Man vs. machine: An investigation of speeding ticket disparities based on gender and race

Sarah Quintanar ()

Journal of Applied Economics, 2017, vol. 20, 1-28

Abstract: This paper analyzes the extent to which police behavior in giving speeding tickets differs from the ticketing pattern of automated cameras, which provide an estimate of the population of speeders. The novel data are obtained from Lafayette, Louisiana court records, and provide specific details about the ticketed driver as well as a wide range of violation characteristics. In contrast to the automated cameras, the probability of a ticketed driver being female is consistently and significantly higher when the ticket was given by a police officer. For African-American drivers this effect is less robust, though in general still positive and significant. This implies that police use gender and race as a determining factor in issuing a speeding ticket. Potential behavioral reasons for this outcome are discussed. The validity of using automated cameras as a population measure for police-issued tickets is thoroughly investigated and supportive evidence is provided.

Keywords: gender bias; racial bias; police; ticketing; automated traffic cameras (search for similar items in EconPapers)
JEL-codes: J71 K42 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Man vs. Machine: An Investigation of Speeding Ticket Disparities Based on Gender and Race (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:cem:jaecon:v:20:y:2017:n:1:p:1-28

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