Binmore on when Bayesian decision theory applies and when it does not
Binmore, a game theorist, examines the foundations of rational decision theory and argues that its standard apparatus is being applied far outside the conditions under which it is valid. His organising distinction, borrowed from Savage, is between a small world, where all states, consequences and probabilities can be specified in advance, and a large world, where they cannot.
His argument is that Bayesian decision theory is correct and unassailable in small worlds and has no justification in large ones. Savage himself said applying his theory to a large world would be utterly ridiculous, and Binmore takes this seriously. He works through the standard justifications for Bayesian priors, including the principle of insufficient reason and various axiomatic derivations, and argues each fails when the state space itself is not known. He also addresses the Ellsberg paradox, ambiguity aversion, and the question of what a probability means when there is no frequency to ground it.
He is critical of both the Bayesian orthodoxy in economics, for extending the theory beyond its warrant, and of some behavioural economics, for treating deviations from a theory that does not apply as evidence of irrationality.
The book is technical and requires mathematics. It offers a diagnosis more than a replacement, since Binmore's positive proposal for large worlds is tentative. For investors the value is precise: it tells you when probability-based reasoning is well founded and when assigning a number is a gesture rather than an analysis, which is the question that most quantitative risk work avoids.
Analytically minded investors and risk practitioners who need to know when probability-based decision analysis is well founded and when it is not.
Chosen by shared topics, the entries that hold them, and the people who recommended both.

