Scale and Capacity Limits in Decentralized FDA Food-Safety Enforcement

TL;DR

This study investigates how FDA food-safety enforcement effectiveness declines as the scale and complexity of monitored environments increase, revealing a nonlinear capacity limit and providing a new analytical framework.

Contribution

It identifies a scale threshold where inspection effectiveness deteriorates and introduces a portable breakpoint estimation method applicable to various enforcement contexts.

Findings

Severe inspection findings increase sharply beyond a certain scale.

Inspection effort per establishment flattens or declines after the threshold.

Monitoring becomes 'too big to monitor' in interconnected production environments.

Abstract

This paper asks whether regulatory monitoring exhibits nonlinear capacity limits as the scale and complexity of the regulated environment increase. Using a county--year panel of U.S. Food and Drug Administration (FDA) inspections merged with local establishment counts, we identify a sharp breakpoint: beyond a threshold scale, severe inspection findings rise while inspection effort per establishment flattens or declines. The threshold and the post-break deterioration vary across food-related industry groups and shift with proxies for local density and connectedness, consistent with monitoring becoming ``too big to monitor" in more interconnected production environments rather than driven by simple reallocation or delay. Methodologically, we provide a portable breakpoint selection and piecewise-estimation framework that can be applied to other enforcement settings.