Hate Crimes against Asian Americans.

Using 1992-2014 data from the National Incident-Based Reporting System (NIBRS), the present study examines the nature and characteristics of hate crimes against Asian Americans by comparing them with those of hate crimes against African Americans and Hispanics. Minority-general and minority-specific models are proposed to guide the analysis. The findings are mixed. The analyses of all victim-related and most offender-related variables show similarities of hate crimes against Asian Americans to those against African Americans and Hispanics. These findings provide support for the minority-general model. Offenders' race and all incident-related variables of hate crimes against Asian Americans, however, differ significantly from those of hate crimes against African Americans and Hispanics. These significant differences provide support for the minority-specific model. © Southern Criminal Justice Association 2021.

Introduction

Asian immigration to the United States increased significantly since the enactment of the Immigration and Naturalization Act in 1965 (Grieco et al., 2012). While Asian Americans are a relatively small minority group, they are one of the fastest-growing racial/ethnic groups in the United States. Statistics from the Census Bureau show that the Asian population increased from 3.5 million in 1980 to 11.9 million in 2000, and further increased to 19.4 million in 2013, accounting for 5.6% of the U.S. population. As the Asian population increased, crimes against Asian Americans also rose over the years. According to the National Crime Victimization Survey (NCVS), the rate of violent crime committed against Asians increased from 8.2 to 16.2 per 1000 persons age 12 or older from 2015 to 2018.1 Data from the New York City Police Department (NYPD) indicate that Asian Americans are the only racial group that experienced increased victimization across all offense types between 2008 and 2019.2 In 2008, for example, Asian American victims accounted for 4.0% of murder victims, 4.7% of rape victims, 11.6% of robbery victims, 5.2% of aggravated assault victims, and 10.3% of all grand larceny victims in the New York City. These numbers increased to 6.9%, 8.0%, 15.6%, 7.7%, and 15.7% respectively in 2019. Hate crimes against Asian Americans have also increased over the years. According to the Federal Bureau of Investigation (FBI), the number of bias-motivated hate crime incidents against Asian Americans had an annual rate of increase of approximately 12% from 2012 to 2014. Although there was a temporary decrease from 2014 to 2015, anti-Asian bias crimes had increased again from 2015 to 2018.3 The 2015 Hate Crime Report by the Los Angeles County Commission on Human Relations likewise indicated that reported crimes targeting Asian Americans tripled from 6 to 18 from 2014 to 2015 (Los Angeles County Commission on Human Relations, 2015).

Recently, as COVID-19 has been spreading dramatically across the United States, hate crimes against Asian Americans have been surging (Cabanatuan, 2020; Gover, Harper, & Langton, 2020; Jeung, 2020). The surge is largely indicated by “hate incidents” reported in mass media and spurred by the current social and political climate in which COVID-19 has been repeatedly labeled as “Chinese virus” or “China virus.” According to a report released by The Asian Pacific Policy and Planning Council and Chinese for Affirmative Action recently, “more than 2,100 anti-Asian American hate incidents related to COVID-19 were reported across the country over a three-month time span between March and June.”4

Although hate crimes against Asian Americans are on the rise, a majority of empirical studies remains directed toward hate crimes committed against African Americans and Hispanics (see, Gladfelter, Lantz, & Ruback, 2017; Grattet, 2009; Green, Strolovitch, & Wong, 1998; King, Baller, & Messner, 2009; King & Wheelock, 2007; Lyons, 2007, 2008). To date, empirical research that focuses on hate crimes against Asian Americans is rare. The nature and characteristics of victims, offenses, offenders, and situational conditions of hate crimes against Asian Americans largely remain unknown.

The purpose of this study is to explore the nature and characteristics of hate crimes committed against Asian Americans by comparing them with hate crimes committed against African Americans and Hispanics. To guide the analysis, two theoretical models are proposed – minority-general and minority-specific models. The minority-general model assumes that the characteristics of hate crimes against Asian Americans are unlikely to differ significantly from hate crimes against African Americans and Hispanics because of the arbitrary or accidental nature of hate crime incidents against racial minorities (Green, McFalls, & Smith, 2001). In contrast, the minority-specific model hypothesizes that hate crimes against Asian Americans are likely to exhibit unique characteristics compared to hate crimes against African Americans and Hispanics due to the underlying stereotypes and perceptions of Asian Americans as a “model minority” (Assalone & Fann, 2017; Koo, Peguero, & Shekarkhar, 2012). Guided by these models, the analysis compares three aspects of hate crimes against Asians with hate crimes against African Americans and Hispanics, which include victim, offender, and incident-related variables.

Research Context

While the term “hate crime” was coined in the 1980s, animosity toward minority groups has a long history in the United States (Chinese Exclusion Act, 1882; Goldstein, 2017). Asian Americans have not been exempt from this hatred. The early 1800s, for example, saw the Arsonists of the Order of Caucasians—a white supremacist group—murdered four Chinese men over White layoffs. This group used boycotts, arson, and murder against Chinese immigrants for the purpose of driving out and eradicating the “Asiatics” responsible for poor economic conditions (Chen, 2017). The Pearl Harbor attack during World War II set off the anti-Japanese sentiment, caused over 100,000 Japanese Americans to be sent to internment camps. Their federally-confiscated property as well as reparations were not returned until 1988 (Japanese American Citizens League, n.d.).

Although the Civil Rights Movement in the 1960s and 1970s was a turning point for Asian Americans, the significant increase of immigrants brought about by both the enactment of the Immigration and Naturalization Act of 1965 (Grieco et al., 2012), and effects of displacement of refugees from the Vietnam War set the stage for a revival in animosity toward Asians (Fong, 2008; Jacobs & Potter, 2000). The success of Japanese automobile manufacturers in the U.S. markets resulted in the infamous murder of Vincent Chin in 1982, whose murderers screamed, “It’s because of you we’re out of work” (Japanese American Citizens League, n.d.; Levin & McDevitt, 2013). In 1987, a New Jersey gang called the “Dotbusters” beat an Asian man into a coma in response to the number of Indian-owned businesses in Jersey City (Chen, 2017). In 1999, Filipino-American Joseph Ileto was fatally shot in Los Angeles because he was “nonwhite” and a “good target of opportunity” (Fong, 2008). In 2001, Kenneth Chiu was fatally stabbed to death by a man who believed “Chinese and blacks have weapons” (Fong, 2008:159).

The historical examples of hate crimes against Asian Americans are highlighted to suggest these occurrences are not a new crime phenomenon. Rather, they are part of a larger, traditional anti-immigrant sentiment. Spurred by politicians, recent waves of immigrants have stimulated the perception that immigrants are a threat that contributes to national, economic, and cultural insecurity (Martinez & Lee, 2000; Stacey, Carbone-Lopez, & Rosenfeld, 2011). Since the spring months of 2020, the spreading of COVID-19 in the United States and around the globe, coupled with some politicians’ racist and xenophobic labels of the virus, has resulted in a surge of hate crimes against Asian Americans (Cabanatuan, 2020; Gover et al., 2020; Jeung, 2020). This pandemic-related stigmatization and the surge of hate crime incidents against Asian Americans demonstrate an important social issue that is historically recurring and deserves research attention.

Research on hate crimes against racial minorities have focused more on those committed against African Americans (Craig & Waldo, 1996; Craig, 1999; Gladfelter et al., 2017; Grattet, 2009; Green et al., 1998; King et al., 2009; King & Wheelock, 2007; Lyons, 2007, 2008), though there have been increasing studies on Hispanics in recent years (Shively, Subramanian, Drucker, & Edgerton, 2013). Hate crimes against Asian Americans has gone largely ignored by researchers.5

While multiple reasons may account for the lack of research on hate crimes against Asian Americans, a major factor is that there lacks statistics of anti-Asian crimes. Simply, a lack of frequent occurrence may affect a researcher’s ability to “analyze reasonably” (Lyons, 2008:365), and may affect the “degree of statistical precision” (Green et al., 1998) of the analysis. Some commenters contend that the low levels of hate crimes against Asian American may be related to the “model minority” status of Asian Americans (Stotzer & Hossellman, 2012). In the higher education system for example, Asians are often perceived as “model minority,” although they may also face and experience issues of racism and discrimination. They are admitted to college because of their high educational achievement, which may “have different meaning to White students and their sense of protecting academia from students of color” (Stotzer & Hossellman, 2012: 649). Furthermore, the low frequencies of hate crimes against Asian Americans may also be the result of lack of reporting that does not capture crime incidents. A national survey of law enforcement officials indicated that Asians were the group most likely to underreport (Davis & Erez, 1998). The language barriers faced by many Asian immigrants prevent them from communicating efficiently about criminal victimization to the police. Their immigration status, cultural differences in conceptions of justice, and a lack of knowledge with the justice system further amplify their reluctance to report to law enforcement (Davis & Erez, 1998).6

Theoretical Models

The current study aims to fill in the research gap by examining the nature and characteristics of hate crimes against Asian Americans. It compares the nature and characteristics with those of hate crimes against African Americans and Hispanics. We propose minority-general and minority-specific models to guide the comparison. The minority-general model assumes that the characteristics of hate crimes against Asian Americans are not likely to differ from those of hate crimes against African Americans and Hispanics significantly. Previous studies suggest that the nature of hate crime incidents is rather arbitrary or accidental (Green et al., 2001). Racial biases may be acted out when a motivated offender has a situational opportunity with a suitable target of racial minority. Such acts may be spontaneous and may not clearly distinguish between the target minority groups.

The defended community perspective seems to be consistent with the minority-general model. According to the perspective, hate crimes emerge because of residents’ strong desire to prevent racial invasion to their community (de Sena, 1990; Rieder, 1987; Suttles, 1972). A defended community is likely to develop when community residents feel threatened for their valued community identities and take actions against that threat. Racially motivated crime is one of the means that some residents may adopt against any “invasion” or threat that they perceive from other racial groups.

Although the previous studies did not aim to compare hate crimes against different minorities,7 some studies indicate that the correlates of hate crime against different minorities are similar. For example, Green et al. (1998) investigated racially motivated anti-minority crimes and demographic/economic factors in New York City between 1987 and 1995. They found that hate crimes against Asians, Latinos, and Blacks are most frequent in predominantly White areas with increased in-migration of minorities.

Using bias crime report data of the Sacramento Police Department from 1995 to 2002, Grattet (2009) examined whether the correlates such as racial composition, concentrated disadvantage, and residential turnover of overall bias crimes had similar effects on anti-black bias offenses. Assuming that many of the neighborhood dynamics associated with bias crimes would operate regardless of the characteristics of the specific target groups, his findings suggest that there are some minor differences of the correlates between overall bias crimes and anti-black bias offenses. Gladfelter et al. (2017) analyzed 2000–2011 data from the Pennsylvania Human Relations Commission (PHRC) finding that community heterogeneity is strongly and significantly associated with lower rates of hate incidents against both Blacks and Hispanics.

In contrast, the minority-specific model assumes that the characteristics of hate crimes against Asian Americans are likely to differ from those against African Americans and Hispanics because of the unique minority status of Asian Americans. Compared to African Americans and Hispanics, Asian Americans have distinct characteristics due to their physical features, cultural traditions, and personal and collective achievements in the United States. In 2015, U.S. Census data show that median household income of Asian Americans was $77,166 compared to $62,950 for White households, $36,898 for African American households, and $45,148 for Hispanic-origin households (Proctor, Semega, & Kollar, 2016). The same data indicate that in 2015, 21.4% of Asian Americans held advanced degrees compared to 13.4% for Whites, 8.2% for African Americans, and 4.7% for Hispanics (Rayan & Bauman, 2016). Because of these achievements, Asian Americans are often regarded as a “model minority.” Their success may be perceived as potential threats by members of other racial groups.

The racial competition perspective on hate crimes assumes that different racial groups possess different positions in the economic system and there is an uneven distribution of material resources across different racial groups (Olzak, 1990, 1992, 2013; Soule & van Dyke, 1999; van Dyke, Soule, & Widom, 2001). Some groups have access to better material recourses than others. During economic downturns, racial conflict and hate crimes may occur when a racial group perceives that their access and privileges to material resources are threatened by other racial groups.

Asian Americans are traditionally regarded as the “model minority.” However, when their successes cross the acceptable threshold, they would be met with hate crimes as a check of power over minorities. “…Asian Americans are second-class citizens – tolerated as long as they remain a quiet and passive ‘model minority,’ but patronized, or worse, when they attempt to exercise their rights” (Fong, 2008: 154). As the Asian Americans Advancing Justice, a nonprofit organization advocating for the civil and human rights of Asian Americans, states, “Asian Americans experience unique challenges in our country’s racial landscape: we are seen as perpetual foreigners, regardless of our relationships to our country. We are painted to be the “model minority“ and pitted against other communities of color” (Asian Americans Advancing Justice, n.d.).

Although there are rare studies comparing hate crime against Asian Americans with other minority groups, a few of previous studies indicated some differences in hate crimes across different minority groups. For example, using the Uniform Crime Report (UCR) hate crime data from 2000 to 2007 and state legal information, Stacey (2015) found that “states that criminalize violations of a person’s civil rights report more anti-Black incidents and states with broader hate crime definitions report more anti-Hispanic hate crime” (Stacy, 2015:897). This relationship, however, was mediated by the presence of a larger minority group and greater minority political power. States with more Blacks relative to Whites, and with more African-American political power, reported fewer anti-Black hate crimes. Similarly, states with a larger Hispanic population relative to Whites reported fewer anti-Hispanic hate crimes.

These findings imply that the correlates of hate crime against minorities may be sensitive to the characteristics of target minorities. Because of the historical racism, social and economic inequality, and cultural differences, different racial minorities such as African Americans, Hispanics, and Asian Americans have different statuses in the United States. The perspective of doing racial difference theory suggests that racial difference has been socially, economically, and culturally constructed between categories of people (Messerschmift, 1997; Perry, 2001; West & Fenstermaker, 1995). “Insofar as people comply and conform to society’s racialized rules of interactive behavior, they are thought to ‘do difference’ in a socially acceptable manner” (Klein & Allison, 2018, pp. 979–980).

Current Study

Guided by the theoretical models, the present study compares three aspects—victim, offender, and incident related variables, respectively—of hate crime against Asian Americans with those against African Americans and Hispanics. The specific research questions examined in the study are:

Do Asian Americans as victims of hate crimes have any unique characteristics compared to those of African American and Hispanic victims?

Do offenders’ characteristics of hate crimes against Asian Americans significantly differ from those of hate crimes against African Americans and Hispanics?

Do the incidents of hate crimes against Asian Americans show any significant differences from those of hate crimes against African Americans and Hispanics?

Data and Methods

Data

National Incident Based Reporting System (NIBRS) data from 1992 to 2014 were used for the analysis. NIBRS is an incident-based comprehensive data collection system, which collects data on each single incident and the arrest of 48 Group A offenses. Compared to UCR data, NIBRS data contains more information on hate crime incidents. Law enforcement agencies submit hate crime information to the FBI through three different approaches: reporting via NIBRS, the electronic hate crime record layout, or Microsoft Excel Workbook Tool (U.S. Department of Justice, Federal Bureau of Investigation, 2017). Agencies that report through the NIBRS system provide substantially more information on hate crimes than that is captured in the other two methods. For example, while information such as the age, sex, race, and ethnicity of offenders, victims, and arrestees is available in the NIBRS system, it is not reported by agencies either through the hate crime record layout or through the Excel Workbook Tool.

Specifically, we used the NIBRS Incident-Level Extract files constructed by Inter University Consortium for Political and Social Research (ICPSR), which contain one record for every crime incident, and merge variables from the offense, victim, and offender segments together. In case that an incident had multiple offenders, victims, or offenses, the information of the first offender, victim or offense was used in the dataset. Overall, a total of 3400 law enforcement agencies reported 28,094 racially motivated hate crimes through NIBRS between 1992 and 2014. We used the subset data of the anti-Asian American, anti-African American, and anti-Hispanic incidents for our analysis. Furthermore, considering the purpose of the current study, we limited the victim type to individual victims, and offense type to violent crimes. These historical data made available sufficient cases to be analyzed and covered more jurisdictions. In total, there were 10,981 violent hate crime incidents against these three racial/ethnic groups in the dataset. Among which were 478 anti-Asian, 8628 anti-African American, and 1875 anti-Hispanic hate crimes.

Because of the challenge and difficulty to collect and record information on reported hate crimes, substantial missing values existed among variables in the dataset. Our data screening showed that missing values were mainly from offender-related variables. For example, there were 2121 (19.3%) missing values in offender race, 1873 (17.1%) missing values in offender sex, 2533 (23.1%) missing values in offender age, and 1798 (16.4%) cases had missing values in all three offender-related variables. When encountering missing values in statistical analysis, missing data imputation might be utilized. When the extent of missing data is beyond 15%, or when many variables have missing values simultaneously, however, imputation of missing values may not be appropriate (Tabachnick, & Fidell, 2007). To examine the pattern of missing values, we created a binary indicator variable. When any of the offender-related, or victim-related variables had missing values, it was coded as one, otherwise, it was coded as zero. The missing patterns among the three racial/ethnic groups were tested. The results showed that 31% of the anti-Asian, 28.4% of the anti-Black, and 28.3% of the anti-Hispanic cases had missing values on victim-, and offender-related variables. The Chi-square test shows that the missing patterns among the three groups are not different significantly (Chi-square = 1.49, df = 2, p = .474).

Information on the incident related variables of residential status, offender-victim-relationship, weapon use, and injury may be difficult for victims to determine and recall due to the emergent nature of hate crimes. It may also be influenced by the police officer’s ability to substantiate or chose to report. To maximize the utility of situational variables, missing values on the variables were coded as unknown (Messner, Mchugh, & Felson, 2004; Tabachnick, & Fidell, 2007).

In addition, because of the historical reasons, Asian Americans may settle in different types of places compared to other minority groups. As a result, they might be subject to different pool of potential offenders or social, political, or economic circumstances, which in turn might intersect with factors engendering hate crimes. To control for the contextual effects, counties where the incident occurred were identified based on police agencies reporting the crimes. U.S. Census 2000 data at county level were utilized to obtain measures of population sizes of different racial groups and economic variables. Since cases originally handled by State Police cannot be assigned to specific counties, they were excluded from the analysis.

Finally, we notice that the dataset contains intra-racial incidents when examining victim and offender races. Since the current study focuses on racially motivated hate crimes, we delete the intra-racial incidents from the analysis. The final sample size for the current analysis is therefore 7136, including 329 anti-Asian, 5463 anti-Black, and 1344 anti-Hispanic hate crime incidents located in 813 counties.

Variables and Measures

To compare and contrast the characteristics of hate crimes against Asian Americans, African Americans, and Hispanics, two binary dependent variables were created using victims’ racial-ethnic identities. The first dependent variable is used to compare hate crimes against Asian Americans and African Americans, which was coded as zero if the crime is against African Americans and as one if, the crime is against Asian Americans. Likewise, the second dependent variable is used to compare hate crimes against Asian Americans and Hispanics which has the same coding (0 = crime against Hispanics and 1 = crime against Asian Americans).

Three groups of independent variables, including victim-, offender-, and incident-related variables were in the analysis. The group of victim variables included victims’ age, sex, and resident status. Victim’s age was measured in years, and it was coded into four groups, 1 = under 18, 2 = 18–34, 3 = 35–44, and 4 = 45 or above. Victim’s sex was a dummy variable coded as 0 = female and 1 = male. Victim’s residential status, indicating whether the victim maintained his/her permanent residence in the locality where the crime occurred, included three categories, 0 = not local resident, 1 = local resident, and 2 = unknown. The group of offender-related variables contained offenders’ age, sex, and race. Similarly, offender’s age was measured in years and was recoded into the same age categories as the measure of victim’s age. Offender’s sex was also coded as 0 = female and 1 = male. Offender’s race was measured with two categories, 0 = White, 1 = non-White.

The group of incident-related variables comprised victim-offender relationships, locations of hate crime incidents, time when hate crime incidents occurred, weapon involvement, injuries, and involvement of substance use in hate crime incidents. The variable of victim-offender relationships was coded as three categories, 0 = stranger, 1 = acquaintance, and 2 = unknown relationship. The locations of hate crime incidents were measured as six categories, 0 = residence/home, 1 = commercial/retail, 2 = highway/road, 3 = school/college, 4 = parking lot/garage, and 5 = other places. Prior studies measured location as three categories including residence, street or open space, and other location (i.e. Messner et al., 2004). Our descriptive analysis of the data showed however, Asian Americans were different from African Americans and Hispanics in a more detailed fashion. Therefore, we decided to keep the measure more specific with more categories. The variable of time when a hate crime incident occurred was measured with four categories, 1 = 1 am to 6 am, 2 = 7 am to 12 pm, 3 = 1 pm to 6 pm, and 4 = 7 pm to 12 am. The Office of Juvenile Justice and Delinquency Prevention (OJJDP) Analysis shows that the number of violent crimes committed by offenders increases from 6 am to 6 pm with a peak around 7 pm to 8 pm, and then decreases until 6 am.8 We coded the crime time in four categories to capture more levels of variations. Similar to Messner and associates’ study (2004), the variable of weapon use contained five categories, 0 = no weapon, 1 = firearm, 2 = personal weapon, 3 = other weapon, and 4 = unknown/NA. The variable of injury was coded in four categories, 0 = no injury, 1 = minor injury, 2 = major injury, and 3 = unknown/NA. Substance use of offenders was a dummy variable, 1 = offenders’ use of alcohol or drug and 0 = unknown/NA.9

Since they were pooled data covering multiple years between 1992 and 2014, it might be necessary to create a time variable to control for the potential variations of definition of hate crimes, data collection processes in NIBRS, and other changes in society. A conventional method is to create a series of time dummy variables indicting the year in which the incident occurs (Lott & Mustard, 1997; Marvell & Moody, 1996). This approach, however, may generate too many time dummy variables for the analysis when it covers more than 20 years of data. As an alternative, a time variable was created, reflecting the change of hate crime definitions and data collection processes made by the FBI.

In the 1990 Hate Crime Statistics Act, hate crimes were defined as “crimes that manifest evidence of prejudice based on race, religion, sexual orientation, or ethnicity” (28 U.S.C. § 534, 1990). Since the adoption of the Act, few significant developments and changes have been observed, including the adoptions of the Violent Crime Control and Law Enforcement Act of 1994 (42 U.S.C. Ch. 136, 1994), which was implemented on January 1, 1997, and the Matthew Shepard and James Byrd, Jr. Hate Crimes Prevention Act of 2009 (18 U.S. Code § 249, 2009), which was implemented in 2013. These newly enacted legislations mandated the FBI to change data collection concerning hate crimes significantly (United States Department of Justice, 2017). The time variable therefore had three categories, 1 = “1992–1996,” 2 = “1997–2012”, and 3 = “2013–2014” (the reference category). This variable was included as a control variable in the analysis (see Table 1 for the descriptive statistics of variables).

Table 1

Descriptive analysis of individual-level variables (n = 7136)

		Total (n = 7136)		Anti-Asian (n = 329)		Anti-Black (n = 5463)		Anti-Hispanic (n = 1344)
		n	%	n	%	n	%	n	%
Victim variables
Victim age	Under 18	1748	24.5	79	24.0	1302	24.1	367	27.3
	18–34	3066	43.0	152	46.2	2309	42.3	605	45.0
	35–44	1225	17.2	49	14.9	965	17.7	211	15.7
	45 or above	1097	15.4	49	14.9	887	16.3	161	12.0
Victim sex	Female	2426	34.0	109	33.1	1957	35.8	360	26.8
	Male	4710	66.0	220	66.9	3506	64.2	984	73.2
Victim	Not local resident	1215	17.0	79	24.0	917	16.8	219	16.3
Residential	Local resident	4624	64.8	197	59.9	3507	64.2	920	68.5
Status	Unknown	1297	18.2	53	16.1	1039	19.0	205	15.2
Offender variables
Offender race	White	6744	94.5	245	74.5	5409	99.0	1090	81.1
	Non-White	392	5.5	84	25.5	54	1.0	254	18.9
Offender sex	Female	1046	14.7	52	15.8	815	14.9	179	13.3
	Male	6090	85.3	277	84.2	4648	85.1	1165	86.7
Offender age	Under 18	1421	19.9	81	24.6	1010	18.5	330	24.6
	18–34	3111	43.6	149	45.3	2358	43.2	604	44.9
	35–44	1244	17.4	51	15.5	987	18.1	206	15.3
	45 or above	1360	19.1	48	14.6	1108	20.3	204	15.2
Incident variables
Victim-offender relationship	Stranger	2212	31.0	129	39.2	1678	30.7	405	30.1
	Acquaintance	3899	54.6	155	47.1	3009	55.1	735	54.7
	Unknown	1025	14.4	45	13.7	776	14.2	204	15.2
Location	Residence/home	2355	33.0	78	23.7	1881	34.4	396	29.5
	Commercial/retail	1050	14.7	67	20.4	791	14.5	192	14.3
	Highway/road	1605	22.5	59	17.9	1240	22.7	306	22.8
	School/college	690	9.7	56	17.0	484	8.9	150	11.2
	Parking lot/garage	572	8.0	26	7.9	412	7.5	134	10.0
	Other	864	12.1	43	13.1	655	12.0	166	12.4
Time	1 am – 6 am	840	11.8	32	9.7	646	11.8	162	12.1
	7 am – 12 am	1400	19.6	51	15.5	1113	20.4	236	17.6
	1 pm – 6 pm	2459	34.5	124	37.7	1866	34.2	469	34.9
	7 pm – 12 pm	2437	34.2	122	37.1	1838	33.6	477	35.5
Weapon	No weapon	363	5.1	22	6.7	275	5.0	66	4.9
	Firearm	323	4.5	8	2.4	222	4.1	93	6.9
	Other weapon	1178	16.5	51	15.5	862	15.8	265	19.7
	Personal weapon	2185	30.6	129	39.2	1525	27.9	531	39.5
	Unknown/NA	3087	43.3	119	36.2	2579	47.2	389	28.9
Injury	No injury	2156	30.2	89	27.1	1648	30	419	31.2
	Minor injury	1633	22.9	107	32.5	1073	19.6	453	33.7
	Major injury	320	4.5	16	4.9	213	3.9	91	6.8
	Unknown/NA	3027	42.4	117	35.6	2529	46.3	381	28.3
Offender using substance	Use of alcohol/drugs	1282	18.0	49	14.9	979	17.9	254	18.9
	Unknown/NA	5854	82.0	280	85.1	4484	82.1	1090	81.1
Control variable
Year	1992–1996	427	6.0	34	10.3	294	5.4	99	7.4
	1997–2012	5861	82.1	260	79.0	4503	82.4	1098	81.7
	2013–2014	848	11.9	35	10.6	666	12.2	147	10.9

The county-level variables obtained from US census 2000 data included total population size, percentage of Asian Americans, percentage of African Americans, percentage of Hispanics, unemployment rate, and median family income in a county. Due to the skewness of the distribution of population size, a logarithm transformation of the variable was performed. A region variable was also created to capture the unmeasured potential difference of cultural traditions, socioeconomic and political variances across different U.S. regions. The variable had four categories, including 0 = South (the reference category), 1 = Northeast, 2 = Northcentral, and 3 = West (see Table 2 for the descriptive analysis of the county level variables).

Table 2

Descriptive analysis of aggregated county-level variables

	Counties with Anti-Asian Crimes (n = 168)		Counties with Anti-Black crimes (n = 713)		Counties with Anti-Hispanic Crimes (n = 417)
	Mean (s.d.)	Range	Mean (s.d.)	Range	Mean (s.d.)	Range
2000 population (logarithm)	5.10 (1.21)	1.56–7.63	4.07 (1.24)	.87–8.59	4.29 (1.38)	.65–8.59
% of Asians in 2000	2.15 (2.11)	.20–13.00	1.06 (1.45)	.00–13.00	1.31 (1.67)	.00–13.00
% of Blacks in 2000	9.54 (12.32)	.10–60.90	7.97 (12.39)	.00–67.30	7.19 (11.04)	.00–63.60
% of Hispanics in 2000	5.45 (6.42)	.50–41.50	4.42 (7.11)	.20–78.20	5.93 (7.50)	.20–45.30
2000 unemployment rate	3.24 (0.93)	1.40–7.10	3.44 (1.43)	.90–28.00	3.32 (1.06)	1.10–8.70
2000 median family income	53,213 (11,445)	34,072-92,146	46,089 (10,218)	20,496-97,225	48,067 (10,654)	24,930-92,146
Region
Northeast	16.1%	0–1	7.0%	0–1	6.7%	0–1
Northcentral	31.5%	0–1	36.6%	0–1	35.5%	0–1
West	16.1%	0–1	13.0%	0–1	22.5%	0–1
South	36.3%	0–1	43.3%	0–1	35.3%	0–1

Analytical Strategies

Two multilevel logistic regression models were analyzed to compare the nature and characteristics of hate crimes against Asian Americans with those against African Americans and Hispanics. Because hate crime incidents were nested in counties, a multilevel approach was adopted to control for the social contextual variations across counties. Specifically, the nested nature of the data was taken into account and the standard errors of parameter estimates were adjusted accordingly with hierarchical modeling. Generalized Hierarchal Linear Modeling (GHLM) modeled random effects of counties and estimated fixed effects of the independent variables in the multilevel logistic regression analyses.

Results

Tables 1 and 2 present the results of descriptive analysis of hate crimes against Asian Americans, African Americans, and Hispanics. In general, hate crimes are most likely targeting young adults at ages 18–34, male, and local residents in all three groups. Asian American victims however, have a higher chance than African Americans and Hispanics to be victimized in places where they are not local residents (24% vs. 16.8% for African Americans and 16.3% for Hispanics). Comparing with Black and Hispanic victims, Asian Americans also have relatively higher chance to be victimized by non-White offenders (25.5% vs. 1.0% for African Americans and 18.9% for Hispanics).

With regard to the incident characteristics, Asian Americans have higher risk to be persecuted by strangers (39.2% vs. 30.7% for African Americans and 30.1% for Hispanics), are less likely to be offended in their residence (23.7% vs. 34.4% for African Americans and 29.5% for Hispanics), and are more likely to be targeted at school/college (17% vs. 8.9% for African Americans and 11.2% for Hispanics). The variables of time, weapon use, injury, and substance show similar patterns for the three groups.

The results for the county-level variables indicate that counties with a marginally higher percent of Asian population are more likely to have hate crimes against Asian Americans. In addition, more hate crimes against Asian Americans are observed in counties with slightly higher median family income. Finally, hate crimes against Asian Americans are more likely to happen in Northeast region.

Table 3 presents the results of two multilevel logistic regression models that compare hate crimes against Asian Americans with those against African Americans and Hispanics respectively.

Table 3

HLM logistic regression models comparing the characteristics of hate crimes against Asian Americans with African Americans, and Hispanics

		Asian vs. African American^ (n1 = 5792; n2 = 723)			Asian vs. Hispanics+ (n1 = 1673; n2 = 463)
Fixed Effect		B	s.e.	Exp(b)	b	s.e.	Exp(b)
Individual-level variables
Victim variables
Victim age	Under 18	−.163	.257	.849	−.144	.271	.866
	18–34	.219	.208	1.244	−.025	.219	.975
	35–44	.170	.233	1.186	−.085	.258	.919
	45 or above a
Victim sex	Female a
	Male	.095	.143	1.099	−.126	.177	.881
Victim residential	Not local resident a
	Local resident	−.211	.174	.809	−.363	.175	.696
Status	Unknown	−.121	.235	.887	−.393	.260	.675
Offender variables
Offender race	White a
	Non-White	3.603	.220	36.718***	.350	.176	1.419*
Offender sex	Female a
	Male	−.112	.181	.894	−.024	.212	.977
Offender age	Under 18	.344	.228	1.411	.007	.254	1.007
	18–34	.113	.187	1.120	.123	.230	1.131
	35–44	−.042	.226	.959	.040	.253	1.041
	45 or above a
Incident variables
Victim-offender relationship	Stranger a
	Acquaintance	−.427	.146	.652**	−.546	.174	.579**
	Unknown	−.302	.208	.739	−.334	.208	.715
Location	Residence/home a
	Commercial/retail	.249	..191	1.282	.250	.211	1.284
	Highway/road	−.258	.190	.773	−.292	.204	.746
	School/college	.958	.233	2.607***	.712	.265	2.039**
	Parking lot/garage	−.111	.282	.895	−.362	.253	.696
	Other	−.061	.232	.941	.035	.237	1.035
Time	1 am–6 am	−.389	.263	.678	−.367	.257	.693
	7 am–12 pm	−.655	.197	.520***	−.381	.214	.683
	1 pm–6 pm	−.175	.134	.839	−.038	.143	.963
	7 pm–12 am a
Weapon	No weapon a
	Firearm	−.447	.499	.639	−1.310	.610	.270*
	Personal weapon	−.072	.250	.930	−.142	.286	.868
	Other weapon	−.268	.280	.765	−.384	.324	.681
	Unknown/NA	−.710	.358	.491*	−.474	.505	.622
Injury	No injury a
	Minor injury	.536	.163	1.709***	.149	.205	1.160
	Major injury	.082	.286	1.085	.048	.327	1.049
	Unknown/NA	.562	.302	1.754	.715	.452	2.044
Offender using substance	Use of alcohol or drugs	−.310	.187	.733	−.128	.194	.880
	Unknown/NA a
Control variable
Year	1992–1996	1.136	.287	3.114***	1.284	.341	3.609***
	1997–2012	.244	.204	1.277	.284	.235	1.328
	2013–2014 a
County-level variables
Intercept		−3.119	.492	.044***	−1.194	.529	.303*
	Total population	−.018	.086	.983	.173	.100	1.189
	Percent of Asian	.140	.036	1.150***	.157	.053	1.170**
	Percent of Black	−.003	.008	.997	.003	.010	1.004
	Percent of Hispanics	−.024	.014	.976	−.084	.023	.919***
	Unemployment rate	.021	.066	1.021	.025	.128	1.026
	Median income	<.001	<.001	1.000	<.001	<.001	1.000
Region	South
	Northeast	.561	.231	1.761*	.541	.298	1.717
	Northcentral	−.581	.207	.651**	−.221	.243	.802
	West	.362	.256	1.514	−.401	.283	.670

^Black is the reference category. n1 = 5792 at the individual level and n2 = 723 at the county level

+Hispanic is the reference category. n1 = 1673 at the individual level and n2 = 463 at the county level

aindicates the reference category in each independent variable

***p < 0.05, p < 0.01

Comparison of Hate Crimes against Asian Americans and African Americans

The results in Table 3 reveal no significant differences regarding victims’ characteristics (i.e., their age, sex, and residential status) of hate crimes against Asian Americans and African Americans. As indicated in Table 1, victims of hate crimes in both racial groups are likely to be male, between the ages of 18 and 34, and local residents of the place where the offenses occurred.

When offender-related variables are compared, significant differences emerge in the race of offenders. Compared to hate crimes against African Americans, hate crimes against Asian Americans are more likely to be committed by non-White offenders (b = 3.60. exp.(b) = 36.72) than White offenders. Other offenders’ characteristics (i.e., sex and age) however, remain similar. Offenders of hate crimes against the two racial groups are likely to be male and young adults at ages of 18–34.

Analysis of incident-related variables shows more significant differences. Comparing with hate crimes against African Americans, hate crimes against Asian Americans are more likely to be committed by strangers than acquaintances (b = −.43, exp.(b) = 0.65). Significant differences are also shown in the locations of hate crimes between the two racial groups. Comparing with African American victims, Asian Americans are more likely to experience hate crimes in schools/colleges (b = 0.96, exp.(b) = 2.61) than in their residence. In contrast, African Americans are more likely to experience hate crime in their residence.10 The time when hate crime incidents occurred differs as well. In comparison with anti-Black hate crime, anti-Asian hate crime has a higher chance to take place in the evening from 7:00 PM to 12:00 AM than in the morning from 7:00 AM to 12:00 AM (b = −.66, exp.(b) = 0.52).

With respect to weapon involvement, or substance use, no significant difference is found in hate crimes against Asian Americans and African Americans. There is a significant difference in the injury situation. Asian Americans are more likely to experience minor injury than no injury (b = .47, exp.(b) = 1.59). The control variable of years also shows some significant effect. The likelihood of hate crimes reported by Asian Americans during the early years (b = 1.14, exp.(b) = 3.11) are higher comparing with African Americans.11

Finally, the results in Table 3 indicate that the relative size of Asian population in a county is likely to increase the chance for them to experience hate crimes (b = .14, exp.(b) = 1.15). Economic variations, however, do not show significant impact. There is also some regional variations. Comparing with African Americans, Asian Americans are more likely to experience victimization of hate crimes in the Northeast (b = .56, exp.(b) = 1.76), but less likely to experience victimization of hate crimes in the Northcentral region (b = −.58, exp.(b) = .65) than in South.12

Comparison of Hate Crimes against Asian Americans and Hispanics

The second model of Table 3 shows the results for the comparison of hate crimes against Asian Americans and Hispanics. Some of the patterns of hate crimes against these two racial groups are similar to those of hate crimes against Asian Americans and African Americans while others differ. For example, there are no significant differences regarding victims’ characteristics in hate crimes against Asians and Hispanics; and other minority offenders are more likely than Whites to commit hate crimes against Asians etc. One distinctive difference however, is that hate crime against Hispanics is more likely to involve firearms compared to crimes against Asian Americans (b = −1.31 exp.(b) = 0.27). Comparing with the patterns of hate crimes against Asian Americans and African Americans, hate crimes against Asian Americans and Hispanics do not show any significant difference in offense time, injuries, and offenders’ substance use. Similarly, the control variable “year” is significant, which indicates that hate crimes reported by Asian Americans during 1992–1996 are higher comparing with Hispanics.

At county level, while the relative size of Asian population is likely to increase the chance of hate crimes against Asians, the relative size of Hispanic population is likely to increase the chance of hate crimes against Hispanics. The regional effect is indistinctive between Asian Americans and Hispanics.

Discussion and Conclusion

Using NIBRS data between 1992 and 2014, and US Census 2000 data at county level, the present study examines the nature and characteristics of hate crimes against Asian Americans in comparison with those against African Americans and Hispanics. Two theoretical models, minority-general and minority-specific models, are proposed to guide the analyses that compare the effects of victim, offender, and incident-related variables. The data reveal several interesting findings.

Victims’ characteristics, including age, sex, and resident status involving hate crimes committed against Asian Americans are similar to those hate crimes committed against African Americans and Hispanics. They are likely to be male, young, and residents of the locality where the crimes occurred. These findings seem providing support for the minority-general model, which assumes that hate crimes against different racial minorities are not likely to differ significantly. The similarities are grounded in certain demographic characteristics of the victims. Young males who reside locally are more likely to become targets of racially motivated hate crimes.

In addition, hate crimes committed against Asian Americans, with respect to the offenders’ age and sex, are comparable to hate crime against African Americans and Hispanics. The offenders are likely to be male and young. As revealed in prior studies, young males in general are the primary perpetrators of hate crimes regardless of their motivation for bias (Steinberg, Brooks & Remtulla, 2003). In decoding offenders’ motivations for committing hate crimes, Levin and McDevitt (2013) suggest that “thrill-seekers” represent the largest group of hate crime offenders. They commit the offense “because of boredom, to have fun, and to feel strong” (Steinberg et al., 2003:981). These findings also provide support for the minority-general model.

Findings of this study, however, also provide support to the minority-specific model, which assumes that hate crimes against different racial minority groups are likely to show significant differences. First, the race of offenders differs significantly across hate crimes against Asian Americans, African Americans, and Hispanics. Specifically, hate crimes against Asian Americans are more likely than hate crimes against either African Americans or Hispanics to be committed by non-White offenders. This finding may be attributed to animosity toward the “model minority” from other minority groups. As aforementioned, the “model minority” stereotype assuming Asian Americans’ success in economics, education, and other opportunities generates potential competition or threats by members of other racial groups, which in turn may lead to resentment to be further acted upon through hate crimes. Offenders of other minorities of color targeting Asian Americans might fit the category of “reactionists” identified by Levin and McDevitt (2013). Instead of acting impulsively, the “reactionists” are motivated by protecting their resources from competitors (Steinberg et al., 2003). This finding might also lend indirect support to the perspective of racial competition motivating hate crimes, which argues that when members of a racial group perceive that their access and privileges to material resources are threatened by other racial groups during economic downturns, racial conflict and hate crimes may occur (Olzak, 1990, 1992, 2013; Soule & van Dyke, 1999; van Dyke et al., 2001). Although the aggregate level economic status does not show effects on the difference, the individual level economic competition hypothesis however, is not tested in the current study. Whether hate crimes are motivated by economic pressure or discomfort of diversity (Green, Abelson, & Garnett, 1999) needs further research.

Second, hate crimes against different racial and ethnic groups show more significant differences in incident variables. Comparing with African Americans, Asian Americans are more likely to be the target of hate crimes in school environments. This variation may again be a sign of the perceived “model minority” stereotype. Painted as a “model,” Asian Americans are more likely to be criticized by other minorities. Envy or jealousy of Asian Americans’ high levels of educational achievement, and their success in the workplace might also lead to feelings of resentment from other racial/ethnic groups.

With respect to the victim-offender relationship, injury, and the time of incident occurrence, different patterns are observed between hate crimes committed against Asian Americans and African Americans. Asian Americans are more likely to be the victim of strangers and suffer minor injuries. Hate crimes against Asian Americans are less likely to occur in the morning than in the evening. Since these findings support the minority-specific hypothesis, the mechanism of variance deserves further exploration.

Some of the variations between hate crimes committed against Asian Americans and African Americans discussed above also occur when comparing hate crimes committed against Asian Americans with Hispanics. For example, there are similar patterns of differences with respect to the victim-offender relationship, the location of hate crime incidents, and the time of incident occurrence. One unique difference between hate crimes committed against Asian Americans and Hispanics is that hate crimes against Asian Americans are less likely to involve a firearm than those committed against Hispanics. This unique difference also deserves further exploration in terms of the statuses and characteristics of Asian Americans and Hispanics. All these significant differences indicate that their minority status and related characteristics of Asian Americans seem to matter in their experiences being hate crime victims, which provide support for the minority-specific model.

Any interpretation of these findings should be made with caution. The data analyzed only include hate crime incidents reported to law enforcement agencies through NIBRS. It is commonly recognized that official data may not reflect the actual prevalence of crimes. This is an especially serious consideration since reporting rates of crimes are the lowest among Asian Americans as well as Hispanics (Davis & Erez, 1998). Furthermore, even if a hate crime was reported by victim, officer’s discretion in identifying and recognizing an incident as hate crime may also significantly influence the inclusion of the data. If police are more likely to interpret a crime against someone of a particular race as a hate crime, that could also skew the comparison and the findings. In addition, agencies reporting through NIBRS comprise less than one-third of all law enforcement agencies in the United States (United States Department of Justice, 2017). Potential bias might exist if racial compositions and other demographic characteristics of jurisdictions that report through NIBRS differ significantly from jurisdictions that do not report through NIBRS system. Consequently, the results of the present analysis may not fully represent the general patterns of hate crimes against Asian Americans, and other minority groups.

With these limitations in mind, this study demonstrates the value of conducting comparative analysis of hate crimes against different racial/ethnic groups to identify incidence similarities and differences. Compared to studies conflate minority groups, the comparative analysis in this article is likely to show how hate crimes target different racial and ethnic groups. Findings suggest that there is a need to conduct further research to more fully understand the Asian Americans’ experience with hate crimes, and to further examine the “model minority” stereotype on hate crimes committed against Asian Americans. Further empirical research is needed to disentangle whether economic competition by minorities and the perceived educational attainment among Asian Americans aggravates the likelihood of hate crime victimization. In addition, hate crime perpetrators targeting Asian Americans may have very different motives from those targeting African Americans or Hispanics. Whether these motives have to do with their perceptions of fairness, their own identities, or it is merely a thrill-seeking, deserves further examinations. Better data need to be collected, and the voices of Asian Americans need to be heard.

We must also acknowledge that Asian Americans may have different ethnic backgrounds and distinct socio-historical experiences in the United States. While Asian Americans collectively experience the stereotype of “model minority,” different Asian subgroups may have gone through different avenues of assimilation or dissimilation, acculturation or segregation, success or poverty. It should be valuable to study the similarities and differences in hate crimes against different ethnic groups of Asian Americans when data are available and sufficient for analysis. The NIBRS data used in the current analysis do not have detailed information of the originality or nationality of the victim. We hope that future studies would be able to collect the data to conduct the analysis.

Our study represents an attempt to address the characteristics of hate crimes that may be common to racial-ethnic minorities and that may be unique to Asian Americans. Such a study and related findings are likely to increase our knowledge and understanding of different cultural traditions and patterns and related social issues. This knowledge and understanding provides a foundation to recognize the reality of cultural diversity, increase awareness of the related social issues, and promote mutual respect.