Limits of Indicators and Models Near Regime Instability

Limits of Indicators and Models Near Regime Instability is a revised theoretical preprint and structural clarification paper. It examines the limits of indicators, metrics, models, and quantitative frameworks when the regime conditions under which they were defined and calibrated begin to shift. The paper argues that indicators and models are regime-bound instruments. Their effectiveness depends on the stability of the assumptions, baselines, variables, filtering procedures, calibration domains, and admissibility conditions that give their outputs interpretative meaning. Near regime instability, these instruments may continue to operate formally while their semantic reliability progressively degrades. The problem is therefore not necessarily insufficient data, poor modeling, or lack of analytical sophistication, but a mismatch between inherited measurement frameworks and changing conditions of systemic stability. The analysis distinguishes indicators as filters rather than direct sensors, examines metric proliferation and signal saturation, and clarifies why model refinement or retro-validation may fail to restore diagnostic clarity when the domain of validity itself is changing. It further separates local model consistency from global interpretative reliability, and description from operational control. The contribution is classificatory and non-prescriptive. The paper introduces no new indicators, meta-metrics, predictive thresholds, early-warning systems, intervention protocols, decision rules, or model-based control strategies. Its purpose is to preserve interpretative discipline by specifying the conditions under which indicators and models remain meaningful, and by clarifying why increased measurement or model complexity does not necessarily produce greater diagnostic clarity near regime transition.