Problem
Research questions and friction points this paper is trying to address.
agent-based models
endogenous growth
statistical model checking
Island Model
quantitative analysis
Statistical Model Checking of the Island Model: An Established Economic Agent-Based Model of Endogenous Growth
🤖 AI Summary
This study addresses the limitations of traditional agent-based economic models, which rely on Monte Carlo simulations lacking formal statistical guarantees and thus struggle to yield rigorous quantitative conclusions. For the first time, the authors systematically integrate Statistical Model Checking (SMC)—a method offering formal statistical assurances—into Fagiolo and Dosi’s island endogenous growth agent-based model. Leveraging the MultiVeStA platform, they automate the analysis of the exploration–exploitation trade-off in technological search. Through Welch’s t-tests for parameter sensitivity analysis, they not only successfully reproduce key stylized facts from the original model and confirm the optimality of moderate exploration rates, but also uncover statistically significant differences in six out of seven parameter comparisons, revealing a saturation effect of knowledge locality. This approach enables reproducible, confidence-interval-equipped quantitative evaluation.
📝 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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Statistical Model Checking
Agent-Based Models
MultiVeStA
Endogenous Growth
Welch's t-test
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