کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
883942 912361 2010 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
On Keynes's conception of the weight of evidence
موضوعات مرتبط
علوم انسانی و اجتماعی اقتصاد، اقتصادسنجی و امور مالی اقتصاد و اقتصادسنجی
پیش نمایش صفحه اول مقاله
On Keynes's conception of the weight of evidence
چکیده انگلیسی

Various 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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Economic Behavior & Organization - Volume 76, Issue 2, November 2010, Pages 338–351
نویسندگان
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