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Article

Salience Bias and Overwork

1
Chair for Contract Theory and Information Economics, University of Würzburg, Sanderring 2, D-97070 Würzburg, Germany
2
Faculty of Law, Business and Economics, University of Bayreuth and CESifo, Universitätsstr. 30, D-95440 Bayreuth, Germany
*
Author to whom correspondence should be addressed.
Games 2022, 13(1), 15; https://doi.org/10.3390/g13010015
Submission received: 14 December 2021 / Revised: 19 January 2022 / Accepted: 21 January 2022 / Published: 26 January 2022
(This article belongs to the Special Issue Behavioral Contract Theory)

Abstract

In this study, we enrich a standard principal–agent model with hidden action by introducing salience-biased perception on the agent’s side. The agent’s misguided focus on salient payoffs, which leads the agent’s and the principal’s probability assessments to diverge, has two effects: First, the agent focuses too much on obtaining a bonus, which facilitates incentive provision. Second, the principal may exploit the diverging probability assessments to relax participation. We show that salience bias can reverse the nature of the inefficiency arising from moral hazard; i.e., the principal does not necessarily provide insufficient incentives that result in inefficiently low effort but instead may well provide excessive incentives that result in inefficiently high effort.
Keywords: context-dependent preferences; hidden action; moral hazard; overwork; salience theory context-dependent preferences; hidden action; moral hazard; overwork; salience theory

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MDPI and ACS Style

Römeis, F.; Herweg, F.; Müller, D. Salience Bias and Overwork. Games 2022, 13, 15. https://doi.org/10.3390/g13010015

AMA Style

Römeis F, Herweg F, Müller D. Salience Bias and Overwork. Games. 2022; 13(1):15. https://doi.org/10.3390/g13010015

Chicago/Turabian Style

Römeis, Fabio, Fabian Herweg, and Daniel Müller. 2022. "Salience Bias and Overwork" Games 13, no. 1: 15. https://doi.org/10.3390/g13010015

APA Style

Römeis, F., Herweg, F., & Müller, D. (2022). Salience Bias and Overwork. Games, 13(1), 15. https://doi.org/10.3390/g13010015

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