by Keynes and Knight on uncertainty First, Knight and Keynes derive from their different philosophical worldviews distinct definitions of uncertainty. Keynes’s is a wholly epistemic uncertainty concept (see Packard and Clark, 2020), the ignorance of an actor regarding the objective and knowable (a priori) probabilities of future outcomes. Such probabilities are discoverable by learning the underlying ‘probability-relations’ between causes and effects. Scientific efforts mitigate uncertainty by illuminating these probability-relations and by producing ever-increasing evidential weight until each uncertainty is eventually absconded. Mark D Packard, Per L Bylund, Brent B Clark An interesting paper that merits a couple of comments. To understand real-world
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Keynes and Knight on uncertainty
First, Knight and Keynes derive from their different philosophical worldviews distinct definitions of uncertainty. Keynes’s is a wholly epistemic uncertainty concept (see Packard and Clark, 2020), the ignorance of an actor regarding the objective and knowable (a priori) probabilities of future outcomes. Such probabilities are discoverable by learning the underlying ‘probability-relations’ between causes and effects. Scientific efforts mitigate uncertainty by illuminating these probability-relations and by producing ever-increasing evidential weight until each uncertainty is eventually absconded.
An interesting paper that merits a couple of comments.
To understand real-world ‘non-routine’ decisions and unforeseeable changes in behaviour, ergodic probability distributions are of no avail. In a world full of genuine uncertainty — where real historical time rules the roost — the probabilities that ruled the past are not those that will rule the future.
Time is what prevents everything from happening at once. To simply assume that economic processes are ergodic and concentrate on ensemble averages — and a fortiori in any relevant sense timeless — is not a sensible way of dealing with the kind of genuine uncertainty that permeates open systems such as economies.
Recognizing that real social and economic processes are nonergodic is important, as uncertainty—not risk—rules the roost. Both Keynes and Knight basically said this in their 1921 books. Thinking about uncertainty in terms of ‘rational expectations’ and ‘ensemble averages’ has had seriously bad repercussions on the financial system.
But — when it comes to characterizing Keynes’ and Knight’s uncertainty theories in terms of epistemology and ontology, Packard et al. get it completely wrong!
Knight’s uncertainty concept has an epistemological founding and Keynes’ definitely has an ontological founding. Of course, this also has repercussions on the issue of ergodicity in a strict methodological and mathematical-statistical sense. I think Keynes’ view is the most warranted of the two.
The most interesting and far-reaching difference between the epistemological and the ontological view is that if one subscribes to the former, the Knightian view, one opens up to the mistaken belief that with better information and greater computer power, we somehow should always be able to reduce model misspecification and/or invent new and better models to calculate probabilities and describe the world as an ergodic universe. As Keynes convincingly argued, that is often (unless we think we actually live our lives in Savage’s ‘small world’) not ontologically possible.
To Keynes, the source of uncertainty was in the nature of the real — nonergodic — world. It had to do, not only — or primarily — with the epistemological fact of us not knowing the things that today are unknown, but rather with the much deeper and far-reaching ontological fact that there often is no firm basis on which we can form quantifiable probabilities and expectations at all.
Sometimes we do not know because we cannot know.