Working Paper: CEPR ID: DP13071
Authors: Christian Bayer; Ralph Luetticke
Abstract: This paper describes a method for solving heterogeneous agent models with aggregate risk and many idiosyncratic states formulated in discrete time. It extends the method proposed by Reiter (2009) and complements recent work by Ahn et al. (2017) on how to solve such models in continuous time. We suggest first solving for the stationary equilibrium of the model without aggregate risk. We then write the functionals that describe the dynamic equilibrium as sparse expansions around their stationary equilibrium counterparts. Finally we use the perturbation method of Schmitt-Grohé and Uribe (2004) to approximate the aggregate dynamics of the model.
Keywords: Numerical methods; Heterogeneous agent models; Linearization; Incomplete markets
JEL Codes: C63; E32
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| perturbation method (C60) | dimensionality reduction (C38) |
| dimensionality reduction (C38) | computational efficiency (C63) |
| dimensionality reduction (C38) | accuracy of approximations (C60) |
| stationary equilibrium (D50) | perturbation method (C60) |
| fixed copula assumption (C10) | speed of computations (C69) |
| perturbation method (C60) | accuracy of approximations (C60) |