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Open AccessArticle

Contribution-Based Grouping under Noise

1
Computational Social Science, ETH Zürich, 8092 Zürich, Switzerland
2
Department of Economics, University of Zurich, 8006 Zürich, Switzerland
3
Morningstar Inc., Behavioral Science Group, Chicago, IL 60602, USA
*
Author to whom correspondence should be addressed.
Games 2017, 8(4), 50; https://doi.org/10.3390/g8040050
Received: 12 October 2017 / Revised: 31 October 2017 / Accepted: 3 November 2017 / Published: 17 November 2017
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. View Full-Text
Keywords: voluntary contributions; behavioral economics; noise; heterogeneity; mechanism design; welfare; efficiency; equality voluntary contributions; behavioral economics; noise; heterogeneity; mechanism design; welfare; efficiency; equality
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MDPI and ACS Style

Nax, H.H.; Murphy, R.O.; Duca, S.; Helbing, D. Contribution-Based Grouping under Noise. Games 2017, 8, 50.

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