Radical Uncertainty

Bryan Caplan has issued a challenge:

Austrian economists often attack the mainstream for ignoring something they call “radical uncertainty,” “sheer ignorance,” or sometimes “Knightian uncertainty.” A common Austrian slogan is that “Neoclassical economists study only cases where people know that they don’t know; we study cases where people don’t know that they don’t know.”

All of this sounds plausible until you press the Austrian to do one of two things:

1. Explain his point using standard probability language. What probability does “don’t know that you don’t know” correspond to? Zero? But if people really assigned p=0 to an event, than the arrival of counter-evidence should make them think that they are delusional, not than a p=0 event has occured.

2. Give a good concrete example.

Austrians (as well as Post Keynesians), I believe, are correct to criticize neoclassical theory in this manner. Neoclassical theory assumes that there is a market of complete contingent contracts with an assigned probability for each anticipated state. This undoubtedly does not reflect reality as there exist states for which no contract is traded. As Keynes explained in “The General Theory of Employment” in the QJE in 1937:

But at any given time facts and expectations were assumed [by the classical economists] to be given in a definite and calculable form; and risks, of which, though admitted, not much notice was taken, were supposed to be capable of an exact actuarial computation. The calculus of probability, though mention of it was kept in the background, was supposed to be capable of reducing uncertainty to the same calculable status as that of certainty itself.

Actually, however, we have, as a rule, only the vaguest idea of any by the most direct consequences of our acts … Thus the fact that our knowledge of the future is fluctuating, vague and uncertain, renders wealth a peculiarly unsuitable subject for the methods of the classical economic theory.

By uncertain knowledge, let me explain, I do not mean merely to distinguish what is known for certain from what is merely probable … The sense in which I am using the term is that in which the price of copper and the rate of interest twenty years hence, or the obsolescence of a new invention are uncertain. About these matter there is no scientific basis on which to form any calculable probability whatever. [Emphasis added.]

The infamous beauty contest described in the General Theory is also a particularly useful analogy for stock market activity and speculation. Of course Keynes was overly pessimistic, in my view, of our ability to form meaningful expectations. Roger Koppl, for example, bridges the gap between Keynes and reality in Big Players and the Economic Theory of Expectations by discussing the emergence of planning horizons, in which each point in the future grows evermore uncertain and therefore the more distant the period, the more open-ended one’s expectations must become. Nevertheless, Keynes’ views on probability theory and economics is much more grounded in reality than the Arrow-Debreu markets for contingent claims.

Perhaps ironically, Keynes’ views on uncertainty are greatly complemented by the work of F.A. Hayek. Whereas Keynes explicitly laid out a vision of why things go wrong, Hayek countered (although not directly) by explaining how things could go right. Hayek’s work on economics and knowledge (here and here, for example) details how, even in the presence of uncertainty and dispersed knowledge, markets serve coordinate behavior and produce efficient outcomes. Similarly, Hayek’s writing on expectations detail how an individual’s views evolve over time and adjust in response to confirmation (or lack thereof) of expectations. Overall, the market provides signals through prices as well as through the profit and loss mechanism and therefore individuals are able to evaluate their expectations and evolve accordingly. Thus, Keynes provides the outline for the radical uncertainty that individuals face and Hayek explains how individuals are able to overcome and cope with said uncertainty. As I have stated previously, this is a much better description of reality than Arrow-Debreu contingent claims.

As to Bryan’s questions, in assigning probabilities (p = x, for example) for events that people don’t know that they don’t know, it is irrelevant what value x takes on as long as their expectations are proven grossly incorrect ex post or the probability of such an event precludes the existence of a contingent contract for that event. Had one posed a question on September 10, 2001 regarding the probability of a terrorist attack the following day the mean probability would undoubtedly not have been equal to 1 (it would likely have been less than 0.01) and I would venture to guess that it is even unlikely that one would have received a single response of 100%. Similarly, for Tyler Cowen’s example of the arrival of the Spaniards.

2 responses to “Radical Uncertainty

  1. I disagree. This is not about markets (and, btw, you can have models with incomplete markets). This is about modeling choice/agents.

    And, in what sense do you speak of a probability “ex post”? Probability = Favorable cases / All cases. Or a subjective quantity.

    A better question would be, I think… is there more than subjected expected utility?

  2. Pingback: More on Radical Uncertainty « The Everyday Economist

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