COVID-19 and Gun Violence: Keeping Unknown Shocks and Volatility in Perspective
The current study estimates the varying effects of the pandemic on gun violence by social distancing type, fatality, and location. Interrupted time series analyses are used to examine weekly crime data from 2016 to 2020 in New York City. Box-Cox power transformation and GARCH techniques are used to...
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| Tipo de documento: | Electrónico Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2023
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| En: |
Criminal justice review
Año: 2023, Volumen: 48, Número: 2, Páginas: 145-167 |
| Acceso en línea: |
Presumably Free Access Volltext (lizenzpflichtig) |
| Journals Online & Print: | Gargar...
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| Verificar disponibilidad: | HBZ Gateway |
| Palabras clave: |
| Sumario: | The current study estimates the varying effects of the pandemic on gun violence by social distancing type, fatality, and location. Interrupted time series analyses are used to examine weekly crime data from 2016 to 2020 in New York City. Box-Cox power transformation and GARCH techniques are used to address the problems of non-normality and heteroscedasticity in the models. There were significant increases in fatal and non-fatal shootings during the relaxation of social distancing. The impact of the BLM protests and depolicing is significant for non-fatal shootings. The pandemic led to greater increases in gun violence in The Bronx, Brooklyn, Manhattan, and Queens, as opposed to Staten Island. In addition, there is some evidence of increases in the volatility of gun violence during the pandemic. High volatility implies crime rates are in severe flux, which then leads to greater uncertainty and fear for public safety. This paper surfaces useful information for guiding policy and practice. |
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| ISSN: | 1556-3839 |
| DOI: | 10.1177/07340168221088571 |