The CVC-SCB Framework: A Unified Micro-Foundation for Consumption, Survival, and Spatial Macroeconomics

This paper presents CVC-SCB — the Consumption Value Chain and Survival-Constrained Biequilibrium framework — a unified theoretical framework that joins three components into a single benchmark: the consumption value chain (CVC) as the network bus that routes each unit of income through the local economy, survival-constrained heterogeneous agents (SC) as the micro engine that turns a household's distance to subsistence into its decisions, and the biequilibrium of goods and labour services (B) as the macro closure that clears the two markets at once. The framework is built on three pillars. First, a consumption kernel K=diag(θ)PK=diag(θ)P routes each unit of income through the local economy and defines the chain multiplier Λ=1T(I−K)−1Λ=1T(I−K)−1, the object through which demand propagates. Second, a survival constraint state Si,tSi,t — disposable funds net of the subsistence floor cmin⁡+κhcmin+κh — replaces the income level as the criterion along which heterogeneous households are ordered, so that a household is fragile or resilient by its distance to the floor, not by its place in the income distribution. Third, a smooth survival penalty (a Stone-Geary displacement of the utility origin) replaces the hard KKT kink, so that consumption contracts smoothly toward the floor as the state vanishes, while the marginal utility of consumption diverges at the floor. From this micro kernel the framework derives, in closed form, the four-quadrant decisions of a household (goods, services, debt, saving), an endogenous fertility demand and an endogenous migration-friction coefficient, and it aggregates these into the joint clearing of the goods and labour-services markets. The framework is designed as the theoretical benchmark for three applications — spatial pluriequilibrium, financial crises and balance-sheet recessions, and endogenous fertility — and it states its limits explicitly: numerical solution and parameter calibration are left to future work, and the paper contains no data.