Towards Credible Agent-Based Policy Simulations: Disentangling Opportunities and Preferences in a Financial Inclusion Case Study of Egypt

2026-10-03

AI Summary

This study addresses the lack of empirical grounding in agent-based policy simulations and the difficulty of disentangling opportunity from preference effects on behavior. Using financial inclusion in Egypt as a case, it proposes a general modeling framework grounded in the capability approach. By integrating multi-source data with expert knowledge through synthetic population generation and two-stage parameter calibration, the method constructs heterogeneous agent models that innovatively calibrate preference parameters under fixed feasibility constraints. This effectively isolates and quantifies the independent contributions of institutional barriers and individual motivations. Ultimately, this work empirically anchors both model assumptions and outputs, significantly enhancing the credibility and decision-making utility of policy simulations.

Abstract

Credibility is a central topic for agent-based models intended to support policy-making. Simulations must not only represent the target scenarios and their core dynamics but also demonstrate that their assumptions, parameters, and outputs are empirically grounded and sufficiently accurate for their intended use. This paper addresses this challenge by presenting a general modelling framework, aligned with the Capability Approach, for building credible policy simulations that rely on data and domain-expert knowledge. It then demonstrates how it can be contextualised and implemented to study the social challenge of financial inclusion in Egypt, building on an agent-based model that represents heterogeneous individuals and firms behaving according to their financial states, barriers, opportunities, and preferences. The model is fitted to real-world data in two stages, initialisation and calibration, which respectively build representative synthetic populations and estimate behavioural parameters. By fixing the feasibility parameters, which determine agents'opportunities, and calibrating preference parameters across different population groups, we are able to distinguish and analyse the role of institutional and social barriers in the system, as well as the role of agents'motivations and priorities. This calibration stage provides transparent and group-specific hypotheses about the drivers of observed financial-inclusion gaps, which can further be analysed as gaps between agents'opportunities and realised outcomes, a very relevant insight for policy-making. This paper is thus a step towards improving the credibility and usefulness of policy simulations, strengthening the relationship between the model, the real target system, and the stakeholders who will use it. The code is available at: \url{https://www.comses.net/codebase-release/df8383cb-f49b-4f09-8cce-73603b59adcc/}.

Problem

• agent-based models
• policy simulations
• credibility
• financial inclusion
• capability approach

Innovation

• Agent-based model
• Policy simulation
• Capability Approach
• Calibration
• Financial inclusion