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Race, Crime, and Police Interaction John MacDonald Professor of Criminology and Sociology University of Pennsylvania September 2 6 , 2021 Conference Paper Federal Reserve Bank of Boston Economic Research Conference Series: Racial Disparities in Today’s Economy, 64th Economic Conference Abstract This paper examines the relationship between racial disparities in poverty, arrests, crime, and police interactions. This study reviews research on racial/ethnic disparities concentrated poverty and its association with disparities in crime victimization and official police interactions. An analysis of 221 large U.S. cities in 2014-2018 examines the association between racial disparities in poverty, unemployment, and arrests. The results show that arrest rates for blacks relative to whites are significantly higher even after controlling for the level of concentrated disadvantage. Even among the cities that rank highest in concentrated disadvantage for whites, blacks on average have higher unemployment and are more likely to live below the poverty line. These findings confirm that blacks and whites on average in large U.S. cities live in largely different environmental contexts. An examination of the spatial concentration of economic disadvantage, crime, and arrest patterns in New York City, Chicago, and Los Angeles for years 2014- 2019 shows that black and Hispanic monthly arrest rates are significantly higher in census block groups with greater levels of concentrated economic disadvantage. Arrest rates for whites and other groups are either negatively associated or have no relationship with the level of concentrated disadvantage. In all three cities, the level of reported crime is more strongly associated with black and Hispanic disparities in arrest rates than concentrated disadvantage. In New York and Chicago, a substantial share of disparities in black arrest rates are driven places in the top five percentiles of reported crime, and the same pattern holds for Hispanic arrest rates in Los Angeles. The results suggest high crime places located in areas with concentrated poverty help explain a significant share of black and Hispanic disparities in arrest rates. The paper concludes that investing in place-based programs that improve public safety could reduce racial disparities in police contact. Introduction Serious crime, poverty, and police activity are highly concentrated by place. Black Americans are on average more likely than white Americans and other groups to live in neighborhoods characterized by concentrated disadvantage, reflecting higher spatial concentrations of poverty, unemployment, joblessness, family disruption, and geographic isolation (Sampson & Wilson, &
Katz, 2018). Just three to five percent of places and street segments in a given city generate at least fifty percent of crime (Sherman et al., 1989; Weisburd, 2006). Racially isolated neighborhoods of concentrated disadvantage are more likely to have these hot spots of crime and police contact (Braga & Weisburd, 2010; Sampson, 2011). The substantial spatial inequality in the concentration of poverty, violent crime, and social resources connect to historic and contemporary patterns of racial residential segregation (Massey & Denton, 1993). The number of calls for service and crime typically influences patterns of police deployment in U.S. cities. The extra-allocation of police to high crime areas is particularly evident in cities like New York that adopted the “new policing model” of linking officer assignments to crime analytics (MacDonald, Fagan, & Geller, 2016). These disparities by place are fundamentally important for thinking about who is most likely to encounter a police officer, especially in the context of highly discretionary activities like the decision to stop and question someone suspected of a crime or make an arrest. In this paper, I examine whether concentrated disadvantage at the city and census block group level explains a significant share of the racial disparities police arrests. I review some of the empirical research on racial disparities in police stops, arrests, and use of deadly force. I discuss how spatial patterns of concentrated disadvantage may help explain a substantial share of racial disparities in the police interactions, like the decision to stop, question, and frisk someone or to make an arrest. The review focuses on published studies that examine racial disparities in stops and arrests, with some discussion of police use of deadly force. An analysis of city level data on arrests for serious crimes examines how much differences in concentrated poverty explain the gap in arrest rates for blacks relative to whites. An analysis of micro data from New York, Chicago, and Los Angeles estimates how the disparities in arrest rates for blacks and Hispanics relative to whites and other groups is accounted for by the level of concentrated poverty and reported crime between census block groups. Finally, I discuss the consequential role of historic and contemporary fractured police-minority relationships and the need for more research on testing how police can collaborate with other municipal service agencies and community groups to address problematic crime hot spots that generate a disproportionate share of arrests. An evidence-based policing model that focuses on places may help reduce racial disparities in police contact and improve public safety in the neighborhoods with the greatest levels of concentrated disadvantage in the U.S.
findings line up with the work of Krivo and Peterson (1996) that finds predominately black neighborhoods with the highest rates of violent crime in Columbus, Ohio are clustered together in the same sections of the city compared to extremely poor predominately white neighborhoods. Krivo and Peterson (2006) similarly find in a study of 79 large US cities that census tracts with higher concentrations of poverty and predominately-black populations have higher rates of violent crime, associations correlated with racial residential segregation. Importantly, the spatial inequality in concentrated poverty is stratified by race such that there are few large U.S. cities where there is a single poor majority white neighborhood that parallels the poorest majority black neighborhoods (Sampson & Wilson, 1995). In states located in the Southwestern U.S., patterns of concentrated poverty emerge for Hispanics relative to whites, but in general, the disparities in poverty, crime, and its spatial location are largest when it comes to black-white differences in large U.S. cities. Sampson, Wilson, and Katz (2018) make a strong case that racial segregation and the concentration of poverty since the 1950s has resulted in stable patterns of disadvantage for black Americans living in deep poverty. While the antecedents to these patterns are numerous, the consequence is that blacks are on average more likely than whites in the population to live in high poverty neighborhoods surrounded by other similarly poor neighborhoods, and those social ties to larger institutions of social control like schools, churches, local government services eroded. A long history of urban sociology has charted how segregating the poor into neighborhoods with high rates of joblessness creates institutional breakdowns (Wilson, 1987; Venkatesh, 2000; Sampson, 2012). Neighborhoods with a high concentration of poverty and serious street crime have fewer community organizations and connections to key city agencies that can help ensure service requests are being met (Sampson, 2012 ). In addition, research indicates that concentrated disadvantage and racial residential segregation is associated with reduced economic mobility. Sharkey ( 2008 ) finds in the Panel of Income Dynamics data that 55 percent of black children growing up in the poorest decile of neighborhoods remain living in the poorest decile of neighborhoods as adults, compared to 19 percent of white children growing up in the poorest decile. Chetty et al. (2014) find that income mobility is substantially lower in areas with higher levels of racial residential segregation. B. Spatial Disadvantage and Racial Disparities in Police Contact
The spatial concentration of disadvantage is also important for helping explain some patterns in racial disparities in police contact and arrests. Sampson (1986) shows that even after controlling for self-reports of serious delinquency youth in Seattle who are black and living higher poverty neighborhoods are more likely to experience a police arrest. These findings suggest that exposure to police and discretion by place and race may condition police discretion in deciding whether to arrest a youth for a crime. Kirk (2006) found in a longitudinal sample of youth in Chicago that the probability of arrest at age seventeen was 29 percent for blacks compared to 12 percent for whites, but that black youth were significantly more likely to live in areas of concentrated poverty that were racially segregated.^1 The expected black-white disparity in arrest rates is 21 percent lower after accounting for neighborhood differences in concentrated poverty, racial segregation, and other factors. There is a considerable body of research suggesting that police deployment and interactions with citizens vary considerably by neighborhood environments. Klinger ( 1997 ) argues that the deployment of police by geography in cities exposes officers in different units to varying levels of crime and disorder. Within patrol areas, norms develop among police officers on the style of policing and their propensity to enforce the law. Research has found that police discretionary decisions to stop a suspect or make an arrest vary considerably by neighborhoods (Fagan and Davies, 200 0 ; Gelman, Fagan, and Kiss, 2007; Smith, 1986). National estimates from the Police Public Contact Survey (PPCS) in 2015, a supplement to the National Crime Victimization Survey, find 14.55 per 1,000 black people report experiencing a street stop in the prior year compared to 9.07 for whites.^2 Here the data suggests that the disparities are greater for street stops than traffic stops, consistent with the fact that police deployment, crime, and poverty are highly concentrated in urban cities in racially segregated neighborhoods. A primary challenge with research on racial disparities in police contact is establishing the benchmark for who should be at risk for a police stop and/or arrest. Ridgeway and MacDonald (2010) and Neil and Winship (2019) provide a summary of the methodological challenges with establishing who is at risk for being stopped by the police and why most approaches do not provide credible inference. Setting aside the issue of the appropriate (^1) For black youth in the sample on average 78 percent of the population of their neighborhoods were comprised of black residents. For white youth on average 49 percent of their neighborhoods were comprised of white residents. (^2) https://bjs.ojp.gov/content/pub/pdf/cpp15.pdf
location characteristics of stops, but that the disparities reverse by 2015 after court settlement reforms. Fryer (2019) shows in a national sample of public police contacts that black respondents are 18 percent more likely than white respondents to report having any use of force in a police interaction in the past year, and that general location and encounter-related factors do not substantially reduce the disparity. An important limitation in this analysis is insufficient base rates and location information to estimate how much racial disparities in force are associated with levels of crime and concentrated disadvantage by places. When it comes to estimating racial disparities in police use of deadly force there are few studies that offer any assessment of the role of place-related factors. Police use of deadly force is rare relative to stops and arrests, so estimates of racial disparities in deadly force that attempt to control for location related factors are likely to be statistically underpowered. Studies have attempted in recent years to estimate disparities in officer involved shootings by comparing rates of shootings for black, Hispanic, and white suspects relative to arrests deemed at greater risk for a shooting (e.g., aggravated assault, robbery, attempted murder of a police officer). Fryer (2019), for example, finds that officers in Houston are less likely to shoot black suspects than white suspects relative to random draw of arrests for aggravated assault against a police officer, attempted murder of a police officer, resisting arrest, evading arrest, interfering in an arrest, and arrests with tasers used. Adding suspect, officer, and encounter related variables does not change the association. Fryer (2019), however, does not assess the associations between shootings and location related factors like crime or concentrated poverty. Klinger et al. (2015) attempt to assess the association between police shootings in general, concentrated poverty, crime, and the percent of black residents of neighborhoods in St. Louis.^3 They find that officer involved shooting rates per neighborhoods are highest in areas with higher levels of gun violence, and that percent of black residents of neighborhoods is not associated with shooting rates. With a total of 230 officer involved shootings over 355 census block groups and a correlation of .69 between firearms violence and percent of black residents, this study is under powered to test for differences across these covariates. Legewie and Fagan (2016) provide one of the only recent city-level (n= cities) studies of black-white disparities in fatal police shootings (collected from crowd source data) per population or per arrests. They find a small association between city-level difference in (^3) In these data over 90 percent of police shootings involved black suspects, and there is no reference group for cases that did not involve shootings, making it impossible to make any inferences about racial disparities.
the unemployment rate for blacks and the rate of black police shootings. Shooting rates are significantly higher for blacks as the share of black-on-white homicide increases, but that the same association is not significant for police shooting rates of whites. However, the difference in coefficients across models is small suggesting that the effects are not substantively different. The study does not show how the black-white disparity in police use of deadly force changes before and after including covariates. Wheeler et al. (2018) offers one of the only studies to assess racial disparities in officer-involved shootings that assesses the association with incident and place- related characteristics. The study calculates disparities in shootings (n=207) based on the rate per times an officer pulled a gun (n=1,702) and finds that black suspects are shot a lower rate per times officers drew a gun, but that neighborhood poverty, racial demographics, and violent crime rates are not associated with the probability of a shooting. However, this study is underpowered to examine location associations given that shootings occur in only 11 percent of incidents where officers pulled a gun on a suspect. Additionally, there is a clear concern that the benchmark is biased. If officers are more likely to draw guns in general on black suspects than they are on white suspects, using weapons drawn as a reference group will mechanically make the fraction of shootings for black suspects lower than it is for white suspects.^4 C. Racial Disparities in Police Contact by Officers Research has also focused on assessing the role that individual officer bias has in generating racial disparities in pedestrian and traffic stops. Several papers rely on methods that attempt to match officers based on work assignments and flag outlier officers whose patterns of stopping minorities differs substantially from their peers (Ridgeway and MacDonald, 2009). These methods are especially useful from a management approach to trying to reduce outliers. In some contexts where the most active officers may be generating a large share of stops of civilians, curtailing the stop activities of outlier officers may reduce population level racial (^4) The same set of authors attempt to address this shortcoming by estimating racial disparities in weapons drawn by officers relative to all use of force incidents, finding that black suspects are less likely to have weapons draw on them in use of force cases relative to white suspects (Worrall et al., 2020). This study, however, may have the same potential selection bias. If police officers have a lower threshold for engaging in use force with black suspects, they can proportionally have fewer cases of drawing a weapon per force event. The study finds that the disparity between black and white suspects shrinks to being non-significant when comparing only use of force cases that result in arrest as a reference group, which suggests that selection could be a threat to the inference from their primary finding. However, the direction and size of the estimate of only arrest cases as a reference is nearly the same as when all use of force cases are a reference, suggesting that one cannot draw a conclusion about selection bias from using this subset of the data.
D. Summary In U.S. cities crime is highly correlated with the concentration of poverty, such that the two go hand in hand. A few studies suggest that street stops are disparate in the places that generate higher levels of serious crime, but few studies examine what share of the racial disparity in arrests is attributable to the environmental context of locations. Additionally, there is the potential that crime is actually a poorly used proxy by the police. Grunwald and Fagan (2019), for example, find during the height of the use of stop, question, and frisk activity in New York City there was very little correlation between an officer indicating suspicion based on the legally permissible indicator of high crime area and the actual level of crime in that area. While criminal behavior in high crime locations may influence a significant share of racial disparities in police stops, perceived suspicion based on loose heuristics of an area being high crime may produce unjustified police actions in stopping individuals. Research on racial disparities in police arrests is especially thin when it comes to understanding how much arrest rates are associated with area differences in reported criminal activity and the level of concentrated disadvantage. Focusing police activity in the highest crime street segments make sense from a crime control perspective, given that crime is highly concentrated by location (Weisburd, 2006), but we have little research that examines how much population level disparities in arrests are driven by the concentration of poverty and crime. II. Racial Disparities in Poverty, Crime, and Police Interactions A. Aggregate Disparities Racial disparities in poverty, crime, and police contact are an established fact in the United States. Data from the census American Community Survey (ACS) estimates of poverty in years 2015 to 2019, for example, shows that blacks and Hispanics consistently have a higher share of the population living below the poverty level. Table 1 shows that all groups there was some improvement between 2015 and 2019, but in general blacks and Hispanics are roughly 2 to 1. times more likely than whites to live in poverty in the United States. Table 1. Race/Ethnic Disparities in Percent Population Living in Poverty Year White Black Hispanic 2015 12.2% 25.4% 22.6% 2016 11.6% 23.9% 21% 2017 11.1% 23% 19.4% 2018 10.9% 22.5% 18.8%
Mean 11.22% 23.20% 19.80% Source: American Community Survey, Census Bureau https://data.census.gov/cedsci/table?q=poverty%20status&tid=ACSST1Y2015.S1701&hidePreview=true Separate analyses examining ACS data by county shows that blacks and Hispanics are on average about 2 times more likely than whites to live below poverty in urban counties with populations of over 500,000 people. These statistics, however, mask how much the disparity in poverty varies by geographic concentration within cities. Table 2 shows the data from the National Crime Victimization Survey and the FBI’s Uniform Crime Reports averaged for years 2015-2019. From these descriptive data, we can compare the proportion of black, white, and Hispanics in the population to representation in race of victims of robbery and aggravated assault reported in the NCVS and arrests of suspected offenders in the UCR. Hispanics are not separately distinguished from racial categories so the percentages exceed 100% when including this group. The data show that a higher proportion of blacks are arrested for robbery and assault compared to their representation in the population or as crime victims. Hispanics and whites are arrested proportionally closer to their victimization proportions in the NCVS. While the black-white disparity is larger in arrests than victimizations, it is hard to draw strong conclusions about the sources of the disparities from these aggregate data. Table 2. Racial Disparities in Victimizations and Arrests for Robbery and Aggravated Assault, Average 2015 - 2019 Race/Ethnicity Population Robbery Victims Robbery Arrests Assault Victims Assault Arrests White 60.4% 47.3% 48.8% 59.5% 62.5% Black 12.5% 18.8% 48.8% 13.3% 33.2% Hispanic 18.3% 23.7% 23.1% 19.8% 24.9% Sources: Bureau of Justice Statistics, NCVS Victimization Tool and FBI, Uniform Crime Reports, 2015-2019. Assaults represent aggravated felony assaults. Given that most interpersonal offenses are intra-racial, the share of blacks arrested for robbery should be substantially lower if arrests are a random sample of those victimized. Data from the 2018 NCVS shows that blacks are about twice as likely to be offenders compared to their victimization percentages.^5 The 2019 NCVS shows that around 46 percent of victims of (^5) See https://bjs.ojp.gov/content/pub/pdf/cv18.pdf table 12.
Table 4. Firearm Homicide Offending, Victimization, and Police Shootings by Race Year Black homicide victims White homicide victims Black homicide offenders White homicide offenders Black police shootings White police shootings 2015 16. 69 1. 76 12. 95 1. 28 0. 63 0. 28 2016 18. 58 1. 99 13. 98 1. 39 0. 57 0. 26 2017 17. 99 1. 97 14. 22 1. 41 0. 54 0. 27 2018 16. 95 1. 84 13. 84 1. 42 0. 55 0. 26 2019 17. 63 1. 77 14. 38 1. 38 0. 60 0. 25 Mean 17. 57 1. 87 13. 87 1. 38 0. 58 0. 26 Notes: Rates per 100,000 population. Data sources; https://github.com/washingtonpost/data-police-shootings https://www.ojjdp.gov/ojstatbb/ezashr/; https://data.census.gov/cedsci/table?d=ACS%201- Year%20Estimates%20Data%20Profiles&tid=ACSDP1Y2019.DP Homicides victims and (known) offenders rates are calculated based on those killed with firearms so that the comparisons between the SHR and Washington Post data on police shootings are consistent. The Washington Post data includes only police homicides caused by firearms. For each of these data sources rates are calculates per 100,000 in the population. The population rates will be slightly off because the SHR does not cover the entire country. The mean homicide victimization rate was 17.57 per 100,000 for blacks and 1. 87 per 100,000 for whites, reflecting a population level black-white disparity of 9. 3. The known homicide offender rate was 13.87 for blacks and 1.38 for whites, a population level disparity of 10. The patterns show that the police shot and killed approximately. 58 blacks compared. 26 whites per 100,000, reflecting a population level disparity of 2. 2. The patterns suggest black-white disparities for gun homicides are the greatest for homicide offenders, homicide victims, and then homicides by police. The aggregate data indicates the black population is more likely than the white population to live in poverty, victimization rates for serious violent crime are higher for blacks relative to whites, and arrests and deadly force by the police are higher for blacks relative to their share of the population but not their share of known violent offenders. National estimates of street stops suggests population level disparities for blacks relative to whites, but it is unclear how much of these differences are reflections of racial bias by the police or differences in perceived violations or criminal behavior. Importantly, aggregate comparisons do not tell one the extent to which racial disparities in police stops, arrests, and the use of deadly force is attributable to differences in concentrated poverty and crime, individual officer bias, or policy choices made on how to deploy police and enforce criminal law violations. In the following
sections, I provide case studies that attempt to address how much the racial disparities in police stops and arrests is attributable to differences across places in crime and concentrated poverty. B. Racial Disparities in Police Stops in New York City Studies across multiple cities suggest that the environmental context of crime and poverty cannot fully explain racial disparities in police stop and frisk rates. Several studies on New York City have examined the rate of street stops after controlling reported crime, calls for police service, and poverty in a location and generally find rates of stops are higher in areas with higher percentages of black residents (Fagan et al., 2010; MacDonald and Braga, 2019). However, few studies examine directly how much of the disparity in stop rates by race is attributable to the level of reported crime in places. Zimroth et al. (201 7 ) show in a report on New York City that the racial disparity in street stops closely parallels the level of reported crime in census blocks. Rather than estimating a statistical model, however, the report simply examines the ratio of stops to crimes reported and how that varies by race and ethnicity of individuals stopped. The ratios show excessive stops relative to crime in the years 2013-2014. In 2015 NYPD management curtailed its emphasis on the use of street stops to control crime, and the racial disparities ratios of stops relative to crime diminished to an insignificant level. In the following section I reproduce this approach of comparing the ratio of stops of a given race or ethnicity to the level of reported crime in a location. Data and Measures Stop, question, and frisk (SQF) and crime data for years 2013- 2015 came from open sources.^7 The SQF data contains information on the reason for the reported stop noted by the police officer, frisks or searches of individuals if made, and enforcement actions taken. SQF data also contains demographic information of the stopped individual. I created indicator variables measuring the race of stopped individuals according to major racial categories of black, Hispanic, and white or other groups. I focus on comparing black and Hispanic ratios of stops relative to crime compared to white and other groups. SQF and crime datasets were geocoded to the nearest census block. Over 95% of reported SQFs and crimes were successfully geocoded for (^7) SQF data is available at: (http://www.nyc.gov/html/nypd/html/analysis_and_planning/stop_question_and_frisk_report.shtml). Crime data is available at: (https://data.cityofnewyork.us/Public-Safety/NYPD-Complaint-Data-Historic/qgea-i56i)
places with the least amount of crime reported. The findings suggest that there are racial disparities in who is committing crime in relatively low crime blocks or that police are engaged in racial profiling in deciding whom to stop and question for suspected criminal activities. C. City Level Arrest Disparities Given the paucity of research in recent years examining the association between racial disparities in concentrated poverty and police arrest rates, the present analysis re-examines this issue with recent data. Data and Measures The data for the city level analysis of arrest disparities between blacks and whites comes the Chalfin et al. (202 0 ) study of police force sizes, crime, and arrests in 242 U.S. cities with populations greater than 50,000 in 1980 and regularly report data to the U.S. Census Bureau Annual Survey of Government (ASG). These data combine city level measures of crime and arrests captured by the Uniform Crime Reports (UCR) system of the Federal Bureau of
Investigation. The final sample consists of 221 cities with complete data on crime and arrests for index offenses (murder, rape, robbery, aggravated assault, burglary, grand larceny, and motor vehicle theft) for blacks and whites for years 2014-2018. Index offenses measure seven felony crimes measured uniformly across cities as part of the FBI’s annual survey of crime. These data were combined with U.S. Census Bureau population for each city captured in the annual American Community Survey (ACS) (five year estimates for years 2014-2018). Race-specific measures of concentrated disadvantage for each city were measured by a standardized composite scale (mean centered at zero) of the black or white percentage of the population living below poverty, the percentage of the population unemployed, and the median household income from ACS data. Measures for population density from the ACS and the per capita public expenditures for each city from the ASG are also included. Region is measured for each city according to Federal Information Processing (fips) classifications (Northeast, Midwest, South, West).^8 Empirical Model The empirical model examines the extent to which race-specific measure of concentrated disadvantage are associated with yearly city level disparities in black and white arrest rates for index offenses. Rates of arrest reflect the per capita population. A Poisson regression model estimates the arrests rate per city (i) for each group (j) (blacks or whites) separately, and includes the population of blacks or whites as exposure variable. This approach converts the counts of arrests to a rate per population (black or white). The model estimated takes the following form: log (
𝑗 ) 𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛𝑖𝑡
= 𝛽 0 + 𝛼k%𝐵𝑙𝑎𝑐𝑘𝑖𝑡 + 𝜇k%𝐻𝑖𝑠𝑝𝑎𝑛𝑖𝑐𝑖𝑡 + ϒ𝐶𝑟𝑖𝑚𝑒 𝑅𝑎𝑡𝑒𝑖𝑡
- 𝜃k𝐶𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑒𝑑 𝐷𝑖𝑠𝑎𝑑𝑣𝑎𝑛𝑡𝑎𝑔𝑒𝑖𝑡 𝑗
- 𝜎𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝐷𝑒𝑛𝑠𝑖𝑡𝑦𝑖𝑡
- 𝜋𝑃𝑒𝑟 𝐶𝑎𝑝𝑖𝑡𝑎 𝐸𝑥𝑝𝑒𝑛𝑑𝑖𝑡𝑢𝑟𝑒𝑠𝑖𝑡 + 𝜂𝑟 + 𝛿𝑡 In each model the black or white arrest rate (λ) per month is estimated assuming a Poisson distribution after controlling for crime rates (reported index offenses), the race/ethnicity percentages of the population (% Black, % Hispanic, % Other), per capita public expenditures, (^8) https://www.census.gov/geographies/reference-files/2020/demo/popest/2020-fips.html
percent for cities that are in the second and third quantile relative to the first quantile. The reductions in black arrest rates by share of the black population does not changes substantively after controlling for concentrated disadvantage (2) or concentrated disadvantage and crime (3). Table 7 also shows that the black arrest rate for index offenses is 31.5 percent higher in cities that rank in the top quantile of black concentrated disadvantage, even after controlling for the crime rate (3). Table 7. City Level Index Arrest Rates for Black, 2014-2018. (1) (2) (3) Index Arrests Black Index Arrests, Black Index Arrests, Black Quantiles % Black=2 0.723^ 0.713^ 0.726** (0.0746) (0.0745) (0.0793) Quantiles % Black=3 0.633^ 0.609^ 0.615** (0.104) (0.0981) (0.102) Quantiles % White=2 1.269^ 1.395^ 1.411* (0.122) (0.132) (0.134) Quantiles % White=3 1.585^ 1.750^ 1.791* (0.320) (0.295) (0.306) Quantiles % Hispanic=2 1.185 1.244 1. (0.139) (0.146) (0.147) Quantiles % Hispanic=3 1.002 1.063 1. (0.166) (0.164) (0.171) Expenditures per 1,000 1.000 1.000 1. (0.0000182) (0.0000185) (0.0000194) Population density 1.000 1.000 1. (0.0000147) (0.0000142) (0.0000147) Year=2015 0.938^ 0.935^ 0.938** (0.0167) (0.0170) (0.0163) Year=2016 0.876^ 0.872^ 0.872** (0.0192) (0.0195) (0.0190) Year=2017 0.852^ 0.849^ 0.850** (0.0236) (0.0235) (0.0228) Year=2018 0.876^ 0.872^ 0.877** (0.0379) (0.0360) (0.0351) Midwest 1.029 1.006 0. (0.141) (0.118) (0.117) South 1.128 1.304^ 1. (0.148) (0.172) (0.170) West 1.361^ 1.547^ 1.483* (0.151) (0.181) (0.180) Disadvantage, Black=2 1.046 1. (0.0941) (0.0912) Disadvantage, Black=3 1.362*^ 1.315
Crime rate 1. (0.0000201) Observations 1055 1055 1055 Exponentiated coefficients (Incidence Rate Ratio); Standard errors in parentheses; Reference groups are 1st^ (0- 33 percentile) for Quantiles, 2014 for year, and Northeast for region. Concentrated Disadvantage represents average of percentage of blacks in poverty, percentage of unemployed, and median household income.
- (^) p < .05, ** (^) p < 0.0 1 Table 8 presents the results from the estimates of the white arrest rate in each city before (1) and after including measures of concentrated disadvantage (2) and crime (3). Cities that rank higher in the proportion of black population have a significantly lower white arrest rates. Column 1 shows that white arrest rate declines by approximately 22.2 and 3 7.3 percent for cities that are in the second and third quantile relative to the first (0-33 percentile) in percentage of black residential population (3). The lower white arrest rate in cities with a majority black population closely mirrors the lower black arrest rate. Table 8 also shows that the white arrest rate for index offenses is 54.8% higher in cities that rank in the top quantile of white concentrated disadvantage, even after controlling for the crime rate (3). Table 8. City Level Index Arrest Rate for White, 2014-2018. (1) (2) (3) Index arrests, White Index arrests, White Index arrests, White Quantiles % Black=2 0.787^ 0.768^ 0.778* (0.0750) (0.0690) (0.0736) Quantiles % Black=3 0.671^ 0.637^ 0.627** (0.0951) (0.0873) (0.0865) Quantiles % White=2 0.732^ 0.837^ 0.818 (0.0803) (0.0710) (0.0688) Quantiles % White=3 0.784 0.875 0. (0.112) (0.114) (0.114) Quantiles % Hispanic=2 1.225^ 1.197 1. (0.125) (0.121) (0.124) Quantiles % Hispanic=3 1.517^ 1.430^ 1.506* (0.204) (0.197) (0.208) Expenditures per 1,000 1.000 1.000 1. (0.0000263) (0.0000256) (0.0000258) Population density 1.000^ 1.000 1. (0.0000183) (0.0000183) (0.0000182) Year=2015 0.956^ 0.953^ 0.952* (0.0114) (0.0115) (0.0106)
