Communication for Public Goods

This paper studies information transmission between multiple agents with di¤erent preferences and a welfare maximizing decision maker who chooses the quality or quantity of a public good (e.g. provision of public health service; carbon emissions policy; pace of lectures in a classroom) that is consumed by all of them. Communication in such circumstances suffers from the agents' incentive to "exaggerate" their preferences relative to the average of the other agents, since the decision maker's reaction to each agent's message is weaker than in one-to-one communication. As the number of agents becomes larger the quality of information transmission diminishes. The use of binary messages (e.g. "yes" or "no") is shown to be a robust mode of communication when the main source of informational distortion is exaggeration.

A Bootstrap Neural Network Based Heterogeneous Panel Unit Root Test: Application to Exchange Rates

This paper proposes a bootstrap artificial neural network based panel unit root test in a dynamic heterogeneous panel context. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided to investigate the Purchase Power Parity (PPP). The combination of neural network and bootstrapping significantly changes the findings of the economic study in favour of PPP.

Confidence and Competence in Communication

This paper studies information transmission between an uninformed decision maker (receiver) and an informed player (sender) who have asymmetric beliefs ("con fidence") on the sender s ability ("competence") to observe the state of nature. We fi nd that even when the material payoffs of are perfectly aligned, the sender s over- and underconfi dence on his information give rise to information loss in communication, although they do not by themselves completely eliminate information transmission in equilibrium. However, an underconfi dent sender may prefer no communication to informative communication. We also show that when the sender is biased, overconfi dence can lead to more information transmission and welfare improvement.