At the time, these damped oscillations seemed to match well the damped harmonic motion of DSGE models. A good crop today foretold of an only slightly less good crop tomorrow. Third, most striking of all, every one of these forecasts was not just wrong but spectacularly so. Few forecasters foresaw even a slight downturn in GDP in 2008 and none foresaw a recession. Yet we witnessed not just a recession but the largest since the 1930s. The one-year-ahead forecast error in 2008 was 8 percentage points. The crop failed and the result was economic famine. While forecasting performance has improved in the period since, there has a continued string of serially correlated errors, with the speed of the recovery consistently over-estimated (Chart 2). The average forecast error one-year-ahead has been consistently negative, averaging 0.5 percentage points per year. The average error two years ahead has been over one percentage point per year. At root, these were failures of models, methodologies and mono-cultures. It has been argued that these models were not designed to explain such extreme events. To quote Robert Lucas once more: “The charge is that the [..] forecasting model failed to predict the events of September 2008. Yet the simulations were not presented as assurance that no crisis would occur, but as a forecast of what could be expected conditional on a crisis not occurring” (Lucas (2009)).
From those assumptions are derived equations of motion for the behaviour of  4  All speeches are available online at www.bankofengland.co.uk/publications/Pages/speeches/default.aspx  4  consumers and firms – which, rather revealingly, are often called the Euler conditions. Then, and only then, are these first-order conditions for behaviour taken to the data to be tested. These models, so derived, predictably exhibit the same damped harmonic motion as Newton’s pendulum. Let me give a couple of examples of this approach in mainstream practice in economics and finance. The most famous equation in finance is probably this one:  Figure 1: The Black-Scholes Formula  Source: Black and Scholes (1973). This is the Black-Scholes options pricing formula (Black and Scholes (1973)). Under a (relatively) small set of assumptions, it provides a (relatively) simple analytical description of how to price a financial option. It cannot rival Einstein for its simplicity and aesthetic beauty. But it nonetheless has many of the trademark characteristics of theoretical physics. That should come as no surprise because this equation was itself drawn from theoretical physics. In seeking a solution to their option-pricing problem, Fisher Black, Myron Scholes and Robert Merton drew an explicit link between their contingent-claims pricing problem and the heat transfer equation in physics (Churchill (1963)). If not quite a lift and shift from theoretical physics, the Black-Scholes formula was certainly a genetic mutation.