A MULTILEVEL TEST OF RACIAL THREAT
THEORY
LISA STOLZENBERG
STEWART J. D'ALESSIO
DAVID EITLE
Florida International University
KEYWORDS: racial threat, racial segregation, benign neglect, arrest
probability, multilevel
We develop a conceptual model articulaiing the mechanisms by
which racial threat is theorized to affect social control, focusing specifically on the influence of the relative size of (he black population on the
likelihood that the police will arrest a black citizen suspected of a violent criminal offense. A multilevel analysis of 145.255 violent crimes reported to police in 182 cities during 2000 shows only qualified support
for racial threat theory. Controlling for the amount of race-specific
crime reported to police, our findings reveal that black citizens actually
have a lower probability of arrest in cities with a relatively large black
population. This finding tends to cast doubt on the validity of the racial
threat hypothesis. No evidence buttresses the claim that economic competition between whites and blacks affects arrest probabilities. However,
results show that in cities where racial segregation is more pronounced
blacks have a reduced risk of being arrested relative to whites. Crimes
involving black offenders and white victims are also more apt to result
in an arrest in cities that are racially segregated. These findings support
the view that racial segregation is an informal mechanism to circumscribe the threat of potentially volatile subordinate populations.
A fairly large and diverse body of research has accumulated that examines the relationship between racial threat and the amount of soeial eontrol that police direct at blacks (Eitle, D'Alessio and Stolzenberg. 2002;
Greenberg. Kessler and Loftin. 1985; Jacobs, 1979; Jaeobs and Britt. 1979;
Jacobs and Helms. 1997; Jacobs and O'Brien, 1998). The main drive behind this research is Bialock's (1967) racial threat theory, whieh proffers
that as the relative size of the black population grows in a given geoC R I M I N O L O G Y VOLUME 42 NUMBER 3 2004
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graphical location, whites perceive an increasing threat to their political,
economic and social ascendancy. As a result, punitiveness and social control are intensified to curtail the likelihood of political and social unrest.
The power of the state is by no means omnipotent in this regard because
the amount of social control blacks experience is predicted to decline
markedly as the black population eclipses the size of the white population
as a direct consequence of the political mobilization of black citizens. This
nonlinear relationship (positive with increasing slope) reflects the ability
of blacks to enhance their political power and influence under a situation
in which their relatively large population size affords them the opportunity
to better mobilize their limited resources for collective action (Horowitz,
1985). White elites are also more inclined to seek accommodation with
threatening groups beyond a given level of accrued political power (Quinney, 1977).
It has also been asserted that competition between whites and blacks
for jobs and other finite economic resources may engender an increase in
the amount of social control imposed on blacks (Blalock, 1967). Conflict
theorists maintain that structural changes such as economic contraction
can alter the extent of overlap between the types of occupations and jobs
that blacks occupy (called niches) and the niches of whites (Barth, 1969;
Olzak. 1990). This overlap engenders more direct competition between
blacks and whites for jobs, with whites perceiving this competition as a
zero-sum gain, with blacks replacing whites in the workforce (Jacobs and
Wood, 1999). Niche overlap can also contribute to perceptions of increased competition between the races, or what Olzak (1990) refers to as
potential competition. That is, workers become cognizant of their potential replacement by employers when the niches of blacks and whites increasingly overlap, serving to increase the perception of economic threat.
Most prior studies testing Blalock's racial threat theory rely exclusively
on ecological data. The principal strategy adopted in previous research has
been to use the relative size of the black population to predict some aggregate measure of social control, such as police force size, police expenditures or arrest rates. If the coefficient for the relative size of the black
population is positive and consequential, it is then adduced as evidence in
support of racial threat theory. If it is not substantive, it is taken as proof
against the theory. However, it is crucial to recognize that even if the coefficient for the size of the black population coefficient is sizable, this does
not necessarily validate Bialock's thesis because racial threat is treated as
having a direct effect on police behavior. It has recently been argued that
the manifestation of prejudicial attitudes and discriminatory behavior patterns are framed at the micro-level in racial threat theory (Quillian. 1995,
1996). As Quillian (1996:820) writes, "the most direct test of the [racial
threat] hypothesis would be to examine if percent black is related to an in-
A MULTILEVEL TEST OF RACIAL THREAT THEORY
675
dividual-level measure of threat and then to see if that measure of threat is
related to prejudice and discrimination."
It is essential to stress that we are by no means suggesting that ecological analyses of this type do not have legitimate investigative value, but
rather that the possibility exists that the use of aggregate data to draw inferences about the discriminatory behavior of individual police officers
may engender faulty conclusions by introducing aggregation bias. Thus, in
the absence of explicit evidence linking aggregate levels of racial threat to
individual discriminatory outcomes and in view of contrary interpretations
of area correlations, research investigating the influence of racial threat on
police discriminatory behavior at the micro-level seems warranted.
A second concern relating to prior research is whether any observed relationship between racial threat and social control can be attributed to
black crime levels. Contrary to the rationale espoused by racial threat theory, the differential crime thesis asserts that the reason why blacks are
more apt to be arrested by police in areas with a large black population is
not because of racial discrimination, but rather because blacks are more
prone than whites to participate in illegal activities. Most prior analyses
are misspecified because they neglect to include a direct measure of black
crime levels. This omission creates a dilemma in interpreting the coefficient estimate for the racial threat variable. The omitted black crime variable is almost certainly correlated with both the relative size of the black
population and levels of social control, so the coefficient estimated for the
relative size of the black population is potentially biased. For example, if
the arrest rate for black citizens is observed to be higher in a city with a
large black population, one cannot determine with any clear empirical certainty whether this relationship is due to police bias or whether it simply
results from black crime levels being higher in these cities. As Myers
(1990:389) points out. "the absence of measures of actual [black] criminality render this [the discriminatory use of the arrest sanction] impossible."
The primary reason for the failure to consider the confounding effect of
race-specific crime in prior research is because data on race-specific crime
levels are not contained in the Uniform Crime Reports (UCR). Without
such information, most investigators have relied on race-specific arrest
rates or the overall crime rate as proxy measures of black crime levels.
However, there are serious problems with the use of these types of measures. To illustrate, a recent study by D'AIessio and Stolzenberg (2003)
challenges the long-held assumption that race-specific arrest data can be
used as a reasonable proxy for race-specific criminal behavior. Using
crime data from the National Incident-Based Reporting System (NIBRS).
which provides information on the offender's race for those crimes that
the offender comes into direct contact with the victim, they show that the
odds of arrest are significantly greater for whites than blacks for robbery,
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STOLZENBERG, D'ALESSIO AND EITLE
aggravated assault and simple assault. These findings suggest that caution
is warranted in the pervasive practice of employing race-specific arrest
rates as a surrogate measure of race-specific criminal offending, at least for
the crimes of robbery and assault. The use of the crime rate as a surrogate
measure of black crime levels is also problematic. Because the overall
crime rate includes crimes committed by blacks, whites and other racial/ethnic groups, it is exceedingly difficult to ascertain whether any relationship evinced between the size of the black population and the amount
of social control imposed on black citizens by the police resulted from racial discrimination.
A third issue relates to the possibility that racial segregation may act as
a mechanism of control by placating the racial threat engendered by a
large black population (Blauner, 2001; Spitzer. 1975). As Spitzer
(1975:649) writes, the state responds to "threatening populations without
individualized manipulation" by a "policy of containment or compartmentalization" which involves "the geographic segregation of large populations." Additionally, as racial segregation increases in a city, black-onbiack crime becomes more prevalent than black-on-white crime (Liska
and Chamlin, 1984). This change in the racial make-up of the offendervictim dyad has two consequences. First, the reduction of black-on-white
crime helps to alleviate pressure on the police by whites to do something
about crimes perpetrated by blacks. Second, the change in the racial
make-up of the offender-victim dyad attenuates the severity of criminal
sanctions imposed on blacks because the state views crimes perpetrated
against blacks as less deserving of official action, or what Liska and Chamlin (1984) refer to as benign neglect. Consistent with the expectation of
benign neglect, Liska, Chamlin and Reed (1985) report that a high percentage of nonwhites and a low level of segregation elevated the certainty
of arrest for both nonwhite and white citizens in seventy-seven U.S. cities.
Other studies reach similar conclusions (Liska and Chamlin, 1984; Liska,
1992). Based on this work, it can be theorized that the effects of racial
threat are influenced by racial segregation, with the relative size of the
black population having an amplified effect in cities with low-levels of racial segregation. However, while it is often assumed that racial segregation
serves as an alternative form of social control that helps to placate the potential threat posed by a large minority population, it is also plausible that
such racial separation may increase awareness of group differences and
fear of the minority group, thereby amplifying pressure for police action
against the minority group (Liska, 1992).
The current study represents a modest attempt to advance the literature
by undertaking a multilevel test of racial threat theory. After merging data
from the National Incident-Based Reporting System (NIBRS) with information contained in the census, we examine whether racial composition
A MULTILEVEL TEST OF RACIAL THREAT THEORY
677
conditions the relationship between an offender's race and the probability
of arrest for 145.255 violent crime incidents reported to police in 182 U.S.
cities during 2(XX).' Drawing from the theoretical rationale outlined by
Quillian (1995, 1996), we theorize that racial discrimination by police officers should not be determined by aggregate levels of racial threat or by the
race of the criminal offender. Rather the key determinate in predicting
whether the police make an arrest for a given reported criminal offense is
the interaction between an offender's race and aggregate levels of racial
composition. That is, relative to race-specific violation frequency as reported by crime victims, the police should be more inclined to arrest
blacks suspected of committing crimes in cities where racial threat is pervasive, controlling for offense severity and other micro- and macro-level
factors. The salience of this cross-level interaction hinges on the assumption that as the size of the black population grows progressively larger, racial discrimination directed against black citizens by police officers becomes more pervasive.
Although not a direct test of racial threat theory, there is some evidence that neighborhood context influences the willingness of police to
arrest and use coercive authority. Using data drawn from 24 police agencies, Smith (1987) reports that the police are more apt to arrest criminal
offenders in racially mixed or minority areas. He also finds that black offenders in predominately white areas are treated less coercively than black
offenders in generally minority areas and that white offenders are treated
similarly regardless of geographical location. However, because this study
was observational, it is entirely plausible that the behavior of the police
officers may have been modified to some degree by the presence of the
observers. Nevertheless. Smith's research is noteworthy because it highlights the need for multilevel studies in which police actions are nested
within differing social contexts.
Others have also considered the possibility thai police behavior may
vary dramatically across differing social contexts. Klinger (1997) for example articulates a systematic theory of how and why police behavior vacillates across physical space. After a comprehensive survey of the relevant
literature, he reaches the conclusion that crime levels within patrol districts have a profound effect on the manner in which police officers enforce the law. Basically, a high level of crime in a small geographical area
is theorized to compromise the ability of both the state and the local populace to regulate criminal behavior. This inability in turn allows for the further escalation of criminal activity in these areas.
1. Although an individual is not typically classified as an offender until he or she is
convicted in a criminal court, we use Ihe term offender throughout Ihe manuscript
to describe the criminal suspect for ease of understanding.
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STOLZENBERG, D ALESSIO AND EITLE
In sum, then, we believe that if the theorized relationship between the
relative size of the black population and aggregate measures of social control can be confirmed using multilevel data with direct measures of black
crime and racial segregation, racial threat theory will garner considerably
more empirical support.
DATA
The micro-level data were obtained from the NIBRS for 182 cities in
eighteen states during 2000." All the 182 cities have an overall population
of at least 25.(K10 people. The NIBRS data are uniquely suited for our purposes because it is possible to link a reported crime incident to a subsequent arrest that was heretofore not feasible with the UCR. The ability to
merge reported crime incident data with arrest data affords us the ability
to calculate the actual probability of arrest by race for crimes communicated to the police where the victim was able to identify the race of the offender/ The NIBRS data are also useful for our intentions because information on micro-level factors associated with a crime incident are
provided along with geocode information that identifies the city where
each crime incident occurred. These geographic identifiers are employed
to match crime incidents with our racial threat measure and with the other
macro-level variables drawn from the 2000 census that are theorized to be
associated with the probabihty of arrest.
2. The eighteen stales include Colorado. Connecticut. Iowa. Idaho, Kansas, Kentucky,
Massachusetts. Michigan, North Dakota. Nebraska. Ohio, South Carolina. Tennessee. Texas. Utah. Virginia. Vermont and West Virginia.
3. NIBRS represents the nexl generation of crime data and it is designed lo replace
the nearly 70-year-old UCR, Its purpose is "to enhance the quantity, quality, and
timeliness of crime statistical data collected by the law enforcement community and
to improve the methodology used for compiling, analyzing, auditing, and publishing
the collected crime data" (Federal Bureau of Investigation. 2(K)():1), NIBRS is
unique because rather than being restricted to a group of eight Index crimes that
the summary-based program uses, it gathers information from individual crime reports recorded by police officers at the time of the crime incident for .S7 different
criminal offenses. The information collected by police typically includes victim and
offender demographics, victim/offender relationship, time and place of occurrence.
weapon use. and victim injuries. Both the guidelines and the specifications used in
the development of NIBRS can be found in the Blueprint for the Future of the Uniform Crime Reporting Program CAbt Associates, 1985),
4. It is important to recognize that we are not attempting in this study to ascertain the
amount of crime actually perpetrated by whites and blacks. Rather we are endeavoring to discern whether racial composition influences the probability of arrest. This
is the most appropriate strategy for evaluating the discriminatory use of the arrest
satiction because the police can only act upon illegal behaviors that come to their
attention.
A MULTILEVEL TEST OE RACIAL THREAT THEORY
679
DEPENDENT VARIABLE
The dependent variable is coded as a dichotomy. Violent crimes reported to the police that resulted in an arrest are coded as one and zero
otherwise."^ We restrict our analysis to violent crimes communicated to the
police where a victim is confronted by the criminal offender and hence is
able to get some indication of the offender's race and other demographic
characteristics.'' The violent crimes include murder/nonnegligent manslaughter, kidnapping/abduction, forcible rape, forcible sodomy, sexual assault with an object, forcible fondling, robbery, aggravated assault, simple
assault and extortion/blackmail. The data are aggregated at the city-level
because this is the smallest geographical unit for which NIBRS data are
made available. The use of city-level data affords us the ability to assess
the conditioning effect of racial composition across a wide range of social
contexts and to maintain comparability with previous research in this area.
MICRO-LEVEL VARIABLES
Our variable of theoretical interest at the micro-level is the race of the
offender as reported to the police by the crime victim.^ If the criminal offender is reported to be black, he or she is coded one and zero if white.^
The offender was reported to be black in 44 percent of the crimes analyzed in this study. Although the validity of this figure relies on the victim's accuracy in identifying the alleged offender's race, the identification
5. A determination cannot be made as to whether the individual arrested by the police
was the same person identified by the victim as the perpetrator of the crime or
whether the individual was actually guilty of the crime. Nevertheless, our inability
to determine these facts has little impact on our conclusions so long as the race of
the offender identified by the crime victim is the same as the race of the individual
arrested by police. In approximately 99 percent of the crime incidents analyzed in
this study, the race of the offender identified by the victim was the same as the person arrested by the police.
6. We excluded from the analysis crime incidents in which there were multiple offenders and/or victims. It was necessary to exclude these cases because it is difficult to
estimate a probability of arrest in Incidents where there were two or more offenders
and/or victims and because there could be white and black offenders involved in the
same crime incident.
7. To identify the race of the offender, the police may have used Information from one
or more witnesses to the crime.
H. Criminal offenders and victims that arc Asian/Pacific Islanders and American Indians/Alaskan Natives were excluded from the study. Victims reported that these
ethnic groups comprised less than one percent of all criminal offenders in 2000.
These ethnic groups also represented less than one percent of crime victims. Hispanics are included in either the white or black racial categories for reported
crimes. Whether an offender is Hispanic can only determined at the point of arrest
in the NIBRS data set.
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STOLZENBERG. D'ALESSIO AND EITLE
of an offender's racial characteristics by a victim is considered to be extremely accurate (Hindelang, 1981). In addition, our research seeks to account for other factors that might reasonably be expected to be related to
the probability of arrest. These micro-level variables encompass criminal
offense characteristics, criminal offender characteristics and victim characteristics. Criminal offense characteristics account for whether Ihe victim
suffered a serious injury during the course of the crime, whether a deadly
weapon was used in the crime and whether the offender perpetrated less
serious ancillary crimes during the commission of the primary offense.
Criminal offense characteristics also include whether it was a black-onwhite offense, a white-on-black offense, an intimate partner offense, the
relationship between the victim and offender and the location of the
crime.'^ The offender characteristic variables, in addition to the offender's
race, include the age of the offender, the gender of the offender and
whether the offender was under the influence of drugs and/or alcohol during the commission of the crime. The variables measuring victim characteristics include the age and gender of the crime victim. Because eaeh of
these variables is posited to affect the likelihood of arrest, including them
as statistical controls permits better estimates of racial composition effects.
The intercept, the offender's race variable and the black-on-white crime
variable are modeled as random, or allowed to vary across the cities because the aim of our study is to model how racial composition affects the
overall likelihood of arrest, the probability that black citizens will be arrested by police and the likelihood that black-on-white crimes will result in
an arrest. We also modeled all of the other micro-level variables as random at the suggestion of an anonymous reviewer, although between-city
variation for these variables is not of interest in this study. All the mierolevel variables were centered by subtracting their grand means, so that the
mean of each variable was zero across all cases. The centering of a variable
is useful because it tends to reduce multicollinearity and because it facilitates interpretation of a randomly varying variable when it becomes the
dependent variable in the between-city models. In our case, for example,
centering allows the offender's race variable to be interpreted as the average gap in arrest probabilities between black and white offenders among
the cities. This variation between cities is the outcome to be explained in
the between-city model.
9. The black-on-white and ihc white-(tn-hlack offense variables are used in Ihe analysis instead of a victim's race variable because a preliminary analysis showed that the
race of the offender and the race of the victim were correlated highly (r = .758).
This high correlation is not surprising when one considers that most violent crime is
intraracial {LaFree, 1982). Including Ihese two offender-victim variables is important because they control for interracial crime, which is of theoretical interest in this
study.
A MULTILEVEL TEST OF RACIAL THREAT THEORY
681
MACRO-LEVEL VARIABLES
All the macro-level variables are derived from the 2000 census. One of
the macro-level variables of theoretical interest is the relative size of the
black population, which is measured as the percent of the population in
each of the cities that is black. This measure necessitates the presumption
that the police are aware of and sensitive to the racial balance in the population. Our use of the relative size of the black population also aids in
maximizing comparability with previous research because this measure is
the most commonly used indicator of racial threat.'" We test the racial
threat hypothesis with a quadratic term in which the percent black population and its square are entered as predictors of the likelihood of arrest. If
the relationship is curvilinear (positive with increasing slope) as predicted
by Blalock (1967), we expect the sign of the coefficient for the black population variable and the sign of the coefficient for its square to be positive
and substantive. Additionally, because the likehhood of arrest might decrease as the size of the black population eclipses the size of the white
population, a significant negative coefficient for the quadratic term in
modeling the effect of racial composition may also be interpreted as supportive of racial threat theory.
Another contextual variable of interest is the ratio of black-to-white
unemployment rate (Jacobs and Wood, 1999; Olzak, 1992). Although most
prior studies employed broad measures of economic threat such as the
Gini index (Jacobs. 1979; Jacobs and Britt. 1979; Liska and Chamlin. 1984;
Liska et al.. 1985). it is debatable as to whether such measures are appropriate because they are not sensitive to race. As Jacobs and Helms
(1999:1503) note, prior research "ignores minorities and implies that the
economic differences between poor whites and the affluent or differences
between poor nonwhites and the affluent have identical effects on punitive
resources." If the economic threat hypothesis has any merit, the coefficient
for the ratio of black-to-white unemployment rate should be positive and
statistically significant.
A third contextual variable of theoretical interest is racial segregation,
which is measured with the white-black dissimilarity index. The dissimilarity index, which is the most commonly used measure of racial segregation
between two groups, reflects their relative distributions across neighborhoods within the same city (or metropolitan area). The dissimilarity index
U). Allhough the relative size of Ihc black population is sometimes considered an imprecise measure of political threat. Eille et al. (2002) evince a correlation of .94 between the size of the black population and the number of black citizens' casting
votes in a general election in South Carolina. This high correlalion suggests that little predictive power would be gained by substituting percent black with another indicalnr of polilica! threat.
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STOLZENBERG, D'ALESSIO AND EITLE
varies between 0 and 100 and measures the percentage of one group that
would have to move across neighborhoods to be distributed the same way
as the second group. (It is a symmetrical measure so that this interpretation can apply to either group). A dissimilarity index of 0 indicates conditions of total integration while a dissimilarity index of 100 denotes conditions of total segregation such that the members of one group are located
in completely different neighborhoods than the second group.
Prior research suggests that several other contextual factors may also
influence the probability of arrest. These variables include the crime rate,
population density, sworn police officer rate, the male population between
16 and 24, and a dummy coded variable indicating whether the city is located in the South or not. We also included factor scores from a principal
components analysis of three indicators of community disadvantage: the
dropout rate; the proportion of households headed by females with children under 18; and the percent of households receiving public assistance
income. A high score on this composite variable indicates a greater level
of community disadvantage. All the macro-level variables were grandcentered prior to their inclusion into the analysis. The means, standard deviations and definitions for the micro- and macro-level variables are presented in Table 1.
Table 1. Means, Standard Deviations and Definitions for the Variables
Mean
.41
S.D.
Offender black
.44
.50
Black-on-white crime
.10
.29
White-on-black crime
.03
.16
Multiple offenses
.05
.21
Serious victim injury
.04
.20
Deadly weapon use
.10
.30
Victim stranger
.09
.29
Intimate partner violence
.44
.50
Crime location
.66
.47
Variable
Offender arrested
,49
Definition
Coded 1 if the offender is arrested. 0
otherwise.
Coded 1 if the offender is black, 0
otherwise.
Coded 1 if the offender is black and the
victim is white. 0 otherwise.
Coded 1 if the offender is white and the
victim is black. 0 otherwise.
Coded 1 if Ihe offender reportedly
committed multiple crimes against the
victim, 0 otherwise.
Coded 1 if the victim suffered a serious
injury. 0 otherwise.
Coded 1 if the offender used a deadly
weapon, 0 otherwise.
Coded 1 if the victim is a stranger to the
offender, 0 otherwise.
Code 1 if the victim is a spouse, ex-spouse.
current or former boyfriend or girlfriend, or
current or former dating partner, 0
otherwise. Intimate partners may be
heterosexual or of the same sex.
Coded 1 if the crime occurred in a
residence, 0 otherwise.
A MULTILEVEL TEST OF RACIAL THREAT THEORY
683
Table 1. Means, Standard Deviations and Definitions for the Variables
Definition
Coded 1 if the offender is male, 0
otherwise.
Offender's age
29.5y
11.65 Age of the offender in years.
.36 Coded I if the offender is under the
Offender Substance abuse
.15
influence of alcohol or drugs, 0 otherwise.
Victim male
.47 Coded 1 if the victim is male. 0 otherwise.
.33
Victim's age
28.52
12.50 Age of the victim in years.
Percent black population
12.35
16.56 Percent of the population that is black.
Percent black population"
425.27 896.05 Percent of the population that is black
(squared).
Black-to-white unemployment 2.17
1.78 Ratio of black-to-white unemployment
rates.
Racial segregation
43.07
13.50 The white-black dissimilarity index ranges
from 0. indicating complete integration, to
100. indicating complete segregation.
Crime rate
965.70 437.04 Number of crimes reported to the police
divided by the city population and
multiplied by lO.OOO.
Population density
2,612.55 1,653.90 Population per square mile of land area.
18.99
6.18 Number of sworn police officers divided by
Police force size
the city population and multiplied by 10,000
people.
Percent male population 16-24 7.7S
4.39 Percent of the population prone to criminal
activity (ages 16-24).
Southern city
.43 A dummy variable coded 1 if the city is
located in the South, 0 otherwise. Controls
for the possibility of a southern subculture
of violence and crime.
Factor scores from Principal Component
Community disadvantage
.00
1.00
Analysis of 3 variables: a) percent of
households with public assistance income;
b) percent of the population (ages 25+) thai
never graduated from high school; and c)
percent of households headed by a single
female (ages 15-64) with children. Larger
scores indicate greater disadvantage.
Variable
Offender male
Mean
,79
S.D.
.41
RESULTS
We employ a nonlinear hierarchical modeling procedure to generate
parameter estimates because the data are multilevel and the dependent
variable is a dichotomy (Bryk. Raudenbush and Congdon, 1996). A penalized quasi-likelihood (PQL) procedure is employed to generate parameter
estimates for the binary outcome (Breslow and Clayton, 1993). There are
a number of methodological advantages for using a multilevel model to
determine whether racial composition conditions the relationship between
an offender's race and the likelihood of arrest. First, multilevel models
avoid violating the assumption of independence among observations be-
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STOLZENBERG, D'ALESSIO AND EITLE
cause they explicitly recognize the clustering of individuals within higherlevel units such as cities. Second, hierarchical models are advantageous for
estimating cross-level effects because all estimates are adjusted for the covariates. despite whether they are measured at the individual or contextual
level. Finally, hierarchical models not only partition the variance between
levels, but they also can statistically separate the variance of the individual-level parameters from sampling variance." The inability to factor out
the sampling variance when data are hierarchical results in an underestimate of the explanatory power of contextual variables.
The results for the within-city analysis are reported in Table 2. These
results show that an offender's race has a statistically discernible effect on
the likelihood of arrest. What is surprising is the direction of this relationship. It appears that whites rather than blacks have a substantially higher
probability of arrest, controlling for other factors. Similar to logistic regression, the exponential values of the estimated coefficients reported in
Table 2 are subject to the same interpretations as odd ratios. These odds
ratios are much more intuitive than the regression coefficients themselves.
The exponential value of the offender's race variable is .93 (e ™). This figure indicates that at the grand means of all the explanatory variables in the
model, the odds of arrest for a black criminal offender are slightly lower
than it is for a white offender.
The finding that whites are more apt than blacks to be arrested by the
police necessitates some elaboration. A few interpretations can account
for this result. It is possible that police view crime complaints adduced by
blacks as less deserving of their attention. Some argue that the police view
crimes reported by blacks as more of a personal and family problem than a
matter requiring official intervention (Hawkins, 1987). Additionally, when
nonwhite victims report these types of crimes to the police, they are often
unable to legitimate their complaint as a crime and pressure police to allocate resources to resolve it.
A second possibility pertains to black citizens' generally negative view
of the police. It is well known that blacks distrust the police more than
whites. For example, a recent national Gallup Poll showed that 36 percent
of black citizens, as compared to 13 percent of white citizens, have an unfavorable opinion of the local police (Gallup and Gallup. 1999). Because
police officers usually arrive too late to see the criminal offense being
committed, they are forced to rely primarily on the testimony of victims
and/or witnesses to gather the requisite evidence to make an arrest. If
11. When the outcome variable is continuous, the estimates can be used to show the
proportion of total variance in the outcome variable that exists across cities. However, when the oulcome variable is dichotomous. as in this study, the variance at the
micro-level cannot be calculated (Raudenbush, 1993).
A MULTILEVEL TEST OF RACIAL THREAT THEORY
685
black citizens are less apt to assist police in the performance of their duties, and because most crimes are intraracial rather than interracial, it
seems probable that crimes involving a black offender would be less likely
to be cleared by arrest.
A third plausible explanation for this finding stems from Donald
Black's (1976) seminal work on the behavior of law and the social control
of crime. Black argues that the application of the law and the quality of
the response of criminal justice actors is influenced by the social structure
of the case —the social location of the actors (namely the victim and the
offender) in the social structure. Central to our findings is Black's claim
that the likelihood that the law will be mobilized successfully is related to
the extent that the parties involved in a criminal case are integrated in the
social structure. Black refers to this concept as morphology. Because
blacks have lower levels of participation in social institutions (education,
employment, marital status), social control agents should be less inclined
to treat offenses involving marginalized people as seriously as they would
offenses involving more integrated people (Black, 1995). Although our
analysis was not designed to test Black's thesis specifically, we feel that
our finding that whites rather than blacks have a higher probability of arrest is consistent with his thesis.
Another noteworthy effect in Table 2 is that the police are less inclined
to arrest a white who commits a violent crime against a black citizen. Although white-on-black crimes are relatively rare occurrences (representing
only about 3 percent of all violent crime), this finding is still intriguing
nonetheless because it is consistent with the expectations of benign neglect. That is, crimes perpetrated against blacks are less deserving of official action, particularly when those crimes are committed by whites. For
intimate partner violence incidents, the probability of arrest is magnified.'^
Whether the victim suffered serious injury also impacts the likelihood of
arrest. The odds of arrest are 1.4 times as large when the offender seriously injures the victim. The coefficient for the deadly weapon variable is
also consequential in this equation. An arrest is more apt to transpire in
violent crimes where an offender uses a deadly weapon. The effects of
several other variables are also important. Net controls, the police are
more Hkely to make an arrest in crimes that involve older victims, younger
offenders, that occur in a private residence and that include offenders under the influence of alcohol and/or drugs.
12. Intimate partner violence is defined as the actual or threatened physical or sexual
violence or psychological and emotional abuse directed toward a spouse, ex-spouse,
current or former boyfriend or girlfriend, or current or former dating partner (Saltzmanetal.. 1999).
686
STOLZENBERG. D'ALESSIO AND EITLE
Finally, the within-city results displayed in Table 2 indicate that the police are not more disposed to effectuate an arrest for violent crimes involving black offenders and white victims. These findings run counter to much
of the literature suggesting that blacks who victimize whites are more
likely to be sanctioned severely by the state because of the elevated status
of white victims in our society. In contrast, the odds of a black offender
being arrested for victimizing a white are not substantially higher than for
any other of the other victim/offender racial combinations.
Our results also show that the estimated between-city variance for the
intercept slope ( T= .994, p < .001) and for the offender's race slope ( T.024, p < .001) are large and statistically significant. These finding suggests
that a substantive amount of variation still exists among the cities regarding the likelihood that the police will effectuate an arrest for a violent offense and that an offender's race influences the probability of arrest. Although the micro-level effect of the black-on-white crime variable is weak
as reported in Table 2, the estimated variance of the black-on-white crime
slope is noteworthy ( T - .028, p < .05). This finding indicates that there is
ample variation among the cities regarding the probability of arrest of
crimes involving black offenders and white victims. However, while there
is variation among the cities in the probability that black-on-white crimes
will result in an arrest, these differences "average out" across all the cities
in the sample. This is why the coefficient for the black-on-white variable
reported in Table 2 is not sizable. If we had found that the estimated variance of the black-on-white crime slope was not statistically different from
zero, there would be no need to undertake the macro-level analysis because there would be no major difference in the treatment of black-onwhite crime by the police across the cities to explain.
The purpose of the between-city model is to use contextual variables to
explain why this variation exists. For example, do any of the contextual
variables impact the likelihood of arrest across the cities in the sample?
Does the relative size of the black population or any of the other contextual variables such as racial segregation condition the relationship between
an offender's race and the likelihood of arrest? What contextual factors
predict the probability of arrest for crimes involving a black offender and
white victim? The between city-level model addresses these questions."
13. Although our within-city model has several other micro-level variables that could
be subjected to the between-city analyses, we did not undertake Ihese additional
analyses because they are not relevant for investigating the relationship between racial composition and the probability of arrest.
A MULTILEVEL TEST OE RACIAL THREAT THEORY
687
The results for the between-city model are reported in Table 3.''* Model
1 of Table 3 displays the results pertaining to whether the contextual variables influence the overall probability of arrest, the likelihood that black
offenders will be arrested and the probability that black-on-white crimes
will result in an arrest. Although not specifically relevant for testing racial
threat theory, two contextual variables have some relevancy in predicting
the overall probability of arrest. In cities with a large black population and
pronounced racial segregation, the police are less likely to effectuate an
arrest for a violent crime. None of the other contextual variables show any
predictive power in this equation.
Table 2. Within-City Probability of Arrest Results
Outcome Predictor
Intercept
Offender black
Black-on-white crime
WhilL'-on-black crime
Multiple offenses
Serious victim injury
Deadly weapon use
Victim stranger
Intimate partner violence
Crime kx:ation
Offender male
Offender's age
Offender substance abuse
Victim male
Victim's ago
><.O5: "/7<.01:"><.(H) 1 {two-lailed tests)
Coefficient
-.107
-.074""
.049
-.117"
.048
.359'"
.202'"
-.033
.598'"
.166""
-.005
-.007'"
. 5 2 5 •••
.021
.01 r"
Standard Error
.075
.021
.027
.045
.053
.045
.045
.044
.()3S
.030
.022
.(H)l
.035
.021
.(Kll
The results for predicting the offender's race-arrest slope are also reported in Model 1 of Table 3. Although the relative size of the black population is theorized to be associated positively with the likelihood of arrest
of black citizens as a result of a racial composition effect, our results fail to
bear this prediction out. Accounting for the amount of race-specific crime
reported to the police and a variety of other contextual factors, we find no
evidence that blacks have a higher proclivity of being arrested in cities
14. We calculated variance inflation factors to determine the exlent lo which any independent variable was a linear combination of two or more other independent variables. All ihe VIFs were well below 3, except for the squared percent black population variable. However, because ihe results produced wilh the squared percent
black population variable are similar to those without this variable, the excessive
collinearity caused by the inclusion of this variable does not appear to have impacted our results adversely.
688
STOLZENBERG. D'ALESSIO AND EITLE
with a relatively large black population. Such a finding is salient because it
tends to cast doubt on racial threat theory. Racial threat theory predicts a
positive relationship between the relative size of the black population and
levels of social control. Social control is expected to increase as the black
population grows.
Visual inspection of Model 1 in Table 3 also reveals that there is a statistically discernible effect of the dissimilarity index on the black-white arrest differential. This effect is analogous to an interaction effect in a traditional regression analysis. A black individual suspected of perpetrating a
criminal offense in a city with a high level of racial segregation has a significantly lower probability of being arrested by police than does a similarly situated offender who is white. Furthermore, when we examine cities
that are relatively integrated the converse is true: black offenders have a
significantly higher probability of arrest than do white offenders. This
phenomenon is graphically illustrated in Figure 1. Figure 1 shows that in
integrated cities blacks are more likely than whites to be arrested, whereas
in racially segregated cities blacks have a reduced risk of apprehension.
This effect, which withstands controls for both micro- and macro-level
variables, is compelling because it suggests that racial segregation may be
acting as an informal mechanism of control.
Figure 1.
Expected Probability of Arrest for Black and White Offenders by Racial Segregation
Expected Probability of Arrest
0.60
— Black Offenders -^White Offenders)
0.55 •
0,50
0.45
0.40
15
20
Low
25
30
35
40
45
50
Racial Segregation
Note: All other micro-level and city-level variables are grand centered.
55
60
65
70
Higfi
A MULTILEVEL TEST OF RACIAL THREAT THEORY
689
Our analysis also demonstrates that the effect of police force size on the
black-white arrest differential is noteworthy. That is, as the number of
sworn police officers rises in a city, the probability of a black offender being arrested increases as compared to a white offender, net controls for
relevant micro- and macro-level variables. Model 1 in Table 3 also shows
that the effect of the black-to-white unemployment measure is trivial in
magnitude and not of substantive importance. As economic competition
increases between whites and blacks, the police are not any more likely to
arrest black citizens. Theoretical work by Blalock (1967) suggests that
economic competition between blacks and whites can lead to an intensification of the amount of informal social control directed at blacks. We find
little support for this argument. In fact, the ratio of black-to-white unemployment has trivial effects in all of the estimated equations.
Given that prior research reports that a victim's race is often important
in determining severity of criminal sanction, we felt it prudent to assess
whether a criminal offender's race interacts with a victim's race in predicting the probability of arrest. It is argued rather frequently that when
blacks victimize whites, the high value attached to a white victim and the
racial fears of authorities engender severe treatment (Black, 1976). The
race of the victim is often reported to play a salient role in the punishment
of criminal offenders (see Pratt. 1998 for a review). Model 1 in Table 3
also shows the effect of the contextual factors on the likelihood of arrest
for black-on-white crimes. Racial segregation is the only variable that
shows any predictive power in this equation. The police are more disposed
to effectuate an arrest for crimes involving black offenders and white victims in cities that are racially segregated. None of the other contextual
variables show any predictive power in this model.
We next introduced a squared term for percent black population into
each of the three equations. The results, which are presented in Model 2 of
Table 3, closely mirror the findings generated in Model L The effects of
each of the variables of interest, or lack thereof, remain relatively stable
across the three equations. Again, in contrast to expectations of racial
threat theory, the effects of the black population variable (negative) and
its squared term (positive) on the overall probability of arrest and on the
black-white arrest differential are significant. The positive squared term
indicates that the negative effect of the size of the black population on the
overall probability of arrest and on the probability of arrest for a black offender begins to decelerate once the black population becomes exceedingly large in a city. Figure 2 graphically depicts the nonlinear relationship
between the relative size of the black population and the probability of arrest for a black offender.
The only substantive changes in Model 2 are that the dissimilarity index
is no longer salient in predicting the overall probability of arrest, whereas
690
STOLZENBERG, D'ALESSIO AND EITLE
the police force size is now significant, when the squared term for percent
black population is added to the equation. However, the effects of racial
segregation on the black-white arrest differential and the black offenderwhite victim differential continue to remain large in magnitude and are of
substantive importance. Additionally, with the exception of the crime rate
variable and the police force size variable in the black-white arrest differential equation, the estimated effects of the other macro-level control
variables remain small and are not of import. The effects of the microlevel variables are also unchanged in Model 2.
Figure 2.
Expected Probability of Arrest for Black Offenders by Percent Black Population
Expected Probability of Arrest for Black Offenders
0.60
0.50
0,40
0.30
0.20
10%
20%
30%
40%
50%
60%
70%
80%
Percent Black Population
Note: All other micro-level and city-level variables are grand centered.
The random parameter variances for the equations estimated in Model
2 of Table 3 show that the estimated variance for the intercept slope ( T.860, p < .001) is still sizeable and statistically significant. This finding
denotes that a substantive amount of between-city variation still exists
among the cities in regards to predicting the overall probability of arrest.
Other contextual variables may help account for this variation. In contrast,
with the addition of the macro-level variables, the estimated parameter
variance for the offender's race slope ( T- .011, p > .05) and the black
offender-white victim slope (T= .025, p > .05), are no longer statistically
significant. These findings imply that we have accounted for most of the
A MULTILEVEL TEST OF RACIAL THREAT THEORY
691
Table 3. Between-City Probability of Arrest Results
Outcome Predictor
Arrest probability differential
Intercept
Percent black population
Percent black population"
Black-to-white unemployment
Racial segregation
Crime rate
Population density
Police foree size
Male population 16-24
Southern city
Community disadvantage
Black-white arrest differential
intercept
Percent black population
Percent black population"
Black-to-white unemployment
Racial segregation
Crime rate
Population density
Police force size
Male population 16-24
Southern city
Community disadvantage
Black-on-white arrest differential
Intercept
Pereent black population
Percent black population"
Black-to-white unemployment
Racial segregation
Crime rate
Population density
Police force size
Male population 16-24
Southern city
Community disadvantage
White-on-black crime
Multiple offenses
Serious victim injury
Deadly weapon use
Victim stranger
Intimate partner violence
Crime location
Offender male
Offender's age
Offender substance abuse
Victim male
Victim's age
Coeff
Model 1
;itd Error
-.092
-.014"
.071
.005
-
-
.026
-.013'
-.022e-2
-.020e-3
.020
-.001
-.114
.124
.037
.006
.018e-2
.O38e-3
.013
-.029
-.O53e-2
-.021
-.005"
-.096e-3
.0I2e-3
,0()S'
-.002
-.008
-.036
,026
.164e-2
,002
,079e-2
—
,008
.005'
,036
.240e-2
—
.030
.003
.087e-3
,020e-3
.005
.009
.069
.042
.046
.053
.045
.044
.044
.038
.031
.022
.001
.035
.021
.001
.n8e-3
-.OO6e-3
-.004
-.001
.064
-.021
-.128"
.042
, 3 6 5 •"•
,203""
-.030
.592"'
.170"'
.001
-.007'"
.520'"
.023
.011'"
'p < .05; "p < .01; '"p < ,001 (two-tailed tests)
.015
.166
.092
.022
.002
,059e-3
.014e-3
,004
.007
.046
.028
Model 2
Coeff
Std Error
-,083
-,040"
.043e-2'
.026
-.009
-,O31e'2
-.021e-3
.027'
.001
-.044
.118
.070
,014
.022e-2
.037
.006
.018e-2
.O37e-3
.014
.015
.173
.091
-.004
-,010'
,15Oe-3'
-.022
-.004'
-,134e-3"
,OO9e-3
,010"
-,001
,020
-.034
.029
.005
.067e-3
.022
,002
.060e-3
.014e-3
.004
.007
,048
.028
-,004
-.001
.043e-3
,009
.006'
.117e-3
-,(K)6e-3
-.003
-,001
,065
-.026
-.138"
.044
.366"'
.205'"'
-,028
.039
.007
.094e-3
.030
,003
.090e-3
.020e-3
.006
.009
,075
,043
,045
.053
.045
.045
.044
.038
.031
,022
,001
,035
.021
.001
.59r"
.172'"
.001
-.007"'
.516'"
.022
,011"'
692
STOLZENBERG, D'ALESSIO AND EITLE
variation in both the black-white offender arrest differential and the black
offender-white victim arrest differential among the cities.'^
CONCLUSION
A sizable body of quantitative research on racial threat and the police
has accrued in recent years. A common feature of these studies is that the
relationship between the relative size of the black population and the
amount of social control directed at black citizens by police was assessed
at the macro-level. In contrast to previous research, the present analysis
used micro-level data drawn from the NIBRS. in conjunction with macrolevel city data, to undertake a multilevel test of Blalock's racial threat theory. We proffered in this paper that an interesting way to test racial threat
theory would be to analyze multilevel data in which the actions of police
officers are nested within specific geographical locations with varying degrees of racial composition. The basic argument is that racial composition
should not have a direct effect on the arrest sanction, but rather should
condition the relationship between an offender's race and the probability
of arrest. That is, in cities where racial threat is pronounced, police officers
should be more apt to arrest black citizens suspected of committing crimes
controlling for other relevant factors related to the likelihood of arrest.
We also attempted to discern whether any pronounced differences in the
likelihood of arrest between blacks and whites or for black-on-white
crimes couid be attributed to differences in racial segregation or economic
threat among the cities.
Results generated from the multilevel analyses fail to furnish unequivocal empirical support for racial threat theory. Findings show that controlling for a number of theoretically relevant micro and macro-level factors,
the relative size of the black population has a negative rather than a positive effect on the overall probability of arrest. As the relative size of the
black population climbs in a city, the overall probability of arrest declines
markedly with a decelerating slope. Crimes involving black perpetrators
are also less apt to result in an arrest in cities with a large black population. These findings are not in accord with the tenets of racial threat theory and speak to the veracity of the claim made in previous investigations
15. To help guard against incorrecl conclusions, we reestimated all models with a sample selection control variable. This logit-bascd "hazard rate" variable accounts for
the exclusion of crime incidents with multiple offenders and/or victims (Berk. I9S3:
Hcckman, 1979). We also estimated a model whereby all the micro-level variables.
with the exception of the intercept, the offender's race variable and the blaek-onwhite crime variable, were fixed, or constrained to be the same for all the cities in
the sample. The results generated from these supplemental analyses were indistinguishable from those reported in Tables 2 and 3.
A MULTILEVEL TEST OF RACIAL THREAT THEORY
693
that state actors respond to the threat posed by a large blaek population
by relying more heavily on social control mechanisms so as to maintain the
dominant position of whites in society. In fact, the exact opposite appears
to be true. It appears that the police are less likely to take official action in
cities with a large black population. Economic threat, community disadvantage, geographical location, youthful male population levels and population density all fail to play notable roles in any of the estimated models.
Only police force size and the aggregate crime rate have any predictive
power in this regard.
Another interesting finding is that racial segregation appears to condition the relationship between an offender's race and the probability of arrest. In racially segregated cities, we find that crimes involving black offenders are much less likely to result in an arrest. This effect persists
despite the inclusion of both micro-level and macro-level predictors of arrest likelihood. Conversely, in racially integrated cities, police are more
apt to effectuate an arrest for crimes involving black offenders. Furthermore, in cities that tend to have high levels of racial segregation, the police
are more inclined to effectuate an arrest for crimes that involve a black offender and a white victim. These findings buttress the argument that racial
segregation acts as an instrument of state control whereby problem populations are managed passively without the need for an excessive reliance
on the police.
Of course, a question will always remain as to whether the evidence
presented here is enough to evaluate racial threat theory, because our results cannot be extrapolated beyond the specific offenses examined. If
drug offenses or other victimless types of crimes were analyzed in this
study, our results might have been radically different. For example, work
by Parker and Auerhahn (1998) shows that blacks suspected of perpetrating drug offenses pose a serious threat to established interests and, as consequence, are more prone to be punished harshly by the state. If we had
been able to analyze drug offenses, the effect of racial composition on the
likelihood of arrest of blacks might have been more substantive, independent of the level of racial segregation. However, it seems unlikely such
analyses will be conducted any time in the near future because drug offenses and other types of victimless crimes are not usually reported to the
police.
Our cross-sectional data are also ill-suited for determining whether the
effect of raeial composition is changing or has changed over time. Thus,
events occurring in society may cause the influence of racial threat on the
arrest sanction to vary over time. Proper investigation of this issue would
necessitate a reliance on longitudinal data. Longitudinal research using
data drawn from NIBRS should be a high priority when the requisite data
become more readily available.
694
STOLZENBERG. D'ALESSIO AND EITLE
Our findings are also subject to measurement criticisms. Although the
salience of the size of the black population on police activities has been
reported routinely in the literature, the arrest sanction is only one possible
measure of social control. Thus, we cannot claim to have fully tested racial
threat theory because a comprehensive test would require data on other
forms of social control (Tolnay and Beck. 1995).
Finally, despite extensive controls for offender and contextual determinants of arrest probability, other salient factors may remain inadequately
measured or even unspecified. For instance, although our analysis shows
that the relative size of the black population and racial segregation both
condition the relationship between an offender's race and the probability
of arrest, the precise mechanisms linking these variables still remain elusive. It is conceivable that police officers' perceptions of the racial composition of the areas that they patrol influence their behavior. For example,
as the size of the black population grows in a city, police may increasingly
perceive crime victims as less deserving of their attention. As a result of
this "deliberate indifference," arrests would be less likely to occur. However, because of data constraints, we are unable to include any information on the perception of racial threat among law enforcement officers in
our study. As a consequence, such theorizing remains merely speculative
in the absence of attitudinal survey data. Future researchers may rectify
this problem, but new data sets with this type of information would need
to be identified.
Despite these shortcomings, the data we have assembled allow us to
make inferences that are useful and important regarding racial threat theory. The multilevel data presented here challenges the assertion that police are more likely to effectuate an arrest in cities with a large black population. Because the relative size of the black population has a negative
rather than a positive effect on the probability of arrest and on the probability that black citizens will be arrested by police does not necessarily
imply that systematic testing of racial threat theory should be abandoned.
There are several profitable avenues for future research. This study has
illustrated the utility of combining micro- and macro-level data to test racial threat theory. Such multilevel data are crucial, as in the present case,
when one wishes to test hypotheses asserting that contextual factors influence an individual's behavior or attitudes. Researchers may wish to undertake additional tests of racial threat theory within a multilevel framework.
We believe we have made a modest beginning in this direction, but more
work is needed.
Another promising line of research is to investigate whether racial
threat manifests itself at the neighborhood rather than at the city level.
KHnger (1997:299) goes even further in arguing that patrol districts should
be used when studying police behavior because neighborhoods are not in-
A MULTILEVEL TEST OF RACIAL THREAT THEORY
695
dependent spatial entities but rather are nested within specific neighborhoods. However, most analysts will probably find it difficult to obtain the
necessary data on police behavior at either the neighborhood or patrol district level across a large number of cities. Nevertheless, such analyses may
still yield empirical support for racial threat theory.
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A MULTILEVEL TEST OF RACIAL THREAT THEORY
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Lisa Stolzenberg is associate professor of criminal justice at Florida International University. She received her B.A. in criminal justice from the
University of Florida and her M.S. and Ph.D. in criminology from Florida
State University. Her work has appeared in a variety of scholarly journals,
including the American Sociological Review, Social Forces, Social Problems, Criminology, Journal of Criminal Law & Criminology and Justice
Quarterly. Her research interests are in exploring all aspects related to the
criminal event. Please direct all correspondence concerning this article to
Lisa Stolzenberg, School of Policy and Management, Florida International
University, University Park Campus—FCA 260A, Miami, FL 33199,
email: stolzenb@fiu.edu.
Stewart J. D'Alessio is associate professor of criminal justice at Florida
international University. He received his B.A. in history from Stetson
University and his M.S. and Ph.D. in criminology from Florida State University. His current research analyzes data drawn from the National Incident-Based Reporting System (NIBRS).
David Eitle is assistant professor of criminal justice at Florida International University. His current research interests include examining the influence of school factors on student deviance, the effects of the social
stratification of criminal justice organizations and the relationship between
cumulative exposure to adversity and young adult crime.