Emergent poverty traps at multiple levels impede social mobility – Nature

Report on Multi-Level Poverty Traps and Their Implications for Sustainable Development Goals

Executive Summary

Achieving the Sustainable Development Goals (SDGs), particularly SDG 1 (No Poverty) and SDG 10 (Reduced Inequalities), is critically dependent on eradicating extreme poverty and inequality. Progress towards these goals is vulnerable to global shocks such as pandemics and climate change, which threaten to reverse gains. This report details the findings from a heterogeneous agent-based model designed to identify the conditions that create and sustain poverty traps at multiple societal levels. The model reveals that vulnerabilities arise from the interaction between individual behaviors and institutional mechanisms. Key findings indicate:

• Individual Drivers: Characteristics such as risk aversion, attention to information, and saving propensity can lead to sub-optimal economic diversification and low capital accumulation, hindering individual progress out of poverty.
• Institutional Reinforcement: Systemic issues, including a lack of financial inclusion (related to SDG 8 and SDG 9), limited access to technology (SDG 9), and economic segregation, amplify individual vulnerabilities, leading to persistent poverty traps and high inequality.
• Intervention Efficacy: The model demonstrates that addressing these interconnected factors yields a “double dividend” by reducing poverty and inequality simultaneously, creating positive feedback loops that enhance resilience to shocks. This theoretical framework can serve as a valuable tool for conducting cost-benefit analyses of intervention strategies aimed at accelerating the 2030 Agenda for Sustainable Development.

1. Introduction: The Challenge to Sustainable Development

The 2030 Agenda for Sustainable Development places the eradication of extreme poverty (SDG 1) and the reduction of inequality (SDG 10) at its core. Despite historical progress, nearly 10% of the global population remains in extreme poverty, lacking access to basic needs essential for human dignity and well-being. Recent global shocks have exacerbated this challenge:

1. The COVID-19 pandemic caused the largest increase in between-country inequality in three decades, potentially reversing years of progress towards SDG 1.
2. Climate change (addressed in SDG 13) disproportionately affects impoverished households, creating significant obstacles to sustainable adaptation and development.

High economic inequality is a primary driver of persistent poverty, concentrating opportunities and resources among a select few and limiting economic mobility for others. This dynamic creates self-reinforcing poverty traps that operate at multiple levels—from individuals and households to entire communities and regions.

1.1. Multi-Level Poverty Traps

Poverty traps are self-reinforcing mechanisms that lock individuals, communities, and regions in a cycle of poverty. Evidence suggests these traps are not confined to a single scale but are “fractal,” meaning they operate at multiple, interacting levels. This multi-level nature has significant policy implications, as interventions at one level can be either reinforced or undermined by dynamics at another, complicating efforts to achieve SDG 1 and SDG 10.

1.2. Persistent Horizontal Inequality

While global inequality between countries has seen some reduction, inequality within countries has surged. This “horizontal inequality”—disparities between distinct identity or geographic groups—is a major impediment to inclusive development. It stems from systemic obstacles related to:

• Access to education (SDG 4)
• Access to resources and technology (SDG 9)
• Financial inclusion (SDG 8)
• Social and economic segregation

Understanding the co-evolution of poverty traps and inequality across these different levels is a critical challenge for designing effective policies to advance the SDGs.

2. Methodology: An Agent-Based Model of Socio-Economic Dynamics

To investigate the linkages between individual behavior, community structure, and institutional access, a two-level agent-based model was developed. The model simulates an economy where heterogeneous agents, connected in a social network, face uninsurable shocks and make decisions about consumption, savings, and investment. This approach allows for the study of emergent poverty and inequality at both individual and community scales, providing a sandbox to test interventions relevant to the SDGs.

2.1. Model Components

1. Agent Social Network: Agents are situated within a social network where connections are based on homophily (similarity in wealth). This structure models how economic segregation can limit opportunities and information flow, directly impacting SDG 10.
2. Community and Investment: Communities are identified within the network, and agents can form self-financing groups to invest in joint projects. This reflects community-level economic activity crucial for SDG 8 (Decent Work and Economic Growth) and SDG 11 (Sustainable Cities and Communities). Projects are either safe (low-return) or risky (high-return), and their viability depends on collective investment.
3. Portfolio Optimization: Agents use Cumulative Prospect Theory (CPT) to make investment decisions, reflecting real-world human decision-making under uncertainty. Heterogeneity in risk aversion, loss aversion, and attention to new information drives different investment strategies.
4. Attention Mechanism: Agents periodically update their investment portfolios based on observed project returns. An “attention” parameter determines how much weight is given to new information, modeling the concept of “information poverty” and its effect on economic outcomes.

3. Results: Emergent Regimes of Poverty and Inequality

The model robustly identifies three distinct steady-state outcomes, or regimes, which represent different pathways in the journey towards achieving SDG 1 and SDG 10.

3.1. Transition from Extreme Poverty to Extreme Inequality

The simulation experiments revealed the following regimes:

• All Poor (12.2% of simulations): The entire population becomes impoverished. This regime represents a complete failure to achieve SDG 1, characterized by high project costs, low saving propensity, and high economic segregation.
• Some Rich (87.7% of simulations): A minority of agents escape poverty and accumulate wealth, while the majority remain trapped. This outcome reflects a common development challenge where progress on SDG 1 is undermined by a failure to address SDG 10, leading to high inequality (Gini coefficients often >0.8).
• All Rich (0.1% of simulations): The entire population prospers. This rare but ideal regime aligns with the successful achievement of both SDG 1 and SDG 10 and is associated with low project costs, low economic segregation, and high saving rates.

These findings mirror the global trend where poverty reduction has often been accompanied by rising inequality, highlighting the interconnectedness of SDG 1 and SDG 10.

3.2. The Emergence of Multi-Level Poverty Traps

Analysis at the community level reveals that poverty traps are indeed multi-scalar. It is possible for some individuals to become wealthy even when all communities are in decline, or for communities to prosper in aggregate while many of their members remain poor. This demonstrates that poverty and inequality can manifest simultaneously:

• At the population level (macro)
• Between different communities (meso)
• Within a single community (micro)

This confirms that achieving the SDGs requires a multi-level policy approach that targets interventions appropriately across different societal scales.

3.3. The Role of Heterogeneity and Information Poverty

Individual differences in behavior significantly impact economic outcomes. The “attention” mechanism shows a direct link to the concept of information poverty. Agents with higher attention (better access to and use of information) can adapt their strategies, but this can also lead to sub-optimal diversification if they overreact to short-term losses. This finding underscores the importance of financial literacy and access to reliable information—key components of SDG 4 (Quality Education)—in building resilience.

3.4. Context-Dependent Interventions

The model was used to test the effectiveness of a one-time capital injection (cash transfer) for the poorest agents. The results were highly context-dependent:

• In the All Poor regime, the intervention failed completely. All targeted agents fell back into poverty, as the injection did not alter the underlying systemic barriers (e.g., high project costs).
• In the Some Rich regime, the intervention was partially successful, with approximately 32% of targeted agents managing to escape poverty.

This demonstrates that asset-based interventions are insufficient in environments with deep systemic constraints. Lasting progress on SDG 1 requires structural changes that create an enabling environment for upward mobility.

4. Discussion: Pathways to Achieving the Sustainable Development Goals

The model’s findings offer critical insights for policies aimed at achieving the 2030 Agenda. The transition from extreme poverty to extreme inequality is not inevitable but is a product of specific individual and institutional dynamics that can be addressed through targeted interventions.

4.1. Inequality as a Driver of Persistent Poverty

The results strongly suggest that high inequality is a primary mechanism that perpetuates poverty traps, making progress on SDG 1 vulnerable to shocks. Horizontal inequality, in particular, is a formidable barrier, as an individual’s economic destiny is largely determined by the community they belong to. Therefore, policies must explicitly target the reduction of inequalities (SDG 10) as a prerequisite for sustainable poverty eradication (SDG 1).

4.2. A Multi-Pronged Strategy for Poverty Alleviation

Based on the analysis, three types of interventions are crucial for fostering social mobility and achieving the SDGs:

1. Capital Inputs: While cash transfers can provide temporary relief, their long-term effectiveness is limited without systemic change. They are most effective in environments where opportunities for upward mobility already exist.
2. Lowering Systemic Barriers: The most effective interventions are those that change the underlying “rules of the game.” Policies should focus on:
   • Improving financial inclusion to lower the costs of entrepreneurship (SDG 8, SDG 9).
   • Promoting social and economic diversity to break down segregation (SDG 10).
   • Enhancing access to technology and education to empower individuals (SDG 4, SDG 9).
   • Strengthening institutions to ensure fairness and justice (SDG 16).
3. Fostering Systemic Transformations: Long-term success requires creating new, sustainable development pathways. This involves fostering innovation, building resilience to shocks (SDG 13), and ensuring that interventions are culturally sensitive and socially just. Addressing sub-optimal diversification by improving skills and creating diverse economic opportunities is key to breaking the cycle of poverty.

5. Conclusion

The fight against poverty and inequality is a complex, multi-level challenge that lies at the heart of the Sustainable Development Goals. This report demonstrates, through a novel agent-based model, that poverty traps emerge from a dynamic interplay of individual behaviors and institutional structures. Progress towards SDG 1 (No Poverty) is fundamentally linked to progress on SDG 10 (Reduced Inequalities), as high levels of inequality create persistent barriers to social mobility and render societies vulnerable to shocks. A one-size-fits-all approach to policy is insufficient. Instead, achieving the 2030 Agenda requires a context-specific, multi-level strategy that combines targeted support for individuals with systemic transformations that create an inclusive and resilient economic landscape for all.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

1. SDG 1: No Poverty

   • The article’s primary focus is on eradicating extreme poverty. It is mentioned in the very first sentence of the abstract and introduction: “Eradicating extreme poverty and inequality are the key leverage points to achieve the seventeen Sustainable Development Goals (SDGs).” The text extensively discusses the mechanisms of “poverty traps,” which are self-reinforcing cycles that keep individuals and communities in poverty.

2. SDG 10: Reduced Inequalities

   • Alongside poverty, reducing inequality is a central theme. The article explicitly states its connection to the SDGs: “…eradicating extreme poverty and reducing inequality within and among countries.” It analyzes “persistent horizontal inequality,” wealth concentration, and economic segregation as key drivers that are intertwined with poverty.

3. SDG 8: Decent Work and Economic Growth

   • The article connects poverty and inequality to factors of economic growth and opportunity. It discusses the importance of financial inclusion, entrepreneurship (undertaking community projects), and capital accumulation. The model explores how access to financial services and productive projects can help individuals escape poverty, which relates to promoting sustained and inclusive economic growth.

4. SDG 13: Climate Action

   • The article identifies climate change as a major shock that makes poverty reduction vulnerable. It states, “climate change is proving to be a major obstacle for impoverished households” and that “the poor are expected to be disproportionately affected by the increasing frequency and intensity of climate-related shocks.” This directly links the challenges of poverty to the need for climate resilience.

2. What specific targets under those SDGs can be identified based on the article’s content?

1. SDG 1: No Poverty

   • Target 1.1: By 2030, eradicate extreme poverty for all people everywhere, currently measured as people living on less than $1.25 a day. The article directly addresses this by focusing on “eradicating extreme poverty” and analyzing the conditions that lead to “poverty traps.” It cites statistics on the global population living in extreme poverty.
   • Target 1.2: By 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions. The article’s model identifies different poverty regimes (“All Poor,” “Some Rich”) and analyzes the factors that allow some agents to escape poverty, which is central to reducing the proportion of people living in poverty.
   • Target 1.5: By 2030, build the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and other economic, social and environmental shocks and disasters. The article explicitly mentions that poverty reduction is “vulnerable to shocks such as pandemics and climate change” and that the poor are disproportionately affected by them.

2. SDG 10: Reduced Inequalities

   • Target 10.1: By 2030, progressively achieve and sustain income growth of the bottom 40 per cent of the population at a rate higher than the national average. The article’s analysis of the “Some Rich” regime, where a minority accumulates wealth while many remain poor, directly relates to the unequal distribution of income growth. The intervention experiments explore how to lift the poorest agents, aligning with this target’s goal.
   • Target 10.2: By 2030, empower and promote the social, economic and political inclusion of all, irrespective of age, sex, disability, race, ethnicity, origin, religion or economic or other status. The article discusses “economic segregation” and “homophily” (the tendency for similar agents to connect), which act as barriers to inclusion. It finds that lower homophily is crucial for prosperity, thereby promoting economic inclusion.

3. SDG 8: Decent Work and Economic Growth

   • Target 8.10: Strengthen the capacity of domestic financial institutions to encourage and expand access to banking, insurance and financial services for all. The article identifies “lack of financial inclusion” as a key institutional mechanism that reinforces poverty traps. It models how reducing the cost of undertaking community projects (parameter θ) can lower barriers to financial well-being and entrepreneurship.

4. SDG 13: Climate Action

   • Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries. The article highlights that “climate change is proving to be a major obstacle for impoverished households and communities to adapt and develop in a sustainable way,” directly linking climate shocks to the vulnerability of the poor and the need for enhanced resilience.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

1. SDG 1: No Poverty

   • Indicator 1.1.1 (Proportion of population below the international poverty line): The article explicitly mentions poverty statistics like “nearly 10% of the world’s population still lives in extreme poverty” and “about 691 million people (8.6% of the world population) living in extreme poverty.” The model’s “All Poor” regime is a simulated representation of this indicator being high.
   • Indicator related to Target 1.5 (Resilience to shocks): While not naming a specific indicator, the article’s model simulates the impact of “economic shocks” on agent wealth. The analysis of how agents in different regimes respond to these shocks implies a measure of resilience. For example, it notes that interventions in the “All Poor” regime fail because they don’t change the underlying vulnerability to shocks.

2. SDG 10: Reduced Inequalities

   • Gini Coefficient: The article explicitly uses the Gini coefficient to measure inequality in its simulation results. Figure 6 is titled “Comparison of final agent wealth distributions and Gini indices,” and the text states that the “Some Rich regime is characterised by high levels of inequality, with Gini coefficients generally taking on values greater than 0.8.” The Gini index is a widely used measure related to Target 10.1.
   • Wealth Concentration: The article implies another measure of inequality by stating, “in representative Some Rich simulations, the top 10% of agents frequently hold well over 80–90% of the total wealth.” This directly measures the concentration of wealth, which is a key aspect of inequality.

3. SDG 8: Decent Work and Economic Growth

   • Access to Financial Services: The article implies the importance of measuring financial inclusion. The parameter θ, representing the “minimum project investment threshold,” is a proxy for barriers to financial access. The finding that a lower θ helps reduce poverty suggests that measuring the real-world equivalent (e.g., access to loans, cost of starting a business) is a crucial indicator. This aligns with the concept behind Indicator 8.10.2 (Proportion of adults with a bank account).

4. Table of SDGs, Targets, and Indicators

Source: nature.com