Likelihood Evaluation of Models with Occasionally Binding Constraints

Pablo Cuba-Borda; Luca Guerrieri; Matteo Iacoviello; Molin Zhong

Board of Governors of the Federal Reserve System

The Federal Reserve, the central bank of the United States, provides the nation with a safe, flexible, and stable monetary and financial system.

April 2019

Likelihood Evaluation of Models with Occasionally Binding Constraints

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

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 misspeci cation, related to the treatment of measurement errors, can interact and compound each other.
Accessible materials (.zip)

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

DOI: https://doi.org/10.17016/FEDS.2019.028

PDF: Full Paper

Last Update: January 09, 2020

Finance and Economics Discussion Series (FEDS)

Likelihood Evaluation of Models with Occasionally Binding Constraints