Estimation of VAR Systems from Mixed-Frequency Data: The Stock and the Flow Case
ISBN: 978-1-78560-353-2, eISBN: 978-1-78560-352-5
Publication date: 6 January 2016
Abstract
This paper is concerned with estimation of the parameters of a high-frequency VAR model using mixed-frequency data, both for the stock and for the flow case. Extended Yule–Walker estimators and (Gaussian) maximum likelihood type estimators based on the EM algorithm are considered. Properties of these estimators are derived, partly analytically and by simulations. Finally, the loss of information due to mixed-frequency data when compared to the high-frequency situation as well as the gain of information when using mixed-frequency data relative to low-frequency data is discussed.
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Acknowledgements
Acknowledgments
Support by the FWF (Austrian Science Fund under contract P24198/N18) is gratefully acknowledged. We thank Prof. Tommaso Proietti, Universita di Roma “Tor Vergata”, Italy, and Prof. Brian D. O. Anderson, Australian National University, Australia, for helpful comments.
Citation
Koelbl, L., Braumann, A., Felsenstein, E. and Deistler, M. (2016), "Estimation of VAR Systems from Mixed-Frequency Data: The Stock and the Flow Case", Dynamic Factor Models (Advances in Econometrics, Vol. 35), Emerald Group Publishing Limited, Leeds, pp. 43-73. https://doi.org/10.1108/S0731-905320150000035002
Publisher
:Emerald Group Publishing Limited
Copyright © 2016 Emerald Group Publishing Limited