Likelihood evaluation of models with occasionally binding constraints

Pablo Cuba-Borda, Luca Guerrieri, Matteo Iacoviello, and Molin Zhong

Applied researchers interested in estimating key parameters of DSGE models face an array of choices regarding numerical solution and estimation methods. We focus on the likelihood evaluation of models with occasionally binding constraints. We document how solution approximation errors and likelihood misspecification, related to the treatment of measurement errors, can interact and compound each other

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Year of publication:	March 12, 2019
Authors:	Cuba-Borda, Pablo ; Guerrieri, Luca ; Iacoviello, Matteo ; Zhong, Molin
Publisher:	Washington, D.C. : Divisions of Research & Statistics and Monetary Affairs, Federal Reserve Board
Subject:	Measurement error \| solution error \| occasionally binding constraints \| particlefilter

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Extent:	1 Online-Ressource (circa 40 Seiten) Illustrationen
Series:	Finance and economics discussion series. - Washington, DC : Board of Governors of the Federal Reserve System, ZDB-ID 2670319-1. - Vol. 2019, 028 FEDS Working Paper ; No. 2019-028
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Arbeitspapier ; Working Paper
Language:	English
Classification:	C32 - Time-Series Models ; C53 - Forecasting and Other Model Applications ; C63 - Computational Techniques
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012181038