Abstract

Mainstream theories of decision making conceptualise uncertainty in terms of a well-defined probability distribution or weighting function. Following Knight, radical Keynesians consider subjective expected utility (SEU) theory and its variants as a restricted theory of decision-making applicable to situations of risk and, hence, of limited relevance to the understanding of crucial economic decisions under conditions of fundamental uncertainty in which probabilities are ill-defined, possibly non-existent. The objective of this paper is to outline a radical Keynesian theory of decision-making under uncertainty, arguing that Keynes's suggestion to a two-dimensional probability-credence framework provides the basis for determining the limitations of mainstream approaches and points the way forward to the construction of a more general encompassing theory relevant to psychologists and economists outside of the Keynesian tradition.