The efficiency of competitive mechanisms under private information

We consider the efficiency properties of exchange economies where privately informed traders behave strategically. Specifically, a competitive mechanism is any mapping of traders’ reports about their types to an equilibrium price vector and allocation of the reported economy. In our model, some traders may have non-vanishing impact on prices and allocations regardless of the size of the economy. Although truthful reporting by all traders cannot be achieved, we show that, given any desired level of approximation, there is such that any Bayesian-Nash equilibrium of any competitive mechanism of any private information economy with or more traders leads, with high probability, to prices and allocations that are close to a competitive equilibrium of the true economy. In particular, allocations are approximately efficient. A key assumption is that there is small probability that traders behave non-strategically.     

More leeway for unilateral trade measures?

The report of the WTO Appellate Body in the shrimp-turtle case may prove to be of fundamental importance for the development of the GATT/WTO system. It asserts that a WTO member can unilaterally condition access to its market on compliance with environmental policies, as long as the regulations are administered in an even-handed manner and do not amount to disguised protectionism. Will the incidence of unilateral trade measures increase dramatically as a result of this decision?     

Greediness and equilibrium in congestion games

We study the class of congestion games for which the set of Nash equilibrium is equivalent to the set of strategy profiles played by greedy myopic players. We show these two coincide iff such games are played over extension-parallel graphs.     

Relative entropy in sequential decision problems

Consider an agent who faces a sequential decision problem. At each stage the agent takes an action and observes a stochastic outcome (e.g., daily prices, weather conditions, opponents' actions in a repeated game, etc.). The agent's stage-utility depends on his action, the observed outcome and on previous outcomes. We assume the agent is Bayesian and is endowed with a subjective belief over the distribution of outcomes. The agent's initial belief is typically inaccurate. Therefore, his subjectively optimal strategy is initially suboptimal. As time passes information about the true dynamics is accumulated and, depending on the compatibility of the belief with respect to the truth, the agent may eventually learn to optimize. We introduce the notion of relative entropy, which is a natural adaptation of the entropy of a stochastic process to the subjective set-up. We present conditions, expressed in terms of relative entropy, that determine whether the agent will eventually learn to optimize. It is shown that low entropy yields asymptotic optimal behavior. In addition, we present a notion of pointwise merging and link it with relative entropy.     

Overcoming free riding in multi-party computations—The anonymous case

This paper addresses the question of multi-party computation in a model with asymmetric information. Each agent has a private value (secret), but in contrast to standard models, the agent incurs a cost when retrieving the secret. There is a social choice function the agents would like to compute and implement. All agents would like to perform a joint computation, which input is their vector of secrets. However, agents would like to free-ride on others' contribution.A mechanism which elicits players' secrets and performs the desired computation defines a game. A mechanism is ‘appropriate’ if it (weakly) implements the social choice function for all secret vectors. namely, if there exists an equilibrium in which it is able to elicit (sufficiently many) agents' secrets and perform the computation, for all possible secret vectors. We show that ‘appropriate’ mechanisms approach agents sequentially and that they have low communication complexity.     

Testing theories with learnable and predictive representations

We study the problem of testing an expert whose theory has a learnable and predictive parametric representation, as do standard processes used in statistics. We design a test in which the expert is required to submit a date T by which he will have learned enough to deliver a sharp, testable prediction about future frequencies. We show that this test passes an expert who knows the data-generating process and cannot be manipulated by a uninformed one. Such a test is not possible if the theory is unrestricted.     

European environmental policy between decentralisation and uniformity

Does the European Union require a common environmental policy? While there are a number of arguments in favour of shifting competences for environmental policy to the European level, there are also fields in which decentralised policies appear to make more sense. The following article reviews the pros and cons of centralism and decentralism in European environmental policy and concludes that the Union must integrate elements of both options into its constitutional order.