## Goodbye, homo economicus. Hello, what?

Concerning the recent financial crisis, Anatole Kaletsky writes

“Academic economists have thus far escaped much blame for the crisis. Public anger has focused on more obvious culprits: greedy bankers, venal politicians, sleepy regulators or reckless mortgage borrowers. But why did these scapegoats behave in the ways they did? Even the greediest bankers hate losing money so why did they take risks which with hindsight were obviously suicidal? The answer was beautifully expressed by Keynes 70 years ago: “Practical men, who believe themselves to be quite exempt from any intellectual influence, are usually the slaves of some defunct economist. Madmen in authority, who hear voices in the air, are distilling their frenzy from some academic scribbler of a few years back.”

What the “madmen in authority” heard this time was the distant echo of a debate among academic economists begun in the 1970s about “rational” investors and “efficient” markets. This debate began against the backdrop of the oil shock and stagflation and was, in its time, a step forward in our understanding of the control of inflation. But, ultimately, it was a debate won by the side that happened to be wrong. And on those two reassuring adjectives, rational and efficient, the victorious academic economists erected an enormous scaffolding of theoretical models, regulatory prescriptions and computer simulations which allowed the practical bankers and politicians to build the towers of bad debt and bad policy.”

The whole article continues in a similar vain:

More challenging to the orthodoxy of academic economics have been approaches that rejected the principle that economic behaviour could be described by precise mathematical relationships at all. Benoit Mandelbrot, one of the great mathematicians of the 20th century, who pioneered the analysis of chaotic and complex systems, describes, in The (Mis)behaviour of Markets, how economists ignored 40 years of progress in the study of earthquakes, weather, ecology and other complex systems, partly because the non-Gaussian mathematics used to study chaos did not offer the precise answers of EMH. The fact that the answers provided by EMH were wrong seemed no deterrent to “scientific” economics.

This is fairly representative of the large number of recent articles and essays suggesting that the current economic distress calls for a rejction of some or all of what the author believes to be the mainstream approach to economics.

Some of these criticisms are valid, although the recent crisis doesn’t make them any more valid. But most miss their targets entirely. Eugene Fama was writing (with Mandelbrot!) about fat tails and non-Gaussian distributions since about the same time he was writing about efficient markets. Bad loans were originated mostly on the basis of data driven credit scoring models, not general equilibrium models where the representative agents have rational expectations. And so on…

That doesn’t mean there aren’t things about economics that could use some fixing. But the proposed solution has to offer some potential for improvement. Theories based on animal spirits, irrational agents, etc. can explain anything but economists ought to be able to do more than point out that “anything is possible and anything can happen.” Even after the fact, theories based on irrationality and animal spirits don’t add very much to the historical narrative. There may come a time when economics will be improved by a deliberate effort to reconcile mainstream economics with the methods and findings of psychology and sociology. I’ll wait until those calling for such a change can enumerate a set of new and improved theories and their concrete implications.

## Recursive justification vs. probabilism

We are like sailors who on the open sea must reconstruct their ship but are never able to start afresh from the bottom. Where a beam is taken away a new one must at once be put there, and for this the rest of the ship is used as support. In this way, by using the old beams and driftwood the ship can be shaped entirely anew, but only by gradual reconstruction.

— Otto Neurath

This sort of recursive justification doesn’t seem to work very well, at least not according to the laws of probability. Consider the simple case where A and B are used to justify C, B and C are used to justify A and A and C are used to justify B.

Since C is derived from A and B, the probability we assign to C cannot exceed the greater of P(A) and P(B), and should in fact be less e.g. to account for the possibility that we’ve reasoned incorrectly and mistakenly concluded that A and B imply C. The same applies to each of the other claims and whatever other claims serve as their basis.

Since all beliefs are to be subject, at least according to a thoroughgoing probabilist, to review, the probability of each must be less than 1. How might this actually work out? What probabilities could we assign that satisfy some basic rules concerning probabilities so that

P(A) < max[P(B),P(C)] < 1

P(B) < max[P(C),P(A)] < 1

P(C) < max[P(A),P(B)] < 1

and correspond to believing A, B and C and yet still leaving open the possibility of revision along Bayesian lines or something similar so that

m < P(A) < 1

m < P(B) < 1

m < P(C) < 1

where m is the minimum sufficient degree of belief such that assigning P(X) = m is equivalent to believing that X?

As it happens, this is a problem without a solution. That is, if our confidence in each of our beliefs comes from our ability to derive it from some subset of our other beliefs, then any level of confidence is unreasonable, according to the laws of probability. Why? Because if we hold N beliefs, recursive justification implies that our degree of confidence in any belief can be no greater than the degree of confidence that we have in the most strongly held supporting belief and so on, implying some clearly impossible relation along the lines of

P(Belief 1) < P(Belief 2) < P(Belief 3) < … P(Belief N) < P(Belief 1).

One attempt at rehabilitation of recursive justification might be to suppose that each belief can be justified by multiple non-intersecting subsets of other beliefs. For example, A is implied by (B,C) and also by (D,E). For the moment, assume away the possibility of mistaken inference to A, so that P(A) = P((B,C) or (D,E)). Could each belief in the set {A,B,C,D,E} be justified from the other beliefs in the set in a way which is consistent with the laws of probability theory? (Whether or not any actual human holds actual beliefs in such a relation is another matter.)

To do: Find numerical values for P(A), P(B), P(C), P(D), and P(E) that allow each belief to be justified by the others, and that satisfy the laws of probability, or show that no such set of values exists.

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