Multi-level poverty traps

At the top of the Sustainable Development Goals sit two important and unresolved global challenges of our modern era: eradicating extreme poverty and reducing inequality. Although extreme poverty has decreased in the last three decades, the global poverty rate has recently increased from 7.8 to 9.1 percent due to the pandemic and climate shocks. Therefore, identifying the mechanisms at the micro (individual) and meso (community) levels, their relationship with social mobility, and implementing effective intervention strategies are critical research objectives to achieve sustainable development targets. Numerous models have been developed to examine the complex social interactions giving rise to inequality and persistent poverty, yet few approaches include multilevel dynamics. Here, we introduce a heterogeneous agent-based model to identify conditions underlying poverty traps at different levels. Three distinct regimes emerge in our model. The first regime is a single equilibrium poverty trap characterized by low wealth and an ineffective response to poverty alleviation interventions. The second regime is a double equilibrium trap that displays high wealth inequality and responds relatively well to interventions. In the third regime, all agents prosper economically. We identify key individual (behavioral) and community (institutional) mechanisms that are important for achieving sustainable reductions in poverty and inequality. At the individual level, behavioral characteristics like risk aversion, attention, and saving propensity can lead to sub-optimal diversification and low capital accumulation. At the community level, institutional drivers such as lack of financial inclusion, access to technology, and economic segregation are key drivers of inequality and poverty traps. Our results show that addressing the above factors can yield 'double dividend' -reducing poverty and inequality within-and-between communities and create a positive feedback loops that can withstand shocks. Finally, we demonstrate that our theoretical model can be used as a sandbox for cost-benefit analysis of intervention strategies.

在可持续发展的目标之巅，存在着两个我们这个时代的重要且尚未解决的全球性挑战：消除极端贫困和减少不平等。尽管在过去三十年中，极端贫困有所减少，但由于疫情和气候冲击，全球贫困率最近从7.8%上升至9.1%。因此，识别微观（个体）和中间层次（社区）层面的机制，以及它们与社会流动性之间的关系，并实施有效的干预策略，对于实现可持续发展目标至关重要。众多模型已被开发出来以考察导致不平等和持久贫困的复杂社会互动，然而，其中很少有方法包括多层次的动态变化。在此，我们介绍了一个异质智能体模型，以识别不同层次下贫困陷阱的潜在条件。在我们的模型中出现了三种不同的状态。第一种状态是一个单一均衡的贫困陷阱，其特征是财富水平低下且对减贫干预措施的反应无效。第二种状态是一个双重均衡陷阱，表现出高财富不平等并对干预措施有相对较好的反应。在第三种状态中，所有智能体都经济繁荣。我们确定了关键的个体（行为）和社区（制度）机制，这些机制对于实现贫困和不等式的可持续减少至关重要。在个体层面，诸如风险规避、注意力集中和储蓄倾向等行为特征可能导致次优的多元化以及资本积累不足。在社区层面，缺乏金融包容性、技术获取和经济隔离等制度驱动因素是导致不平等和贫困陷阱的关键因素。我们的结果显示，解决上述因素可以实现‘双重红利’——在社区内部和社区之间减少贫困和不平等，并形成能够抵御冲击的正反馈循环。最后，我们证明了我们的理论模型可以作为干预策略成本效益分析的沙盒使用。