System Shift Risk, Chokepoint Severity, and Macroeconomic Resilience: Quarter-Level Exploratory Evidence from A Configuration-Based Framework - Raymond Rubianto Tjandrawinata (Al-Makki Publisher, 2026)
This study develops and evaluates the System Shift Economics framework as a configuration-based approach for diagnosing macroeconomic vulnerability and adaptive resilience. The framework proposes that forward-looking macroeconomic outcomes are shaped not only by current status categories, but by the interaction between structural pressure and adaptive capacity. Using 203 quarter-level macroeconomic observations — with forward-looking outcomes available for 199 observations — the study constructs a System Shift Risk Score from seven coded variables: System Condition, Domain Lock, Actor Complexity, Chokepoint Severity, Position Quality, Strategy Quality, and Feedback Maturity. The primary outcomes assessed are four-quarter-ahead GDP loss, crisis status, progression toward adaptive recovery, and overall success. The results provide exploratory support for the framework. Chokepoint Severity significantly predicts both four-quarter-ahead GDP loss and crisis probability. Strategy Quality and Feedback Maturity significantly predict Success and Progression in logistic models. The System Shift Risk Score outperforms the baseline status classification across all outcomes, improving explanatory power for GDP loss and discriminatory performance for crisis, success, and progression. Random Forest feature importance analysis identifies the composite risk score and Feedback Maturity as consistently relevant predictors. Cluster analysis further reveals three theoretically coherent regimes: Adaptive/low-risk, Transitional/medium-risk, and Stagnant/high-risk. The findings suggest that macroeconomic resilience is better understood as a system configuration rather than a static status condition. As the framework is newly operationalised, the evidence should be interpreted as exploratory rather than confirmatory; future validation will require independent samples, robustness checks, and external forecasting benchmarks.