Or, The Risk of Extrapolating Linear Trends Against Non-Linear Systems.
A common habit in forecasting, particularly in energy futures & economic growth, is to take roughly linear trends and extend them over the next few decades. The notion is that there is inertia in what has already happened that will make the future look markedly similar, or at least there will likely be a more-or-less linear movement along an existing path. For example, many forecasts suggest that energy consumption will increase by 50% towards the year 2035. This is based on data over the past 30 years that is then extrapolated forward along expectations, so you get graphs that look like this one from the EIA’s 2009 Annual Energy Outlook Early Release Overview:
The graph shows mostly linear growth in energy consumption. The assumptions here are that, given previous growth rates, and given a rough set of expectations about future growth, energy consumption will steadily grow across all sectors. Yet you’ll notice a few bumps & dips for transportation & industrial in the later months of 2008 and early 2009. These suggest outlier events. Outliers are the unexpected events, the Black Swans that come out of nowhere and blow expectations out of the water. In this case, economic activity got a big boost by the inflated gains of the securities market, then took a dive after all the hidden risks came to the surface. The following graph from the same EIA report highlights the 2008 economic black swan:
Here we see the market prices for the primary energy sources. This graph really shows the instability churned up by the securities outlier. As the ultimate determinant of just about all economic activity (nothing happens without energy) we can see energy prices climbing at the same time demand was ramping up (compare to the last graph of consumption). Then heading into the crash energy prices plummet as fears mount, workforces are downsized, factories go dark, and productivity retracts in the face of economic doom. In spite of expectations the market collapse came as a surprise. Yet, forecasts still commit global energy consumption to a future of roughly 50% growth in demand (see those post-2010 consumption lines in the first graph?). In spite of obvious turbulence in past performance the forecasts assume typical, linear economic growth out to 2035.
While such linear approximations offer hope of anticipating and, hence, preparing for the future, to some degree they represent a logical fallacy of projecting linear trends onto complex, non-linear systems. Living systems like weather patterns, anthills, and global economics are approximately non-deterministic. That is, they’re so complex and have so many feedback mechanisms that they’re mostly unpredictable (weather predictions are still only more-or-less valid for about 5 days out). Much of this complexity arises from the turbulence generated by feedback loops and interconnections across every scale of the system. The power laws underlying dynamic systems take small values and iterate them over time into very large values. This is the mechanism underlying the oft-mentioned Butterfly Effect and one of the drivers for outlier events. Imagine a dust devil spinning up on an otherwise calm desert floor.
Nature seeks homeostasis – a dynamic equilibrium around a point of stability. The counterpoint to runaway feedback loops and suddenly emergent outliers are the damping effects of control elements. In climate, the tendency for hot & cold to equalize will usually mitigate a storm and return clear skies. The dust devil gives up it’s angular momentum to shifting pressure & temperature gradients. Looking at our current affairs we see that total economic collapse has (so far) been averted through aggressive attempts to dampen the turbulence by injecting massive amounts of state capital into the financial system. These interventions & market regulations are control structures put in place to govern for relative economic homeostasis. When they work and things are relatively quiet, they keep those trend projections nice & linear.
Linear projections help us continue to get things done based on fairly reliable expectations. But avoiding the next economic catastrophe requires a deep study of the many threads & amplifiers that drive black swan events. Outliers occupy the thin edge of statistical possibility yet almost always have tremendous consequences. They are, by nature, entropic & disruptive, shifting the territory and demanding new adaptations. To return to the global energy domain, what outliers might be slowly iterating to challenge the forecasts of 50% growth in demand? What catastrophic black swans might be lurking off the radar? What scientific breakthroughs and game-changing innovations might be weaving together towards a complete re-orientation of power requirements, transport, or industrial fuel?
The mobile phone is a great example of a high-impact outlier with a small physical footprint that achieved global ubiquity within 10 years, shredding the linear projections of numerous industries. The pace & breadth of it’s adoption suggests that interventionary technologies can rather quickly have major impacts, challenging heavily invested and entrenched businesses. Imagine an energy outlier with a similar device profile that enabled people to generate & store enough power to run a small home or drive an electric car 100 miles.
Studying a system for outliers and looking for the signals & trends that might lead to the next Black Swan, as well as examining the conditions that have led to previous outlier events, can inform forecasts that are much more attuned to resiliency and adaptation.