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叶 航

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现代经济学的裂变与新生  

2008-12-23 00:16:01|  分类: 默认分类 |  标签: |举报 |字号 订阅

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现代经济学的裂变与新生:

神经科学将怎样改变主流经济理论

    2008年9月,《科学》杂志刊登了一篇德尔加多等人用现代神经成像技术对拍卖叫价者神经系统进行研究的文献。根据惯例,凡是较重要的研究成果,《科学》杂志会在同一期刊物中约请一位相关领域的权威科学家对这一研究作一个简约的评论。马斯金,2007年诺贝尔经济学奖的得主之一,也是现代经济学拍卖理论和机制设计理论的创始人之一,无疑就成了这项研究成果最合适的评论人。

    但是,作为一名坚定的主流经济学家,马斯金其实并不是一名合格的评判者。从他的评论(见以下转载)中,我们读到是“礼节性的认可”和“被修饰的怀疑”。事实上,这从该评论的标题“神经数据能改进经济学吗?”中,我们就能大致感受到的作者的立场。

    在我看来,目前最适合但当这一评论人的应该是苏黎世大学国家经济实验室的恩斯特·费尔教授。虽然,今年不到60岁的他还未获得诺贝尔经济学奖,但我预测未来10年内,他将是这一奖项最有实力的竞争者之一。从2004年开始,他就在国际最重要的学术期刊发表了一系列有关神经经济学的论文,并且是国际神经经济学学会的主要创始人。

    我曾经撰文指出,神经经济学将在两大领域对目前的主流经济理论作出重大改进或挑战:

    第一,从本体论的角度,深化经济学关于理性的假设和认识;比如对人类理性行为神经基础的认识,对理性决策、风险偏好、效用的基数性质等一系列经济学基本假设的深化,无疑将大大加强经济学和经济分析的科学性;而所有这些,必须依赖神经科学为人的经济行为和理性决策提供更为坚实的科学描述,才有可能成为现实;而并不是像马斯金“轻描淡写”所说的那样:“神经学上的发现对改进经济学分析具有甚大的潜力——是我们应该认可的思想,而且应当远在神经科学与经济学结成一体之前就被认可了”;

    第二,神经经济学对人类道德感和正义感的研究,将极大地挑战主流经济学目前有关经济人自利偏好的理论假设;事实上,这也是我认为的,神经经济学有可能彻底改变主流经济学的最重要的突破方向;而我上面提到的恩斯特·费尔,正是这一前沿研究领域最杰出的代表,他2004年8月发表在《科学》杂志的论文《利他惩罚的神经基础》,就是这一前沿研究最重要、最经典的文献。在这篇文献中,费尔教授和他的研究团队利用正电子扫描技术(PET)揭示了人类正义感的神经机制,揭示了我们人类为什么会不顾自身危险作出正义的行为;而正是这一研究,将颠覆主流经济学有关“经济人”理性假设的根基;为我们带来一个全新的、能够包容人类道德行为和正义行为的经济学;虽然,真正达到这一目的还将经过十分艰巨的努力;但它的前景是清晰可见的,它是本世纪以来,国际经济学界最前沿、最重要的研究领域;也是我们浙江大学ICSS的奋斗目标。

    毫无疑问,一个只能为“自利”行为提供解释的经济学理论是不完全、不完善的。新的经济理论必将对人性作出更为全面的描述和解释,从而,它也将指导我们人类的经济生活和经济制度不断走向更加完善。

   参考阅读:科学与实证:一个基于神经元经济学的综述(一)

   参考阅读:科学与实证:一个基于神经元经济学的综述(二)

 

神经数据能改进经济学吗?

马斯金

(《科学》2008年9月刊)

    现代神经影像技术——如功能性核磁共振造影(fMRI)、正电子发射断层扫描等——能让我们得以窥视实验对象在做诸如拍卖如何喊价竞标之类的经济决策时脑内的活动。伏隔核多巴胺释放的数据、或纹状体血氧浓度的数据——见《科学》期刊现期1849页德尔加多等人的文章(1)——本身就的确令人神往。问题是这些数据是否也能改进我们对经济行为的理解? 

    对这个问题的回答,众口不一。神经经济学家卡墨勒等人最近曾预言“总有一天,我们会有办法用神经学上的精细描述代替在经济学上沿用已久的简单数理概念。”2与其相反,经济理论家古尔以及培森多佛则主张神经学数据与经济学无甚瓜葛,因为“经济学对人脑的生理既不作假设也不下结论。”3囿于时下经济学惯常的研究方法,古尔-培森多佛的断言是对的。因为在一个标准的经济模型里,决策者总是面临数种选择,而求解这个模型的目的就是要预言该研究对象会采取哪种选择。这种模型对研究对象的大脑状态既不作任何假设,也不作任何断言;只要预言能搞得准确,也没有必要作什么假设、或作什么断言。不过,以该标准选择模型为根据所作的预测有时远远不能令人满意;因此,从原则上讲, 在这个方面,我们或许还能有所作为;办法就是让模型的预测行为不仅依赖于不同的经济选择,而且也依赖于神经生理学方面的数据。

    可是神经经济学界迄今还没建构成这样的一种扩展型(译者注:即增加神经学新变量为解释性变量)的模型。此外,即便这种模型建构得成,要想在实验室之外的环境里进行人脑扫描,还要解决两个棘手的难题,那就是强人所难的唐突如何规避,个人隐私如何保护。不过,这个领域进展很快,我们很有理由对最终的水到渠成抱乐观的态度,尽管神经学数据与例行日见的经济学之整合也许还是很多年后的事情。

    问题是在这个美妙的日子到来之前,人脑扫描的数据能不能派上什么用场?德尔加多等人所倡导的一种可能的应用就是以该数据区判各种标准的、不带神经生理学变量(例如血氧水平变化)的经济模型。经济现象中令人不解者,大部分都允许相当多个、可以想象到的、各自不同但又互作候补的解释。神经学的数据在这个方面可资利用,通过对后续试验作出建议、或通过提出新的假说,来提高对这些解释好中选优的挑拣效率。以上的作者们就是取此途径试图阐释实验对象在高喊价者赢的拍卖(译者注:此即所谓“第一价格暗标拍卖”,喊最高价者赢,并付此最高价换取标的物。)实验中的行为。神经学数据可派用场,这一点他们或许弄对了;但是把这条道理应用到拍卖之上,他们还不像是已经获得完全成功。

    在一个高喊价者赢的拍卖里,标的物的潜在买者们各自投入暗标(亦即各自喊价,但互相保密)。开标后,喊最高价者赢,并付此最高价给卖者换取标的物。高喊价者赢的拍卖要求买者在竞标时采用策略性的行为。如果对于一个标的物买者评价为v,她的喊价必得严格地小于v,因为如果喊价等于她的实际评价,就是赢了也没有赚头:所获标的物评价为v, 但她的付出也是v。那么,她的喊价要削掉多少——亦即喊价要比她对标的物评价少掉几分——则取决于她对于其他竞标者行为之期望。博弈论预言了每一个买者在竞标时应如此行事,亦即,在假定其他所有买者均比照自己一样行事的条件下,须得将自己的期望所得极大化。这种结果,即所谓的均衡。 

    在德尔加多等人的一个实验里,有两个买者,他们对标的物评价的赋值可看作是独立且随机地从一个数值由0到100的均匀概率分布中取出。如果两个买者都是风险-中性——这就是说,买者的期望所得等于她的赢标净利(标的物评价减去喊价)乘以赢标概率——那么,在均衡的时候,买者们喊价都应只等于评价的一半。可是,德尔加多等人却发现——许多别的类似的实验也有同样的发现——实验对象往往喊价高于如上结果:也就是说,他们“喊价过高。”  

    德尔加多等人讨论了有关喊价过高的两个标准解释。其一是,实验对象不应是风险-中性,而应是风险-嫌恶的——这也就是说,在一个以货币计输赢的赌局里,实验对象对赌局期望值(译者注:期望值是一个确定的数值)之偏爱严格地胜过对赌局本身(译者注:赌局本身可大赢也可大输,是一个或然值)之偏爱。其二是,战胜对方可给赢方带来一种额外的心理满足感。不过,以上作者们未曾提及的是,他们所讨论的这两个假说现在已都被认为是不无问题,不甚可靠的了:最近的一些实验证据似乎都与两者存有冲突(4)。令人欣慰的是,德尔加多等人也提出他们自己的、建立在他们所做的fMRI研究基础之上的解释 。

    不幸的是,他们的这个新假说究竟是什么还不是完全清楚。fMRI的数据显示,实验对象拍卖失标的反应,表现为纹状体血氧水平降低,但在赢标时血氧水平并未因此而有显著改变。作者们解释了这个结果,认为这暗示了实验对象体验着一种“失标恐惧感”,而且正是这种恐惧感成了喊价过高的原因。不过,要对恐惧感做到形式显明的建模——使之精准正确——却不是一件轻而易举的事情。   

    倒有一个浑然天成的建模窍门,那就是只要在实验对象拍卖失标的时候 从她的所得里减去某个数量。作者们做了如此的实验改动,但结果却与作者们在后续实验里之所见不相一致。在这些后续实验里,采用了两种不同的处理手段:其一,事先给了实验对象一笔奖金S不过她也被告知,万一失标,这笔钱要交还;其二,承诺实验对象,如她赢标,她会拿到奖金S.   这两种手段,从事后看,是等效的:无论是哪一种,当且仅当她赢标时,才能拿到奖金。可是, 实际上,实验对象却在前者情形里比在后者情形里喊价更高。这种行为与“支付裁减”假说(之预言)大相径庭,因为如果该假说为真,竞标者在以上两种情形里的行为应当一致。此外,要想找到一种既浑然天成又可作替代的“失标恐惧感”的建模构想使之能同时解释德尔加多等人所做的两个实验的结果,看起来相当困难。即便如此,还有一个著名的原理,可以解释后续实验中两种处理所带来的行为差异:这个原理即“禀赋效果”5。当实验对象一开头就被给了一笔奖金S,她有可能心生占有欲;从而,较之先得行事之后才有可能在实验终了时获取一笔或然性奖金的情形,她就有可能更积极地行事以求保住奖金。

    至于说研究对象为何喊价过高,其答案也许是高喊价者赢的拍卖太复杂了,令典型的竞标者无法做到全然系统的分析。竞标者轻易即可看出她得削减喊价(使之严格小于评价v)才能有赚头。不过,她仍不想将喊价削减过多,因为削减喊价也减少了她赢标的概率。一个简单的经验法则就是只将喊价稍稍削减。不过其直接的结果就是喊价过高,因为风险-中性的竞标者在均衡时的喊价要求作相当程度的削减:竞标者的喊价只能是其评价的一半。

    简言之,德尔加多等人对竞标者在拍卖失标时纹状体血氧水平下降的揭示,确实是一个引人兴趣的神经生理学上的发现,虽然这个发现是不是已经导致了对竞标者行为建构较佳的经济模型还不是很清楚。尽管如此,德尔加多等人的哲学思想——亦即,神经学上的发现对改进经济学分析具有甚大的潜力——是我们应该认可的思想,而且应当远在神经科学与经济学结成一体之前就被认可了。

附:原文 

Can Neural Data Improve Economics?

Eric Maskin 

    Modern neuroimaging techniques---functional magnetic resonance imaging (fMRI), positron emission tomography scans, and so on---allow us to peer inside the brain and see what is going on when experimental subjects make economic decisions such as how to bid in auctions. The data on, say, dopamine release in the nucleus accumbens, or---as Delgado et al. (1) report on page 1849 of this issue---blood oxygen in the striatum, are certainly fascinating in their own right. But can they improve our understanding of economic behavior? 

    Opinions diverge on this question. Neuroeconomists Camerer et al. recently predicted that “We will eventually be able to replace the simple mathematical ideas that have been used in economics with more neurally-detailed descriptions” (2). By contrast, economic theorists Gul and Pesendorfer maintain that neuroscience evidence is irrelevant to economics because “the latter makes no assumptions and draws no conclusions about the physiology of the brain” (3). Limited to current practice in economics, the Gul-Pesendorfer assertion is correct. In a standard economic model, a decision-maker is confronted with several options, and the purpose of the exercise is to predict which one the subject will select. The model assumes and asserts nothing about the subject’s brain states, nor is there any call for it to do so as long as the prediction is accurate. But predictions based on standard choice models are sometimes far from satisfactory, and so in principle, we might improve matters by allowing predicted behavior in the model to depend not only on the economic options but also on neurophysiological information. 

    So far, the field of neuroeconomics has not developed such an expanded model. Moreover, even when it does so, there are knotty problems of obtrusiveness and privacy to be resolved before one could perform brain scans outside the laboratory. The field has been moving quickly enough so that there is cause for optimism that all this will ultimately transpire, but integrating neural information into everyday economics is probably a good many years off.  

    What can be done with brain scans before that happy time? One possibility advocated by Delgado et al. is to use them for discriminating among standard economic models, in which neurophysiological variables (such as changes in blood oxygen levels) do not appear. Most puzzling economic phenomena admit quite a few conceivable alternative explanations, and neural data can streamline the process of finding the best one---suggesting follow-up experiments or new hypotheses. The authors use this approach to try to illuminate subjects’ behavior in high-bid auction experiments. While they are probably right about how neural data can be useful, their application of this principle to auctions does not seem entirely successful. 

    In a high-bid auction, each potential buyer for the item being sold makes a sealed bid (i.e., quotes an amount of money without disclosing that amount to the other buyers). The buyer making the highest bid wins the item and pays the seller that bid. High-bid auctions call for strategic behavior by buyers. If the item is worth v to a buyer, she will bid strictly less than v, because bidding her actual valuation would gain her nothing: She would get something worth v but also pay v. How much she “shades” her bid---that is, bidding below what the item is worth to her---will depend on what she expects others will do. Game theory predicts that each buyer will bid so as to maximize her expected payoff, given that all other buyers do the same. The result is what is called an equilibrium. 

    In one of the Delgado et al. experiments, there are two buyers, whose assigned valuations for the item being sold are drawn independently from a uniform distribution on the numbers between 0 and 100. If the buyers are risk-neutral---that is, if a buyer’s expected payoff is her net gain from winning (valuation minus bid) times the probability of winning---then in equilibrium, the buyer will bid half her valuation. However, Delgado et al. found---as have many other similar experiments---that subjects generally bid more than this: They “overbid.” 

    Delgado et al. discuss two standard explanations for overbidding. One is that subjects are risk-averse rather than risk-neutral---they strictly prefer the expectation of a monetary gamble to the gamble itself. The other is that they get an extra psychic benefit from beating out another buyer. What the authors do not mention, however, is that both hypotheses are now considered somewhat dubious: Recent experimental evidence seems in conflict with each of them (4). Thus, it is welcome that Delgado et al. propose their own explanation, based on fMRI studies they performed. 

    Unfortunately, it is not completely clear what this new hypothesis is. The fMRI data show that subjects experience a lower blood oxygen level in the striatum in response to losing an auction, but no significant change in reaction to wining one. The authors interpret this result as suggesting that subjects experience “fear of losing” and that this fear accounts for their overbidding. But actually modeling fear explicitly---making it precise---does not seem straightforward. 

    A natural modeling device would be simply to subtract something from the subject’s payoff when she loses. However, such a modification would not accord with the authors’ findings in their subsequent experiment. In the follow-up, there were two treatments: one in which a subject is initially given a bonus sum of money S but told that she has to return it if she loses the auction; the other in which the subject is promised that if she wins she will get S. The two treatments are, ex post, identical: In both cases, the subject ends up with the bonus if and only if she wins. However, in practice, subjects bid more in the former treatment than the latter. Such behavior sharply contradicts the “payment subtraction” hypothesis, under which behavior in the two treatments would be the same. Moreover, it seems difficult to find a natural alternative formulation of the “fear of losing” idea that explains the results simultaneously from both Delgado et al. experiments. Even so, there is a well-known principle that could account for the behavioral discrepancy between the two treatments in the follow-up experiment: the “endowment” effect (5). When a subject is given a bonus S at the outset, she may become possessive and so move more aggressively to retain it than she would act to obtain a contingent bonus at the end of the experiment.                                                                                                    

    As for why subjects overbid, perhaps the answer is that high-bid auctions are just too complex for a typical buyer to analyze completely systematically. The buyer will easily see that she has to shade her bid (bid strictly below v) to get a positive payoff. Still, she won’t want to shade too much because shading reduces her probability of winning. A simple rule of thumb would be to shade just a little. But this leads immediately to overbidding, because risk-neutral equilibrium bidding entails a great deal of shading: A buyer will bid only one-half her valuation.  

    In short, Delgado et al.’s discovery of a dip in striatal blood oxygen levels when buyers lose in an auction is an intriguing neurophysiological finding, although it is not so clear that it has yet led to a better economic model of buyers’ behavior. Still, the philosophy of Delgado et al.---that neural findings show great potential for improving economic analysis---is one that should be endorsed, well before the time when neuroscience and economics become one.  

 

参考文献: 

  1.M. R. Delgado, A. Schotter, E. A. Ozbay, E. A. Phelps, Science 321, 1849 (2008).

  2.C. Camerer,  G. Loewenstein,  D. Prelec, J. Econ. Lit.43, 9 (2005).

  3.F. Gul, W. Pesendorfer, “The case for mindless Economics,”

    www.princeton.edu/-pesendor/mindless.pdf (2005).

  4.J. Kagel, D. Levin, “Auctions: A survey of experimental research, 1995-2008,”

    www.econ.ohio-state.edu/kagel/Auctions_Handbook_vol2.pdf (2008).

  5.R. Thaler, J. Econ. Behav. Org. 1. 39 (1980).

  6.I thank NSF for research support.

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