The Bank of England (BoE) has been strongly criticised for failing to predict the surge in inflation. Had it done so, it could have reacted more quickly and prevented inflation from rising as high as 11% in autumn 2022.

The bank acknowledges this failing and has asked former Federal Reserve chairman Ben Bernanke to lead a review of its forecasting models for both inflation and GDP growth.

I’ve been doing my own analysis of the BoE’s record by comparing how it has performed relative to other forecasting models. This demonstrates the scale of the bank’s failing – and it turns out to have been compounded by a second error that may have made the situation worse.

Different forecasting models

The bank is not completely transparent about how it forecasts inflation, drawing on a number of in-house mathematical models. It also factors in market expectations of interest rates and the bank’s judgement of where variables such as energy prices and the pound are heading. In my analysis, I refer to this as model 1.

As for the alternatives, model 2 is called a “quantile” model. It incorporates three elements: a measure of whether the economy is overheating, known as the output gap; the history of inflation; and the effect of quantitative easing (QE), in which central banks have tried to stimulate their economies by “creating” money.

Model 3, known as an econometric vector autoregressive (VAR) model, seeks to fully capture international effects on the UK economy. It looks at the interactions between pressures in the global supply chain, the output gap, inflation and the Bank of England benchmark interest rate. It also incorporates oil prices and global geopolitical risk, which tends to be be ignored by forecasting models.

Meanwhile, model 4 is a lot simpler, looking purely at the history of inflation to predict where it’s heading (we call this an autoregressive (AR) model).