2014 VEHICLE STOPS EXECUTIVE SUMMARY
Concerns by the citizens of Missouri and the Missouri legislature regarding allegations of racial profiling by law enforcement prompted the passage of state law Section 590.650, RSMo (2000), which was enacted Aug. 28, 2000. Racial profiling has been defined as the inappropriate use of race by law enforcement when making a decision to stop, search or arrest a motorist.
Missouri’s state law requires that all peace officers in the state report specific information including a driver’s race for each vehicle stop made in the state. Law enforcement agencies are required to provide the data to the Attorney General, and the Attorney General is required to compile the data and report to the Governor no later than June 1 of each year. The law allows the Governor to withhold state funds for any agency that does not comply with the law. State law requires that all information be reported to the Attorney General’s Office by March 1.
The summary of statewide racial profiling data has been provided by Scott H. Decker, professor and director of the School of Criminology and Criminal Justice at Arizona State University; Richard Rosenfeld, professor in the Department of Criminology and Criminal Justice at the University of Missouri-St. Louis; and Jeffrey Rojek, assistant professor in the Department of Criminology and Criminal Justice at the University of South Carolina. Table 1. 2014 statewide summary of results
| ||Total ||White ||Black ||Hispanic ||Asian ||Am. Indian ||Other |
|Population ||4,730,501 ||3,914,998 ||515,828 ||139,109 ||80,677 ||19,168 ||60,721 |
|Stops ||1,681,382 ||1,317,360 ||304,321 ||30,782 ||14,845 ||1,934 ||12,140 |
|Searches ||100,038 ||68,620 ||27,381 ||3,049 ||433 ||151 ||404 |
|Arrests ||81,849 ||54,520 ||24,027 ||2,520 ||358 ||107 ||317 |
|State population % ||100.00% ||82.76 ||10.90 ||2.94 ||1.71 ||0.41 ||1.28 |
|Disparity index ||- - - ||.95 ||1.66 ||.62 ||.52 ||.28 ||.56 |
|Search rate ||5.95 ||5.21 ||9.00 ||9.91 ||2.92 ||7.81 ||3.33 |
|Contraband hit rate ||25.11 ||26.87 ||21.39 ||19.48 ||24.02 ||27.15 ||20.79 |
|Arrest rate ||4.87 ||4.14 ||7.90 ||8.19 ||2.41 ||5.53 ||2.61 |
Notes: Population figures are 2010 census estimates for persons 16 and older who designated a single race. Hispanics may be of any race. Other includes persons of mixed race and unknown race.
Disparity index = (proportion of stops / proportion of population). A value of 1 represents no disparity; values greater than 1 indicate over-representation, values less than 1 indicate under-representation.
Search rate = (searches / stops) X 100.
Contraband hit rate = (searches with contraband found / total searches) X 100.
Arrest rate = (arrests / stops) X 100.
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This report summarizes the data from 622 law enforcement agencies in Missouri for 2014. An additional 61 agencies indicated they made no traffic stops during the year. This represents 97.7% of the 699 law enforcement agencies in the state.
The agencies filing reports recorded a total of 1,681,382 vehicle stops, resulting in 100,038 searches and 81,849 arrests. Table 1 breaks out the stops, searches and arrests by race and ethnic group. Footnote 1
Four summary indicators are included in Table 1 that may be useful in assessing racial profiling in traffic stops. The first, termed the “disparity index,” relates each group’s proportion of total traffic stops to its proportion of the driving-age population 16 years old and older. Footnote 2
A value of 1 on this index indicates that a group’s proportion of vehicle stops equals its population proportion: it is neither “under-represented” nor “over-represented” in vehicle stops. Values above 1 indicate over-representation, and those below 1 indicate under-representation.
For example, the 1,317,360 whites who were stopped accounted for 78.3 percent of all vehicle stops in 2014.
Approximately 82.8% of Missouri’s driving-age population identified as “White.” The value for whites on the disparity index is, therefore, .95 (.783/.828). Whites were stopped, in other words, at slightly below the rate expected based on their fraction of the population age 16 and older from the 2010 Census.
The same is not the case for several other groups. African-Americans represent 10.9 percent of the population 16 years and older but 18.1 percent of all vehicle stops, for a value on the disparity index of 1.66. This means that African-Americans were stopped at a rate 66 percent greater than expected, based on their proportion of the population of people aged 16 and older.
Hispanics, Asians, American Indians, and persons of mixed or unknown race were stopped at rates well below their proportion of the driving-age population.
The values on the disparity index for the different groups can be compared directly to one another. For example, the likelihood that an African-American motorist was stopped is 1.75 times that of a white motorist (1.66/.95). In other words, African-Americans were 75 percent more likely than whites to be stopped based on their respective proportions of the Missouri driving-age population in 2014.
It should be remembered that the disparity index is a gauge of the likelihood drivers of a given race or ethnic group are stopped based on their proportion of the residential population 16 and older, not on the population of motorists on the state’s streets, roads and highways. A group’s share of the residential population 16 and older may or may not be similar to its proportion of drivers in the reporting area, and when there is a large discrepancy between the two numbers, the disparity index will be skewed.
When this occurs, it may largely be due to the fact that motorists are often stopped in municipalities, counties, or even states in which they do not reside. For example, a county may have a very low percentage of African-American residents, but a higher percentage of African-American motorists passing through the county due to the location of a state or federal highway. If local law enforcement stops some number of African-American motorists passing through the county, the number of stops may be highly disproportionate to the number of African-American county residents—resulting in a high disparity index—but less disproportionate to the actual number of African-Americans who drive through the county. Because no data is available for the racial demographics of motorist traffic, it cannot be calculated for purposes of this report.
A second indicator that can be used to assess racial profiling is the “search rate,” or the number of searches divided by the number of stops (x 100). In this report, searches include both searches of drivers and searches of the vehicle and property within.
The search rate for all motorists who were stopped is 5.95 percent. Asian drivers were searched at a rate well below the statewide average, while African-Americans and Hispanics were searched at rates above the statewide average.
Like the stop rates, the search rates for the different groups can be compared directly with one another. African-Americans were 1.73 times more likely to be searched than whites (9.00/5.21). Hispanics were 1.90 times more likely than whites to be searched (9.91/5.21).
The reasons for conducting a search and the outcome of the search (such as finding 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, or other reasons. These searches may or may not result in an arrest.
Other searches are conducted incident to arrest, which means that there is no other reason given for the search other than arrest. Searches are almost always performed when there is an outstanding arrest warrant, whether or not contraband may be present.
The third summary indicator, the “contraband hit rate,” reflects the percentage of searches in which contraband is found. Contraband was found in 25.1 percent of all searches conducted in 2014. There is some variation, however, in the contraband hit rate across race and ethnic groups.
The contraband hit rate for whites was 26.9 percent, compared with 21.4 percent for African-Americans and 19.5 percent for Hispanics. This means that, on average, searches of African-Americans and Hispanics are less likely than searches of whites to result in the discovery of contraband. This difference may result in part from the higher arrest rates for African-Americans and Hispanics—if there is an arrest, there will be a search whether or not the arresting officer suspects the subject has contraband.
The “arrest rate” is the fourth summary indicator included in Table 1 that may be useful for assessing racial profiling. Just under 5 percent of all vehicle stops resulted in an arrest (81,849/1,681,382). The probability of arrest varies across racial and ethnic groups.
Approximately 7.9 percent of the stops of African-Americans and 8.2 percent of the stops of Hispanics resulted in arrest, compared with about 4.1 percent of the stops of whites.
There are two appendices to this year’s report. Appendix A presents the vehicle stop analysis using the statewide proportions of race and ethnicity, rather than those for each jurisdiction.
This year’s report compares the 2014 disparity index to the disparity indexes for 2000 through 2013. These comparisons are presented in Appendix B. Footnote 3
For each agency, the disparity index for each race-ethnic group is presented for 2000-2014. For the state as a whole, the key indicators generally show small changes between the years 2013 and 2014.
The search rate (the percentage of stops in which a search is conducted) decreased between 2013 and 2014 for white, African-American, and Hispanic drivers, remained the same for Asians, and increased for American Indians. The arrest rate for African-Americans decreased (from 10.31 percent to 9.00 percent) and decreased for Hispanics (from 10.23 percent to 9.91 percent) between 2013 and 2014.
A reasoned determination of the existence of racial profiling in a community requires a comprehensive evaluation of the full range of information compiled in the agency reports. This brief summary of selected indicators for the state as a whole is intended to encourage those local evaluations and dialogue.
|Table 2. Agencies that did not submit reports by March 1, 2015 as required by state law |
|Bates City Police Department* ||BNSF Railway Police ||Camden Point Police Department* |
|Camden Police Department ||Claycomo Police Department* ||Crystal Lakes Police Department* |
|Deepwater Police Department ||East Lynne Police Department* ||Edgerton Police Department |
|Edina Police Department* ||Ferguson Police Department* ||Hurley Police Department |
|Lilbourn Police Department ||Morley Police Department ||Naylor Police Department |
|New Melle Police Department ||St. Louis Park Rangers ||Wellston Police Department |
* The following agencies submitted their mandatory reports late, and therefore have been included in the statistical analysis for this Report, despite having missed the statutory deadline: Crystal Lakes Police Department, Claycomo Police Department, Ferguson Police Department, Edina Police Department, Camden Point Police Department, East Lynne Police Department, Bates City Police Department.
|Table 3. Agencies that submitted incomplete reports |
|Lockwood Police Department |
|Table 4. Agencies that reported no stops (many contract out vehicle stops to other agencies) |
|Altenburg Police Department ||Atlanta Police Department ||Bell City Police Department |
|Berger Police Department ||Bevier Police Department ||Birmingham Police Department |
|Bland Police Department ||Bunker Police Department ||Canalou Police Department |
|Catron Police Department ||Clarksdale Police Department ||Clarkson Valley Police Department |
|Cool Valley Police Department ||Cooter Police Department ||Cowgill Police Department |
|Dellwood Police Department ||Dudley Police Department ||Emma Police Department |
|Eolia Police Department ||Everton Police Department ||Fairfax Police Department |
|Farber Police Department ||Fisk Police Department ||Gainesville Police Department |
|Gasconade Police Department ||Gilman City Police Department ||Golden City Police Department |
|Grandin Police Department ||Hale Police Department ||Holland Police Department |
|Irondale Police Department ||Jackson County Drug Task Force ||Jennings Police Department |
|Keytesville Police Department ||Kimmswick Police Department ||Lake Annette Police Department |
|Lake Lafayette Police Department ||Marston Police Department ||Mayview Police Department |
|Mineral Area College DPS ||Missouri Department of Revenue ||Mokane Police Department |
|Montrose Police Department ||Norborne Police Department ||Novinger Police Department |
|Olympian Village Police Department ||Pasadena Park Police Department ||Shannon County Sheriff's Department |
|Sheldon Police Department ||St. George Police Department ||St. Louis Community College at Forest Park |
|Tallapoosa Police Department ||Taos Police Department ||Theodosia Police Department |
|Union Pacific Railroad Police - St. Louis ||Uplands Park Police Department ||Walker Police Department |
|Westwood Police Department ||Wildwood Police Department ||Williamsville Police Department |
|Windsor Police Department ||Wyatt Police Department || |
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Fourteen years ago, Missouri released its first report on vehicle stop data. This report represents the fourteenth annual analysis of vehicle stop data in Missouri, a review that includes information about 1,681,382 million stops by law enforcement in the state during 2014. The report can be compared to data going back to 2000.
The analysis in 2005, 2006, 2007, 2008 and 2009 used census estimates to reflect the changes in Missouri’s population since the 2000 census. That census was the benchmark for the previous five reports. The 2010, 2011, 2012, 2013 and 2014 analysis used census estimates from the 2010 census.
As our state’s population changes in number and demographics, these census estimates can help provide a more accurate benchmark to analyze the data.
The overall number of stops reported increased in 2014. As it has in the past, the disparity index for African-American drivers continues to be of significant concern. The disparity index for African-American drivers increased from 1.59 in 2013 to 1.66 in 2014. The disparity index for Hispanic drivers also increased slightly from .61 in 2013 to .62 in 2014. Both groups continue to have search rates significantly higher than that of white drivers.
These findings continue a disturbing trend for African-American drivers in Missouri. The disparity index for African-American drivers has increased steadily over the last fifteen years, with only slight, temporary drops three times: to 1.34 in 2004 from 1.36 in 2003, to 1.61 in 2010 from 1.62 in 2009 and to 1.57 in 2012 from 1.63 in 2011.
The 2014 disparity rate of 1.66 compares to a rate of 1.27 fifteen years ago, and is the highest we have seen since data collection began in 2000.
The pattern is striking: the data tell us that in 2014, Missouri’s African-American drivers were 75 percent (1.66/.95) more likely than white drivers to be stopped on Missouri’s roads. Just 14 years earlier, in 2000, the difference was only 31% (1.27/.97).
With 622 law enforcement agencies conducting vehicle stops in Missouri, there is no single explanation why these disparities exist. This report provides statistical information so the data from each agency can be examined, and appropriate questions asked of those agencies.
While statistical disproportion does not prove that law enforcement officers are making vehicle stops based on the perceived race or ethnicity of the driver, the compilation and analysis of data provides law enforcement, legislators, and the public with a starting point as they consider improvements to process and changes to policy to address these issues.
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Footnote 1: Hispanics may be of any race. About 1 percent of the population designated two or more races. These persons are included in the “other” category along with persons of unknown race.
Footnote 2: The population totals in the table are from the 2010 Census.
Footnote 3: Caution should be used when comparing 2000 to subsequent years, especially for smaller agencies, because the 2000 figures are based on only four months of traffic data, while those for subsequent years are based on the full calendar year.
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