improves incentives by making high effort relatively more likely. I relax the conventional assumption of risk neutrality and show that risk-sharing concerns are sufficient for the aforementioned qualitative properties of equilibrium to hold. Finally, I demonstrate that, depending on the severity of the originator's preference for liquidity or need to share risk, each setting may be more conducive for signalling.In chapter three, I propose a simple and intuitive way to transform canonical signalling games with exogenous types into games in which the informed agent endogenously generates her private information through an unobservable costly effort decision. I provide portable results on the differentiability of action functions and existence of equilibrium. I then apply these results to classic models of security design and the job market to demonstrate the practical usefulness of endogenous effort. In particular, my approach in these applications lends theoretical support to stylised facts that cannot be derived from the standard signalling framework.
|Date of Award||5 Nov 2018|
- University Of Strathclyde
|Supervisor||Alexander Dickson (Supervisor) & Giuseppe De Feo (Supervisor)|