This study establishes a novel computational design of experiments (DoE) framework to model the spatial transmission, dynamic persistence, and structural baseline shifts of global climate, energy, and geopolitical shocks across 47 subnational food Consumer Price Index (CPI) subclasses in Panama (2017–2025). This framework deploys an interactive panel factorial model with fixed effects to capture non-linearities alongside a major domestic structural breakpoint in June 2023. The empirical contributions are threefold. First, the study demonstrates that inflation is spatially heterogeneous, proving that price transmission in Panama operates via an interior-to-capital vector where international energy price shocks (WTI) initially impact provincial nodes (Resto Urbano) subsequently propagates via an interior –to – capital transmission vector, experiencing an ultra-short half-life of 0.3 months (approximately 9 days) before spilling over into the metropolitan core. Second, it reveals that climate shocks induce permanent structural baseline shifts known as “step effects” in the Consumer Price Index (CPI). Specifically, El Niño anomalies trigger a permanent +0.010 step-shift in the price floor of prepared food services; meanwhile, La Niña anomalies systematically disrupt maritime logistics, driving uniform baseline step-shifts in fish (+0.013 Metropolitan, +0.012 Resto Urbano). Third, it identifies structural hysteresis following the June 2023 breakpoint, revealing a permanent 7.04% increase in the urban cereal price floor (θ = 0.0704).  To operationalize these parameters, a subnational Early Warning System (EWS) is proposed and validated against dynamic error correction mechanisms (ECM). This tool advances food security governance by enabling policymakers to execute targeted logistics-buffer operations against climate step-shifts, deploy localized energy-shock social protection programmes at provincial gateway nodes within the identified 9-day transmission window, and recalibrate minimum nutritional social protection floors to account for structural cereal hysteresis.

Keywords

Computational design of experiments, Consumer Price Index, Oceanic Niño Index, La Niña and Geopolitical Uncertainty