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On the relationship between Keynes's conception of evidential weight and the Ellsberg paradox
No full textA number of scholars have noted that Ellsberg’s seminal 1961QJE critique of the subjective expected utility model bears certain resemblances to ideas expressed in J. M. Keynes’s 1921 A Treatise on Probability. Ellsberg did not mention Keynes’s work in his article and referred instead to F. Knight’s distinction between ‘risk’ and ‘uncertainty’, thus inspiring a literature on various aspects of ‘Knightian uncertainty’. Nevertheless, the recent publication of Ellsberg’s PhD dissertation [Ellsberg, D. (2001). Risk, ambiguity and decision. New York: Garland Publishing], submitted to the University of Harvard in 1962, reveals that Ellsberg was actually aware of Keynes’s work. This gives rise to a number of interesting questions concerning the relation between the two authors’ works. The present paper, drawing in part on a conversation with Ellsberg, attempts to answer these questions. It turns out that the ‘mystery’ of why Ellsberg did not mention Keynes in his QJE article has a simple solution, namely that his dissertation was only completed after he had written the QJE article and that he had only come across Keynes after writing the QJE article. However, it is argued that although Ellsberg recognised the link between his notion of ambiguity and Keynes’s conception of the weight of argument in his PhD dissertation, he did not fully appreciate the fact that Keynes was more concerned with ‘practical’ rather than ‘conventionalised’ choice situations. To this extent, therefore, it is fair to say that ‘Knightian uncertainty’ is in many ways closer to the ideas expressed by Keynes than by Knight, and Keynes’s actual contribution to modern decision theory has been underestimated
Uncovering unknown unknowns: Towards a Baconian approach to management decision-making
Get PDFBayesian decision theory and inference have left a deep and indelible mark on the literature on management decision-making. There is however an important issue that the machinery of classical Bayesianism is ill equipped to deal with, that of “unknown unknowns” or, in the cases in which they are actualised, what are sometimes called “Black Swans”. This issue is closely related to the problems of constructing an appropriate state space under conditions of deficient foresight about what the future might hold, and our aim is to develop a theory and some of the practicalities of state space elaboration that addresses these problems. Building on ideas originally put forward by Bacon (1620), we show how our approach can be used to build and explore the state space, how it may reduce the extent to which organisations are blindsided by Black Swans, and how it ameliorates various well-known cognitive biases
On Keynes's conception of the weight of evidence
Get PDFVarious modern decision theories seek to capture the intuition behind Keynes's conception of evidential weight. Keynes was nevertheless hesitant about the practical relevance of weight in the process of rational decision making because of the 'stopping problem' of finding a rational principle to decide where to stop the process of acquiring information in forming a probability judgment before making a decision. This paper discusses the relevance of the stopping problem by way of an inquiry into the nature, properties and implications for rational decision making of Keynes's conception of evidential weight. It is argued that in practical choice situations the decision maker often decides where to stop the process of acquiring information by following Keynes's advice to consider the degree of completeness of the available information before making a decision. This method implies that the decision maker is able to arrive at an assessment of the dimension of what may be called her 'relevant ignorance'. By considering some examples of how the acquisition of new evidence may affect the decision maker's behaviour, it is argued that it is in fact possible to talk reasonably about relevant ignorance, or what are sometimes called 'unknown unknowns', and that this concept might explain a range of human behaviours. While this concept does not provide a rational principle to solve the stopping problem, it does provide a method of inquiry for dealing with a number of paradoxes not solvable within the Bayesian approach
F. H. Knight’s Risk, Uncertainty, and Profit and J. M. Keynes’ Treatise on Probability after 100 years
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De Finetti and Savage on the normative relevance of imprecise reasoning: a reply to Arthmar and Brady
Get PDFThis paper examines the claim that de Finetti and Savage completely rejected the notion of indeterminate, as distinct from imprecise, probabilities. It argues that their examination of imprecise reasoning refers both to descriptive and normative issues, and that the inability for a decision-maker to commit to a single prior cannot be limited to measurement problems, as argued by Arthmar and Brady in a recent contribution to this Journal. The paper shows that de Finetti and Savage admitted that having an interval of initial probabilities may sometimes have normative relevance, thereby leaving an opening for indeterminate probabilities
Borrowing from Keynes' <i>A Treatise on Probability</i> : A non‐probabilistic measure of uncertainty for scenario planning
Get PDFScenario planning is a tool used to formulate contingent but potentially impactful futures to aid strategic decision-making. A crucial element of many versions of scenario planning is an assessment of levels of uncertainty about the broad drivers of change within the system under consideration. Despite the importance of this element, the scenario planning literature is largely silent on the appropriate conception of uncertainty to use, exactly what it attaches to and how it might be measured. This paper seeks to fill this gap by advancing a non-probabilistic measure of uncertainty based on the concept of evidential weight drawn from the economist John Maynard Keynes' 1921 A Treatise on Probability
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