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Efficient and robust inference of models with occasionally binding constraints

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Abstract

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.

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  • Giovannini, Massimo & Pfeiffer, Philipp & Ratto, Marco, 2021. "Efficient and robust inference of models with occasionally binding constraints," JRC Working Papers in Economics and Finance 2021-03, Joint Research Centre, European Commission.
    • Handle: RePEc:jrs:wpaper:202103
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    Cited by:

    1. Matthias Burgert & Philipp Pfeiffer & Werner Roeger, 2021. "Fiscal policy in a monetary union with downward nominal wage rigidity," Working Papers 2021-16, Swiss National Bank.
    2. Cardani, Roberta & Croitorov, Olga & Giovannini, Massimo & Pfeiffer, Philipp & Ratto, Marco & Vogel, Lukas, 2021. "The Euro Area's pandemic recession: A DSGE interpretation," JRC Working Papers in Economics and Finance 2021-10, Joint Research Centre, European Commission.
    3. Cardani, Roberta & Croitorov, Olga & Giovannini, Massimo & Pfeiffer, Philipp & Ratto, Marco & Vogel, Lukas, 2022. "The euro area’s pandemic recession: A DSGE-based interpretation," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    4. Croitorov, Olga & Giovannini, Massimo & Pfeiffer, Philipp & Ratto, Marco & Vogel, Lukas, 2022. "Fiscal Stabilisation in a Low-Interest and High-Debt Environment," VfS Annual Conference 2022 (Basel): Big Data in Economics 264142, Verein für Socialpolitik / German Economic Association.

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    More about this item

    Keywords

    DSGE; occasionally binding constraints; nonlinear estimation; Piecewise Kalman Filter;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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