Is Probability Theory Relevant for Uncertainty? A Post Keynesian Perspective

Mainstream perspectives involving uncertainty presume that expectations are based on either a statistical analysis of past data, with market signals providing information about objective probabilities, or on subjective perceptions of these probabilities founded on the axioms of expected utility theory. Post Keynesians, following Keynes, have developed a different perspective, where probability distributions are not the basis for comprehending real world behavior under uncertainty. According to this analysis, there are many important situations where "true" uncertainty exists regarding future consequences of today's choices. Whenever conditions of true uncertainty prevail, human behavior may differ systematically from what is implied by the standard expected utility perspective. This paper explains how the Post Keynesian perspective differs from the orthodox probability theory approach, thereby providing a more general theory which can explain long-run decisions regarding liquidity demands, investment decisions, the existence of long period underemployment equilibrium, the long-run nonneutrality of money, and the unique and important role Keynes assigned to nominal contracts and especially the money wage contract.