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Efficient and robust inference of models with occasionally binding constraints

Details

Identification
JRC nr: JRC124394
Publication date
13 April 2021

Description

This paper proposes a piecewise-linear Kalman filter (PKF) to estimate DSGE models with occasionally binding constraints. This method expands the set of models suitable for nonlinear estimation. It straightforwardly handles missing data, non-singularity (more shocks than observed time series), and large-scale models. We provide several applications to highlight its efficiency and robustness compared to existing methods. Our toolkit integrates the PKF into Dynare, the most popular software in DSGE modeling.

Authors:

GIOVANNINI Massimo, PFEIFFER Philipp, RATTO Marco

Files

jrc124394.pdf
English
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