Estimation and forecasting in vector autoregressive moving average models for rich datasets

Dias, G.F. and Kapetanios, G. (2018) Estimation and forecasting in vector autoregressive moving average models for rich datasets. Journal of Econometrics, 202 (1). pp. 75-91. ISSN 0304-4076

Abstract

Metadata

Item Type: Article
Authors/Creators:
  • Dias, G.F.
  • Kapetanios, G.
Copyright, Publisher and Additional Information:

© 2017 Elsevier. This is an author-produced version of a paper subsequently published in Journal of Econometrics. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Keywords: VARMA; Weak VARM; AIterative ordinary least squares (IOLS) estimator; Asymptotic contraction mapping; Forecasting; Rich and large datasets
Dates:
  • Published: January 2018
  • Published (online): 24 August 2017
  • Accepted: 5 June 2017
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Economics (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 10 Apr 2019 15:52
Last Modified: 24 Aug 2019 00:42
Status: Published
Publisher: Elsevier
Refereed: Yes
Identification Number: 10.1016/j.jeconom.2017.06.022
Open Archives Initiative ID (OAI ID):

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