1. Dubuque PD Traffic Stop Analysis
June 2017

2. Goal of the Study Look for Disproportionality in:
(1) The decision to make a stop, and
(2) The outcome of the stop

3. Definitions Disproportionality Stop Disproportionality Outcome
A difference between police data and an expected value
Stop Disproportionality
A difference between racial demographics of police stops & a benchmark
Outcome
A difference in the racial demographics percentages of stop outcomes

4. Decision to stop
We analyzed traffic stops made by the DPD between January 1st, and December 31st 2015.
Goal: to compare the percentage of minority drivers stopped to a valid benchmark

5. Where the traffic stops were made

8. Traffic Observer Locations and Findings

9. Observation Locations and Numbers
Correlation r for inter-surveyor observations within each location equals 0.63

10. Day verses Night Observations
Night and day benchmark values are not significantly different from one another (mean difference = 0.001; t = 0.057; p = 0.95)

11. Correspondence between bench & census
Census and Max benchmark values are not significantly different from one another (mean difference = 0.01; t = 0.47; p = 0.64)

13. Zone 1 adjustments
Break into block groups

14. Final Benchmark Values in Observation Zones
Census and Final benchmark values are not significantly different from one another (mean difference = 0.032; t = 0.995; p = 0.33)

15. DPD stops compared to the benchmark

16. Stops compared to benchmark

17. Weighted average across all zones for department as a whole
A Low Level of Disproportionality
Estimated margin of error is greater than

18. Days vs Nights Days zone min % bench stops 1.1 0.12 0.11 170 1.2 0.08
219
1.3
0.17
0.15
393 4
0.02
0.05
214 5
0.24
0.2
330 6
101
7.1
0.23 64
7.2
0.1
106 9
0.10
176 11
0.03
349 99
0.07
1024
Nights
zone
min %
bench
stops
1.1
0.15
0.11
142
1.2
0.17
101
1.3
0.20
240 4
0.06
0.05 52 5
0.23
0.2
350 6
0.19
0.12 73
7.1
0.28 39
7.2
0.14
0.1 37 9
0.08
170 11
0.07
174 99
0.09
660

19. Disparity Index Summary
Days
Nights
Dept.
Disparity
0.009
0.045
0.024
Stops
3146
2038
5184

20. Discussion
(1) The mean level of disproportionality for the department as a whole is low at roughly 2 percentage points above benchmark values. Within margin of error
(2) The mean level of disproportionality for stops occurring during daylight hours is less than 1 percentage point above benchmark values. Within margin of error
(3) The mean level of disproportionality for stops occurring during nighttime hours equals roughly 4.5 percentage points above benchmark values. Just outside margin of error

21. Stop Decision Conclusions
Analyses found no significant levels of disproportionality for the department as whole. Specifically,
Virtually no disproportionality in traffic stops during daylight hours (60% of all stops occur in daylight).
Low levels of disproportionality during nighttime hours.

22. Citations, Arrests, and Search Requests
Outcomes
Citations, Arrests, and Search Requests

23. Citations
Odds Ratio = 1.21
Minority drivers are slightly more likely to be ticketed on a traffic stop

24. Arrests (raw) Odds Ratio = 3.49
Minority drivers are more likely to be arrested on a traffic stop

25. Arrests (adjusted for warrants)
Odds Ratio = 2.66
Minority drivers are more likely to be arrested on a traffic stop

26. Search Requests Odds Ratio = 6.08
Note: The number of search requests is very small. Therefore, the odds ratio may not be a valid indicator of disproportionality. The data show that the DPD request to search very infrequently. On average this occurs once every 260 stops.

27. Moving or Equipment Violation
Reason for the Stop
Moving or Equipment Violation

28. Moving Violations Odds Ratio = 0.69 (1.44)
Whites are more likely to be stopped for moving violations

29. Equipment & Registration Violations
Odds Ratio = 1.45
Minority drivers are more likely to be stopped for an equipment violation

30. Multivariate Analyses

31. The control variables used
Time of day
Gender
Type of violation
Age of driver
Location of the stop

32. Logistic Regression Results
The results of logistic regression show that controlling for important variables does not substantively change the results for citations, arrests and search requests. However, the results also show that racial differences in stops for moving & equipment violations become no longer significant

33. Conclusions
Very low levels of disproportionality in traffic stops. Minority member drivers are not over represented in stops. No evidence of racial profiling
Low levels of disproportionality in citations. White drivers and minority members drivers are nearly equally likely to receive a citation as the result of a stop
Higher levels of disproportionality in arrests. The odds that minority member drivers are arrested on a traffic stop are about two-and-a-half times higher than for white drivers.