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Mixed-Frequency Vector Autoregressive Models

This views expressed herein are solely those of the authors and do not necessarily reflect the views of the Norges Bank. The usual disclaimers apply.

Abstract

The development of models for variables sampled at different frequencies has attracted substantial interest in the recent literature. In this article, we discuss classical and Bayesian methods of estimating mixed-frequency VARs, and use them for forecasting and structural analysis. We also compare mixed-frequency VARs with other approaches to handling mixed-frequency data.

Keywords

Acknowledgements

Acknowledgment

We are grateful to Lutz Kilian for helpful comments on a previous draft. The second author likes to thank the financial support of a Fernand Braudel Senior Fellowship of the European University Institute, Florence.

Citation

Foroni, C., Ghysels, E. and Marcellino, M. (2013), "Mixed-Frequency Vector Autoregressive Models

This views expressed herein are solely those of the authors and do not necessarily reflect the views of the Norges Bank. The usual disclaimers apply.

", VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims (Advances in Econometrics, Vol. 32), Emerald Group Publishing Limited, Leeds, pp. 247-272. https://doi.org/10.1108/S0731-9053(2013)0000031007

Publisher

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Emerald Group Publishing Limited

Copyright © 2013 Emerald Group Publishing Limited