Decision-making under uncertainty: ‘after Keynes’

I have a new discussion paper. I am happy to take comments here, on LinkedIn, at the more formal Economics e-journal site or by email (if you have it!), but wish to record substantive comments on the journal site while continuing to build up a site of whatever any school of thought may think is relevant, with my comments, here.

Please do comment somewhere.

Clarifications

I refer to Keynes’ ‘weights of argument’ mostly as something to be taken into account in addition to probability. For example, if one has two urns each with a mix of 100 otherwise identical black and white balls, where the first urn is known to have equal number of each colour, but the mix for the other urn is unknown, then conventionally one has equal probability of drawing a black ball form each urn, but the weight of argument is greater for the first than the second.

Keynes does fully develop his notion of weights and it seems not to be well understood, and I wanted my overview of Keynes’ views to be non-contentious. But from some off-line comments I should clarify.

Ch. VI para 8 is worth reading, followed by Ch. III para 8. Whatever the weight may be, it is ‘strengthened by’:

  • Being more numerous.
  • Having been obtained with a greater variety of conditions.
  • Concerning a greater generalisation.

Keynes argues that this weight cannot be reduced to a single number, and so weights can be incomparable. He uses the term ‘strength’ to indicate that something is increased while recognizing that it may not be measurable. This can be confusing, as in Ch. III para 7, where he refers to ‘the strength of argument’. In simple cases this would just be the probability, not to be confused with the weight.

It seems to me that Keynes’ concerns relate to Mayo’s:

Severity Principle: Data x provides a good evidence for hypothesis H if and only if x results from a test procedure T which, taken as a whole, constitutes H having passed a severe test – that is, a procedure which would have, with very high probability, uncovered the discrepancies from H, and yet no such error is detected.

In cases where one has performed a test, severity seems to roughly correspond to have a strong weight, at least in simpler cases. Keynes’ notion applies more broadly. Currently, it seems to me, care needs taking in applying either to particular cases. But that is no reason to ignore them.

 

 

Dave Marsay

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About Dave Marsay
Mathematician with an interest in 'good' reasoning.

4 Responses to Decision-making under uncertainty: ‘after Keynes’

    • Dave Marsay says:

      Thanks, Egmont. Your first starts “Science restricts itself to things that can be known.” By ‘known’ I take it that there is no uncertainty, or at most tame probabilistic uncertainty. Thus, for example, if I were to ask to what precise value the proportion of tosses/flips that will yield ‘Heads’ will tend for a given coin, this is outside the scope of science, since I cannot know. If I have already performed some experiments then I may be able to assign a probability distribution, but only subject to some quite strict assumptions.

      If science were like this, then we could apply conventional decision theory. All would be well. But then we could not ask about global warming, potential epidemics or economies. It seems to me that contemporary usage allows a much wider class of enquiries to be regarded as science. This results in a less stringent (and reliable) type of knowledge. It seems important, therefore, to map the type of decision-making to the type of knowledge, and particularly its conditionality. Economics seems to suffer by getting this wrong.

  1. Pingback: Uncertainty is not just probability | djmarsay

  2. Pingback: More to Uncertainty than Probability! | djmarsay

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