Abstract (Translated):
Translating theoretical frameworks of National Economic Security (NES) into actionable policy requires robust, empirical, and multi-dimensional measurement systems. Traditional economic metrics - designed primarily to track output velocity, financial efficiency, and short-run equilibrium - fail to capture systemic vulnerabilities, non-linear shock propagation, and strategic dependencies within complex global networks. This paper operationalizes the Comprehensive and Dynamic National Economic Security (CDNES) conceptual model by constructing a multi-tiered, quantitative indicator framework. Mapping the national economy as a Complex & Dynamic Adaptive System (CDAS), we construct an analytical taxonomy across three structural levels (macro, meso, micro) and five functional vectors: Financial, Industrial/Supply Chain, Technological, Energy/Resource, and Human Capital. To overcome the limitations of standard linear composite indices-where high performance in one domain mathematically masks critical failures in another-we formulate a non-compensatory geometric and min-operator mathematical aggregation architecture. Furthermore, we integrate Dynamic Inoperability Input-Output (DIIM) parameters to capture threshold effects and time-to-recovery dynamics. The resulting framework bridges abstract systemic security theory with executive decision-support toolkits, providing a rigorous empirical foundation for real-time risk monitoring, strategic stress-testing, and anti-fragile policy design.
