UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting. (16th July 2019)

• Record Type: Journal Article
• Authors: Koop, Gary; McIntyre, Stuart; Mitchell, James
• Is Part Of: Journal of the Royal Statistical Society. Volume 183:Number 1(2020)
• Page Start: 91
• Page End: 119
• Publication Date: 2019-07-16
• Subjects: Bayesian methods -- Entropic tilting -- Mixed frequency -- Nowcasting -- Regional nowcasting -- Vector auto‐regressions; Social sciences -- Statistical methods -- Periodicals; Statistics -- Periodicals; 300.15195
• DOI: 10.1111/rssa.12491
• Languages: English
• ISSNs: 0964-1998

Abstract

Summary: 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.