1 Introduction

The relationship between hate group activity and hate crime is theoretically ambiguous. Hate groups may incite criminal or violent behavior in support of their beliefs. On the other hand, meetings and protests may serve as a way for members to orally vent their frustrations, thereby reducing the likelihood of criminal or violent acts. Hate groups may also protect their members from future bias-based violence.

The Southern Poverty Law Center (SPLC), an authority on hate group activity, declared that the number of active white supremacist hate group chapters in the United States increased by 33 %, from 350 to 488, between 1997 and 2007.Footnote 1 Yet, over the same period, the number of hate crimes recorded in the United States fell by 6.1 %, from 8,443 to 7,945. Figure 1 depicts the slow and steady increase in the total number of active white supremacist chapters and the decline in hate crimes reported across the United States.

Fig. 1
figure 1

Number of hate crimes and number of Ku Klux Klan, Neo-Nazi, Skinhead, and Christian Identity Chapters in the US: 1997–2007 (Sources: Southern Poverty Law Center 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008 and Federal Bureau of Investigation various years)

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A small number of empirical studies have investigated potential sources of hate crimes. Yet all but one fail to include a measure of hate group activity. McDevitt and Levin (1993) use Boston data to discover that many hate crimes involve violence directed at dissimilar others moving into a previously segregated area. Medoff (1999), in a cross-sectional state estimation, finds that market wages, mean age, and law enforcement are correlated with hate crime activity, but urbanization, occupational status, and social mobility are not. Gale et al. (2002) use a panel of 37 states from 1992 through 1995 and find that hate crime rates are negatively correlated with law enforcement expenditures and positively associated with unemployment rates, abuse rates, and the parity of income between blacks and whites. Ryan and Leeson (2011) use state-level panel data from 2002 through 2008 to find that unemployment and poverty are strongly associated with more hate crime, whereas demographics and, most notably, the number of hate groups are not. If hate groups do not actually influence hate crime, then resources devoted to tracking and eradicating hate groups may not be a productive way for law enforcement to address bias-based crime.

However, this counterintuitive result that hate groups are not related to hate crimes may be due to Ryan and Leeson’s methodology and not the underlying relationship. First, Ryan and Leeson estimate the hate group-hate crime relationship using the number of chapters at the state level even though hate group chapters are often local phenomena that occur on a small scale. Second, even if hate group members are not committing crimes, their presence may signal to local community members that a particular bias is acceptable. Third, Ryan and Leeson include unclassified hate groups. This “Other” category includes organizations whose members hold biased views but do not advocate violent acts against the targets of their bias.

Addressing these three weaknesses by using US county-level panel data from 1997 through 2007 and controlling for county fixed effects, I find that hate crimes are 19.1 % more likely to occur in counties with active white supremacist group chapters. Excluding hate crimes listed as antiwhite, the presence of one or more white supremacist chapters is associated with a 19.7 % to 24 % higher rate of hate crimes and a 22 % to 25 % higher rate of hate crimes committed by white perpetrators. I am also able to reject three alternative hypotheses that are consistent with these positive correlations: (1) that white supremacist groups are symptomatic of the overall bias-based antagonism in a county; (2) that the presence of one or more active white supremacist group chapters is correlated with some idiosyncratic factor that influences hate crime rates for that county-year; and (3) that white supremacist groups form as protection against recent increases in hate crimes perpetrated by nonwhites or listed as antiwhite.

Section 2 presents a historical look at the evolution of hate crime legislation in the United States. Section 3 discusses hate groups. Section 4 lays out the estimation methodology. Sections 5 and 6 discuss the data and the estimated relationship between white supremacist chapters and hate crimes. Section 7 investigates alternative hypotheses. Section 8 offers concluding remarks.

2 Hate crime

Biased violence, motivated by racism, xenophobia, anti-Semitism, and other prejudices, has been documented throughout history from the Old Testament description of the genocides of Amalekites and Midianites to more recent ethnic and religious-based violence in Bosnia and Sudan. The United States practice of categorizing certain violent activity directed at individuals based on their ethnic or social characteristics as “hate crimes,” however, is a recent phenomenon. Jenness and Grattet (2001) suggest that support for the idea of treating bias-motivated violence as a unique type of crime was born out of the combination of the modern civil rights movement and the crime victims’ rights movement.

In the 1960s and 1970s, civil rights groups sought ways to reduce violence based on race, ethnicity, religion or other differences. Some civil rights organizations, such as the Anti-Defamation League of B’nai B’rith (ADL) and the SPLC, began gathering information on the characteristics and locations of bias-motivated violence. During the same period, the victims’ rights movement developed in response to the Warren Court’s expansion of defendants’ rights (Weed 1995; Maroney 1998). The victims’ rights movement brought attention to the direct trauma resulting from the violence and the psychological “abuse suffered at the hands of police, prosecutors, social medical service providers and judges” (Jenness and Grattet 2001: 27). Led by Wisconsin in 1981, states began passing victims’ rights legislation. By 1989, 42 states had passed victims’ rights bills (Weed 1995).

Following the victims’ rights movement, civil rights groups began seeking specific legal redress. Beginning with Washington and Oregon in 1981, states began enacting hate crime legislation that criminalized violence directed at groups based on their racial, ethnic, religious, and other characteristics. The federal response culminated in the 1990 passage of the Federal Hate Crime Statistics Act. The law defines hate crimes as criminal incidents that are at least partially directed against the victims’ race, religion, sexual orientation, or ethnicity/nationality. The law also instructs the FBI to collect and report hate crime data from agencies actively documenting and willing to report hate crime statistics voluntarily.Footnote 2

Differences in how agencies define and report crime, and particularly hate crime, are problematic in any empirical study. Although hate crime documentation has improved, there are still serious problems associated with crime statistics (Gale et al. 2002). DiIulio (1996) identifies two potentially severe measurement errors in crime data: underreporting by victims and misreporting by law enforcement agencies. By comparing the Uniform Crime Report to other sources of crime data, Besci (1999) shows that wide variation exists between crime data sources. Furthermore, Grove et al. (1985) find that reported crime rates are closer to the actual crime rates for less ambiguous crimes, such as homicide, than for more ambiguous crimes, such as aggravated assault.

The core concept of a hate crime is fuzzy and therefore can make classification difficult (Jacobs and Potter 1998). However, Martin (1995, 1996) and Boyd et al. (1996) find that the process is less error-prone than is suggested by Jacob and Potter. “[F]ar from finding it problematic to interpret and classify specific incidents, police detectives engage in certain routine practices in order to determine the hate-related status of an incident” (Boyd et al. 1996: 821). Unfortunately, Boyd et al. (1996) also show that reporting methods differ across jurisdictions, causing comparisons across divisions to be suspect. This article looks only at changes in the hate crime rate within each county, which does not eliminate any ambiguity and subjectivity that may occur over time within a given agency or across agencies at the sub-county level. Thus, any empirical results must be interpreted through a critical lens.

3 Hate groups

The Southern Poverty Law Center (2010) defines a hate group as an organization having “beliefs or practices that attack or malign an entire class of people, typically for their immutable characteristics” (http://www.splcenter.org/get-informed/hate-map). White supremacists believe that race is a central characteristic that encompasses behavioral and cultural components and that whites are responsible for all of the advances realized in western civilization. White supremacists view recent changes in western culture, with its greater emphasis on multicultural ideas, as threatening the future of western society (Ezekiel 1995). Therefore, white supremacist organizations battle to reclaim the traditional lifestyle of earlier white generations (Ezekiel 1995; Bushart et al. 2000; Ferber 2000). For example, racist skinhead recruiters look for areas where the status quo is threatened and then seek out individuals suffering psychological stress or those experiencing cultural anomie (Messner and Rosenfeld 1994; Wooden and Blazak 2000). The skinheads will then attack the person least like them who is perceived to be threatening the status quo as a way to build rapport with potential future members (Blazak 2001). If this is correct, hate crime rates should be higher in counties where white supremacist groups are present.

Ezekiel (1995) classifies hate group members into four categories based on their degrees of involvement and self-control. Those most deeply involved with high levels of self-control are leaders and lieutenants. These core members keep the group alive and are rarely involved in violence directly. The lieutenants reinforce these ideas with codes of secrecy and dress. They will sacrifice a great deal to avoid seeming disloyal.

Ordinary members make up the largest subset of the group. These members have little desire to harm nonmembers. Ordinary members often drop out when police begin investigating group activities.

The third type of member is deeply involved but lacks self-control: the loose cannons. Highly unpredictable, these individual always are the first to act. Although leaders often disavow the behavior of loose cannons, their actions nevertheless may make ordinary members feel as though they are part of a highly important cause.

The last type of member is the potential terrorist. The potential terrorist exhibits Munger’s (2006: 132) ‘culture of loyalty’ and truly believes in the group’s ideology, literally because he wants grounds for radical action. He needs the comradeship of like-minded people to organize and carry out his terrorist plot (Ezekiel 1995). These individuals are often urged to participate in a series of individual or small cell acts of violence against the state to trigger a larger race war (Berlet and Vysotsky 2006).

Like all types of voluntary organizations, white supremacist groups must overcome the collective action problem (Blazak 1998). They do so by requiring certain costly signals, such as tattoos, body piercings, and acts of violence. These actions reveal commitment to the organization and grant an active member certain privileges and benefits.Footnote 3 Joining reveals that the benefits of membership are greater than the costs associated with signaling commitment to the group.Footnote 4

Much of the benefit comes from mutual assistance and understanding (Cohen 1955). Ezekiel’s (1995) interviews find that most members of white supremacist groups have lost a parent; becoming a member provides a support network. He also finds that most members are either physically small or suffer from poor health. Thus, the group provides a form of physical protection.

This protection is, in a sense, somewhat like that provided by organized crime groups, such as the Sicilian Mafia, the Japanese Yakuza, and prison and youth gangs. In his work on gangs, Klein (1995) summarizes the psychological factors of membership: “the gang is seen as an aggregate of individuals held together more by their own shared incapacities than by mutual goals. Primarily, group identification is important as it serves individual needs; it leads to delinquent group activity only secondarily and only in the absence of prosocial alternatives” (Klein 1995: 201). Thus, Klein’s argument suggests that hate groups may not affect the hate crime rate if they serve more of a prosocial role.

Furthermore, recent empirical work by Sobel and Osoba (2009) on youth gangs suggests that gangs form in response to government’s failure to protect youth against violence.Footnote 5 Without gangs, the level of violence may actually be higher. If white supremacist chapters form to protect their members’ physical well-being, white supremacist chapters may be associated with less crime, including less hate crime.

Though white supremacist groups may protect members from future bias-based violence, these groups face different potential threats than those faced by organized crime, prison gangs, and youth gangs. Organized crime groups protect physical well-being, both in and out of prison, protect land, enforce contracts, and resolve contract disputes, whether or not these agreements would be recognized by the government (Gambetta 1993; Hill 2006). Prison gangs, such as the Mexican Mafia, also provide these services even though most of their contracts would not be recognized by central governments (Skarbek 2011). Youth gangs provide physical protection where government does not or will not (Sobel and Osoba 2009). To be successful, these alternative governance organizations must have long time horizons (McGuire and Olson 1996).Footnote 6

The violence committed by white supremacist groups, however, is not used to enforce contracts. It is a way to project power and attract new members (Ezekiel 1995; Blazak 2001). Thus, the protection offered is somewhat different from that of, say, the Sicilian Mafia, in which violence is usually to protect a member from potential violence or to resolve a contract dispute. Violence by white supremacists is more likely to demonstrate that they can control their surroundings and are prepared for the coming race war (Ezekiel 1995; Bushart et al. 2000; Shanks-Meile 2001). Thus, white supremacist group formation may be less about protection from recent hate crimes and more about mobilizing for future racial conflicts (Ezekiel 1995).

There are other differences as well. Outside the inner circle of leaders and ideologists, white supremacist group membership is fluid (Ezekiel 1995). This differs from gangs and organized crime, where exit is punished, sometimes fatally. In this sense, white supremacist groups may be less like alternative governance organizations and more like confrontational political organizations where ideology holds the groups together (Kriesi et al. 1995; Berlet and Vysotsky 2006). If most white supremacists join based on ideology and not for protection from threats, recent hate crimes against whites, or crimes perpetrated by nonwhites, may not incite white supremacist activity.

White supremacist groups are by no means identical. Each organization has different levels of ideologies, prohibitions, and goals, and thus each solves the problem of collective action in a variety of ways. Racist skinheads and neo-Nazi members, unlike Ku Klux Klan and Christian Identity members, often display tattoos or wear distinctive clothing to signal membership.Footnote 7 Furthermore, each group type and chapter expresses its biased views differently; some are often physically violent while others are not.

4 Estimation method

This article examines four hypotheses:

  1. 1.

    White supremacist activity is associated with higher hate crime rates.

  2. 2.

    White supremacist activity is symptomatic of the overall level of bias-based violence.

  3. 3.

    White supremacist activity is correlated with some idiosyncratic factor that influences hate crime rates.

  4. 4.

    White supremacist groups form for protection from recent increases in antiwhite hate crimes or hate crimes by nonwhites.

To determine whether the hate crime rate is associated with white supremacist activity, one would ideally measure white supremacist activity in terms of the number of active members. Unfortunately, the SPLC does not report membership information. Without membership data, I am unable to distinguish between a chapter with 40 members and a chapter with 20 members. Moreover, the formation of new white supremacist chapters may be the result of the splintering of one large group, and a reduction in the number of chapters may be the result of a merger.Footnote 8 Therefore, I follow Jefferson and Pryor (1999) and Mulholland (2010) and focus on whether hate crime rates are different when a county is home to one or more active white supremacist chapters.

I first construct a dichotomous variable, active it :

$$ \mathit{active}_{\mathit{it}}=\left \{ \begin{array}{l@{\quad}l} 1& \mbox{if number of active white supremacist chapters is } > 0\\ 0 & \mbox{if no active white supremacist chapters are present} \end{array} \right . $$
(1)

I then estimate the effect of one or more active white supremacist chapters on the overall rate of hate crime:

$$ \mbox{\textit{hate\ crime}}_{\mathit{it}}= \alpha +\beta \cdot \mathit{active}_{\mathit{it}} +\delta \cdot x_{\mathit{it}}+\rho_{i}+\eta_{t}+\varepsilon_{\mathit{it}}, $$
(2)

where hate crime it is the hate crime rate in county i in year t, active it indicates presence of an active white supremacist group chapter, x it is a vector of explanatory variables for county i in time period t, and δ is a vector of county parameters to be estimated. The control variables in x it include real median household income; the unemployment rate; the real unemployment benefit per unemployed citizen; the poverty rate; the percentages of the population that are black, Hispanic, and white; the population density; the percentage of males aged 15 through 44; and the overall crime rate.Footnote 9 I include time-invariant, county-specific effects represented by ρ i to control for omitted variables that differ between counties but are constant over time.Footnote 10 This fixed effects estimation methodology relies on within-county variation. The year dummies, η t , control for omitted changes over time that affect all counties similarly. The error term, ε it , is clustered by county in order to account for nonrandom errors within each panel (Rogers 1993; Williams 2000; Wooldridge 2002).

There are flaws associated with the collection of hate crime data that may bias the estimates. First, many states and local governments do not have formal guidelines on how to complete a hate crime report.Footnote 11 Second, only a fraction of all hate crimes are reported. If counties with active chapters are more likely to report hate crimes, this biases the estimates upward. If counties with active white supremacist chapters are less likely to report hate crimes, this biases the estimates downward. Third, in some counties hate crime reporting is conducted only by a fraction of state and local agencies. If localities with active chapters are less likely to be covered by hate crime reporting, this biases the estimates downward. If agencies are less likely to file a report when chapters are present, the estimates will be biased downward. Finally, if agencies fail to submit hate crime information when there are no white supremacist chapters, the estimates will be biased upward.

5 Hate crime and hate group data

Hate crime data come from the FBI’s annual report, Hate Crime Statistics (FBI various years). First published in 1992, Hate Crime Statistics compiles hate crime reports voluntarily submitted by various law enforcement agencies. In 1992, Hate Crime Statistics covered only 51 % of the US population from 42 states. By 1997, 83 % of the population from 48 states and DC were covered. Between 1997 and 2007 the percentage of the population covered ranged from a high of 86.6 % in 2004 to a low of 80.0 % in 1998.

Figure 2 maps the highest hate crime rate for each county between 1997 and 2007.Footnote 12 In 1997, approximately 21 % of counties reported at least one hate crime. In 2007, 27 % of counties reported at least one hate crime. Between 1997 and 2007, 60.6 % of counties reported at least one hate crime.Footnote 13

Fig. 2
figure 2

Maximum hate crime rate in a given year: 1997–2007

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Collecting information on hate groups is difficult at best (Himmelstein 1998; Dobratz and Shanks-Meile 2000). Moreover, the reporting by mainstream media and watchdog groups, such as the Anti-Defamation League and the SPLC, is often questioned for its accuracy because of the organizations’ incentives to portray hate groups as large threats to society (Kaplan 1997).Footnote 14 In the absence of other sources, social scientists such as Ferber and Kimmel (2004), Berlet (2004), and Ryan and Leeson (2011) have followed Freilich (2003), who states that “the prudent course of action is to utilize the data, while recognizing the potential problems associated with it” (Freilich 2003: 93).

The SPLC considers a group active if its members engage in any of the following: marches, rallies, speeches, meetings, leafleting, publishing literature, or committing criminal acts. The SPLC tracks hate groups “using hate group publications and websites, citizen and law enforcement reports, field sources and news reports” (SPLC, http://www.splcenter.org/get-informed/hate-map).Footnote 15 In 1997, the SPLC began gathering data for all known active hate group chapters by city.Footnote 16 Although the SPLC now tracks many types of organizations, data for the Ku Klux Klan, neo-Nazi, racist skinhead, and Christian Identity groups only are available for every year from 1997 to 2007.Footnote 17 Approximately 25 %, or 793, counties were home to at least one active white supremacist group chapter.Footnote 18

Figure 3 depicts the change in the overall presence of active Ku Klux Klan, neo-Nazi, racist skinheads, and Christian Identity chapters between 1997 and 2007. The 32 counties shaded in red were always home to at least one active white supremacist chapter. Counties shaded blue witnessed at least one year with one or more active white supremacist chapters and one year without an active chapter. Because the empirical analysis includes fixed effects, these 761 counties, representing 49 states, provide the empirical variation in white supremacist chapters. All remaining counties, shown in white, were never home to an active white supremacist chapter.

Fig. 3
figure 3

Change in hate group presence from 1997 through 2007

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Table 1 displays the county-level summary statistics for hate crime rates by various types of victims and perpetrators, the presence of white supremacist activity, and the independent control variables used in the estimations. The average hate crime rate for the entire sample is 0.16 per 10,000 residents. Excluding hate crimes listed as antiwhite, the hate crime rate falls to 0.13 per 10,000. Looking only at hate crimes committed by whites, excluding crimes listed as antiwhite, results in a rate of 0.07 per 10,000. In about 9 % of county-year observations, at least one active white supremacist chapter is reported.

Table 1 Summary statistics
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6 The relationship between white supremacist groups and hate crime

The results of the fixed effects estimation of Eq. (2) are reported in column one of Table 2.Footnote 19

Table 2 Hate Crime Rate 1997–2007
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Using the full sample, the presence of an active white supremacist chapter is associated with 285 more hate crimes per 10,000 residents.Footnote 20 With an average number of hate crimes per 10,000 residents of 1,494, the presence of an active white supremacist chapter is associated with a 19.1 % higher hate crime rate.Footnote 21

Given the panel nature of these data and the presence of first-order autocorrelation, I use the Arellano-Bover (1995) and Blundell-Bond (1998) General Method of Moments (GMM) dynamic panel estimator and include a lagged dependent variable as an explanatory variable.Footnote 22

$$ \mbox{\textit{hate\ crime}}_{\mathit{it}}= \alpha +\lambda \cdot \mbox{\textit{hate crime}}_{i,t-1}+\beta \cdot \mathit{active}_{\mathit{it}}+\delta \cdot x_{\mathit{it}}+\rho_{i}+\eta_{t}+ \varepsilon_{\mathit{it}} $$
(3)

In this specification, both the lagged hate crime rate and the overall crime rate are endogenous variables. All others variables are treated as exogenous. I address the endogeneity of the one-year lag of hate crimes and the overall crime rates by using internal instruments, namely lagged levels and lagged differences in the hate crime rate and the overall crime rate.Footnote 23 Column 2 in Table 2 reports the estimated results using the two-stage GMM estimation method.Footnote 24 For the overall sample, the GMM estimator returns a similarly significant relationship between white supremacist activity and hate crime rates: an increase of 18.4 %.Footnote 25

However, this measure of hate crimes includes hate crimes that white supremacist groups are unlikely to perpetrate: antiwhite hate crimes. In addition, the measure includes hate crimes committed by nonwhites. Therefore, I repeat the estimations in Eqs. (2) and (3) but replace the dependent variable with hate crimes excluding those listed as antiwhite.Footnote 26 As reported in columns 1 and 2 of Table 3, I find that the presence of a white supremacist chapter is associated with 243 to 299 more non-antiwhite hate crimes per 10,000 residents, an increase of between 19.5 % and 24 %.Footnote 27 I then exclude hate crimes committed by nonwhites and focus on hate crimes committed by whites with nonwhite victims.Footnote 28 The estimates are reported in columns 3 and 4 of Table 3.Footnote 29 The presence of a white supremacist chapter is associated with between 135 and 155 more white-on-nonwhite hate crimes, an increase of between 21.8 % and 25.1 %. In both cases, I continue to find that the presence of an active white supremacist group is associated with higher hate crime rates. This suggests that white supremacist chapters play a direct role in hate crime.

Table 3 Hate Crime Rate Excluding Anti-White and Hate Crime Rate with White Perpetrator and Non-White Victim
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7 Alternative hypotheses

The results above support the theory that white supremacist members commit hate crimes. However, the results are also consistent with three competing hypotheses: (1) the presence of one or more white supremacist chapters is a symptom of the overall level of distrust and violent antagonism among various citizens in a county; (2) the presence of one or more active white supremacist chapters is correlated with some idiosyncratic factor that influences hate crime rates for that county-year; and (3) recent increases in hate crime lead to chapter formation for self-defense. The following subsections seek to determine the validity of these alternative hypotheses.

7.1 Distrust and antagonism

To examine whether white supremacist activity is associated with the overall level of antagonism, I estimate whether the hate crimes listed as antiwhite or the hate crimes committed by nonwhites are correlated with white supremacist activity. If the relationship is positive, white supremacist activity may capture the overall bias-motivated antagonism in a county and not just white supremacist activity. A negative or insignificant relationship would further support the hypothesis that white supremacists commit hate crimes.

I first estimate the relationship between white supremacist chapters and hate crimes committed by nonwhites by replacing the dependent variable in Eq. (2) with the rate of hate crimes committed by nonwhites. The fixed effect estimation results in column 1 of Table 4 shows no statistical relationship between white supremacist groups and hate crimes with nonwhite perpetrators. However, the GMM estimator in column 2 reports a positive relationship, suggesting that presence of a hate group may be symptomatic of overall antagonism. This result may come about if white supremacists inflame biases against one or more groups.

Table 4 Hate Crimes Committed by Non-Whites and Hate Crimes Comiriotted by Non-Whites Listed as Anti-White
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I then replace the dependent variable with antiwhite hate crimes committed by nonwhites. The estimated relationship is reported in columns 3 and 4 in Table 4. Both the fixed effects and the GMM estimation reject the hypothesis that white supremacist groups are simply a proxy for violent antagonism.

7.2 Correlation with an idiosyncratic factor that influences hate crime rates

Although Tables 2 and 3 and much of Table 4 suggest a positive relationship between white supremacist activity and hate crimes, an increase in hate crimes could be due to some other idiosyncratic reason correlated with hate group formation. That is, the estimated coefficient on active it in Eqs. (2) and (3) may be biased if the measure of hate group activity, active it , is correlated with the error term, ε it . One way to reduce the potential bias is to replace active it with its one year lagged values, active it−1, and reestimate Eqs. (2) and (3) using the same independent variables as before.Footnote 30

Table 5 reports the estimated coefficients on active it−1.Footnote 31 Panel A replicates the regressions from Table 2, Panel B replicates Table 3, and Panel C replicates Table 4. Panel A in Table 5, reports the estimated coefficient on active it−1 using the overall hate crime rate, hate crime it , as a dependent variable. Although both the fixed effect and GMM estimates are positive, only the GMM estimator is statistically significant. This mixed result suggests that the presence of a chapter may be correlated with idiosyncratic factors that influence the annual county hate crime rate.

Table 5 Replacing Hate Group Presence t with Hate Group Presence t−1
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The first two columns of Panel B in Table 5 report the estimated relationship between the presence of a white supremacist chapter in the previous year and all current non-antiwhite hate crimes. Unlike the results shown in Panel A, this relationship continues to be both positive and significant: The presence of one or more white supremacist chapters in the previous year results in a 20.4 % to 26.6 % increase in the probability of current non-antiwhite hate crime. Furthermore, in columns 3 and 4 of Panel B, I find that the presence of one or more white supremacist chapters is associated with at least a 32.4 % increase in hate crimes perpetrated by whites against nonwhite victims the following year.

Panel C in Table 5 reestimates the regressions in Table 4 with active it−1 in place of active it ; none of the estimated coefficients are significant. These are stronger results than those in Table 4. Thus, this alternative estimation shows no significant relationship between white supremacist activity and hate crimes by nonwhites whether antiwhite or not.

7.3 Protection from hate crimes

The results in Table 3, Table 4 (save for column 2), and Panel B of Table 5 suggest that white supremacists are the source of higher hate crime rates. However, these positive correlations are also consistent with the formation of chapters in anticipation of future increases in hate crime by nonwhites or hate crimes with an antiwhite bias.

To determine whether current changes in hate crimes perpetrated by nonwhites are related to past changes in white supremacist activity or lagged changes in hate crimes by nonwhites, I estimate Eq. (4).

(4)

Column 1 of Table 6 shows that the coefficient estimates on lagged chapter activity are not significant. This reinforces the notion that nonwhites do not commit more hate crimes when a county witnesses a change in the activity of white supremacist chapters. In other words, past formation of white supremacist chapters does not stimulate nonwhites to commit hate crimes.

Table 6 Expected Future Hate Crimes Committed by Non-Whites and Hate Croup Activity
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To test whether chapters form in response to recent changes in hate crimes by nonwhites, I construct the trichotomous variable Δactive it where:

$$ \Delta \mathit{active}_{\mathit{it}}=\left \{\begin{array}{l@{\quad}l} -1 & \mbox{if a county is no longer home to an active white supremacist chapter}\\ 0& \mbox{if a county realizes no change in the presence or lack of presence} \\ & \mbox{of a chapter}\\ 1& \mbox{if a county is no longer free of white supremacist activity}\end{array} \right . $$
(5)

I then replace the dependent variable in Eq. (4) with Δactive it and use an ordered logistic estimator:

(6)

Column 2 in Table 6 shows the results. The coefficient on hate crimes by nonwhites is again not significant, suggesting that current white supremacist activity is not related to past hate crimes committed by nonwhites.Footnote 32

8 Conclusion

The presence of one or more active white supremacist chapters in a county raises the overall hate crime rate by 19.1 %. Excluding hate crimes listed as antiwhite reveals that chapter activity is associated with a 19.5 % to 24 % higher hate crime rate. Hate crimes committed by white perpetrators against nonwhites is also 21.8 % to 25.1 % higher when at least one white supremacist chapter is active. Antiwhite hate crimes perpetrated by nonwhites are not associated with white supremacist chapters, rejecting the possibility that chapter activity is symptomatic of the overall level of bias-motivated antagonism.

White supremacist chapters do not appear to form in response to hate crimes perpetrated by nonwhites or antiwhite hate crimes by nonwhites. In this respect, white supremacist groups appear to operate more as a social movement and less like gangs (Sobel and Osoba 2009). Nor do they appear to enforce contracts or resolve contractual disputes like Hispanic gangs (Skarbek 2011) or organized crime such as the Sicilian Mafia (Gambetta 1993). This difference may be due to the role of ideology and the source of the perceived threats. Gangs and organized crime emerge as a way of providing effective governance, most notably physical protection and the ability to enforce contracts and resolve disputes. Though membership in a white supremacist group may provide some form of protection, the group does not enforce contracts or resolve contract disputes. Members organize to stop the perceived degradation of western culture. This difference between alternative governance organizations and white supremacist groups may also be a function of how law enforcement agencies address hate crimes versus crimes committed by gangs or organized crime.

There are several possible reasons why the results presented here differ from Ryan and Leeson (2011), who find no relationship between hate groups and hate crimes. First, Ryan and Leeson estimate the hate group-hate crime relationship using the number of chapters at the state level, whereas my analysis uses an indicator variable for chapter presence at the county level. If hate groups are local phenomena, then white supremacist groups are much more likely to direct their frustration at local residents. Because of local differences, aggregation may result in lost variation and reduce the estimated effect. Moreover, because the Southern Poverty Law Center (SPLC) does not report chapter size, the number of chapters may be a noisy measure of the magnitude of hate group activity.

Second, even if a hate group is not actively seeking to commit crimes, its presence may signal to local community members that a particular bias is acceptable. Nonmembers may act out against those viewed as inferior by the white supremacists because such views are present in the community. Spillover effects, if they exist at all, are much more likely to be local in nature and thus lost when aggregating to the state level.

Third, the estimations presented here include only the Ku Klux Klan, neo-Nazi, racist skinhead chapters, and Christian Identity churches that are listed with a city or county location. This differs from Ryan and Leeson’s measure in two respects. First, Ryan and Leeson count all chapters or churches by state whether or not a city or county location is known. Second, Ryan and Leeson include all types of hate groups counted by the SPLC. Therefore, their list includes three additional hate groups: neo-Confederates, black separatists and others. This “Other” category includes scientific research institutes, recording studios, religious organizations, rights organizations, and retail outlets.Footnote 33 Although these organizations may hold biased views that “malign an entire class of people,” the majority do not advocate violence (SPLC, http://www.splcenter.org/get-informed/hate-map).

The estimated relationship between white supremacist activity and hate crime suggests that monitoring these groups would reduce hate crime rates. Furthermore, in communities without such laws, representatives and law enforcement officials may want to consider enacting hate crime laws and white supremacist monitoring laws. Further work is needed to determine which types of white supremacist groups are more likely to commit hate crimes. In addition, further research is required to determine whether the presence of black separatist organizations, such as the New Black Panther Party, and Patriot organizations are associated with the commission of hate crimes in the United States.