This feature, above all others, probably explains these models’ ubiquity in policy organisations. Not least in the light of the crisis, however, the potential pitfalls of these approaches have also become clearer of late. Recently, these models have been subject to stinging critiques (Romer (2016)). One  1  “If you hit a rocking horse with a stick, the movement of the horse will be very different from that of the stick. The hits are the cause of the movement, but the system’s own equilibrium laws condition the form of movement” (Wicksell (1918)). 2 Attributed to Robert Lucas in Sargent (2001). 6  All speeches are available online at www.bankofengland.co.uk/publications/Pages/speeches/default.aspx  6  common complaint is that they may not do an especially good job of describing the real world, especially in situations of economic stress. Exhibit one is that they offered a spectacularly poor guide to the economy’s dynamics around the time of the global financial crisis. To illustrate, Chart 1 plots the range of forecasts for UK GDP growth from 2008 onwards produced by 27 economic forecasters (including the Bank) in 2007, the dawn of the financial crisis. Three features are notable. First, pre-crisis forecasts were very tightly bunched in a range of one percentage point, perhaps because they were drawn from similar models. The methodological mono-culture produced, unsurprisingly, the same crop. Second, these forecasts foresaw a continuation of the gentle undulations in the economy seen in the decade prior to the crisis - the so-called Great Moderation (Bernanke (2004)).
At the macro level, they have been used to simulate and reproduce the way stars produce energy, using a nuclear fusion reactor here on Earth, an approach that has the potential to provide clean energy for billions of years (Turrell (2013)). Simulating the processes powering stars is modest by comparison with ABMs which aim to model the entire universe. In 1985, one of the first comprehensive computational models of the universe was published, with over 32,000 particles representing known matter (Davis et al (1985)). As estimates put the number of 80  protons and neutrons in the Universe at 10 , this ABM was impressively parsimonious (Penrose (1999)). These models have generated important insights, including the role of “dark matter” in the evolution of galaxies. Not all applications of ABMs are, however, large in scale and universal in application. A 1987 paper called “Why the Brazil Nuts Are on Top” used an ABM with agents of different physical sizes to explain how mixed nuts segregate over time when shaken, with Brazil nuts generally rising to the surface (Rosato et al (1987)). This research was not as nuts as it sounds. It has since found real-world applications in industries such as pharmaceuticals and manufacturing. 14  All speeches are available online at www.bankofengland.co.uk/publications/Pages/speeches/default.aspx  14  Figure 6: Segregation of nuts  Figure 7: The universe  Source: Sae Rpss (CC-BY-SA-3.0). Nuts (image available here). Source: NASA Headquarters - Greatest Images of NASA (NASA-HQ-GRIN) (public domain). Spiral galaxy in the constellation Coma Berenices (image available here).