School of Economics and Finance

October 2016

The table below presents the one year ahead forecasts for quarterly (annualised) GDP growth and RPI inflation estimated using data upto Q2-2016. The forecasts are an average of the projection for the four quarters of 2016. The forecasts are derived using 15 econometric models.

The aim is to provide a wide ranging statistical outlook for the UK economy that is largely free from conditioning assumptions and judgement.

Details on the models and forecasts can be found at: http://cremfi.econ.qmul.ac.uk/efp/index.php

Forecast summary and key highlights for 2017 can be found here.

Key Highlights:

  • UK RGDP is expected to grow by 2.09% in 2016. However, the forecast variance is 0.25 across models.

  • UK Inflation is expected to be 2.12% in 2016. However, the forecast variance is 0.12 across models.

  • In comparison, UK Treasury Independent Consensus Forecasts are 1.8% and 2.2% for UK RGDP and Inflation.

  RGDP Growth Inflation
  Mean Dispersion Mean Dispersion
Autoregr. Moving Average 2.16 [1 - 3.3] 2.73 [-1.9 - 7.1]
TVP Factor Augmented VAR 2.23 [2 - 2.4] 1.94 [1.5 - 2.4]
Bayesian VAR 2.26 [1.3 - 3.2] 2.09 [-1.1 - 5.3]
Fin. Threshold VAR 2.38 [1.5 - 3.2] 2.04 [-1.1 - 5.2]
Large Bayesian VAR 2.06 [1.2 - 2.9] 1.81 [-1.4 - 4.9]
Fin. Smooth Transition VAR 2.35 [1.4 - 3.3] 2.31 [-1.6 - 6.3]
Threshold VAR 2.30 [1.3 - 3.2] 1.95 [-0.8 - 4.8]
Smooth Transition VAR 2.29 [1.2 - 3.3] 2.56 [-1.4 - 6.5]
DSGE 0.31 [-11.5 - 12.1] 1.61 [-3.3 - 6.4]
TVP VAR 2.18 [2 - 2.4] 2.05 [1.7 - 2.3]
Markov Switching VAR 2.22 [1.8 - 2.6] 2.47 [0.4 - 4.6]
Mixed Frequency VAR 2.06 [0.4 - 3.8] 1.48 [-1.4 - 4.3]
Unobserved Component SV 2.12 [1.9 - 2.3] 2.39 [1.1 - 3.7]
BVAR Common SV 2.21 [1.7 - 2.7] 2.24 [0.6 - 3.9]
BVAR t Disturbances 2.25 [1.6 - 2.9] 2.13 [-0.3 - 4.6]
Average 2.09   2.12  
Highest 2.38   2.73  
Lowest 0.31   1.48  
Variance 0.25   0.12  
Average: Average of forecasts across Cremfi Forecast. Project Models
Dispersion: 10% - 90% Quantiles of Forecast Distribution. TVP: Time Varying Parameter,
DSGE: Dynamic Stochastic General Equilibrium, VAR: Vector Autoregressive, SV: Stochastic Volatility