Do (sex) crimes increase during the United States Formula 1 Grand Prix?
Author(s)
Piquero, AR
Piquero, NL
Riddell, JR
Griffith University Author(s)
Year published
2019
Metadata
Show full item recordAbstract
Objectives: We examine whether violent, property, or sex trafficking–related crime increased during the 2018 Formula 1 United States Grand Prix in Austin, Texas. Methods: Ordinary least squares regression models, time series trend analysis, and forecasted prediction intervals based on autoregressive integrated moving average models are used to analyze daily crime incident data gathered by the Austin Police Department. Results: There is no evidence to suggest a statistically significant increase in any of the analyzed crime types during the Formula 1 race weekend. Conclusions: Our findings are directly relevant to the state ...
View more >Objectives: We examine whether violent, property, or sex trafficking–related crime increased during the 2018 Formula 1 United States Grand Prix in Austin, Texas. Methods: Ordinary least squares regression models, time series trend analysis, and forecasted prediction intervals based on autoregressive integrated moving average models are used to analyze daily crime incident data gathered by the Austin Police Department. Results: There is no evidence to suggest a statistically significant increase in any of the analyzed crime types during the Formula 1 race weekend. Conclusions: Our findings are directly relevant to the state of Texas’ human trafficking plan requirement for reimbursement from the state’s major events reimbursement fund. While we do not find the event increases crime, our data are limited to official crime incidents and exclude non-reported and undetected offenses. Future research should focus on potential differences between auto racing and other mega sporting events.
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View more >Objectives: We examine whether violent, property, or sex trafficking–related crime increased during the 2018 Formula 1 United States Grand Prix in Austin, Texas. Methods: Ordinary least squares regression models, time series trend analysis, and forecasted prediction intervals based on autoregressive integrated moving average models are used to analyze daily crime incident data gathered by the Austin Police Department. Results: There is no evidence to suggest a statistically significant increase in any of the analyzed crime types during the Formula 1 race weekend. Conclusions: Our findings are directly relevant to the state of Texas’ human trafficking plan requirement for reimbursement from the state’s major events reimbursement fund. While we do not find the event increases crime, our data are limited to official crime incidents and exclude non-reported and undetected offenses. Future research should focus on potential differences between auto racing and other mega sporting events.
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Journal Title
Journal of Experimental Criminology
Note
This publication has been entered into Griffith Research Online as an Advanced Online Version
Subject
Criminology