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Symposium 2015

Solution for Dealing with Radical Uncertainty

The Challenge

One of Karl Popper’s key insights about human predictive capacity was that "Quite apart from the fact that we do not know the future, the future is objectively not fixed. The future is open: objecti ...

One of Karl Popper’s key insights about human predictive capacity was that "Quite apart from the fact that we do not know the future, the future is objectively not fixed. The future is open: objectively open." But most macroeconomists and finance theorists have presumed exactly the opposite. They have increasingly come to rely on internally consistent models that fully specify in advance how market participants might alter the ways in which they make decisions and how aggregate outcomes unfold over time. Models in this spirit, such as so called "rational expectations" (RE) models have not been highly effective in predicting macroeconomic outcomes. They also do poorly at accounting for the behavior of asset prices.

Technology is forcing agents to abandon rational choice behavior

 

The background
Economics is essentially a theory of individual behavior, and specifically how agents choose between alternatives. Its core theory is that of rational choice. Agents gather information—which might not be complete—on the attributes of alternatives and compare them to their preferences. A key dimension of “attributes” is price. This model underpins a great deal of policy in the West, e.g., pricing the unemployed back into work by reducing benefits. The model is not wrong. But the areas of social and economic activity to which it is relevant are shrinking rapidly. When the theory was formalized in the late 19th century, it was a reasonable description of much of the world—agents could gather information on alternatives. Cyber society alters this dramatically. Simon (1955) was already concerned that humans lacked the processing capacity to behave “rationally.” Dirk Helbing estimates that the volume of data which humans produced in our entire history up to the mid-2000s is now produced every single day. Beinhocker estimates that a typical consumer in New York City faces in principle 10 billion alternatives each day. Uncertainty is simply a special case of this more general problem. We lack the processing capacity to make “rational” choices in many areas of activity in the 21st century.

The implications
Cyber society—technology—is forcing agents to use a different type of rule in making choices. The attributes of alternatives are becoming much less relevant. Essentially, agents use some form of copying heuristic. This was suggested by Keynes (1937), Alchian (1950), Simon (op.cit.), for example. “Copying” models have a strong tendency to be self-reinforcing. A classic illustration of this is the work of Brian Arthur on path dependency and lock-in (for example, Arthur (1989)). They tend to lead to monopolistic/oligopolistic outcomes—e.g., many markets shares on the web.

The solution
Copying models based on evolutionary principles are highly congruent with empirical evidence of outcomes. These models are based essentially on copying, but allow for a (small) probability of “innovation,” of choosing something no-one has chosen before. The larger is the innovation weight, the less likely concentrated outcomes become, and the greater is effective competition. So the solution requires the rate of innovation to be raised. The problem of declining innovation is such that only the public sector can kick start the process which leads to a solution. Moving averages of 20 year growth rates of real GDP in the main EU economies has been falling continuously since 1970. But this requires a completely different attitude on the part of both the European Commission and national governments within the EU. Rather than subsidize declining industries, as the Italians are currently doing with the major steel plant in Southern Italy, or support research which offers only marginal increases in the stock of knowledge, the state itself needs to operate much more like American venture capitalists. Potentially disruptive technologies and applications need to be supported, with a full understanding of the fact that most of them will fail (Ormerod 2005).

Values
“Creative destruction” is undoubtedly disruptive and imposes costs on those who bear its immediate impact. But as Mokyr et al. (2015) state “Nineteenth-century political economists lacked an ability to predict new job categories like the personal fashion consultants, cyber security experts, and online-reputation managers of the twenty-first century”.

 

References

Simon, Herbert A. “A behavioral model of rational choice.” The Quarterly Journal of Economics (1955): 99-118.

Alchian, Armen A. “Uncertainty, evolution, and economic theory.” The Journal of Political Economy (1950): 211-221.

Arthur, W. Brian. “Competing technologies, increasing returns, and lock-in by historical events.” The Economic Journal (1989): 116-131.

Mokyr, Joel, Chris Vickers, and Nicolas L. Ziebarth. “The History of Technological Anxiety and the Future of Economic Growth: Is This Time Different?.” The Journal of Economic Perspectives 29.3 (2015): 31-50.

Keynes, J.M. “The general theory of employment”, The Quarterly Journal of Economics 51.2 (1937): 209-223.

Ormerod, Paul. “Why Most Things fail: Economics, Extinction and Evolution” (2005): Faber and Faber, London.

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