TY - JOUR
T1 - Social optima of need-based transfers
AU - Kayser, Kirk
AU - Armbruster, Dieter
N1 - Funding Information:
We thank Athena Aktipis and Lee Cronk for introducing us to the Osotua NBT system and for many useful discussions. Support through National Science Foundation, USA grants DMS-1515592 and DMS-1313312 is gratefully acknowledged.
Funding Information:
We thank Athena Aktipis and Lee Cronk for introducing us to the Osotua NBT system and for many useful discussions. Support through National Science Foundation, USA grants DMS-1515592 and DMS-1313312 is gratefully acknowledged.
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/12/15
Y1 - 2019/12/15
N2 - 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.
AB - 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.
KW - Agent-based models
KW - Cutting-stock optimization
KW - Diversification
KW - Need-based transfers
KW - Risk-sharing networks
KW - Wealth redistribution
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U2 - 10.1016/j.physa.2019.04.247
DO - 10.1016/j.physa.2019.04.247
M3 - Article
AN - SCOPUS:85065594483
SN - 0378-4371
VL - 536
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
M1 - 121011
ER -