Statistical Model Checking of the Island Model: An Established Economic Agent-Based Model of Endogenous Growth

TL;DR

This paper demonstrates how statistical model checking, specifically Multi-VeStA, can provide formal, reproducible analysis of the Island Model ABM, confirming key facts and revealing new insights with statistical confidence.

Contribution

It introduces the application of statistical model checking to an established economic ABM, enabling formal analysis and sensitivity testing with confidence intervals.

Findings

Reproduced key stylized facts with formal confidence intervals.

Confirmed the optimality of moderate exploration rates.

Identified a saturation effect in knowledge locality.

Abstract

Agent-based models (ABMs) are increasingly used to study complex economic phenomena such as endogenous growth, but their analysis typically relies on ad-hoc Monte Carlo exercises without formal statistical guarantees. We show how statistical model checking (SMC), and in particular Multi-VeStA, can automate and enrich the analysis of a seminal ABM: the Island Model of Fagiolo and Dosi, which captures the exploration-exploitation trade-off in technological search. We reproduce key stylized facts from the original model with formal confidence intervals, confirm the optimality of moderate exploration rates, and perform a counterfactual sensitivity analysis across returns to scale, skill transfer, and knowledge locality. Using MultiVeStA's built-in Welch's t-test, 6 out of 7 pairwise parameter comparisons yield statistically different growth trajectories, while the exception reveals a saturation effect in knowledge locality. Our results demonstrate that SMC offers a principled, reproducible methodology for the quantitative analysis of agent-based economic models.