Bayesian detection of supply-chain cost pressure in a shipping- and trade-exposed economy: evidence from Türkiye

Abstract Shipping- and trade-exposed economies need measures that distinguish cost pressure from operational disruption. We construct a six-block Monthly Systemic Cost-pressure and Supply-chain index (MSCS) for Türkiye using 78 monthly observations and estimate Bayesian structural time-series counterfactuals from January 2020–February 2026. March 2026 observed MSCS is 115.608, against a counterfactual mean of 111.264; the deviation is 4.344 points (90% CrI 2.355 to 6.225; Pr > 0 = 1.0000). The March–June cumulative deviation is 17.953 index-point months (90% CrI 7.454 to 28.193; Pr > 0 = 0.9975). Energy and fertilizer–agriculture show the clearest March block signals. Transport-and-storage H-PPI increased in observed levels but remained below its fitted trend mean, and the March Logistics–Transport block credible interval included zero. Neither Mersin throughput nor nominal intermediate-goods imports showed an abnormal downside deviation under the specified trend models. These results indicate cost pressure, not directly established operational disruption. Because the post-event window contains only four monthly observations, the estimates do not establish medium- or long-run persistence. Origin-specific standardisation, rolling forecasts, 26 placebos and specification checks evaluate predictive reliability; the placebo rank is 1/27. The estimates remain conditional on model assumptions and a revised data snapshot rather than a real-time vintage replay. The contribution is a transparent pressure-monitoring architecture connecting shipping, logistics and trade indicators to posterior uncertainty and an illustrative institutional-review protocol.