|Appears in Collections:||Economics Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Uncertainty: A Diagrammatic Treatment|
|Citation:||Dow S (2016) Uncertainty: A Diagrammatic Treatment, Economics, 10 (2016-3), pp. 1-25.|
|Abstract:||The purpose of this paper is to clarify the difference between the mainstream and Keynesian understandings of uncertainty which persists in spite of superficial similarities. It is argued that the difference stems from the mainstream habit of thinking in terms of a full-information benchmark, where uncertainty arises from incomplete information. Degrees of uncertainty (or ambiguity) refer to the quantifiable extent of incompleteness. In contrast, Keynesian uncertainty cannot, even in principle, be eliminated. By treating uncertain knowledge as the norm, Keynesian uncertainty theory analyses differing degrees of uncertainty in relation to grounds for belief and thus considers the cognitive role of institutions and conventions in influencing the degree of uncertainty. The paper offers a simple diagrammatic representation of these differences, and illustrates its use with different depictions of the crisis, its aftermath and the policy response appropriate to each understanding.|
|Rights:||© Author(s) 2016. Licensed under the Creative Commons License - Attribution 3.0 Proper attribution of authorship and correct citation details should be given|
|20126 Uncertainty diagrammatic treatment in Economics.pdf||220.35 kB||Adobe PDF||View/Open|
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