Anyway, this is in the intro (p5), and I found it a perfect encapsulation of a core problem in foresight thinking — quantitative vs qualitative methods — well worth retyping out to have on hand for reflection. Here goes:

“The story that I have to tell is marked all the way through by a persistent tension between those who assert that the best decisions are based on quantification and numbers, determined by the patterns of the past, and those who base their decisions on more subjective degrees of belief about the uncertain future This is a controversy that has never been resolved.
The issue boils down to one’s view about the extent to which the past determines the future. We cannot quantify the future, because it is an unknown, but we have learned how to use numbers to scrutinize what happened in the past. But to what degree should we rely on the patterns of the past to tell us what the future will be like? Which matters more when facing a risk, the facts as we see them or our subjective belief in what lies hidden in the void of time? Is risk management a science or an art? Can we even tell for certain precisely where the dividing line between the two approaches lies?
It is one thing to set up a mathematical model that appears to explain everything. But when we face the struggle of daily life, of constant trial and error, the ambiguity of the facts as well as the power of the human heartbeat can obliterate the model in short order.”

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Keynesian or saltwater economics by contrast holds that free markets often behave irrationally and inefficiently, and therefore need corrective policy from government. Saltwater economists say people and institutions often behave in ways contrary to the general good, or in ways that can bring markets (on which they depend) to their knees. Sound familiar?

Anyway, a recent Knowledge@Wharton article comments: “Like a natural science, freshwater economics lends itself to complex, often elegant mathematical modeling. The freshwater view is that consumers, offered an array of choices, will select the one that is best for them — a straightforward assertion that can be neatly expressed in mathematical formulae.

“In contrast, many assertions made in behavioral economics are more challenging to express mathematically. ‘Behavioralists’ argue that consumers don’t always act in their own interests, especially when they fail to understand the choices on offer or succumb to irrational impulses involving those choices… but such impulses are inherently vague and difficult to define.”

Cognitive bias

In other words mathematically modeling the economic future is possible if humans and the markets they create are rational, but far less possible if we act irrationally.

Now, as elaborated in Future Savvy, the fact that humans make irrational choices due to many cognitive biases and heuristics  is indisputable, not least since the work of  Tversky and Kahneman. Biases and heuristics such as “anchoring,” “recency effect,” “personal validation fallacy,” “herd mentality,” and so on, in which people make irrational choices, are well documented.

That’s why mathematical projections of economic behavior are unreliable. The economy may be counted in numbers, but it is still a human system, with associated inefficiency and irrationality. Blow this little debate in economic forecasting up large, and you have the essential problem with quantitative forecasting of any type. It assumes, erroneously, a freshwater view of humanity.

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