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arXiv 1909.08706econ.GNq-fin.EC
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退休金制度的代际政治动力学:基于代理人的模型

Generational political dynamics of retirement pensions systems: An agent based model

Sérgio Bacelar, Luis Antunes

摘要:

为福利国家,特别是公共退休金提供资金的困难越来越大,这是生育率和出生率下降以及预期寿命增加的结果之一。退休金的动态通常在经济学中使用重叠世代模型进行研究。这些模型是基于简化的假设,如使用一个代表性的代理,以减轻问题的易处理性。或者,我们建议使用基于代理的建模(ABM),放松对这些假设的需要,使使用交互和异构代理分配特别重要的代际关系的研究。我们从经济学和政治学的角度来看待养老金动态。我们建立的模型,遵循ODD协议,将试图了解动态的选择公共与私人退休养老金的不同代理人的偏好冲突,但也从他们之间的合作。这些个人偏好的汇总是通过投票完成的。我们结合了一个微观模拟的方法,随着时间的推移,合成人口的演变,与ABM的方法研究不同的代理类型之间的相互作用。我们的目标是描绘公共养老金制度的生存条件,从利己主义和利他主义的个人和集体行为之间的关系出现。

英文摘要:

The increasing difficulties in financing the welfare state and in particular public retirement pensions have been one of the outcomes both of the decrease of fertility and birth rates combined with the increase of life expectancy. The dynamics of retirement pensions are usually studied in Economics using overlapping generation models. These models are based on simplifying assumptions like the use of a representative agent to ease the problem of tractability. Alternatively, we propose to use agent-based modelling (ABM), relaxing the need for those assumptions and enabling the use of interacting and heterogeneous agents assigning special importance to the study of inter-generational relations. We treat pension dynamics both in economics and political perspectives. The model we build, following the ODD protocol, will try to understand the dynamics of choice of public versus private retirement pensions resulting from the conflicting preferences of different agents but also from the cooperation between them. The aggregation of these individual preferences is done by voting. We combine a microsimulation approach following the evolution of synthetic populations along time, with the ABM approach studying the interactions between the different agent types. Our objective is to depict the conditions for the survival of the public pensions system emerging from the relation between egoistic and altruistic individual and collective behaviours.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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