UK regional nowcasting using a mixed frequency vector autoregressive model

Stuart McIntyre, Gary Koop, James Mitchell

Research output: Working paper

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Abstract

Data on Gross Value Added (GVA) are currently only available at the annual frequency for the UK regions and are released with significant delay. Regional policymakers would benefit from more frequent and timely data. The goal of this paper is to provide these. We use a mixed frequency Vector Autoregression (VAR) to provide, each quarter, nowcasts (i.e. forecasts of current GVA which is as yet unknown due to release delays) of annual GVA growth for the UK regions. The information we use to update our regional nowcasts comes from GVA growth for the UK as a whole as this is released in a more timely and frequent (quarterly) fashion. To improve our nowcasts we use entropic tilting methods to exploit the restriction that UK GVA growth is a weighted average of GVA growth for the UK regions. In this paper, we develop the econometric methodology and test it in the context of a real time nowcasting exercise.
Original languageEnglish
Place of PublicationGlasgow
PublisherUniversity of Strathclyde
Publication statusPublished - 3 Jul 2018

Publication series

NameStrathclyde Discussion Papers in Economics
PublisherUniversity of Strathclyde
No.5
Volume18

Keywords

  • regional nowcasting
  • gross value added
  • vector autoregression

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