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通过最近的文献阅读，已经嗅到了行为经济学目前的最重要的亟待解决的问题：

准贝叶斯法则(Quasi-Bayesian Law)的推广和建模工作。行为经济学向主流的回归，这一块是关键。Robin等人现已对一些特殊情况做出了很出色的模型，但是，作为有成为新范式可能的准贝叶斯律，还需进一步一般化。

如果大家认为还有什么是目前行为经济学研究的前沿问题，欢迎回帖发表意见！

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关键词：行为经济学 行为经济 经济学 Bayesian ROBIN 行为经济学

楼主可否谈谈对贝叶斯法则的理解,以及准贝叶斯法则与贝叶斯法则之间的区别和联系.

把我的看法贴出来,请批评指正.

Bayesian法则的与经典统计理论的一个显著不同是在对参数的估计判断中使用了先验概率的信息.通过先验概率提高参数估计的效果.经典统计理论认为在一个分布函数中参数与随机变量具有截然不同的性质,参数的本质是确定性的常量,而贝叶斯学派的学者把参数也作为一种随机变量看待,例如一个消费函数Y(消费)=AX(收入)+B+随机误差,用样本估计出A的值称为消费倾向,而此A代表的是平均的消费倾向,现实世界中不同个体的消费倾向各不相同,那么AX+B不同与Y的部分是随机误差项的扰动还是A本身的随机性质造成的呢?在概率与统计理论的框架之内是不能判定的也无法证明的,这也是贝学派与经典理论的一个重要区别.

在把参数作为随机变量的基础上,贝学派参数估计的理论基础是建立在测度论的基础之上的,通过把后验概率作为已知参数分布函数的随机变量的条件概率,通过一系列转换,转换为参数的条件概率密度与样本的经验分布之间的乘积.

P(X)=P(&|X)f(x)转化为P(X)=P(X|&)*h(&),然后h(&)=P(X)/P(X|&)得出参数的估计.(字符不全,不准确)

经典统计理论的表示方法则是:f(x ; &),就是对参数基本性质的认识不同.

准Bayesian法则俺不懂,请大家讨论.

[em04][em04][em04]

三楼说的是贝叶斯分析最最基本内容，基本无讨论必要。

我说的是讨论准bayesian法则,希望能给出介绍或贴出文章.

Quasi-Bayesian theory

http://www.cs.cmu.edu/afs/cs/user/fgcozman/www/Research/QuasiBayesian/FiniteConvex/node4.html

[此贴子已经被作者于2005-12-23 12:17:36编辑过]

Behavioral Economics: Past, Present, Future

A promising recent modeling approach is “quasi-Bayesian”

—viz., assume that people misspecify a set of hypotheses, or encode

new evidence incorrectly, but otherwise use Bayes’rule. For example,

Rabin and Schrag(1999) model “confirmation bias” by assuming

that people who believe hypothesis A is more likely than B will never

encode pro-A evidence mistakenly, but will sometimes encode

pro-Bevidence as being supportive of A. Rabin (2002) models

the “law of small numbers”in a quasi-Bayesian fashion by assuming

that people mistakenly think a process generates draws from a hypothetical

“urn”without replacement, although draws are actually independent

(i.e., made withreplacement). He shows some surprising implications of

this misjudgment. For example,investors will think there is wide variation

in skill of, say, mutual-fund managers, even if there isno variation at all. (A

manager who does well several years in a row is a surprise if performanceis

mistakenly thought to be mean-reverting due to “nonreplacement”, so quasi-

Bayesians conclude that the manager must be really good.

Barberis, Shleifer and Vishny (1998) adopt such a quasi-Bayesian

approach to explain why the stock market under-reacts to information in the

short-term and overreacts in the long term.In their model, earnings follow a

random walk but investors believe,mistakenly, that earnings have positive

momentum in some regimes and regress toward the mean in others. After

one or two periods of good earnings, the market can’t be confident that

momentum exists andhence expects mean-reversion; but since earnings

are really a random walk, the market is toopessimistic and is underreacting

to good earnings news. After a long string of good earnings,however, the

market believes momentum is building. Since it isn’t, the market is too

optimistic and overreacts.

[此贴子已经被作者于2005-12-23 12:54:54编辑过]

实际上，所谓准，就在于它认为人们对数据、信息的处理，还是遵从经典的贝叶斯法则的，只是对于每个信息的赋值过程受到各种bias的影响而被扭曲了。

具体的内容请参见Robin等人的文献。清风版主上面引的那篇Camerer教授的综述文章也有简要讨论。

决策理论这个不大好做的。许多看似有道理的思路要定量模型化就很难说清楚了。比如Rubinstein,Schmeidler的similarity决策,case-based。

behavioral contract理论也比较热门的。

从Simon开始，经济学家就发现，要搞清楚人们是如何思考的，这实在是太困难了。

我觉得要推广行为经济学，需要更多的普及工作，好比主流经济学需要借助通俗教科书一样。没有通俗教科书，行为经济学很难光大。闲人早先写过几篇，现在很少看到类似贴子了，期待ing。