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Optimal information disclosure and o...
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Zhang, Mengxi.
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Optimal information disclosure and optimal learning.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Optimal information disclosure and optimal learning./
Author:
Zhang, Mengxi.
Published:
Ann Arbor : ProQuest Dissertations & Theses, : 2015,
Description:
104 p.
Notes:
Source: Dissertation Abstracts International, Volume: 77-07(E), Section: A.
Contained By:
Dissertation Abstracts International77-07A(E).
Subject:
Economics. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10018223
ISBN:
9781339506630
Optimal information disclosure and optimal learning.
Zhang, Mengxi.
Optimal information disclosure and optimal learning.
- Ann Arbor : ProQuest Dissertations & Theses, 2015 - 104 p.
Source: Dissertation Abstracts International, Volume: 77-07(E), Section: A.
Thesis (Ph.D.)--Boston University, 2015.
This dissertation addresses the effect of information on firm and individual behavior. The first chapter examines the design of an optimal feedback mechanism by an informed principal and uses the results to explain why firms tend to assign coarse subjective ratings to their employees. When a firm has private information about an employee's ability, it can communicate this information through a subjective evaluation mechanism. I characterize the firm's optimal disclosure policy as a function of the worker's ability distribution and provide an algorithm to compute it. Further, I show that with some reasonable restrictions on the ability distribution, the firm's optimal strategy is always to reward the best workers, fire the worst ones, and assign one central rating to the rest.
ISBN: 9781339506630Subjects--Topical Terms:
517137
Economics.
Optimal information disclosure and optimal learning.
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Source: Dissertation Abstracts International, Volume: 77-07(E), Section: A.
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Adviser: Barton L. Lipman.
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Thesis (Ph.D.)--Boston University, 2015.
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This dissertation addresses the effect of information on firm and individual behavior. The first chapter examines the design of an optimal feedback mechanism by an informed principal and uses the results to explain why firms tend to assign coarse subjective ratings to their employees. When a firm has private information about an employee's ability, it can communicate this information through a subjective evaluation mechanism. I characterize the firm's optimal disclosure policy as a function of the worker's ability distribution and provide an algorithm to compute it. Further, I show that with some reasonable restrictions on the ability distribution, the firm's optimal strategy is always to reward the best workers, fire the worst ones, and assign one central rating to the rest.
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The second chapter investigates an informed principal's optimal feedback strategy in a dynamic setting. I first consider the case where both parties have non-binding outside options. In this case, if the principal ever wants to reveal any information, she will do so at the earliest possible stage. Moreover, the optimal disclosure policy can be characterized in the same way as in the static case. The same conclusion holds for the case where both parties have binding and constant outside options. I also discuss the case where both parties have binding and time-variant outside options. After incorporating firms' need to promote and/or to retain workers, the model is used to explain wage dynamics.
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The third chapter models a decision maker who "rationally" distorts his own belief to avoid the feeling of regret. People often suffer from regret when they realize that their previous choices were suboptimal. As a result, in a dynamic setting where information is revealed gradually, people are tempted to deny new negative information in order to avoid regret. At the same time, they are also aware of the economic cost of such belief distortions. A "rational" decision maker will optimally trade off these two concerns and choose his own belief accordingly. This tradeoff makes the past affect current decisions and hence can explain the sunk cost fallacy.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10018223
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