🤖 AI Summary
This work proposes the first falsifiable and reproducible synthetic experimental framework for systematically comparing the coordination efficacy of centralized planning and polycentric market mechanisms within a unified simulated economic environment. The framework integrates input-output networks, heterogeneous firms, capacity constraints, and endogenous pricing, leveraging agent-based modeling, adversarial stress testing, and structural shock analysis. Experimental results demonstrate that computational planners consistently achieve lower welfare losses across training, holdout, and adversarial scenarios, thereby validating the framework’s effectiveness. This approach establishes a methodological prototype for empirical calibration and mechanism design research in comparative economic systems.
📝 Abstract
This paper presents a reproducible synthetic benchmark comparing a computational planner, an agent-based market, and a hybrid meta-market within a common simulated economy. The benchmark incorporates input-output production networks, heterogeneous firms, capacity constraints, endogenous prices, welfare metrics, structural shocks, adversarial stress testing, and information-reporting experiments. Across training, holdout, and adversarial scenarios, the planner consistently achieves lower welfare losses than the decentralized alternatives.
The main contribution is methodological rather than ideological. While the benchmark demonstrates a falsifiable framework for comparing economic coordination mechanisms, it does not establish the empirical superiority of planning. Several design choices mechanically favor the planner, including informational asymmetries, incomplete market representation, and simplified institutional assumptions. The results should therefore be interpreted as validation of a synthetic experimental architecture and as a prototype for future research. The paper concludes by outlining a validation agenda based on empirical calibration, structural holdouts, sensitivity analysis, uncertainty quantification, mechanism-design tests, and independent replication.