UK regional nowcasting using a mixed frequency vector autoregressive model with entropic tilting

Gary Koop, Stuart McIntyre, James Mitchell

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Abstract

Output growth data for the UK regions are available at only annual frequency and are released with significant delay. Regional policy makers would benefit from more frequent and timely data. We develop a stacked, mixed frequency vector auto-regression to provide, each quarter, nowcasts of annual output growth for the UK regions. The information that we use to update our regional nowcasts includes output growth data for the UK as a whole, as these aggregate data are released in a more timely and frequent (quarterly) fashion than the regional disaggregates which they comprise. We show how entropic tilting methods can be adapted to exploit the restriction that UK output growth is a weighted average of regional growth. In our realtime nowcasting application we find that the stacked mixed frequency vector-autoregressive model, with entropic tilting, provides an effective means of nowcasting the regional disaggregates exploiting known information on the aggregate.

Original languageEnglish
Pages (from-to)91-119
Number of pages29
JournalJournal of the Royal Statistical Society: Series A
Volume183
Issue number1
Early online date16 Jul 2019
DOIs
Publication statusPublished - 31 Jan 2020

Keywords

  • nowcasting
  • Vector Autoregression
  • growth

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Stuart McIntyre

Person: Academic

Research Output

  • 1 Citations
  • 1 Working paper

UK regional nowcasting using a mixed frequency vector autoregressive model

McIntyre, S., Koop, G. & Mitchell, J., 3 Jul 2018, Glasgow: University of Strathclyde, (Strathclyde Discussion Papers in Economics; vol. 18, no. 5).

Research output: Working paper

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