Statistical Measurement of Bilateral Trade Restrictions: A Monthly Index Based on Rolling-Baseline SPE Decomposition

Export controls and economic sanctions have become increasingly frequent and covert, yet existing measurements either record de jure measures without observing enforcement, or presume known events at annual frequency. This paper transplants the monitoring paradigm of statistical process control (SPC) onto bilateral trade data and constructs the Rolling-Baseline Trade Suppression (RBTS) index, which relies solely on monthly customs records. A rolling baseline with selective updating identifies the in-control regime; idiosyncratic residuals from factor decomposition are calibrated and smoothed, yielding restriction readings in σ units that are comparable across commodity-partner pairs and over time. Two classified case studies and a blind test covering 120 sanction pairs on the full U.S. export matrix show that explicitly restricted pairs respond at the event or announcement month, pairs listed on paper but not actually restricted stay flat, and covert restrictions without formal texts are quantified; in the blind test, readings rise strictly monotonically with the ex-ante verified severity of measures (median shares of above-threshold cells 0.58%, 3.26% and 5.47% across three severity tiers). Simulations delineate the effective working zone of the index, with a minimum detectable effect of about 50% sustained suppression. The index complements list-based measures and provides a new statistical tool for monitoring trade restrictions.