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Online Estimation of DSGE Models

Marco Del Negro, Frank Schorfheide, Michael Cai, Edward Herbst, Ethan Matlin and Reca Sarfati
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Edward Herbst: Board of Governors of the Federal Reserve System (U.S.)

No 20190821, Liberty Street Economics from Federal Reserve Bank of New York

Abstract: The estimation of dynamic stochastic general equilibrium (DSGE) models is a computationally demanding task. As these models change to address new challenges (such as household and firm heterogeneity, the lower bound on nominal interest rates, and occasionally binding financial constraints), they become even more complex and difficult to estimate?so much so that current estimation procedures are no longer up to the task. This post discusses a new technique for estimating these models which belongs to the class of sequential Monte Carlo (SMC) algorithms, an approach we employ to estimate the New York Fed DSGE model. To learn more, check out this paper of ours.

Keywords: Sequential Monte Carlo; DSGE models; Online (search for similar items in EconPapers)
JEL-codes: E2 (search for similar items in EconPapers)
Date: 2019-08-21
New Economics Papers: this item is included in nep-dge and nep-ore
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