Frank Ramsey — a portrait and a critique

from Lars Syll

Mainstream economics nowadays usually assumes that agents that have to make choices under conditions of uncertainty behave according to Bayesian rules, axiomatized by Ramsey (1931) and Savage (1954) — that is, they maximize expected utility with respect to some subjective probability measure that is continually updated according to Bayes theorem. If not, they are supposed to be irrational, and ultimately — via some “Dutch book” or “money pump” argument — susceptible to being ruined by some clever “bookie”.

Bayesian Stats Joke | Data science, Mathematik meme, Mathe witzeBayesianism reduces questions of rationality to questions of internal consistency (coherence) of beliefs, but – even granted this questionable reductionism – do rational agents really have to be Bayesian? As I have been arguing elsewhere (e. g. herehere and here) there is no strong warrant for believing so.

In many of the situations that are relevant to economics, one could argue that there is simply not enough adequate and relevant information to ground beliefs of a probabilistic kind and that in those situations it is not really possible, in any relevant way, to represent an individual’s beliefs in a single probability measure.

Say you have come to learn (based on your own experience and tons of data) that the probability of you becoming unemployed in Sweden is 10 %. Having moved to another country (where you have no own experience and no data) you have no information on unemployment and a fortiori nothing to help you construct any probability estimate. A Bayesian would, however, argue that you would have to assign probabilities to the mutually exclusive alternative outcomes and that these have to add up to 1 if you are rational. That is, in this case – and based on symmetry – a rational individual would have to assign a probability of 10% of becoming unemployed and 90% of becoming employed.

That feels intuitively wrong though, and I guess most people would agree. Bayesianism cannot distinguish between symmetry-based probabilities from information and symmetry-based probabilities from an absence of information. In these kinds of situations, most of us would rather say that it is simply irrational to be a Bayesian and better instead to admit that we “simply do not know” or that we feel ambiguous and undecided. Arbitrary and ungrounded probability claims are more irrational than being undecided in face of genuine uncertainty, so if there is not sufficient information to ground a probability distribution it is better to acknowledge that simpliciter, rather than pretending to possess a certitude that we simply do not possess. 

I think this critique of Bayesianism is in accordance with the views of John Maynard Keynes’ A Treatise on Probability (1921) and General Theory (1937). According to Keynes we live in a world permeated by unmeasurable uncertainty – not quantifiable stochastic risk – which often forces us to make decisions based on anything but rational expectations. Sometimes we “simply do not know.” Keynes would not have accepted the view of Bayesian economists, according to whom expectations “tend to be distributed, for the same information set, about the prediction of the theory.” Keynes, rather, thinks that we base our expectations on the confidence or “weight” we put on different events and alternatives. To Keynes, expectations are a question of weighing probabilities by “degrees of belief”, beliefs that have preciously little to do with the kind of stochastic probabilistic calculations made by the rational agents modelled by Bayesian economists.

In economics, it’s an indubitable fact that few mainstream neoclassical economists work within the Keynesian paradigm. All more or less subscribe to some variant of Bayesianism. And some even say that Keynes acknowledged he was wrong when presented with Ramsey’s theory. This is a view that has unfortunately also been promulgated by Robert Skidelsky in his otherwise masterly biography of Keynes. But I think it’s fundamentally wrong. Let me elaborate on this point (the argumentation is more fully presented in my book John Maynard Keynes (SNS, 2007)).

It’s a debated issue in newer research on Keynes if he, as some researchers maintain, fundamentally changed his view on probability after the critique levelled against his A Treatise on Probability by Frank Ramsey. It has been exceedingly difficult to present evidence for this being the case.

Ramsey’s critique was mainly that the kind of probability relations that Keynes was speaking of in Treatise actually didn’t exist and that Ramsey’s own procedure  (betting) made it much easier to find out the “degrees of belief” people were having. I question this both from a descriptive and a normative point of view.

What Keynes is saying in his response to Ramsey is only that Ramsey “is right” in that people’s “degrees of belief” basically emanate from human nature rather than in formal logic.

Patrick Maher, former professor of philosophy at the University of Illinois, even suggests that Ramsey’s critique of Keynes’s probability theory in some regards is invalid:

Keynes’s book was sharply criticized by Ramsey. In a passage that continues to be quoted approvingly, Ramsey wrote:

“But let us now return to a more fundamental criticism of Mr. Keynes’ views, which is the obvious one that there really do not seem to be any such things as the probability relations he describes. He supposes that, at any rate in certain cases, they can be perceived; but speaking for myself I feel confident that this is not true. I do not perceive them, and if I am to be persuaded that they exist it must be by argument; moreover, I shrewdly suspect that others do not perceive them either, because they are able to come to so very little agreement as to which of them relates any two given propositions.” (Ramsey 1926, 161)

I agree with Keynes that inductive probabilities exist and we sometimes know their values. The passage I have just quoted from Ramsey suggests the following argument against the existence of inductive probabilities. (Here P is a premise and C is the conclusion.)

P: People are able to come to very little agreement about inductive proba- bilities.
C: Inductive probabilities do not exist.

P is vague (what counts as “very little agreement”?) but its truth is still questionable. Ramsey himself acknowledged that “about some particular cases there is agreement” (28) … In any case, whether complicated or not, there is more agreement about inductive probabilities than P suggests …

I have been evaluating Ramsey’s apparent argument from P to C. So far I have been arguing that P is false and responding to Ramsey’s objections to unmeasurable probabilities. Now I want to note that the argument is also invalid. Even if P were true, it could be that inductive probabilities exist in the (few) cases that people generally agree about. It could also be that the disagreement is due to some people misapplying the concept of inductive probability in cases where inductive probabilities do exist. Hence it is possible for P to be true and C false …

I conclude that Ramsey gave no good reason to doubt that inductive probabilities exist.

Ramsey’s critique made Keynes more strongly emphasize the individuals’ own views as the basis for probability calculations, and less stress that their beliefs were rational. But Keynes’s theory doesn’t stand or fall with his view on the basis of our “degrees of belief” as logical. The core of his theory — when and how we are able to measure and compare different probabilities —he doesn’t change. Unlike Ramsey, he wasn’t at all sure that probabilities always were one-dimensional, measurable, quantifiable or even comparable entities.

  1. August 5, 2022 at 9:20 pm

    Banks used to “maximize expected utility” based on risk adjusted interest rates but, after the introduction of risk weighted bank capital requirements, they do so based on risk adjusted returns on required equity. And the world does not understand how that distorts.

  2. deshoebox
    August 6, 2022 at 12:15 am

    Good post, Prof. Syll, and highly relevant. I would like to mention three things in support. First, non-transitive preferences. (Why do economists ignore these?) In any case where there are three or more alternatives and at least three criteria for choosing, it is easy to get a situation where A>B, B>C, but C>A. You can easily. map out the basic idea by considering a diner where they have three kinds of pie, apple, blueberry, and cherry, and you choose which kind to get based on freshness, size of slice, and flavor. If you prefer apple to blueberry because it outranks blueberry on two out of three criteria, and you prefer blueberry to cherry (for the same reason), you might also very well prefer cherry to apple. This is an example of a non-transitive preference, which when you think about it is probably often or even usually the case. Second, people generally don’t know why they make the decisions they make. This has become apparent from brain science, where they can now see the pattern of neuronal excitation (if that is the right term) that accompanies a decision. Further, when asked, the decision-maker will explain their decision by choosing from a range of criteria considered socially acceptable and will then believe that that is the actual reason for the decision, even when it demonstrably is not. Third, and finally, it is not possible to assign probabilities to individual events, so it is meaningless to say that someone believes their chance of unemployment in Sweden is ten percent. Yes, the unemployment rate might be ten percent, but that person’s odds are not the result of a random process. They depend, rather, on a number of factors, some within the control of the person and some not. It cannot, therefore, be intelligible to equate rationality with a person’s ability to compare probabilities of individual events that might affect that person.

  3. ghholtham
    April 26, 2023 at 1:04 pm

    It is extremely discuss to discuss the usefulness of Bayesian methods in total abstraction. The validity of the theorem is not in doubt; the issue is when to apply it. That must depend on what question you are trying to answer and the nature of the information at your disposal. The most important reason for the popularity of Bayesian methods is that they have been shown to work in a wide range of practical applications, whatever methodological concerns people may have had ex ante.
    Consider Lars example of the unemployed Swedish expatriate. If he does not know his chances of employment then he doesn’t know. Bayes does not pretend to tell him. But what is the practical issue facing him? What questions does he need to answer? Bayes says nothing about what he is supposed to believe or do until his objectives and his information set are specified. If he has to take decisions in a situation of uncertainty, he will deploy what information he has and make educated guesses. As he gets more information he will revise the guesses. Then we are in territory where we can consider and probably employ Bayesian methods. Bayesians do not assert that probabilities exist in nature; they are talking about dealing with uncertainty as best you can. We never know everything and seldom know absolutely nothing about our circumstances. And in practice we do not act as if either is the case.

  4. ghholtham
    April 26, 2023 at 3:35 pm

    There you have one of the greatest flaws in so much economics. It theorises as if people do know everything about their circumstances. Or at least everything except for the intrusion of a specifiable random error process. Most of the nonsense in economics comes from ignoring or trivialising uncertainty. People not only don’t know everything but they know they don’t know everything and behave accordingly. I am in complete agreement with Lars on that point.
    People, faced with uncertainty, however, do not generally say “we just don’t know” and relapse into a catatonic state. They make guesses, adopt heuristics and proceed to act. If we know roughly what they know, it is reasonable to look for regularities in their behaviour and to investigate how they respond to new information. The use of subjective probability is legitimate in framing theories to characterise how people behave. As economists we are not trying to forecast the future, containing as it will events beyond our purview, like earthquakes and scientific inventions. We are supposed to be able to say something about how people do, and probably will, react.

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