Social optima of need-based transfers

Kirk Kayser, Dieter Armbruster

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Need-based transfers (NBTs) are actions to compensate losses after disasters. This form of risk pooling consists of connected individuals in a social network transferring wealth from those above a threshold, e.g. welfare threshold, to individuals below threshold in order to preserve the recipient's viable participation in the economy. Such systems are of interest to researchers ranging from evolutionary biologists studying the food sharing of bats to anthropologists studying the gifting of cattle among pastoral societies or mutual help arrangements among ranchers. In this paper, the comprehensive impact of transfer organization and network evolution is studied using agent-based simulations. It is found that in the short-term an optimal transfer rule is similar to a regressive cutting-stock optimization heuristic; however, such a rule has detrimental long-term impact as it leads to a vulnerable wealth distribution. Thus an optimal transfer scheme should both efficiently execute immediate disaster recovery and establish a secure wealth distribution. Also, the most successful network evolution model is one that encourages low variance in the node degrees, leading to equal sharing of the risk and benefit of such an NBT insurance relationship. These results provide a motivated guidance for empirical studies of existing NBT practices and suggestions for optimal implementation of similar resource management in volatile environments.

Original languageEnglish (US)
Article number121011
JournalPhysica A: Statistical Mechanics and its Applications
DOIs
StatePublished - Jan 1 2019

Keywords

  • Agent-based models
  • Cutting-stock optimization
  • Diversification
  • Need-based transfers
  • Risk-sharing networks
  • Wealth redistribution

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

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