Automated and Distributed Statistical Analysis of Economic Agent-Based Models

TL;DR

This paper introduces an automated, model-independent framework for statistical analysis of agent-based models, enhancing reproducibility, efficiency, and robustness in simulation-based economic research.

Contribution

It presents novel algorithms that automate statistical testing, simulation management, and analysis phases for agent-based models, improving accuracy and usability.

Findings

Applied to macro-financial ABM, yielded new insights.

Corrected previous erroneous conclusions in literature.

Automated techniques distinguished transient and steady-state behaviors.

Abstract

We propose a novel approach to the statistical analysis of stochastic simulation models and, especially, agent-based models (ABMs). Our main goal is to provide fully automated, model-independent and tool-supported techniques and algorithms to inspect simulations and perform counterfactual analysis. Our approach: (i) is easy-to-use by the modeller, (ii) improves reproducibility of results, (iii) optimizes running time given the modeller's machine, (iv) automatically chooses the number of required simulations and simulation steps to reach user-specified statistical confidence, and (v) automates a variety of statistical tests. In particular, our techniques are designed to distinguish the transient dynamics of the model from its steady-state behaviour (if any), estimate properties in both 'phases', and provide indications on the (non-)ergodic nature of the simulated processes - which, in turn, allows one to gauge the reliability of a steady-state analysis. Estimates are equipped with statistical guarantees, allowing for robust comparisons across computational experiments. To demonstrate the effectiveness of our approach, we apply it to two models from the literature: a large-scale macro-financial ABM and a small scale prediction market model. Compared to prior analyses of these models, we obtain new insights and we are able to identify and fix some erroneous conclusions.