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Contribution-Based Grouping under Noise

Heinrich H. Nax (), Ryan O. Murphy (), Stefano Duca () and Dirk Helbing ()
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Heinrich H. Nax: Computational Social Science, ETH Zürich, 8092 Zürich, Switzerland
Ryan O. Murphy: Department of Economics, University of Zurich, 8006 Zürich, Switzerland
Stefano Duca: Computational Social Science, ETH Zürich, 8092 Zürich, Switzerland
Dirk Helbing: Computational Social Science, ETH Zürich, 8092 Zürich, Switzerland

Games, 2017, vol. 8, issue 4, 1-23

Abstract: Many real-world mechanisms are “noisy” or “fuzzy”, that is the institutions in place to implement them operate with non-negligible degrees of imprecision and error. This observation raises the more general question of whether mechanisms that work in theory are also robust to more realistic assumptions such as noise. In this paper, in the context of voluntary contribution games, we focus on a mechanism known as “contribution-based competitive grouping”. First, we analyze how the mechanism works under noise and what happens when other assumptions such as population homogeneity are relaxed. Second, we investigate the welfare properties of the mechanism, interpreting noise as a policy instrument, and we use logit dynamic simulations to formulate mechanism design recommendations.

Keywords: voluntary contributions; behavioral economics; noise; heterogeneity; mechanism design; welfare; efficiency; equality (search for similar items in EconPapers)
JEL-codes: C C7 C70 C71 C72 C73 (search for similar items in EconPapers)
Date: 2017
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