A Comparison of Ideologically-Motivated Homicides from the New Extremist Crime Database and Homicides from the Supplementary Homicide Reports Using Multiple Imputation by Chained Equations to Handle Missing Values

Abstract

This study took advantage of the new open-source Extremist Crime Database (ECDB) to overcome obstacles to studying domestic far-right terrorism from a criminological perspective. In the past, exclusive definitions and inclusion criteria have limited available data on violent crimes committed by domestic far-right terrorists, and official data on violent crimes fail to capture offenders’ links to domestic far-right terrorism and ideological motivation (e.g., anti-government, anti-abortion, anti-religion). Therefore, little is known about the nature of far-right terrorist violence and how such violence is similar to and different from routine or more common forms of violence. Focusing on homicides, this study addressed why and how open-source terrorism data and official crime data can be comparatively analyzed. In doing so, we also demonstrate the utility of synthesizing terrorism and official crime data sources. Data on 108 far-right terrorist homicides were taken from the ECDB. Data on 540 common homicides (five comparison homicides for each far-right terrorist homicide) were randomly sampled from the 2000 Supplementary Homicide Reports. Using multiple imputation by chained equations and logistic regression, we imputed missing values and estimated models to compare the two homicide types on 12 different victim, offender, and event characteristics. Relative to common homicides, we found that far-right terrorist homicides were significantly more likely to have white offenders, multiple victims, multiple offenders, and to occur between strangers, and they were significantly less likely to have white victims, to be carried out with a firearm, and to occur in cities with more than 100,000 residents.