Likelihood Evaluation of Models with Occasionally Binding Constraints
40 Pages Posted: 22 Apr 2019
Date Written: 2019-04-19
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
Suggested Citation: Suggested Citation