Forecasting the Severity of Mass Public Shootings in the United States

Publication Title

Journal of Quantitative Criminology

Document Type


Department or Program


Publication Date



Flat-tail distribution, Forecasting, Mass public shootings


Objectives: Mass shootings seemingly lie outside the grasp of explanation and prediction, because they are statistical outliers—in terms of their frequency and severity—within the broader context of crime and violence. Innovative scholarship has developed procedures to estimate the future likelihood of rare catastrophic events such as earthquakes that exceed 7.0 on the Richter scale or terrorist attacks that are similar in magnitude to 9/11. Methods: Because the frequency and severity of mass public shootings follow a distribution resembling these previously studied rare catastrophic event classes, we utilized similar procedures to forecast the future severity of these incidents within the United States. Results: Using a dataset containing 156 mass public shootings that took place in the U.S. between 1976 and 2018, we forecast the future probability of attacks reaching each of a variety of severity levels in terms of the number of gunfire victims killed and wounded across three different choices of tail model, three different scenarios for future incident rates, and other parameters. Using a set of mid-range parameters, we find that the probability of an event as deadly as the 2017 massacre in Las Vegas occurring before 2040 is 35% (90% uncertainty interval [8, 72]) and we characterize how this projection varies substantially with choice of modeling parameters. Conclusions: Our results suggest an uncertain, but concerning, future risk of large-scale mass public shootings, while also illustrating how such forecasts depend on assumptions made about the tail location and other details of the severity distribution model.