Jefficiency vs. Efficiency in Social Network Models
AbstractThe mainly used welfare criterion in the social network literature is Bentham´s utilitarian concept. The shortcomings of this concept are well-known. We compare the outcomes of the utilitarian concept with the Nash social welfare function. By using a Taylor approximation we deduce a formula which allows the direct comparison of both concepts. The implications of welfare considerations of important network formation models are evaluated by using the multiplicative concept. We introduce a new symmetric connection model which is related to Nash´s welfare function in the same way as the original model is related to the utilitarian function. Based on the observation that heavy tail distributions like the power law distribution and the Pareto distribution can be explained by multiplicative structures we propose to use multiplicative utility functions in social network models. Furthermore, multiplicative utility and welfare functions together exhibit favorable characteristics both in normative and positive terms. Many empirically observed social networks have structures which are better modelled by multiplicative functions. From the normative perspective, multiplicative functions might be attractive since the Nash product introduces some form of justice.
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Bibliographic InfoPaper provided by Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute of Economics (VWL) in its series Darmstadt Discussion Papers in Economics with number 36779.
Date of creation: Mar 2006
Date of revision:
Publication status: Published in Darmstadt Discussion Papers in Economics . 161 (2006-03)
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social networks; welfare; efficiency; Nash product; jefficiency; justice;
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- repec:dar:vpaper:36781 is not listed on IDEAS
- Möbert, Jochen, 2006. "Classification of Network Formation Models," Darmstadt Discussion Papers in Economics 36781, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute of Economics (VWL).
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