Forecasting the UK economy with a medium-scale Bayesian VAR

Sílvia Domit, Francesca Monti, Andrej Sokol*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


We estimate a Bayesian VAR (BVAR) for the UK economy and assess its performance in forecasting GDP growth and CPI inflation in real time relative to forecasts from COMPASS, the Bank of England's DSGE model, and other benchmarks. We find that the BVAR outperformed COMPASS when forecasting both GDP and its expenditure components. In contrast, their performances when forecasting CPI were similar. We also find that the BVAR density forecasts outperformed those of COMPASS, despite under-predicting inflation at most forecast horizons. Both models over-predicted GDP growth at all forecast horizons, but the issue was less pronounced in the BVAR. The BVAR's point and density forecast performances are also comparable to those of a Bank of England in-house statistical suite for both GDP and CPI inflation, as well as to the official Inflation Report projections. Our results are broadly consistent with the findings of similar studies for other advanced economies.

Original languageEnglish
Pages (from-to)1669-1678
Number of pages10
Issue number4
Early online date6 Jan 2019
Publication statusPublished - 1 Oct 2019


  • Bayesian methods
  • Econometric models
  • Inflation forecasting
  • Macroeconomic forecasting
  • Vector autoregression models


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