Statistical Model Checking of the Island Model: An Established Economic Agent-Based Model of Endogenous Growth
This provides a principled, reproducible methodology for economists and researchers studying complex economic phenomena like endogenous growth, though it is incremental as it applies an existing method to a new domain.
The authors tackled the problem of analyzing agent-based economic models, which typically lack formal statistical guarantees, by applying statistical model checking to the Island Model, reproducing key findings with confidence intervals and showing that 6 out of 7 parameter comparisons yield statistically different growth trajectories.
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.