Macroeconomic machine dreams

1 July, 2016 at 08:36 | Posted in Economics | 1 Comment

blog_robot_overlordsMany mainstream macroeconomists  hold on to the hope that they will not be doomed forever to always ‘fight the last war,’ but instead, building on timeless microfoundational rules — Lucas ‘deep parameters’ — they will be able to predict upcoming problems before they happen. Adding some new little twist to the DSGE model will make all the difference …

What these economists ‘forget,’ however, is that to produce these n:th variations of the basic DSGE model, they still have to make ridiculously simplifying assumptions to make the models ‘forecast’ anything.

This is nothing but the age-old machine dream of neoclassical economics — an epistemologically founded cyborg dream that disregards the fundamental ontological fact that economies and societies are open — not closed — systems.

the-only-function-of-economic-forecasting-is-to-make-astrology-look-respectable-quote-1The empirical and theoretical evidence is clear. Predictions and forecasts are inherently difficult to make in a socio-economic domain where genuine uncertainty and unknown unknowns often rule the roost. The real processes that underly the time series that economists use to make their predictions and forecasts do not confirm with the assumptions made in the applied statistical and econometric models. Much less is a fortiori predictable than standardly — and uncritically — assumed. The forecasting models fail to a large extent because the kind of uncertainty that faces humans and societies actually makes the models strictly seen inapplicable. The future is inherently unknowable — and using statistics, econometrics, decision theory or game theory, does not in the least overcome this ontological fact. The economic future is not something that we normally can predict in advance. Better then to accept that as a rule “we simply do not know.”

In an interesting discussion on the hopelessness of accurately modeling what will happen in the real world, Nobel laureate Kenneth Arrow – in Eminent Economists: Their Life Philosophies (CUP 1992) – pretty well sums up what the forecasting business is all about:

It is my view that most individuals underestimate the uncertainty of the world. This is almost as true of economists and other specialists as it is of the lay public. To me our knowledge of the way things work, in society or in nature, comes trailing clouds of vagueness … Experience during World War II as a weather forecaster added the news that the natural world as also unpredictable. cloudsAn incident illustrates both uncertainty and the unwillingness to entertain it. Some of my colleagues had the responsibility of preparing long-range weather forecasts, i.e., for the following month. The statisticians among us subjected these forecasts to verification and found they differed in no way from chance. The forecasters themselves were convinced and requested that the forecasts be discontinued. The reply read approximately like this: ‘The Commanding General is well aware that the forecasts are no good. However, he needs them for planning purposes.’


1 Comment

  1. We come again and again to the same basic point, which might be summarized in two observations: First, that mainstream economics fails to distinguish analytic from synthetic reasoning, analytic theory from operational modeling in its understanding of its own methodology. This is a profound epistemic error, which leads again and again to an inability among economists to distinguish a knowledge of a priori economic theory from <a posteriori knowledge of the institutional economy.
    Many critics seem almost as reluctant to make use of this basic distinction, drawn from epistemology and the philosophy of science, as the most stubborn fundamentalist defenders of the mainstream faith. It should not be that hard, but apparently it is, to distinguish a geometry from cartography.
    But it is hard, apparently, and we should inquire into why. One reason for the difficulty is this: geometry forms a kind of analogue to a map. The abstract lines and points of geometry, though without measure, correspond to the abstracted lines and points of a map.
    Which brings me to the second observation: the pervasive role of uncertainty in the actual economy breaks the analogue. It is simply not possible to introduce an assumption of pervasive uncertainty into analytic theory and get anything done. The theorist can take half-measures, to sneak up on uncertainty and explore its implications, by assuming some aspect of uncertainty, but the theorist can never take uncertainty whole and complete, without breaking the ability of the analysis to reach a result. Pervasive and complete uncertainty, as an axiom, would destroy tractability.
    The result is an analytic theory that can propose no analogues for operational models of actual institutional economies. The “geometry” of economic theory, without uncertainty, offers misleading ideals, like perfect competition; while the actual institutional economy is shaped by pervasive uncertainty into something quite different. Uncertainty, a factual reality that must shape any accurate operational model, turns the suggestive analogues of analytic theory upside down.
    The situation is hopeless as long as economists persist in trying to make theoretical analysis do much more than it is capable of doing, while neglecting the necessary work of studying the actual economy with suitable and realistic operational models that acknowledge pervasive uncertainty.

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