A dynamic factor model to predict firearm homicides in the U.S.

Predicting the number of homicides with firearms is an important step toward improved and reactive policy in public health. In the United States, accurate datasets on firearm homicides are released only yearly, such that timely reactions to rise in firearm violence are not possible.

In their new paper, PhD student Salvador Ramallo and Professors Máximo Camacho, Manuel Ruiz Marín (all from University of Murcia, Spain) collaborated with Maurizio Porfiri and proposed a dynamic factor model to predict homicides with firearms in the United States, based on official data and easy-to-access variables. Their new model outperforms other state-of-the-art techniques, offering a potent tool for policy-making.

Read the full paper “A dynamic factor model to predict homicides with firearm in the United States” in the new issue of the Journal of Criminal Justice here.

 

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