Paper: arXiv 2605.10447

Authors: Stefano Blando, Giorgio Fagiolo, Mauro Napoletano, Tania Treibich, Andrea Vandin

Abstract

Agent-based models (ABMs) are increasingly used in macroeconomics, but their analysis still often relies on ad hoc Monte Carlo campaigns with heterogeneous statistical effort across parameter settings. We show how statistical model checking (SMC), implemented through MultiVeStA, can provide a principled analysis layer for a realistic macroeconomic ABM without rewriting the simulator in a dedicated formalism. Our case study is the heuristic-switching Keynes+Schumpeter(K+S) model, analysed hrough a transient sensitivity campaign over one-parameter sweeps, two macro observables (unemployment and GDP growth), and one auxiliary micro-level probe (market share) on the post-warmup phase of a 600-step horizon. The analysis is driven by reusable temporal queries, observable-specific precision targets, and confidence-based stopping rules that automatically determine the simulation effort required by each configuration. Results show a clear contrast across parameter families: macro-financial and structural sweeps produce the strongest transient effects, whereas several heuristic-rule sweeps remain much weaker under the same precision policy. More broadly, the paper shows that SMC can support reproducible and informative quantitative analysis of substantively rich economic ABMs, while making uncertainty estimates and simulation cost explicit parts of the reported results.

Complexity vs Empirical Score

  • Math Complexity: 3.5/10
  • Empirical Rigor: 7.5/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper focuses on the practical application of Statistical Model Checking (SMC) via the MultiVeStA framework to improve the robustness of agent-based macroeconomic simulations. While it lacks deep analytical derivations, it demonstrates high rigor through the implementation of automated, precision-controlled sensitivity analysis and systematic handling of stochastic simulation output.

Research Flowchart

  flowchart TD
    A[<b>Research Goal:</b> Principled analysis of macroeconomic ABMs] --> B[<b>Data/Inputs:</b> Keynes+Schumpeter Model & Temporal Queries]
    B --> C[<b>Methodology:</b> Statistical Model Checking via MultiVeStA]
    C --> D[<b>Processes:</b> Transient Sensitivity Analysis & Confidence-based Stopping Rules]
    D --> E[<b>Variables:</b> Unemployment, GDP Growth, & Market Share]
    E --> F[<b>Outcomes:</b> Explicit uncertainty, reproducible analysis, & identified parameter impact]