Working Paper

Likelihood Evaluation of Models with Occasionally Binding Constraints

Abstract: 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.

Keywords: Measurement error; Solution error; Occasionally binding constraints; Particle filter;

JEL Classification: C32; C53; C63;

Access Documents


Bibliographic Information

Provider: Board of Governors of the Federal Reserve System (U.S.)

Part of Series: Finance and Economics Discussion Series

Publication Date: 2019-04-19

Number: 2019-028

Pages: 40 pages