ArXiv TLDR

Sandpile Economics: Theory, Identification, and Evidence

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2604.13890

Diego Vallarino

physics.soc-phcs.LGecon.EMecon.THstat.ML

TLDR

Sandpile Economics explains how evolving production networks' geometric fragility leads to disproportionate economic crises, using Forman-Ricci curvature.

Key contributions

  • Introduces "Sandpile Economics" to model macroeconomic instability from disequilibrium production networks.
  • Uses Forman-Ricci curvature of input-output graphs to measure local substitution possibilities in supply chains.
  • Demonstrates that low curvature leads to power-law distributed cascade sizes, implying unbounded crisis amplification.
  • Empirically, negative curvature predicts lower output growth and explains cross-country differences in economic resilience.

Why it matters

This paper provides a novel, network-based explanation for economic crises, moving beyond traditional models. It introduces Forman-Ricci curvature as a key metric to predict systemic fragility and resilience, demonstrating its empirical power over standard network metrics.

Original Abstract

Why do capitalist economies recurrently generate crises whose severity is disproportionate to the size of the triggering shock? This paper proposes a structural answer grounded in the evolutionary geometry of production networks. As economies evolve through specialization, integration, and competitive selection, their inter-sectoral linkages drift toward configurations of increasing geometric fragility, eventually crossing a threshold beyond which small disturbances generate disproportionately large cascades. We introduce Sandpile Economics, a formal framework that interprets macroeconomic instability as an emergent property of disequilibrium production networks. The key state variable is the Forman--Ricci curvature of the input--output graph, capturing local substitution possibilities when supply chains are disrupted. We show that when curvature falls below an endogenous threshold, the distribution of cascade sizes follows a power law with tail index $α\in (1,2)$, implying a regime of unbounded amplification. The underlying mechanism is evolutionary: specialization reduces input substitutability, pushing the economy toward criticality, while crisis episodes induce endogenous network reconfiguration and path dependence. These dynamics are inherently non-ergodic and cannot be captured by representative-agent frameworks. Empirically, using global input--output data, we document that production networks operate in persistently negative curvature regimes and that curvature robustly predicts medium-run output dynamics. A one-standard-deviation increase in curvature is associated with higher cumulative growth over three-year horizons, and curvature systematically outperforms standard network metrics in explaining cross-country differences in resilience.

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