Risk vs Uncertainty

There is a big fuss (and considerable confusion) in the literature about the distinction between risk and uncertainty. According to Frank Knight (1885-1972), the distinction is (or rather should be) that risk is measurable, say by a probability distribution, whereas uncertainty is unmeasurable.

The term Knightian uncertainty is often used to emphasize the fact that the “uncertainty is unmeasurable” (e.g. it cannot be quantified by a probability distribution).

It can be argued, however, that this distinction is sterile in that in most cases the distinction is a matter of degree rather than type. So, if a distinction has to be made, it should be more refined, to allow a spectrum of intermediate levels of “measurablility”, ranging from say “very poor” to “excellent”.

And this what Nassim Taleb (2007) has to say about this in the Black Swan (page 128) :

In real life you do not know the odds; you need to discover them, and the sources of uncertainty are not defined. Economists, who do not consider what was found by noneconomists worthwhile, draw an artificial distinction between Knightian risk (which you can compute) and Knightian uncertainty (which you cannot compute), after one Frank Knight, who rediscovered the notion of unknown uncertainty and did a lot of thinking but perhaps never took risks, or perhaps lived in the vicinity of a casino. Had he taken financial or economic risk he would have realized that these “computable” risks are largely absent from real life! They are laboratory contraptions.

In any case, in the literature it is common practice to indicate the degree of “uncertainty” by using a variety of terms, such as

deep, essential, extreme, fundamental, hard, high, Knightian, profound, radical, severe, strict, substantial, true, true Knightian

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