2019 VEHICLE STOPS EXECUTIVE SUMMARY

• Analysis
• View Agency Reports
• Appendix A: Local Vehicle Stops in Proportion to State Racial Composition
• Appendix B: Disparity Index Scores for 2000-2019 Data Compare
• Appendix C: Resident and Non-Resident Driver Disparity Index Scores

In 2019, the 1,161,680 Whites who were stopped accounted for 76.2% of all vehicle stops. Whites comprise an estimated 82.8% of Missouri’s driving age population. Therefore, the value for Whites on the disparity index is .92 (.762/.828). Blacks represent 10.9% of Missouri’s driving-age population but 19.5% of all vehicle stops, for a disparity index of 1.79.

Hispanics (0.79), Asians (0.54), American Indians (0.33), and persons of mixed or unknown race (0.71) were stopped at rates well below an expectation based upon their portion of the driving-age population.

The values on the disparity index for the different groups can be compared directly to one another by dividing their values. For example, the likelihood that a Hispanic motorist was stopped is 1.46 times that of an Asian motorist (.79/.54).

Limitations

The disparity index relies upon a benchmark to set the expected rate at which members of a racial/ethnic group should be stopped. The actual rate of stops is then compared against this benchmark to calculate the disparity index. The 2019 Vehicle Stops Report uses the racial/ethnic portions of the driving-age (16+) 2010 Census populations of each jurisdiction for its benchmarks. This is an imperfect benchmark as a person does not need to live in an area to drive through it and a person may not drive despite being old enough to legally do so. This dynamic can lead to the racial/ethnic makeup of drivers on a jurisdiction’s roadways differing from that of its residential population. The extremely low disparity index value for American Indians, for example, could indicate that they are under-represented among the state’s motorists. In addition, the benchmark population figures are nine years older than the vehicle stops data they are compared to. The age of these estimates may lead to some jurisdictions’ population estimates differing significantly from their current values

To minimize the distortion of the disparity index caused by the use of nine year-old population benchmarks, this year’s report uses population estimates from the 5-year American Community Survey (ACS) covering 2014 – 2018. However, the 2010 Census populations are the “default” estimate as the breakdown in reporting of racial/ethnic groups in the ACS is more limited than the Census. To generate the typical Census-based disparity indexes, each group’s benchmark population only includes non-Hispanic individuals and all Hispanic individuals are placed in the Hispanic category. However, the ACS only reports non-Hispanic population totals for Whites, meaning it is impossible to separate Hispanic individuals from non-White populations for the purposes of calculating the disparity index. This results in non-White Hispanic individuals being double counted in the 2018 ACS disparity index calculations, once in their racial group and once in the Hispanic group.

Analysis of the 2010 Census data found that 61% of Missouri’s Hispanic population was White, while 34% would fall into the “Other” category of this report which consists of those reporting “Other” or two or more races. This means that the distortion in the benchmark population for non-White races is limited across the state, though it is possible calculations for jurisdictions with larger non-White Hispanic populations could be distorted to a greater degree. The 2018 ACS disparity indexes should be viewed as supplemental information for analyzing traffic stop disproportions

Appendices to this report can provide useful analysis to partially alleviate these issues. Appendix A uses statewide rather than local racial/ethnic population portions to generate disparity index calculations, reducing the impact of the residency issue. Appendix C makes use of the residency question added to the Vehicle Stops Report form for the 2019 reporting cycle to only use traffic stops of residents of an agency’s jurisdiction when generating the disparity index. This allows an analyst to control for driver residency when examining an agency’s report.

2. Search Rate

A second metric that can be used to assess traffic enforcement is the “search rate,” or the number of searches divided by the number of stops (x 100). Searches include both searches of drivers and searches of the vehicle and property within

The search rate for all motorists who were stopped in 2019 was 6.74%. Asians were searched at a rate well below the statewide average (2.83%), while Blacks (8.86%) and Hispanics (8.30%) were searched at rates above the average for all motorists who were stopped. Whites were searched at a rate below the state average at 6.23%. The search rate for racial/ethnic groups can also be directly compared with one another. Hispanic drivers were 2.93 times more likely to be searched than Asian drivers (8.30/2.83).

Limitations

The reasons for conducting a search and the outcome of the search (i.e. discovery of contraband) should be considered when making comparisons across groups. Some searches are conducted with the consent of the driver, or because the officer observed suspected contraband in plain view, had reasonable suspicion that an individual may possess a weapon (Terry search), or other reasons. These searches may or may not result in an arrest

Other searches are conducted incident to arrest—this means that there is no other reason given for the search other than arrest. As mentioned above, searches are almost always performed when there is an outstanding arrest warrant, whether or not contraband may be present

It is notable that the search rate, along with the other post-stop metrics, are not subject to the benchmarking issues that affect the stop disparity index. The benchmarks for the post-stop metrics are the number of stops reported, so no estimation is involved in their calculation, making them more reliable metrics for assessing possible bias.

3. Contraband Hit Rate

The third summary metric, the “contraband hit rate,” reflects the percentage of searches in which contraband is found. Contraband was found in 35.4% of all searches conducted in 2019. Little difference exists in the contraband hit rate for searches of White and Black drivers (35.9% vs. 34.9%). The contraband hit rate for other groups is somewhat lower. For example, searches of Hispanic drivers resulted in a contraband hit rate of 28.4%. This means that, on average, searches of White and Black drivers are more likely than searches of Hispanics to result in the discovery of contraband.

Limitations

While the contraband hit rate is not subject to benchmark issues, the degree of discretion officers have in their searches should still be considered when examining contraband hit rates. The difference in contraband hit rates among racial/ethnic groups may result in part from the higher arrest rates for Blacks and Hispanics—if there is an arrest, there will be a search whether or not the arresting officer suspects the subject has contraband. This may deflate the contraband hit rate since searches are being completed based on procedure rather than suspicion of contraband.

4. Arrest Rate

The “arrest rate” is the fourth summary metric included in Table 1 that may be useful for assessing bias in traffic enforcement. Statewide, 4.89% of all traffic stops resulted in an arrest (74,553/1,524,640)

Approximately 6.21% of the stops of Blacks, 6.34% of the stops of Hispanics, and 4.68% of the stops of American Indians resulted in arrest, compared with about 4.55% of the stops of Whites. Asians (2.34%) and people of mixed or unknown race (3.91%) had lower arrest rates than Whites. The dynamic of Blacks and Hispanics being arrested at a higher rate likely impacts search and contraband hit rates as described above.

Limitations

Like the other post-stop metrics, the arrest rate does not suffer from benchmark issues, however, officer discretion should still be considered as described above.

Conclusion

Missouri is a vast and complex state at the crossroads of the country. Each of its communities is unique and presents many dynamics that must be comprehensively evaluated when assessing the possibility of bias in traffic enforcement. Each agency’s report should be read in conjunction with its entries in each of the appendices and in the context of the dynamics of the community it serves. This report is subject to limitations as described above and simply aims to provide a starting point for local dialogue.

Appendices

Appendix A: Local Vehicle Stops in Proportion to State Racial Composition
Appendix A presents the traffic stop analysis using the statewide proportions of race and ethnicity, rather than the local proportions of each jurisdiction. This is valuable as it reduces the impact of the residency benchmark issue on the disparity index of each agency.

Appendix B: Disparity Indexes for 2000-2018 Compared
Appendix B compares the 2019 disparity index to the disparity indexes for 2000 through 2018. For each agency, the disparity index for each race-ethnic group is presented for 2000-2019. For the state as a whole, the key metrics generally show small changes between 2016 and 2018.

Appendix C: Resident and Non-Resident Stops
Appendix C displays the number and percentage of traffic stops of residents of the jurisdiction where the stop occurred separately from the total number of stops (i.e., stops of residents + stops of nonresidents). Disparity Indexes for the different population groups are also shown.

Appendix C uses the addition of the driver residency question in the 2018 reporting cycle to provide a disparity index calculated using only traffic stops of drivers who reside in the agency’s jurisdiction. Readers should acknowledge that a driver’s residency may not accurately reflect where the driver spends the majority of their time. Many Missourians commute from one community to another for work and leisure, so the demographics of drivers on the road may not reflect those living in the community. By restricting the calculation to only those drivers who reside in a community, the calculation may include drivers who spend the majority of their time in another jurisdiction while excluding those who commute into the jurisdiction for the majority of the day.

*Agency did not submit data by the statutory deadline, but did provide data for inclusion in the report.