Immigrant Organizations and Neighborhood Crime

Abstract

We examine the impact of immigrant-serving organizations on neighborhood crime in the Los Angeles Metropolitan area, while accounting for other community correlates of crime as well as potential endogeneity. We estimate longitudinal negative binomial regression models that test for the main, mediating, and moderating effects of immigrant-serving organizations. We found that immigrant-serving organizations generally have crime-reducing effects for all types of crime. We also find that high immigrant concentration is associated with lower levels of crime in general, and this effect is moderated by the number of organizations, which underlines the importance of accounting for these organizations when studying the nexus of immigrant concentration and neighborhood crime.

Keywords

immigrant organization neighborhood crime

Introduction

Studies find little evidence that areas with more immigrants are at heightened risk of neighborhood crime (Desmond & Kubrin 2009; Kim et al., 2018; Kubrin & Ousey 2009; Ousey & Kubrin 2014; Trager & Kubrin 2018). In fact, research typically shows that immigrant concentration has a null effect, or in some cases, a negative effect on neighborhood crime rates. Theoretical frameworks explaining such a relationship include immigrant self-selection, heightened informal social control, stronger family structure, and immigrant revitalization (Kubrin & Ishizawa 2012; Kubrin & Ousey 2009; Martinez, 2006). With few exceptions (Harris et al., 2018; Xie & Baumer 2021), little research has empirically examined these theoretical mechanisms.

In the current study, we posit that voluntary organizations—particularly, immigrant-serving organizations that act on behalf of immigrants and provide services to immigrants—may be an important factor to help explain lower crime rates in immigrant neighborhoods, and we empirically examine whether this is the case. The theoretical notion of the beneficial effects of voluntary organizations is derived from social disorganization theory, which posits that neighborhood structural characteristics such as socioeconomic disadvantage, residential instability, and racial/ethnic heterogeneity can impede the formation of self-regulatory capability to solve community problems including crime and disorder (Morenoff et al., 2001; Sampson & Groves 1989; Taylor 1997). Socially disorganized neighborhoods may have relatively fewer voluntary organizations (and organizational participation) that can facilitate the provision of services and goods for the formulation of social ties and informal social control (Bursik & Grasmick 1993; Slocum et al., 2013; Wo et al., 2016). The theoretical insights regarding the importance of voluntary organizations may be directly applicable to the context of immigrant communities. In particular, voluntary organizations may mediate the impact of immigrant concentration on neighborhood crime rates. That is, voluntary organizations may account for the crime-reducing effect of immigrant concentration in neighborhoods by engendering social interaction, and facilitating mutual trust and informal social control among immigrants. Hinting at this possibility, some studies find that immigrant-serving organizations do, in fact, enhance the density of social networks and increase solidarity among immigrants by providing necessary social and economic assistances (Chow 1999; Cordero-Guzman 2005; De Leon et al., 2009).

An alternative possibility is that immigrant voluntary organizations may serve as a moderator of this relationship. In this view, immigrant neighborhoods do not necessarily give rise to more immigrant voluntary organizations as a mediator, but rather the ability of immigrant concentration to foster informal social control through informal social networks is enhanced in neighborhoods with more immigrant voluntary organizations providing formal social connections. The consequence is a multiplicative relationship. The current study empirically investigates immigrant voluntary organizations as both a potential mediator and moderator in the immigration concentration-neighborhood crime relationship.

A challenge with measuring the effects of voluntary organizations is the possibility of endogeneity. Voluntary organizations may be more likely to locate in more socially disorganized neighborhoods with higher crime rates given the likely greater presence of potential patrons for the services these voluntary organizations provide (Small & McDermott 2006; Small & Stark 2005; Peck 2007). At the same time, it is possible that immigrants are more likely to settle in relatively safer neighborhoods (MacDonald et al., 2013). As a consequence, a negative association between immigrant concentration and crime could be temporally endogenous. These considerations imply the need to utilize longitudinal data to more accurately capture the associations among immigrant concentration, voluntary organizations, and neighborhood crime.

In short, although a large body of research examining immigrant concentration and neighborhood crime documents a null or negative association between the two, relatively fewer studies attempt to assess the possible factors that may explain such an association. The current study theoretically posits the importance of immigrant-serving voluntary organizations, and empirically examines their impact on neighborhood crime, while accounting for other community correlates of crime as well as potential endogeneity. The current study investigates whether immigrant-serving organizations mediate or moderate the relationship between immigration and crime in neighborhoods using longitudinal data from the Los Angeles Metropolitan Area. In the subsequent section, we theorize the critical role of immigrant voluntary organizations. Following that, we discuss our data and analytical approach, and present the findings from the analyses. We close by discussing the implications of the findings for research on the immigration-crime nexus as well as for social disorganization theory more generally.

Immigrant Neighborhoods and Crime

As noted above, research shows that neighborhood immigrant concentration typically has a null, or even negative, association with crime. Indeed, “the major finding of a century of research on immigration and crime is that immigrants nearly always exhibit lower crime rates than native groups” (Martinez & Lee 2000, p.125). Several theoretical explanations are proposed for such an association including immigrant selection, family structure, immigrant revitalization, among others. Most relevant to the current study is an explanation that enhanced social control from strong ties and trust within immigrant communities helps reduce crime (Desmond & Kubrin 2009; Kubrin & Ishizawa 2012; Kubrin & Ousey 2009; Martinez & Valenzuela 2006). Specifically, it is theorized that immigrant neighborhoods tend to have higher levels of social cohesion and trust among residents due to similar social, cultural, and linguistic backgrounds, which may enhance informal social control and collective efficacy (Sampson et al., 1997).

Despite these and related claims, theories on the connection between crime and immigration have not been sufficiently empirically evaluated, remaining “largely undeveloped and untested” (Mears 2002, p. 287). Prior research has not sufficiently assessed whether social factors mediate the immigration-crime relationship in the manner predicted by key theoretical arguments (Ousey & Kubrin 2009), leaving questions unanswered about the underlying nature of the immigration-crime nexus. Mears (2002, p. 284) argues, “On the whole. . .empirical tests of these different theories fail to assess adequately the role of key variables such as ‘social disorganization,’ ‘strain,’ ‘cultural values’. . .” This is problematic because most theories predict the immigration-crime relationship is indirect, operating through demographic, economic, and family structures (Kubrin 2013; Ousey & Kubrin 2009). There are exceptions to this, however. A handful of studies have provided empirical support that immigrant concentration tends to reduce crime through various mechanisms such as reinvigorating religious organizations in communities (Harris et al., 2018), home ownership, residential stability, and exposure across residential neighborhoods (Xie & Baumer 2021).

Although previous studies have provided important insights about crime in immigrant neighborhoods, most are cross-sectionally designed, ignoring the possibility of endogeneity. Specifically, immigrants (especially first generation immigrants) may seek to settle in relatively safer areas when they arrive in the U.S. If this is the case, a potential methodological challenge is temporal endogeneity. As a result, evidence from cross-sectional studies may provide more information on how crime affects immigrant concentration in a neighborhood rather than the reverse. A longitudinal study design, therefore, is necessary to account for the temporal reciprocal relationship when studying immigrant communities and crime.

Voluntary Organizations and Neighborhood Crime

Prior studies find that voluntary organizations can impact neighborhood crime control by providing social services, activities, and events, which enhance social ties, cohesion, and informal social control among residents (Bursik & Grasmick 1993; Morenoff et al., 2001; Peterson et al., 2000; Sampson & Groves 1989; Slocum et al., 2013; Triplett et al., 2003; Wo, 2018; Wo et al., 2016). The theoretical background of the crime-controlling effect of voluntary organization derives from social disorganization theory.

Voluntary organizations (or organizational participation) can encourage the formation of social ties and informal social control, and thus reduce neighborhood crime (Bursik & Grasmick 1993; Morenoff et al., 2001; Slocum et al., 2013). In Bursik and Grasmick (1993)’s systemic model, organizations are theorized as a key source of social control by structuring social ties at three levels: Private control, Parochial control, and Public control. Private control is based on intimate ties among close family or friends. Parochial control is exerted through broader social ties of acquaintances, while public control derives from drawing resources from the public domain to improve the neighborhood. Voluntary organizations arguably shape social control at all three levels. As such, a strong voluntary organizational base can offer opportunities for residents to engage in informal surveillance and intervention, which increases neighborhood capability to effectively solve problems including crime.

Voluntary organizations may also exert crime control effects in the neighborhood by providing services and resources to people in need. Thus, they can be effective in the provision of necessary social services to residents (Hipp et al., 2010; Hipp & Yates 2009). Vocational organizations, for instance, can provide job training or information for job searches, which can reduce unemployment rates while human service organizations can offer various social resources for residents in need, including family counseling, services for single parents, care for substance abuse, legal assistance, and more (Wo et al., 2016). Moreover, organizations can provide the locus for recreational activities and events through which local residents build social trust and cohesion. As a consequence, neighborhood organizations have the potential to help reduce residents’ inclinations toward criminal behavior and enhance informal surveillance, thus reducing crime in neighborhoods.

Immigrant-Serving Organizations as a Mediator

The crime-control benefits of voluntary organizations may be even more directly applicable to the setting of immigrant-serving organizations. A primary example of immigrant-serving organizations are ethnic/immigrant service centers that provide necessary resources and help for immigrants to settle in the neighborhood, as well as promote awareness of cultural diversity. Immigrant-serving organizations may have crime-reducing effects by facilitating informal social control through enhanced social networks and ties, especially among immigrants in the neighborhood. This is because they can help immigrants integrate into the neighborhood, and encourage them to participate in local activities. Moreover, immigrant-serving organizations provide a locus for immigrants to build social ties and social networks, which potentially contribute to the formation of informal social control.

According to Cordero-Guzman (2005), immigrant-serving organizations play various roles at different stages of immigrants’ integration such as helping their constituents in maintaining their cultural roots and homeland connections. Furthermore, these organizations promote economic ties, business connections, and social relationships among immigrants. In sum, immigrant-serving organizations can “play a central role in the orientation of immigrants, their reconstruction of social ties, and their adaptation and incorporation process…all aspects of community formation and development, including building community pride and identity” (Cordero-Guzman, 2005, p. 908).

Indeed, a handful of studies find empirical evidence of such a role for immigrant-serving organizations. For instance, De Leon et al. (2009) find that immigrant-serving organizations in the Washington, D.C. metropolitan area, which provide a wide range of programs and services to foreign-born residents (e.g., cultural and language programs maintaining ethnic identity and solidarity), help immigrants by encouraging them to participate civically in their local communities. Chow (1999) also finds that multiservice centers for Chinese immigrants, which deliver services characterized by the DECENT (developmental, educational, comprehensive, empowerment, networking, and teamwork) principle, were successful in providing informal help networks and promoting social ties and trust among Chinese immigrants.

Kubrin et al. (2019) examined whether immigrant/ethnic voluntary organizations, one key measure of institutional completeness, explain lower risk of crime in neighborhoods across the Southern California region. However, they found no relationship between these organizations and neighborhood violent and property crime rates, contrary to theoretical expectations. This limited empirical evidence might be attributable to temporal dynamics associated with these organizations, a question we consider in the current study that employs a longitudinal design. Immigrant/ethnic organizations can undergo changes over time, which can bring about changes in the surrounding landscape and social environment. Indeed, Wo et al. (2016) theorized temporally dynamic aspects of organizations on neighborhood crime, arguing that accounting for the temporal placement of organizations is important. That is, even if a new organization reduces crime over some period of time, this will eventually achieve a new, lower equilibrium level of crime. The implication is that it is important to measure organizations within a longitudinal setting.

Immigrant-Serving Organizations as a Moderator

A competing hypothesis is that rather than operating as a mediator of the immigrant concentration and crime relationship, immigrant organizations operate as a moderator of this relationship, something to which previous research has paid relatively less attention. In this view, the crime-reducing effect of immigrant concentration is enhanced in neighborhoods with a high concentration of immigrant-serving organizations. That is, greater social homogeneity and informal social networks among immigrants will increase informal social control and thus reduce crime in the area, and more immigrant-serving organizations in the neighborhood serve to accentuate such crime control benefits overall.

The argument here is that a greater concentration of immigrant organizations would potentially produce a multiplier effect given the generally heightened informal social control in the area. As such, although immigrant-serving organizations can provide benefits including crime controlling effects, a neighborhood with a greater density of such organizations would provide even more informal social control engendering a stronger negative effect on crime when there is also a large concentration of immigrants. The current study examines both possible mediating and moderating effects of immigrant-serving organizations.

Data and Methods

The study site is the Los Angeles Metropolitan Area (LA Metro Area), which is the urbanized area in the Counties of Los Angeles, Orange, and San Bernardino defined by the U.S. Census Bureau. The LA Metro Area is an ideal setting for the current study because it is racially and ethnically heterogeneous and is one of the largest destinations among diverse groups of immigrants from around the world. Previous studies highlight that traditional immigrant destinations such as the LA Metro Area receive large inflows of immigrants and thus have political, economic, and social structures that foster favorable conditions for immigrants (Portes & Rumbaut 2014; Ramey 2013).

We focus on neighborhoods within the LA Metro Area. We employed ¼ mile block egohoods for the unit of analysis (Hipp and Boessen 2013). An egohood constitutes a ¼ mile radius surrounding a focal Census block as a neighborhood, accounting for spatial patterns of residents in neighborhoods. The study combined four datasets at the egohood level from the National Center of Charitable Statistics (NCCS), the U.S. Census Bureau, Reference USA business data, and ofﬁcial crime data reported by local police departments.

Dependent Variables

The dependent variables are the counts of crime incidents (aggravated assault, robbery, burglary, larceny, and motor vehicle theft) aggregated to the egohood level from 2000 to 2010. Crime data are from the Southern California Crime Study (SCCS). These are official crime data reported by local police agencies with geographic information such as addresses or 100 blocks, which were then classified into Uniform Crime Report (UCR) categories. We used the subset of cities for which we have crime data for years between 2000 and 2010, resulting in a sample of 94,328 egohoods in 110 cities across the Los Angeles Metropolitan Area. Crime events were geocoded to latitude and longitude points using ArcGIS 10.2, and then aggregated to egohoods. The geocoding match rate was 94%, which is quite satisfactory (Ratcliffe, 2004). SCCS data have been used in prior studies (e.g., Hipp & Kubrin 2017; Kim & Hipp 2020; Kubrin et al., 2018).

Immigrant Organization Measures

The main independent variables are the number of immigrant-serving organizations from the National Center for Charitable Statistics (NCCS). The NCCS data provide information on voluntary organizations including addresses and the types of activities/operations. We geocoded all organizations from 2000 to 2010 using ArcGIS 10.2 and aggregated to egohoods. We used NCCS information on an organization’s activities/operations to create a category directly related to social services for immigrants: Immigrant-serving organizations. We also constructed three organizational measures that may indirectly serve immigrants in neighborhoods: (1) Human Services, (2) International and Foreign Affairs, and (3) Civil Rights, Social Action, Advocacy. For more detailed information of the organization types for these four measures, see Appendix Table A1.

Other Neighborhood Measures

We account for other neighborhood structural characteristics using data from the U.S. Census. We use the U.S. Census for 2000 and 2010 and the American Community Survey 5-year estimates (ACS) to create measures for each year from 2007 to 2010 based on the midpoint of the 5-year ACS data (e.g., the 2005–2009 ACS was used to create the 2007 measures) and employ linear interpolation to create measures from 2001 to 2006. To capture the level of socioeconomic status in the neighborhood, we created a concentrated disadvantage index. This factor score includes four measures: percentage at or below 125% of the poverty level, percentage of single-parent households, average household income, and percentage with at least a bachelor’s degree. The last two measures loaded reversely in the factor score. A Herfindahl index based on five racial/ethnic groups (White, African American, Latino, Asian, and other races) was computed to capture racial/ethnic heterogeneity in the neighborhood, and takes the following form:

H = 1 - \sum_{j = 1}^{J} G_{j}^{2}

(1)

where $G_{j}$ indicates the proportion of the population of racial/ethnic group j out of J groups. We included the percent African American and percent Latino to account for racial and ethnic minorities in the neighborhood. To measure residential stability, we utilize the percent home owners. We also include the percent persons aged 15 to 29 to control for the presence of a crime-prone age group in the area. To measure immigrant concentration, we created a measure of the percent foreign born.¹ Finally, previous studies find that non-residential business activities have crime-enhancing effects (Bernasco & Block 2011). To account for criminal opportunity structure, we include the number of total business employees (divided by 1,000) and the number of retail business employees (divided by 1,000) using the Reference USA business data. Summary statistics for variables included in the models are reported in Table 1.

Table 1.

Summary Statistics.

	M	SD
Crime
Robbery	5.70	9.81
Aggravated assault	8.67	13.98
Burglary	10.69	10.41
Larceny	27.76	36.31
Motor vehicle theft	11.62	13.53
Number of organizations
Immigrant-serving organizations	0.11	0.45
Human services	0.46	1.58
International and foreign affairs	0.08	0.35
Civil rights, social action, advocacy	0.06	0.90
Structural characteristics
Concentrated disadvantage	−1.50	9.99
Racial/ethnic heterogeneity	0.46	0.17
Percent Black	7.74	14.46
Percent Latino	39.85	29.45
Percent home owners	53.89	27.65
Percent vacant units	4.98	4.77
Percent aged 15–29	21.62	7.45
Percent immigrants	33.76	15.21
Number of business employees (/1,000)
Retail	0.08	0.21
Total	0.73	1.92

Analytic Strategy

To address potential temporal endogeneity, we use data over 11 years (2000–2010) and employ a longitudinal data analytic strategy using the xtnbreg command in STATA version 15. We estimate random-effects negative binomial regression models including the independent variables time-lagged by 1 year. We include dummy variables for the years to control for unmeasured year-specific effects on crime. We employ a negative binomial regression approach to handle over-dispersion in the count outcomes (Osgood, 2000) with logged population as an exposure term and set the coefficient equal to 1 in all models. The inclusion of the exposure term effectively translates the outcomes to crime rates. The general expression of our longitudinal models is:

E (y_{t}) = e x p (α + B_{1} Y_{t - 1} + B_{2} X_{t - 1} + B_{3} Z_{t - 1} + B_{4} E_{t - 1} + B_{5} K_{t} + ν)

(2)

where $y_{t}$ is the dependent variable (the number of crime events in the current year), $α$ is an intercept, $Y_{t - 1}$ is for logged crime rates in the previous year to control for endogeneity, $X$ represents a matrix of organizational measures in the previous year, Z is a matrix of the structural characteristic variables of the previous year, $E$ is a matrix of the number of business employees in the previous year, K is a matrix of the dummy variables for years, and ν is the overdispersion term following a gamma distribution.

Results

We begin with baseline models using the traditional approach with a measure of the percent foreign born population in egohoods, along with the control variables. As presented in Table 2, we find that immigrant concentration is negatively associated with violent and property crime, consistent with the literature. In particular, we observe that a one standard deviation increase in the percent foreign born population results in 1% (exp (β × SD) − 1) less robbery, 15%, 7%, 5%, and 11% less aggravated assault, burglary, larceny, and motor vehicle theft, respectively, the following year, while accounting for the other measures in the models.

Table 2.

Longitudinal Negative Binomial Regression Models: Immigrant Concentration and Crime.

Variables (1-year lagged)	Robbery	Aggravated assault	Burglary	Larceny	Motor vehicle theft
Percent immigrants	−0.001*	−0.011**	−0.005**	−0.003**	−0.008**
Percent immigrants	−2.260	−52.658	−29.198	−21.917	−45.288
Structural characteristics
Concentrated disadvantage	0.013**	0.012**	−0.007**	−0.016**	0.009**
Concentrated disadvantage	21.885	22.367	−15.740	−43.799	20.456
Racial/ethnic heterogeneity	0.132**	0.206**	0.207**	0.397**	0.343**
Racial/ethnic heterogeneity	6.887	12.209	14.492	31.593	23.935
Percent Black	0.015**	0.018**	0.003**	0.004**	0.006**
Percent Black	68.899	90.464	21.151	26.889	35.850
Percent Latino	0.010**	0.018**	0.002**	0.003**	0.012**
Percent Latino	51.623	101.953	14.300	20.979	81.579
Percent home owners	−0.013**	−0.002**	−0.001**	−0.003**	−0.006**
Percent home owners	−90.186	−16.581	−5.523	−29.127	−57.098
Percent vacant units	0.002**	0.006**	0.009**	0.013**	0.001**
Percent vacant units	5.364	12.630	23.401	47.768	2.361
Percent aged 15–29	−0.018**	−0.013**	−0.008**	−0.007**	−0.011**
Percent aged 15–29	−40.184	−30.225	−23.363	−27.570	−32.428
Number of business employees (/1,000)
Retail business employees	0.183**	0.079**	0.078**	0.052**	0.071**
Retail business employees	30.319	18.563	19.883	19.136	25.237
Total business employees	0.010**	0.019**	−0.002**	0.001*	0.011**
Total business employees	14.937	31.582	−3.273	2.384	19.456
Previous year crime
Crime rate (logged)	2.366**	2.470**	1.919**	1.374**	1.936**
Crime rate (logged)	142.182	128.560	217.673	378.077	217.149
Intercept	−4.551**	−4.814**	−4.657**	−4.498**	−4.640**
Intercept	−219.97	−265.42	−308.44	−352.22	−298.25
N	94,328	94,328	94,328	94,328	94,328

Note. T-values are presented below the coefficients.

Fixed effects of each year (dummy variables) are included but not shown.

p < .05 (two-tail test). **p < .01 (two-tail test).

We next estimate a set of models to examine the relationship between voluntary organizations and crime in neighborhoods. The complete set of regression coefficients is reported in Table 3. We first assess how much smaller the coefficients of percent foreign-born are compared to those in Table 2 as an assessment of a mediation effect. As shown, the coefficients reported in Table 3 are substantially similar to Table 2, suggesting little evidence of a mediation effect of the organizational measures in the models. At the same time, we do observe that immigrant-serving organizations generally appear crime reducing for all types of crime, even if they do not operate as a mediator of the immigrant concentration measure. For example, one more immigrant-serving organization is associated with 3% to 6% lower crime rates 1 year later for the five crime types.

Table 3.

Longitudinal Negative Binomial Regression Models: Immigrant-Serving Organizations and Crime.

Variables (1-year lagged)	Robbery	Aggravated assault	Burglary	Larceny	Motor vehicle theft
Percent immigrants	−0.001*	−0.010**	−0.005**	−0.003**	−0.008**
Percent immigrants	−2.315	−51.294	−27.842	−21.831	−44.824
Number of organizations
Immigrant-serving organizations	−0.060**	−0.042**	−0.056**	−0.022**	−0.031**
Immigrant-serving organizations	−20.544	−13.826	−19.812	−10.710	−11.199
Human services	0.011**	−0.003**	−0.003**	−0.004**	0.003**
Human services	10.411	−2.910	−2.598	−5.345	3.062
International and foreign affairs	0.016**	−0.041**	−0.037**	0.021**	−0.003
International and foreign affairs	4.283	−10.301	−11.352	8.868	−1.014
Civil rights, social action, advocacy	0.011**	−0.010**	−0.001	0.008**	−0.000
Civil rights, social action, advocacy	3.920	−3.843	−0.319	3.721	−0.128
Structural characteristics
Concentrated disadvantage	0.013**	0.011**	−0.007**	−0.016**	0.009**
Concentrated disadvantage	22.400	21.870	−16.265	−43.815	20.359
Racial/ethnic heterogeneity	0.137**	0.207**	0.210**	0.397**	0.344**
Racial/ethnic heterogeneity	7.152	12.299	14.749	31.609	24.030
Percent Black	0.015**	0.018**	0.004**	0.004**	0.006**
Percent Black	68.252	90.619	21.741	26.993	35.765
Percent Latino	0.010**	0.018**	0.002**	0.003**	0.012**
Percent Latino	51.021	100.902	13.162	20.787	81.324
Percent home owners	−0.013**	−0.002**	−0.001**	−0.003**	−0.006**
Percent home owners	−89.750	−17.821	−7.339	−29.530	−57.343
Percent vacant units	0.003	0.006	0.009	0.013	0.001
Percent vacant units	5.976	13.130	24.423	48.083	2.642
Percent aged 15–29	−0.017**	−0.012**	−0.008**	−0.007**	−0.011**
Percent aged 15–29	−39.386	−29.747	−23.339	−27.243	−32.481
Number of business employees (/1,000)
Retail business employees	0.187**	0.080**	0.080**	0.052**	0.071**
Retail business employees	30.830	18.751	20.384	19.312	25.346
Total business employees	0.010**	0.020**	−0.001	0.001**	0.011**
Total business employees	15.454	33.035	−0.908	3.009	19.624
Previous year crime
Crime rate (logged)	2.362**	2.467**	1.915**	1.373**	1.935**
Crime rate (logged)	141.862	128.443	217.492	377.756	217.159
Intercept	−4.558**	−4.811**	−4.652**	−4.497**	−4.638**
Intercept	−220.34	−265.16	−308.34	−352.11	−298.09
N	94,328	94,328	94,328	94,328	94,328

Note. T-values are presented below the coefficients.

Fixed effects of each year (dummy variables) are included but not shown.

p < .05 (two-tail test). **p < .01 (two-tail test).

The results, however, are more mixed when considering other types of neighborhood organizations. For example, although one more human services organization results in about a 0.3% reduction in aggravated assault, burglary, and larceny 1 year later, the same change results in about 0.3% to 1% more motor vehicle thefts and robberies, respectively, 1 year later. Likewise, the presence of more International and Foreign Affairs organizations leads to fewer aggravated assaults and burglaries, but more robberies and larcenies the following year. Finally, we observe that Civil Rights, Social Action, and Advocacy organizations also exhibit a mixed pattern. A greater presence of these organizations in a neighborhood results in fewer aggravated assaults the next year, but increases in burglaries and motor vehicle thefts.

For the final set of analyses, we examine interaction effects between the measures of organizations and the percent foreign-born to test whether moderating effects exist. We test these interactions one at a time by adding an interaction term for each organization type and the percent foreign-born in the models, respectively. We plot the predicted crime rates for these interactions, and graph these interactions in Figures 1 to 5 for the five crime types. We visually display the effect of these four organization types at varying levels of immigrant concentration (Low = −1 SD, Med = mean, and High = +1 SD). Interaction coefficients are reported in Appendix Tables A2 and A3.

Figure 1.

Interactions: percent immigrants and organizations (robbery): (a) interaction: percent immigrants and immigrant/ethnic organizations (robbery), (b) interaction: percent immigrants and human services organizations (robbery), (c) interaction: percent immigrants and international and foreign affairs organizations (robbery), and (d) interaction: percent immigrants and civil rights, social action, advocacy organizations (robbery).

Figure 2.

Interactions: percent immigrants and organizations (aggravated assault): (a) interaction: percent immigrants and immigrant/ethnic organizations (aggravated assault), (b) interaction: percent immigrants and human services organizations (aggravated assault), (c) interaction: percent immigrants and International and foreign affairs organizations (aggravated assault), and (d) interaction: percent immigrants and civil rights, social action, advocacy organizations (aggravated assault).

Figure 3.

Interactions: percent immigrants and organizations (burglary): (a) interaction: percent immigrants and immigrant/ethnic organizations (burglary), (b) interaction: percent immigrants and human services organizations (burglary), (c) interaction: percent immigrants and international and foreign affairs organizations (burglary), and (d) interaction: percent immigrants and civil rights, social action, advocacy organizations (burglary).

Figure 4.

Interactions: percent immigrants and organizations (larceny): (a) interaction: percent immigrants and immigrant/ethnic organizations (larceny), (b) interaction: percent immigrants and human services organizations (larceny), (c) interaction: percent immigrants and international and foreign affairs organizations (larceny), and (d) interaction: percent immigrants and civil rights, social action, advocacy organizations (larceny).

Figure 5.

Interactions: percent immigrants and organizations (motor vehicle theft): (a) interaction: percent immigrants and immigrant/ethnic organizations (motor vehicle theft), (b) interaction: percent immigrants and Human services organizations (motor vehicle theft), (c) interaction: percent immigrants and international and foreign affairs organizations (motor vehicle theft), and (d) interaction: percent immigrants and civil rights, social action, advocacy organizations (motor vehicle theft).

We generally find strong evidence that voluntary organizations moderate the relationship between immigrant concentration and crime. For three of the crime types—aggravated assault, burglary, and larceny—the general pattern is that voluntary organizations in combination with a higher immigrant concentration results in less crime. In Figure 2, we see that neighborhoods with a combination of high immigrant concentration and many of these voluntary organizations report lower aggravated assault (the one exception is for human service organizations, which have no effect). For example, in Figure 2(a) we see on the left side of the graph that with a low immigrant concentration the presence of immigrant-serving organizations makes little difference for aggravated assault; however, with greater immigrant concentration, there is lower crime when there are many of these organizations (the blue line). The pattern is similar for burglaries (Figure 3), as high immigrant concentration neighborhoods that also have many of these organizations have fewer burglaries (the exception is for immigrant-serving organizations, which have no effect). For larcenies (Figure 4) a combination of high immigrant concentration and the presence of immigrant-serving organizations results in the lowest larceny rate. Although neighborhoods with more international and foreign affairs organizations have higher larceny rates, this effect is nearly eliminated if there is high immigrant concentration.

The moderating effects of these organizations for the immigrant concentration and robbery relationship are completely the opposite of these first three crime types. For robbery, the combination of many of these voluntary organizations along with a high immigrant concentration results in higher robbery rates, as seen in Figure 1. For international and foreign affairs organizations, and civil rights, social action and advocacy organizations, the presence of these organizations along with high immigrant concentration results in the highest robbery rates. Although neighborhoods with immigrant-serving organizations have lower robbery rates, this beneficial effect is notably reduced if there is high immigrant concentration. This may reflect that immigrants are, in fact, targets for this acquisitive crime, a point to which we return in the Discussion section. Finally, we note that the interaction effects for motor vehicle theft (Figure 5) are substantively weak.

We briefly describe the results for other neighborhood measures included in the models. Concentrated disadvantage is positively associated with violent crime but negatively associated with property crime, whereas racial/ethnic diversity is negatively associated with all types of crime in the neighborhood. Percent African Americans and percent Latinos in the neighborhood are positively associated with all crime types, while percent home owners and percent persons aged 15 to 29 are negatively associated with all crime types. For the business employee measures, we found that more retail and total business employees results in more crimes, in general. Finally, crime in the previous year predicts more crime next year, consistent with a recent body of studies on the temporal stability of the spatial patterns of crime.

Discussion

Although research has sufficiently examined the association between immigrant concentration and neighborhood crime, reporting typically a null or negative association, relatively fewer studies have focused on trying to explain this association, including examining immigrant-serving organizations and their role in the immigration-crime nexus. The current study theoretically posited that immigrant-serving organizations can yield crime control benefits by structuring social ties and cohesion among immigrants and providing necessary services and resources, which potentially enhance neighborhood informal social control. We also proposed that immigrant-serving organizations can moderate the relationship between immigrant concentration and crime in the neighborhood. Empirically testing each possibility, one primary contribution is that the study more comprehensively examines the relationships among immigrant concentration, voluntary organizations, and neighborhood crime.

One key finding is that immigrant-serving organizations generally have crime-reducing effects for all types of crime. These organizations are mostly ethnic/immigrant service centers that provide necessary resources and aid for immigrants, which potentially increases social cohesion and informal social control. We suspect that such organizations bring crime control benefits in neighborhoods because compared to other types of organizations, they work more directly with immigrants, encouraging them to participate in the local community and to settle in the neighborhood. Moreover, ethnic/immigrant centers can be a locus to build social ties and social networks among immigrants by holding local events, which potentially enhance informal social control. These organizations can also enhance awareness of cultural diversity and minority rights in general, helping to reduce intergroup bias and develop knowledge-based mutual trust between immigrant and non-immigrant residents.

Unlike immigrant-serving organizations that exhibit consistent crime-reducing effects, the other organization types that we expected to have more indirect consequences for immigrants (i.e., Human services; International and foreign affairs; and Civil rights, social action, advocacy) showed more mixed findings. The number of human services organizations was associated with reduced aggravated assaults, burglaries, and larcenies but increased robberies and motor vehicle thefts. One explanation is that some organizations may, instead, provide criminal opportunities by increasing the number of potential offenders and targets in the area.

According to crime pattern theory, voluntary organizations might affect the presence and number of potential offenders and targets in places (Brantingham & Brantingham, 1995). That is, voluntary organizations can increase the number of visitors in the area, which enhances the probability of the convergence of potential offenders and targets at the same time and place. In this sense, some organizations potentially function as crime generators that “particular areas to which large numbers of people are attracted for reasons unrelated to any particular level of criminal motivation they might have or to any particular crime they might end up committing” (Brantingham & Brantingham, 1995, p. 7). This may especially be the case for the crimes of robbery and motor vehicle theft, both of which can occur when a person is out and about.

Another key finding is that we were able to detect moderation effects between immigrant concentration and organizations. We find that high immigrant concentration is associated with lower levels of crime in general, and this effect is enhanced by the presence of more organizations. This underscores the importance of accounting for organizational contexts that accentuate the crime-reducing effect of immigrant concentration in neighborhoods. Specifically, we find that high immigrant concentration is negatively associated with neighborhood crime, and this crime-reducing effect is accentuated to some degree if there are also more organizations (immigrant-serving organizations, in particular). This finding suggests that there will be effective control benefits from immigrant-serving organizations when combined with higher immigrant concentration in the neighborhood. Stated alternatively, crime-reducing effects of immigrant concentration can be reinforced if a sufficient number of immigrant-serving organizations exist in the neighborhood.

For robbery, the interaction effects are more complicated. We find that the control benefits immigrant concentration might have for reducing crime can be undone if there are many organizations (International and foreign affairs organizations, and civil rights, social action and advocacy organizations). That is, in neighborhoods with fewer of these organizations, immigrant concentration reduces the risk of robbery; however, it shows a pronounced crime-enhancing effect in areas with more organizations. These findings may be related to the existing evidence that Latinos are likely to be targeted for robberies, potentially due to their immigrant status and the possibility they are more likely to carry cash given participation in the cash economy (Hipp et al., 2009). This, combined with their presumed greater presence out and about in neighborhoods with more of these organizations, could result in more robberies due to an increase in attractive targets (Brantingham & Brantingham, 2008). Further research is necessary to explore how these organizations impact informal social control and potential guardianship in neighborhoods. Nonetheless, results of the moderating effects confirm the importance of examining the potential interactive association between immigrant-serving organizations, immigrant concentration, and the risk of robbery, simultaneously.

In spite of the contributions of this study, we acknowledge certain limitations. First, although providing important insights for understanding the impact of immigrant-serving organizations, we were unable to pinpoint the mechanisms regarding how they facilitate social cohesion among immigrants, which requires direct measures of informal social control. While it is beyond the scope of the study to measure such mechanisms, we hope future research will attempt to examine the specific mechanisms of informal social control among immigrants to identify why the associations among immigrant-serving organizations, immigrant concentration, and neighborhood crime exist. Another challenge pertains to the classification of organizations. Although we employ four organizational types that are arguably most salient for immigrants, organizations within a category may have dissimilar goals and activities. It is possible that specific organizations within certain categories can have considerably different effects on the dynamics among immigrants, organizations, and neighborhood crime. Thus, future research may want to employ more fine-grained organization classifications.

We also acknowledge that official crime data are not free from measurement error. Immigrants (undocumented, in particular) may be more hesitant to contact formal law enforcement due to fear of being questioned about their status and the possibility of deportation. A lower percentage of crime incidents may be reported in immigrant neighborhoods due to fewer reports from immigrants. Nevertheless, we believe this issue is less of a problem here given our study area—the Los Angeles Metropolitan Area. Note that the largest city in our study site, Los Angeles, is a sanctuary city where municipal policies prohibit police or city employees from questioning individuals about their immigration status. Moreover, Baumer (2002) found no empirical evidence of systematic underreporting issue of Part 1 crime incidents. Finally, the Los Angeles Metropolitan Area has high racial/ethnic heterogeneity and a large immigrant population. Given that this is a traditional immigrant destination, it is an open question for future research to examine if the patterns observed are generalizable to other regions, particularly new immigrant destinations.

In conclusion, we theoretically proposed and empirically examined the associations among immigrant-serving organizations, immigrant concentration, and neighborhood crime. We theorized that the crime-reducing effect of immigrant concentration can be explained by immigrant-serving organizations that can enhance social ties, cohesion, and informal social control among immigrants as well as non-immigrant local residents in neighborhood. The results of the study suggest that immigrant-serving organizations generally offer crime control benefits in neighborhoods. We also find that measures of immigrant-serving organizations moderated the relationship between immigrant concentration and crime, emphasizing the importance of accounting for these organizations when studying the immigrant concentration-neighborhood crime nexus.

Footnotes

Appendix A

Table A3.

Interaction Models: Number of Organizations and Percent Immigrants (Property crime).

	Burglary				Larceny				Motor vehicle theft
	IMM	EEP	EEQ	EER	IMM	EEP	EEQ	EER	IMM	EEP	EEQ	EER
Number of organizations	−0.044**	0.014**	0.021**	0.041**	0.003	0.011**	0.074**	0.011*	−0.006	0.018**	−0.008	0.005
Number of organizations	−6.268	6.482	2.627	6.319	0.596	6.752	12.641	1.965	−0.806	8.085	−0.983	0.843
Percent immigrant	−0.005**	−0.005**	−0.005**	−0.005**	−0.003**	−0.003**	−0.003**	−0.003**	−0.008**	−0.008**	−0.008**	−0.008**
Percent immigrant	−27.454	−26.255	−26.846	−27.196	−21.140	−20.487	−20.786	−21.726	−44.230	−43.680	−44.676	−44.640
Interaction terms	−0.000	−0.000**	−0.001**	−0.001**	−0.001**	−0.000**	−0.001**	−0.000	−0.001**	−0.000**	0.000	−0.000
Interaction terms	−1.882	−8.195	−7.952	−6.758	−5.353	−9.697	−9.776	−0.459	−3.508	−7.527	0.646	−0.959
Intercept	−4.652**	−4.657**	−4.656**	−4.654**	−4.496**	−4.500**	−4.499**	−4.497**	−4.639**	−4.642**	−4.638**	−4.639**
Intercept	−308.335	−308.325	−308.336	−308.363	−351.956	−352.144	−352.084	−352.087	−298.086	−298.121	−297.677	−298.067
N	689,985	689,985	689,985	689,985	689,985	689,985	689,985	689,985	689,985	689,985	689,985	689,985

Note. **p < .01(two-tail test), *p < .05 (two-tail test), †p < .05 (one-tail test), T-values are presented below the coefficients, IMM = Immigrant-serving organizations; EEP = human services; EEQ = international and foreign affairs; EER = civil rights, social action, advocacy.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is supported by NIJ Grant 2019-R2-CX-0056.

ORCID iDs

Young-An Kim

Charis E. Kubrin

Notes

Author Biographies

Young-An Kim is an Assistant Professor in the College of Criminology and Criminal Justice at Florida State University. His research interests focus on various areas such as neighborhoods and crime, criminology of place, immigration and crime, and spatial analysis.

John R. Hipp is a Professor in the department of Criminology, Law and Society at the University of California Irvine. His research interests focus on how neighborhoods change over time, how that change both affects and is affected by neighborhood crime, and the role networks and institutions play in that change. He approaches these questions using quantitative methods as well as social network analysis. He has published substantive work in such journals as American Sociological Review, Criminology, Social Forces, Social Problems, Mobilization, City & Community, Urban Studies, and Journal of Urban Affairs. He has published methodological work in such journals as Sociological Methodology, Psychological Methods, and Structural Equation Modeling.

Charis E. Kubrin is Professor in the Department of Criminology, Law and Society at the University of California Irvine. Her research focuses on neighborhood correlates of crime, with an emphasis on race and violent crime. Recent work examines the immigration-crime nexus across neighborhoods and cities. In addition to her work in peer-reviewed journals, Kubrin is co-author of Researching Theories of Crime and Deviance (Oxford University Press 2008) and Privileged Places: Race, Residence, and the Structure of Opportunity (Lynne Rienner 2006) and co-editor of Introduction to Criminal Justice: A Sociological Perspective (Stanford University Press 2013), Punishing Immigrants: Policy, Politics, and Injustice (New York University Press 2012), and Crime and Society: Crime, 3rd Edition (Sage Publications 2007).

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