On the Explicit Connections Between Keynes’s Chapter 15 of the A Treatise on Probability(1921) and Chapter Four of the General Theory(1936):Keynes’s Method in the General Theory is Inexact Measurement and Approximation using Imprecise Probability from the A Treatise on Probability

M. E. Brady
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Abstract

Keynes, as he had done in all of his major works either directly or indirectly, from the 1913 Indian Currency and Finance through the General Theory in 1936, always used his A Treatise on Probability method and methodology of inexact measurement and approximation when performing a technical analysis. This involves Keynes’s use of interval valued probability to deal with the problem of uncertainty. Uncertainty involves non(sub ) additive probability that introduces the immense complications of non additivity and non linearity into an analysis of decision making. Uncertainty, U, itself is a function only of the Evidential weight of the argument,w,or U=g(w). It occurs if Keynes’s Evidential Weight of the Argument,V(a/h) =w ,where 0≤w≤1,is less than 1.A w<1 automatically creates some degree of uncertainty. In Keynes’s system of logical probability, there is no other way of modelling uncertainty except as an a)interval estimate or a b) decision weight, like his conventional coefficient of risk and weight,c.In the Keynes -Townshend correspondence on 1937-1938 in Vol. 29 of the CWJMK,Keynes emphasizes that Townshend was correct in his conclusion that the entire concept of the liquidity preference theory of the rate of interest rested on his weight of the evidence analysis. Keynes told Townshend ,who was intellectually lost, to reread pages 148 and 240 of the General Theory. Of course, it is on these two pages that Keynes’s makes the connection between uncertainty and weight as an inverse function. Only in chapter 26 of the A treatise on probability, however,is V(a/h), from chapter 6, set equal to w,where 0≤w≤1,in chapter 26. However,after some 84 years,it is now clear to me that this was not enough.Keynes also needed to have told Townshend to read page 160 of the A treatise on probability and pp.39-40 and 43 of chapter 4 of the General Theory, since no economist in the 20th century has been able to connect Keynes’s condition for uncertainty to exist,w<1, with interval valued or imprecise probability.
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论凯恩斯《概率论》第15章(1921)与《通论》第4章(1936)的明确联系:《通论》中凯恩斯的方法是《概率论》中不精确概率的不精确测量和近似
从1913年的《印度货币与金融》到1936年的《通论》,凯恩斯在他所有直接或间接的主要著作中,在进行技术分析时,总是使用他的《概率论》方法和不精确测量和近似的方法。这涉及到凯恩斯使用区间值概率来处理不确定性问题。不确定性涉及非(次)可加性概率,在决策分析中引入了非可加性和非线性的巨大复杂性。不确定性,U,本身只是论证的证据权重w的函数,或者U=g(w)。如果凯恩斯论证的证据权重V(a/h) =w(其中0≤w≤1)小于1,就会出现这种情况。w<1会自动产生一定程度的不确定性。在凯恩斯的逻辑概率系统中,除了a)区间估计或b)决策权重之外,没有其他方法来模拟不确定性,就像他的传统风险和权重系数c一样。在《CWJMK》第29卷1937-1938年的凯恩斯-汤森通信中,凯恩斯强调汤森的结论是正确的,即利率的流动性偏好理论的整个概念取决于他对证据分析的权重。凯恩斯让汤森德重新阅读《通论》的148页和240页,汤森德当时已经神志不清了。当然,正是在这两页上,凯恩斯把不确定性和权重作为反函数联系起来。然而,只有在A论概率的第26章中,第6章的V(A /h)在第26章中被设为等于w,其中0≤w≤1。然而,在大约84年之后,我现在清楚地认识到,这还不够。凯恩斯也需要告诉汤森去读《概率论》(A treatise on probability)第160页和《通论》(General Theory)第4章第39-40页和43页,因为在20世纪,没有一个经济学家能够把凯恩斯的不确定性条件w<1与区间值或不精确概率联系起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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