J M Keynes on the Definition of Uncertainty: Why Uncertainty must come in Degrees and has nothing to do with Ergodicity or Non Ergodicity

Abstract

<p>Keynes’s definition of uncertainty is directly based on his weight of the argument (evidence) relation, analyzed in chapters 6 and 26 of the A Treatise on Probability (1921), page 148,as well as the footnote on page 148 ,of the General Theory (1936) ,and multiple pages of his February, 1937 Quarterly Journal of Economics article. There is no discussion of the definition of Uncertainty in his exchanges with Jan Tinbergen in 1939-40 in the Economic Journal.</p><p><br />Paul Davidson and his Post Keynesian-Institutionalist supporters base their Ergodic-Non Ergodic approach to the definitions of uncertainty and risk on the inductive fallacy of Conditional A priorism (Long Runism).The claim , made by Paul Davidson and his Post Keynesian-Institutionalist supporters for over 30 years, that decision makers are able to identify the ergodicity or non ergodicity of long run stochastic sequences or series of events or outcomes in the short run ,based on Davidson’s claim that decision makers are able to know or learn of the convergence properties of such series or sequences, which can only be known “in the long run “(infinity), by examining sub series or sub sequences ,is patently false and not accepted by any scholar in any other academic field .</p><p><br />Davidson bases his binary approach to uncertainty, which rules out any concept of different degrees to knowledge (certainty) and unknowledge (uncertainty), on both metaphysical speculations and/or a priori claims to knowledge. There can be no such thing as probable knowledge under this binary approach.</p>