City Research Online

Abstract

This article promotes the use of panel data methods in nowcasting. This shifts the focus of the literature from national to regional nowcasting of variables like gross domestic product (GDP). We propose a mixed-frequency panel VAR model and a bias-corrected least squares estimator which attenuates the bias in fixed effects dynamic panel settings. Simulations show that panel forecast model selection and combination methods are successfully adapted to the nowcasting setting. Our novel empirical application of nowcasting quarterly U.S. state-level real GDP growth highlights the success of state-level nowcasting, as well as the gains from pooling information across states.

Publication Type:	Article
Additional Information:	© 2022 The Author(s). Published with license by Taylor and Francis Group, LLC This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher Keywords:	Model averaging, model selection, nowcasting, panel data, state-level GDP
Subjects:	H Social Sciences > HB Economic Theory H Social Sciences > HG Finance
Departments:	Bayes Business School Bayes Business School > Finance
SWORD Depositor:	Symplectic Administrator

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