April 2019

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 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

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Last Update: January 09, 2020