利益對立與信譽考量：真實狀態不完全揭露下的專家策略

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题名:	利益對立與信譽考量：真實狀態不完全揭露下的專家策略
作者:	龔海翔;XIANG,GONG HAI
贡献者:	經濟學系
关键词:	專家;決策者;利益對立;固定偏好;真實狀態;聲譽;訊息傳遞;均衡;advisor;decision maker;opposite interests;biased preferences;true state of the world;reputation;information;equilibrium
日期:	2013-07-29
上传时间:	2013-08-22 12:08:49 (UTC+8)
出版者:	國立中央大學
摘要:	決策者要針對某件事情做決策, 但是他並不瞭解事情的真實狀況, 所以他想徵求相關專家的建議, 但專家有可能是好專家, 利益與他一致有可能是壞專家, 利益與他對立, 決策者要根據已知訊息做出最符合真實狀況的決策, 而專家也要根據自己瞭解的情況和自身的利益做出合適的建議。本文主要參照 Morris (2001) 的做法, 在他原有模型的基礎上, 把壞專家有固定偏好這一假設修改為壞專家與決策者利益對立, 並比較修改後的結果與 Morris(2001) 原有的結果有何不同。同時, 本文還新增了真實狀態只有一定機率被揭露這一假設, 並探討此機率對壞專家行為的影響。與 Morris (2001) 不同的是, 本文發現: 當壞專家和決策者利益對立時, 首先, 因壞專家沒有固定偏好, 所以好專家沒有動機刻意發送某種與壞專家固定偏好相反的建議去提高自己的聲譽其次, 專家期初的聲譽較低時不會出現任何有傳遞有效訊息的均衡, 決策者會按照真實狀態的初始分配進行決策最後, 真實狀態是否被揭露對壞專家的策略行為影響很大。 A decision maker has to consult domain experts(advisors) to make precise decisions when he can’t totally grasp the desired knowledge about the environment. Unfortunately, not all the experts share the same interests with him, which means some domain experts would act for their own optimal reward rather than for the decision maker’s. This paper mainly follows the method of Morris (2001), based on his model, we replace the assumption that the bad advisor has biased preferences with a new assumption that the bad advisor has opposite interests to the decision maker’s, and then we compare the outcome under the two different assumptions .Moreover, we add an assumption that the true state of the world can be publicly observed with a positive probability, and we discuss how this probability affect the bad advisor’s behavior. Unlike the results of Morris (2001), we find that: First,because the bad advisor is biased in a particular direction, the good advisor has no reputation incentives to send the advice which is opposite to that particular direction Second, there will exist no informative equilibrium when advisors have quite low reputation, and the decision maker will act according to the initial distribution of the true state Finally, whether the true state of the world is publicly observed or not has substantial impact on bad advisors’ behavior.
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