  We present a methodology for representing probabilistic relationships in a
general-equilibrium economic model. Specifically, we define a precise mapping
from a Bayesian network with binary nodes to a market price system where
consumers and producers trade in uncertain propositions. We demonstrate the
correspondence between the equilibrium prices of goods in this economy and the
probabilities represented by the Bayesian network. A computational market model
such as this may provide a useful framework for investigations of belief
aggregation, distributed probabilistic inference, resource allocation under
uncertainty, and other problems of decentralized uncertainty.
