We propose a new method for computing equilibria in heterogeneous-agent models with
aggregate uncertainty. The idea relies on an assumption that linearization offers a good
approximation; we share this assumption with existing linearization methods. However,
unlike those methods, the approach here does not rely on direct derivation of first-order
Taylor terms. It also does not use recursive methods, whereby aggregates and prices would
be expressed as linear functions of the state, usually a very high-dimensional object (such …

We propose a new method for computing equilibria in heterogeneous-agent models with
aggregate uncertainty. The idea relies on an assumption that linearization offers a good
approximation; we share this assumption with existing linearization methods. However,
unlike those methods, the approach here does not rely on direct derivation of first-order
Taylor terms. It also does not use recursive methods, whereby aggregates and prices would
be expressed as linear functions of the state, usually a very high-dimensional object (such …