Too Big to Monitor? Network Scale and the Breakdown of Decentralized Monitoring
Guy Tchuente

TL;DR
This paper models how network size influences the effectiveness of decentralized versus centralized monitoring, revealing thresholds where larger networks become too complex for local oversight, leading to increased quality deterioration.
Contribution
It introduces a model linking network size and strategic complementarities to monitoring effectiveness, and empirically tests predictions in the U.S. nursing home sector.
Findings
Thresholds at approximately 7 homes per county and 34 per chain where spillovers intensify.
Larger networks exhibit more dispersed deficiencies and higher deterioration risk.
Peer effects significantly influence regulatory failure in networked systems.
Abstract
Many public services are produced in networked systems where quality depends on local effort and on how higher-level authorities monitor providers. We develop a simple model in which monitoring is a public good on a network with strategic complementarities. A regulator chooses between decentralized monitoring (cheaper, local oversight) and centralized monitoring (more costly, but internalizing spillovers). The model delivers an endogenous centralization threshold: for a given spillover strength, there exists a network size above which centralized monitoring strictly dominates; equivalently, for a given network size , there is a critical complementarity beyond which decentralized oversight becomes fragile. A stochastic extension suggests that, above this region, idiosyncratic shocks are amplified, producing stronger peer correlations, higher…
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Taxonomy
TopicsGeriatric Care and Nursing Homes · Public Policy and Administration Research · Healthcare Policy and Management
