Joint Liability Model with Adaptation to Climate Change

2024-04-22

AI Summary

Smallholder credit markets lack systematic integration of climate risk and sustainability assessment. Method: This paper pioneers the localization of ESG principles to individual smallholders, developing an Environment–Society–Economy (ESE) three-dimensional sustainable credit scoring framework embedded within a joint-liability lending model. We incorporate climate uncertainty via a mean-variance utility function and employ climate-scenario-driven Monte Carlo simulations to theoretically derive and empirically identify a negative relationship between ESE scores and optimal group size in joint-liability lending. Contribution/Results: First, we propose the inaugural ESE scoring paradigm tailored specifically for smallholders. Second, we establish an ESE-driven, climate-resilient credit mechanism. Third, agent-based simulations demonstrate that the framework significantly enhances financial inclusion while improving the trade-off between default rates and loan accessibility under climate shocks—including droughts and floods.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Mechanism Design
• Reasoning under Uncertainty: Other Foundations of Reasoning under Uncertainty

Application Category

• Economics, Online Markets and Human Computation: Sustainability of Web economics
• Responsible Web: Sustainability and climate impact of web technologies
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

This paper extends the application of ESG score assessment methodologies from large corporations to individual farmers' production, within the context of climate change. Our proposal involves the integration of crucial agricultural sustainability variables into conventional personal credit evaluation frameworks, culminating in the formulation of a holistic sustainable credit rating referred to as the Environmental, Social, Economics (ESE) score. This ESE score is integrated into theoretical joint liability models, to gain valuable insights into optimal group sizes and individual-ESE score relationships. Additionally, we adopt a mean-variance utility function for farmers to effectively capture the risk associated with anticipated profits. Through a set of simulation exercises, the paper investigates the implications of incorporating ESE scores into credit evaluation systems, offering a nuanced comprehension of the repercussions under various climatic conditions.

Problem

• Extending ESG scores to individual farmers' production
• Integrating agricultural sustainability into credit evaluation
• Investigating ESE score impacts under climate change

Innovation

• Integrating agricultural sustainability into credit evaluation
• Developing holistic ESE score for individual farmers
• Using joint liability models with climate adaptation