Should stabilization policy focus on reshaping upstream economic structure or on tightening downstream credit conditions? This paper compares two broad classes of stabilization tools that meet minimum standards of verifiability and institutional identifiability. One class, generator-shift tools, operates by reallocating the distribution of economic upside, thereby narrowing participation gaps. The other class, amplifier-damping tools, works by directly constraining leverage and credit-bridging channels—such as margin requirements, haircuts, risk weights, and capital constraints—without altering underlying structural allocations. To ensure meaningful comparison, the analysis imposes budget neutrality and introduces a common resource metric that standardizes policy intensity across tools. The paper estimates unit-cost effects on output, tail risk, and shock sensitivity, and maps policy bundles onto a unified institutional stability frontier. Identification relies on staggered policy adoption designs combined with a locked estimation and reporting protocol to enhance transparency and reproducibility. Beyond conventional econometric diagnostics, the paper embeds institutional features—such as policy finality, monotonic enforcement regimes, version bundling, and failure windows—into internal falsification tests that strengthen causal credibility. Mechanism analysis further decomposes credit expansion into explicit and shadow channels, pre-commits to structured reporting rules, and tracks substitution dynamics to address concerns that some tools may merely shift risk off balance sheets rather than reduce it. Overall, the paper contributes a reusable and audit-ready framework that transforms policy tool comparison from narrative assessment into a comparable, cost-auditable, frontier-based causal evaluation.
Topo Labs CY (Wed,) studied this question.