Using the Sequence-Space Jacobian to Solve and Estimate Heterogeneous-Agent Models
Adrien Auclert (),
Matthew Rognlie () and
No 26123, NBER Working Papers from National Bureau of Economic Research, Inc
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.
JEL-codes: C63 E21 E32 (search for similar items in EconPapers)
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Working Paper: Using the Sequence-Space Jacobian to Solve and Estimate Heterogeneous-Agent Models (2019)
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