Assortative Matching with Inequality in Voluntary Contribution Games

Stefano Duca (), Dirk Helbing and Heinrich H. Nax
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Stefano Duca: ETH Zürich
Dirk Helbing: ETH Zürich
Heinrich H. Nax: ETH Zürich

Computational Economics, 2018, vol. 52, issue 3, No 11, 1029-1043

Abstract: Abstract Voluntary contribution games are a classic social dilemma in which the individually dominant strategies result in a poor performance of the population. However, the negative zero-contribution predictions from these types of social dilemma situations give way to more positive (near-)efficient ones when assortativity, instead of random mixing, governs the matching process in the population. Under assortative matching, agents contribute more than what would otherwise be strategically rational in order to be matched with others doing likewise. An open question has been the robustness of such predictions when heterogeneity in budgets amongst individuals is allowed. Here, we show analytically that the consequences of permitting heterogeneity depend crucially on the exact nature of the underlying public-good provision efficacy, but generally are rather devastating. Using computational methods, we quantify the loss resulting from heterogeneity vis-a-vis the homogeneous case as a function of (i) the public-good provision efficacy and (ii) the population inequality.

Keywords: Assortative matching; Public goods; Heterogeneity; Inequality; Computational economics (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10614-017-9774-5

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