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.
File(s): File format is application/pdf https://www.federalreserve.gov/econres/feds/files/2019028pap.pdf
Part of Series: Finance and Economics Discussion Series
Publication Date: 2019-04-19
Pages: 40 pages