CFDP 1928R

Information and Volatility


Publication Date: December 2013

Revision Date: June 2014

Pages: 66


In an economy of interacting agents with both idiosyncratic and aggregate shocks, we examine how the information structure determines aggregate volatility. We show that the maximal aggregate volatility is attained in a noise free information structure in which the agents confound idiosyncratic and common components of the payoff state, and display excess response to the common component, as in Lucas (1972). The upper bound on aggregate volatility is linearly increasing in the variance of idiosyncratic shocks, for any given variance of aggregate shocks. Our results hold in a setting of symmetric agents with linear best responses and normal uncertainty. We show our results by providing a characterization of the set of all joint distributions over actions and states that can arise in equilibrium under any information structure. This tractable characterization, extending results in Bergemann and Morris (2013b), can be used to address a wide variety of questions.


Incomplete information, Bayes correlated equilibrium, Volatility, moments restrictions, Linear best responses, Quadratic payoffs

JEL Classification Codes:  C72, C73, D43, D83