Highway to the Danger Zone: Spatial Considerations of Catalytic Converter Theft
Limited research exists on catalytic converter theft despite it being a persistent issue for years. This study relies on police data for catalytic converter thefts (n = 414) in a medium-sized city for 18 months in 2021–2022. The study also uses vehicle registrations in the county, and Census data. N...
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| Tipo de documento: | Electrónico Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2025
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| En: |
Criminal justice review
Año: 2025, Volumen: 50, Número: 1, Páginas: 53-66 |
| Acceso en línea: |
Volltext (lizenzpflichtig) |
| Journals Online & Print: | Gargar...
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| Verificar disponibilidad: | HBZ Gateway |
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| Sumario: | Limited research exists on catalytic converter theft despite it being a persistent issue for years. This study relies on police data for catalytic converter thefts (n = 414) in a medium-sized city for 18 months in 2021–2022. The study also uses vehicle registrations in the county, and Census data. Negative binomial regression models use Census Block Groups (n = 92) and consider neighborhood and environmental characteristics. The most likely vehicles to have catalytic converters stolen are the Honda Element, Toyota Prius, and Ford E-Series van. More than half of thefts occurred in parking garages and parking lots. Regression models find that the most consistent predictor of catalytic converter theft is adjacency to arterial roadways. Results suggest police departments should target efforts at parking garages and lots near highways, close to downtown, in areas that experience other kinds of crime. The situation changes when considering additional neighborhood characteristics, though highways are still a significant predictor. |
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| ISSN: | 1556-3839 |
| DOI: | 10.1177/07340168231162374 |