by It may be argued … that the betting quotient and credibility are substitutable in the same sense in which two commodities are: less bread but more meat may leave the consumer as well off as before. If this were, then clearly expectation could be reduced to a unidimensional concept … However, the substitutability of consumers’ goods rests upon the tacit assumption that all commodities contain something — called utility — in a greater or less degree; substitutability is therefore another name for compensation of utility. The crucial question in expectation then is whether credibility and betting quotient have a common essence so that compensation of this common essence would make sense. Just like Keynes underlined with his concept of ‘weight of argument,’ Georgescu-Roegen,
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It may be argued … that the betting quotient and credibility are substitutable in the same sense in which two commodities are: less bread but more meat may leave the consumer as well off as before. If this were, then clearly expectation could be reduced to a unidimensional concept … However, the substitutability of consumers’ goods rests upon the tacit assumption that all commodities contain something — called utility — in a greater or less degree; substitutability is therefore another name for compensation of utility. The crucial question in expectation then is whether credibility and betting quotient have a common essence so that compensation of this common essence would make sense.
Just like Keynes underlined with his concept of ‘weight of argument,’ Georgescu-Roegen, with his similar concept of ‘credibility,’ underscores the impossibility of reducing uncertainty to risk and thereby being able to describe choice under uncertainty with a unidimensional probability concept.
In ‘modern’ macroeconomics — Dynamic Stochastic General Equilibrium, New Synthesis, New Classical, and New ‘Keynesian’ — variables are treated as if drawn from a known ‘data-generating process’ that unfolds over time and on which we, therefore, have access to heaps of historical time-series. If we do not assume that we know the ‘data-generating process’ – if we do not have the ‘true’ model – the whole edifice collapses. And of course, it has to. Who honestly believes that we should have access to this mythical Holy Grail, the data-generating process?
‘Modern’ macroeconomics obviously did not anticipate the enormity of the problems that unregulated ‘efficient’ financial markets created. Why? Because it builds on the myth of us knowing the ‘data-generating process’ and that we can describe the variables of our evolving economies as drawn from an urn containing stochastic probability functions with known means and variances.
This is like saying that you are going on a holiday trip and that you know that the chance of the weather being sunny is at least 30% and that this is enough for you to decide on bringing along your sunglasses or not. You are supposed to be able to calculate the expected utility based on the given probability of sunny weather and make a simple decision of either or. Uncertainty is reduced to risk.
But as both Georgescu-Roegen and Keynes convincingly argued, this is not always possible. Often we simply do not know. According to one model the chance of sunny weather is perhaps somewhere around 10% and according to another – equally good – model the chance is perhaps somewhere around 40%. We cannot put exact numbers on these assessments. We cannot calculate means and variances. There are no given probability distributions that we can appeal to.
In the end, this is what it all boils down to. We all know many activities, relations, processes, and events are of the Georgescu-Roegen-Keynesian uncertainty type. The data do not unequivocally single out one decision as the only ‘rational’ one. Neither the economist nor the deciding individual can fully pre-specify how people will decide when facing uncertainties and ambiguities that are ontological facts of the way the world works.
Some macroeconomists, however, still want to be able to use their hammer. So they decide to pretend that the world looks like a nail, and pretend that uncertainty can be reduced to risk. So they construct their mathematical models on that assumption. The result: financial crises and economic havoc.
How much better — how much bigger chance that we do not lull us into the comforting thought that we know everything and that everything is measurable and we have everything under control — if instead, we could just admit that we often simply do not know and that we have to live with that uncertainty as well as it goes.
Fooling people into believing that one can cope with an unknown economic future in a way similar to playing at the roulette wheels, is a sure recipe for only one thing — economic disaster.