Essays on Prospect Theory, Dynamic Contracting and Procurement

Abstract

This dissertation collects work concerning the way individuals deal with imperfect information, both related to their knowledge of themselves and of others. The second chapter shows that bounded rationality, in the form of limited knowledge of utility, is an explanation for common stylized facts of prospect theory like loss aversion, status quo bias and non-linear probability weighting. Locally limited utility knowledge is considered within a classical demand model framework, suggesting that costs of inefficient search for optimal consumption will produce a value function that obeys the loss aversion axiom of Tversky and Kahneman (1991). Moreover, since this adjustment happens over time, new predictions are made that explain why the status quo bias is reinforced over time. This search can also describe the behavior of a consumer facing an uncertain future wealth level. The search cost justifies non-linear forms of probability weighting. The effects that have been observed in experiments will follow as a consequence.The third chapter looks to understand how firms create and maintain long term relationships with consumers, or how procurement relations evolve over time, by studying a dynamic variant of the classical two-type-buyer contract in mechanism design. It is less trivial and more interesting if the utility determinant (or utility type) is not fixed or completely random, and fair assumptions are that it is either stochastic, or given by a distribution whose parameters are common knowledge. The first approach is that of Battaglini (2005), while the second is pursued in this paper. With two possible types of buyers, the buyer more likely to have a high utility type will receive the first-best allocations, while the other will receive the first best only if he has the high utility type. The last chapter analyzes a dynamic procurement setting with promise keeping, where two firms (agents) with private information on their costs contract competitively with a principal. To this end, two models are proposed and the optimal allocations are determined. The agents face liquidity constraints, which induce distortions when high marginal costs are reported. We deduce that the principal uses promised utilities to incentivize the agents, which act as state variables in the recursive maximization problem. High cost types are allocated less than efficient quantities and the inefficiency of the allocation is relieved as the promised utilities increase.