Staff Working Paper No. 1,165
By Davide Brignone and Michele Piffer
This paper shows how the structural representation of a vector autoregressive (VAR) model can support forecast analysis. We offer a unified framework that formalises how the structural form of the model can help form a narrative for two key statistics in real-time VAR forecasting: the forecast errors relative to the outturn of the data, and the consequent revisions of the forecast. To illustrate the method developed, we conduct a stylised real-time exercise on the UK, focusing on the inflation surge that followed the pandemic. We show that the inflation forecast produced by a four-variable VAR model was revised upwards not only due to contractionary supply-side shocks, but also due to a mix of expansionary demand-side shocks, and a revision in the past shocks.
Structural forecast analysis 