Using the Sequence-Space Jacobian to Solve and Estimate Heterogeneous-Agent Models

• 成果类型: Article
• 署名作者: Auclert, Adrien; Bardoczy, Bence; Rognlie, Matthew; Straub, Ludwig
• 署名单位: Stanford University; Centre for Economic Policy Research - UK; National Bureau of Economic Research; Federal Reserve System - USA; Federal Reserve System Board of Governors; Northwestern University; Harvard University
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA17434
• 发表日期: 2021
• 页码: 2375-2408
• 关键词: incomplete markets model; uncertainty; INEQUALITY; WEALTH; prices; shocks; macro

摘要

We propose a general and highly efficient method for solving and estimating general equilibrium heterogeneous-agent models with aggregate shocks in discrete time. Our approach relies on the rapid computation of sequence-space Jacobians-the derivatives of perfect-foresight equilibrium mappings between aggregate sequences around the steady state. Our main contribution is a fast algorithm for calculating Jacobians for a large class of heterogeneous-agent problems. We combine this algorithm with a systematic approach to composing and inverting Jacobians to solve for general equilibrium impulse responses. We obtain a rapid procedure for likelihood-based estimation and computation of nonlinear perfect-foresight transitions. We apply our methods to three canonical heterogeneous-agent models: a neoclassical model, a New Keynesian model with one asset, and a New Keynesian model with two assets.