Causal Inference
Evaluating the effects of New Jersey’s extreme risk protection order law on firearm violence among men and women Aayush Chitransh* Aayush Chitransh Chitransh New Jersey Institute of Technology
Statement of purpose:
In 2019, New Jersey implemented an Extreme Risk Protection Order (ERPO) law to reduce firearm-related violence. Evidence suggests that ERPO laws may affect firearm homicide rates differently for men and women. It is also plausible that those effects can be attributed to cities’ violence burden and law implementation practices. In New Jersey in particular, Camden, Elizabeth, Jersey City, Newark, Paterson and Trenton comprise approximately 12% percent of the state’s population yet account for 53% of fatal and non-fatal shootings. This study evaluated the causal effect of ERPO law on firearm homicide between men and women across six counties that housed these cities: Camden, Union, Hudson, Essex, Passaic, and Mercer, respectively.
Method:
We used the Augmented Synthetic Control Method to evaluate the effectiveness of the ERPO law on men and women in the six counties. First, we considered the impact of the law at the county level and then we applied the same framework separately for men and women. Control units included all counties from the eight most geographically proximate states that had not implemented an ERPO law: Kentucky, Maine, New Hampshire, North Carolina, Ohio, Pennsylvania, Tennessee, and West Virginia.
Result and conclusion:
When considering the entire population, the law was observed to reduce firearm homicides in Camden, Essex, Hudson and Union counties, but not in Mercer and Passaic. Among men, similar reduction in firearm homicide rates was observed in the four aforementioned counties. Only in Union did firearm homicide rates decline for women.
Significance:
Results suggest that the ERPO law had a significant impact in four of the six counties, with stronger effects observed among male subgroups. Further analysis could consider city-level comparisons between high- and low-crime areas to better understand local variation in policy outcomes by gender.