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

Adrien Auclert*, Bence Bardóczy, Matthew Rognlie, Ludwig Straub

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)2375-2408
Number of pages34
Issue number5
StatePublished - Sep 2021


  • Computational methods
  • general equilibrium
  • heterogeneous agents
  • linearization

ASJC Scopus subject areas

  • Economics and Econometrics


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