Solving the Incomplete Markets Model with Aggregate Uncertainty using Explicit Aggregation

We construct a method to solve models with heterogeneous agents and aggregate uncertainty that is simpler than existing algorithms; the aggregate law of motion is obtained neither by simulation nor by parameterization of the cross-sectional distribution, but by explicitly aggregating the individual policy rule. This establishes a link between the individual policy rule and the set of necessary aggregate state variables. In particular, the cross-sectional average of each basis function in the individual policy rule is a state variable. That is, if the individual capital stock, k, (or k²) enters the policy function then the mean of k (or the mean of k²) is a state variable. The laws of motions for these aggregate state variables are obtained by explicit aggregation of separate individual policy functions for the different elements.