Behavioral agency theory: new foundations for theorizing about executive compensation

Alexander Pepper and Julie Gore

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: This article describes new micro-foundations for theorizing about executive compensation, drawing on the behavioral economics literature and based on a more realistic set of behavioral assumptions than those that have typically been made by agency theorists. We call these micro-foundations “behavioral agency theory.” In contrast to the standard agency framework, which focuses on monitoring costs and incentive alignment, behavioral agency theory places agent performance at the center of the agency model, arguing that the interests of shareholders and their agents are most likely to be aligned if executives are motivated to perform to the best of their abilities. We develop a line of argument first advanced by Wiseman and Gomez-Mejia and put the case for a more general reassessment of the behavioral assumptions underpinning agency theory. A model of economic man predicated on bounded rationality is proposed, adopting Wiseman and Gomez-Mejia’s assumptions about risk preferences, but incorporating new assumptions about time discounting, inequity aversion, and the trade-off between intrinsic and extrinsic motivation. We argue that behavioral agency theory provides a better framework for theorizing about executive compensation, an enhanced theory of agent behavior, and an improved platform for making recommendations about the design of executive compensation plans.

Keywords: agency theory; behavioral theory; compensation; bonuses and benefits; motivation; top management teams (search for similar items in EconPapers)
JEL-codes: J50 (search for similar items in EconPapers)
Date: 2015-03
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (44)

Published in Journal of Management, March, 2015, 41(4), pp. 1045-1068. ISSN: 0149-2063

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