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HOW SHOULD WE RECONCILE SELF-REGARDING AND PRO-SOCIAL MOTIVATIONS? A RENAISSANCE OF “DAS ADAM SMITH PROBLEM”

Published online by Cambridge University Press:  07 January 2021

Natalie Gold
Natalie Gold*
Affiliation:
Philosophy, University of Oxford, United Kingdom
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Abstract

“Das Adam Smith Problem” is the name given by eighteenth-century German scholars to the question of how to reconcile the role of self-interest in the Wealth of Nations with Smith’s advocacy of sympathy in Theory of Moral Sentiments. As the discipline of economics developed, it focused on the interaction of selfish agents, pursuing their private interests. However, behavioral economists have rediscovered the existence and importance of multiple motivations, and a new Das Adam Smith Problem has arisen, of how to accommodate self-regarding and pro-social motivations in a single system. This question is particularly important because of evidence of motivation crowding, where paying people can backfire, with payments achieving the opposite effects of those intended. Psychologists have proposed a mechanism for the crowding out of “intrinsic motivations” for doing a task, when payment is used to incentivize effort. However, they argue that pro-social motivations are different from these intrinsic motivations, implying that crowding out of pro-social motivations requires a different mechanism. In this essay I present an answer to the new Das Adam Smith problem, proposing a mechanism that can underpin the crowding out of both pro-social and intrinsic motivations, whereby motivations are prompted by frames and motivation crowding is underpinned by the crowding out of frames. I explore some of the implications of this mechanism for research and policy.

Keywords

AltruismDas Adam Smith Problemframinginstitutionsmarketsmoral sentimentsmotivation crowdingpro-socialityself-interestself-regardtrust
Type
Research Article
Information
Social Philosophy and Policy , Volume 37 , Issue 1 , Summer 2020 , pp. 80 - 102
Copyright
© Social Philosophy & Policy Foundation 2020

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