Consumer-Driven Black Market Displacement (CBDT) Framework: A Behavioral-Utility Heuristic for Illicit-to-Legal Market Transition

ABSTRACT CBDT Framework is the first formal consumer-utility heuristic to predict illicit-market collapse under staggered cannabis legalization. Five scaled levers—price gap (g), density (D), safety (S), convenience (F), enforcement (E)—plus a fragmentation modifier (F_frag) feed a logistic adoption curve. Practitioner-seeded priors (25 years of market participation) are heuristically calibrated on 2019–2022 data from Colorado, Michigan, and Oregon; out-of-sample validation on 2023–2025 data from California, New York, and Washington yields Mean Absolute Error (MAE) = 5%. This paper presents the framework’s structure, initial validation results, and transparent documentation of known limitations. Formal panel regression with confidence intervals and expanded state-quarter panel (50+ observations) are planned for Phase 2 (Q1–Q2 2026). ETHICAL STATEMENT This framework analyzes regulatory optimization of legal cannabis markets without taking normative positions on legalization itself. The analysis is offered to improve policy effectiveness in jurisdictions that have chosen legalization, recognizing legitimate concerns about public health, youth access, and impaired driving. CORE EQUATIONS ΔU = 4(−g) + D + 1.2S + F + 0.6E − 0.8 × F_frag Legal Share = 1 / (1 + e^(−ΔU)) RELATED RESOURCES • Harvard Dataverse (archival version): https://doi.org/10.7910/DVN/MDVDTQ • Project website & updates: https://cbdttheory.com