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

Adrien Auclert, Bence Bardóczy, Matthew Rognlie and Ludwig Straub

No 26123, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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)
Date: 2019-07
New Economics Papers: this item is included in nep-dge, nep-ecm, nep-mac and nep-ore
Note: EFG ME
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Citations: View citations in EconPapers (29)

Published as Adrien Auclert & Bence Bardóczy & Matthew Rognlie & Ludwig Straub, 2021. "Using the Sequence‐Space Jacobian to Solve and Estimate Heterogeneous‐Agent Models," Econometrica, Econometric Society, vol. 89(5), pages 2375-2408, September.

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Journal Article: Using the Sequence‐Space Jacobian to Solve and Estimate Heterogeneous‐Agent Models (2021)
Working Paper: Using the Sequence-Space Jacobian to Solve and Estimate Heterogeneous-Agent Models (2019)
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