The misery of Britain’s post-COVID cost-of-living crisis is compounded by the Bank of England’s (BoE) glaring failure to forecast higher inflation rates. What was initially brushed off as a ‘transitory’ issue turned into a persistent problem, destabilizing the financial markets and shaking the foundations of economic confidence.
The BoE’s miscalculation has had far-reaching consequences. Their reluctance to step on the brakes, believing inflation was a temporary hiccup, led them to respond slowly. When they realised the severity of the situation, they had to enact drastic measures, raising rates at a pace that sent shockwaves through the British economy. Despite these efforts, inflation has remained stubborn and has only recently begun to slow, largely because the Bank failed to control expectations early on.
Unlike the U.S. Federal Reserve, the Bank has failed to properly identify inflationary risk and the costs of sleeping at the wheel are starting to manifest. Because of these abrupt rate rises, higher mortgages are harming households and a cost of credit crisis may be just around the corner. But how did the Bank of England get it all so wrong?
The root of this misjudgment lies in the BoE’s belief that the inflationary surge was primarily supply-side and therefore transitory. This assumption proved erroneous due to a confluence of factors. There was excessive money growth during the COVID-19 pandemic, during which the government injected vast amounts of liquidity into the economy while economic activity ground to a near halt. Concurrently, expectations surrounding inflation drifted from the target, exacerbating the situation.
But it wasn’t just about excessive liquidity. Global events, like the Russian war in Ukraine, further strained supply chains already beleaguered by post-COVID bottlenecks. With more money chasing fewer goods, inflationary pressures mounted. While the Bank was aware of this supply-side shock, their model wrongly assumed these pressures to be transitory. Thus, the Bank’s models seemingly overlooked signs of runaway expectations and surging money growth. By the time the alarm bells rang loud enough, the damage was already done, and the aforementioned ripple effects were set in motion.
This prompts the urgent question: How can we prevent such modelling failures from recurring? Or, if that’s too ambitious, how can we at least minimise their likelihood?
The BoE’s recent predicament has sparked a debate amongst economists. Some argue that deciphering inflationary trends is more an art than a science. There is merit to this viewpoint, especially when considering the multifaceted nature of economies in a globalised world. However, this shouldn’t absolve economists and institutions from refining their approaches; moving away from a data-driven approach is just as dangerous as becoming absorbed within it – what we need instead is a completely different framework.
Taking a cue from engineering might be the way forward. Engineers, when faced with a problem, don’t just rely on old templates; they adapt, innovate, and iterate. If a solution fails, they return to the drawing board, armed with new data and insights. There’s no one-size-fits-all, but a toolbox approach, where various models and theories can be applied based on the problem at hand.
In the quest for economic predictability and the respectability that comes with it, there’s been an over-reliance on rigid models. These models, while valuable, are not infallible. The BoE’s oversight serves as a stark reminder of this fact. As we move forward, a more dynamic, adaptive, and holistic approach to economic modelling, one that draws inspiration from engineering, might be the key to understanding and navigating the ever-evolving economic landscape.
Continue to Part 2…
