Subject Area

Economics

Abstract

This thesis analyzes two experiments where experts are facing other-regarding versus self-interested choices on behalf of their clients. The experimental models isolate and examine singular aspects of the complex varied transactions that transpire between experts and their clients every day. Prior literature modeling experts in dictator games or expert advice games shows that given a clear choice with direct culpability that experts are willing to make “fair” other regarding decisions that sacrifice some of their own monetary outcome to increase the outcome for others. However, in these same experiments with the same subject, experts are willing to hide behind many different mechanisms that remove this clear culpability and thus divert the blame for their more self-interested choices. Experts are willing to pay $1 to take all the money and run as though the opportunity to share with others did not exist. When the blame for the decision can be placed on another person, on the computer, on chance (a payment distribution with probabilities) the experts tend to switch to less-fair actions. This all implies that people sometimes make fair choices, but whenever there is a screen of plausible deniability, their mental accounting avoids personal culpability for an increase in unfair outcomes. These two experiments test if experts likewise use 1) communication or 2) ambiguity as a deeper screen than uncertainty in order to find a way to justify unfair choices that they would not make without this opportunity. These economics experiments are performed in a laboratory setting where the element of interest can be isolated, and the other aspects of the transaction are controlled. But the fundamental questions being asked are applicable to many common types of commercial transactions throughout the economy and thus might be informative in thinking about public policy around expert client transactions.

Degree Date

Fall 2021

Document Type

Dissertation

Degree Name

Ph.D.

Department

Economics

Advisor

Timothy Salmon

Second Advisor

Bo Chen

Third Advisor

Omer Ozak

Fourth Advisor

Kyle Hyndman

Number of Pages

122

Format

.pdf

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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