Financial crises exhibit strikingly repetitive morphology: leverage drift in expansions, state-dependent tightening amplification, and thick left tails in contractions. These patterns are commonly attributed to “credit cycles” and balance-sheet frictions. This paper proposes a more upstream primitive: crises become credit-clearing crises when capitalization gains fail to enter the broad sector as deployable, unencumbered buffers. To make this primitive auditable and falsifiable, we introduce Two-Layer Transactions (TLT) and Long-Term Layer Settlement (LTL). A transaction is complete if and only if price-layer settlement and long-term-layer settlement both occur. The long-term layer is settlement-grade only when it satisfies five auditable conditions: (i) existence of an enforceable settlement object, (ii) third-party replayability, (iii) verifiable finality, (iv) auditable hard-budget accounting, and (v) version binding with visible activation discipline. These object-layer gates define the admissible domain of non-levered absorption capacity (A) and the slow state (g) that summarizes deficiencies in grant coverage, deployability, and unencumberedness. On this foundation, the paper defines the Residual-Claim Absorption Structure (RCAS) and derives a theorem chain linking higher (g) to lower (A(g)), greater reliance on credit bridging, and larger output losses under tightening. The amplification result holds globally, including at kinks, via diminishing differences. With debt stickiness and tightening-compressed bridging limits, the model generates leverage drift, threshold crises, and tail deterioration as (g) rises. For falsification, we propose an attenuation–non-replication mechanism signature: in shock-based specifications, adding the strictly lagged channel interaction (st × bt−1) attenuates the tightening-by-gap interaction (st × gt−1), and this attenuation does not replicate under negative controls, permutations, or placebo leads. The main text provides a zero-data verification harness as a template; the Online Appendix outlines a light-data empirical blueprint using widely available public series.
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