Emergent poverty traps at multiple levels impede social mobility.

Area of Science:

• Socioeconomic modeling
• Development economics
• Computational social science

Background:

• Eradicating extreme poverty and inequality are crucial for achieving the Sustainable Development Goals (SDGs).
• Poverty and inequality reduction efforts are vulnerable to global shocks like pandemics and climate change.
• Existing models often lack multilevel dynamics essential for understanding complex social interactions.

Purpose of the Study:

• To introduce a heterogeneous agent-based model to identify conditions causing poverty traps at multiple levels.
• To analyze the interplay between individual behaviors and institutional factors in perpetuating poverty and inequality.
• To explore intervention strategies for mitigating poverty and inequality and enhancing resilience.

Main Methods:

• Development of a heterogeneous agent-based model (ABM).
• Simulation of individual characteristics (risk aversion, saving propensity) and institutional mechanisms (financial inclusion, technology access).
• Analysis of multilevel poverty traps and steady-state outcomes.

Main Results:

• Vulnerabilities to poverty traps arise from the interaction of individual and institutional factors.
• Individual traits like low saving propensity and institutional issues like financial exclusion reinforce poverty.
• Interventions addressing these factors create a "double dividend" by reducing poverty and inequality and building resilience.

Conclusions:

• The developed model identifies key drivers of multilevel poverty traps.
• Addressing both individual and institutional mechanisms is vital for sustainable poverty and inequality reduction.
• The model serves as a sandbox for evaluating the cost-benefit of development interventions.