Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting

38 Pages Posted: 8 May 2023 Last revised: 8 May 2023

See all articles by Gary Koop

Gary Koop

University of Strathclyde, Glasgow - Strathclyde Business School - Department of Economics

Stuart G. McIntyre

University of Strathclyde

James Mitchell

Federal Reserve Bank of Cleveland

Aubrey Poon

University of Kent - School of Economics

Ping Wu

University of Strathclyde, Glasgow - Strathclyde Business School - Department of Economics

Date Written: May 8, 2023

Abstract

Interest in regional economic issues coupled with advances in administrative data is driving the creation of new regional economic data. Many of these data series could be useful for nowcasting regional economic activity, but they suffer from a short (albeit constantly expanding) time series which makes incorporating them into nowcasting models problematic. Regional nowcasting is already challenging because the release delay on regional data tends to be greater than that at the national level, and "short" data imply a "ragged edge" at both the beginning and the end of regional data sets, which adds a further complication. In this paper, via an application to the UK, we develop methods to include a wide range of short data into a regional mixed-frequency VAR model. These short data include hitherto unexploited regional VAT turnover data. We address the problem of the ragged edge at both the beginning and end of our sample by estimating regional factors using different missing data algorithms that we then incorporate into our mixed-frequency VAR model. We find that nowcasts of regional output growth are generally improved when we condition them on the factors, but only when the regional nowcasts are produced before the national (UK-wide) output growth data are published.

Keywords: Regional data, Mixed-frequency data, Missing data, Nowcasting, Factors, Bayesian methods, Real-time data, Vector autoregressions

JEL Classification: C32, C53, E37

Suggested Citation

Koop, Gary and McIntyre, Stuart G. and Mitchell, James and Poon, Aubrey and Wu, Ping, Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting (May 8, 2023). FRB of Cleveland Working Paper No. 23-09, https://doi.org/10.26509/frbc-wp-202309, Available at SSRN: https://ssrn.com/abstract=4441188

Gary Koop

University of Strathclyde, Glasgow - Strathclyde Business School - Department of Economics ( email )

100 Cathedral Street
Glasgow G4 0LN
United Kingdom

Stuart G. McIntyre

University of Strathclyde

16 Richmond Street
Glasgow 1XQ, G1 1XQ
United Kingdom

James Mitchell (Contact Author)

Federal Reserve Bank of Cleveland ( email )

East 6th & Superior
Cleveland, OH 44101-1387
United States

HOME PAGE: http://https://www.clevelandfed.org/en/our-research/economists/james-mitchell.aspx

Aubrey Poon

University of Kent - School of Economics ( email )

CT2 7NP
United Kingdom

Ping Wu

University of Strathclyde, Glasgow - Strathclyde Business School - Department of Economics ( email )

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