From commitment to non-commitment: allowing type dynamic in Laffont and Tirole's regulation model

This paper investigates the introduction of type dynamic in the La ont and Tirole's regulation model. The regulator and the rm are engaged in a two period relationship governed by short-term contracts, where, the regulator observes cost but cannot distinguish how much of the cost is due to e ort on cost reduction or e ciency of rm's technology, named type. There is asymmetric information about the rm's type. Our model is developed in a framework in which the regulator learns with rm's choice in the rst period and uses that information to design the best second period incentive scheme. The regulator is aware of the possibility of changes in types and takes that into account. We show how type dynamic builds a bridge between com- mitment and non-commitment situations. In particular, the possibility of changing types mitigates the \ratchet e ect". We show that for small degree of type dynamic the equilibrium shows separation and the welfare achived is close to his upper bound (given by the commitment allocation).

Centralized allocation in multiple markets

We study the problem of centralized allocation of indivisible objects in multiple markets. We show that the set of allocation rules that are group strategy-proof and Pareto-efficient are sequential dictatorships. Therefore, the solution of the joint al-location in multiple markets is significantly narrower than in the single-market case. Our result also applies to dynamic allocation problems. Finally, we provide conditions under which the solution of the single-market allocation coincides with the multiple-market case, and we apply this result to the study of the school choice problem with sibling priorities.

Dynamic hedging with stocastic differential utility

In this paper we study the dynamic hedging problem using three different utility specifications: stochastic differential utility, terminal wealth utility, and we propose a particular utility transformation connecting both previous approaches. In all cases, we assume Markovian prices. Stochastic differential utility, SDU, impacts the pure hedging demand ambiguously, but decreases the pure speculative demand, because risk aversion increases. We also show that consumption decision is, in some sense, independent of hedging decision. With terminal wealth utility, we derive a general and compact hedging formula, which nests as special all cases studied in Duffie and Jackson (1990). We then show how to obtain their formulas. With the third approach we find a compact formula for hedging, which makes the second-type utility framework a particular case, and show that the pure hedging demand is not impacted by this specification. In addition, with CRRA- and CARA-type utilities, the risk aversion increases and, consequently the pure speculative demand decreases. If futures price are martingales, then the transformation plays no role in determining the hedging allocation. We also derive the relevant Bellman equation for each case, using semigroup techniques.