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If you cannot access the final versions of the papers, penultimate versions can often be found on the University of California scholarship open access site.

Books

Hipp, John R (2022). The Spatial Scale of Crime: How Physical and Social Distance Drive the Spatial Location of Crime. Routledge. Now available!

—WINNER of the 2023 James Short Senior Scholar Award for best book or paper published, from the Division of Communities and Place in the American Society of Criminology—

Combining insights from two distinct research traditions—the communities and crime tradition that focuses on why some neighborhoods have more crime than others, and the burgeoning crime and place literature that focuses on crime in micro-geographic units—this book expores the spatial scale of crime. Criminologist John Hipp articulates a new theoretical perspective that provides an individual- and household-level theory to underpin existing ecological models of neighborhoods and crime. A focus is maintained on the agents of change within neighborhoods and communities, and how households nested in neighborhoods might come to perceive problems in the neighborhood and then have a choice of exit, voice, loyalty, or neglect (EVLN).

A characteristic of many crime incidents is that they happen at a particular spatial location and a point in time. These two simple insights suggest the need for both a spatial and a longitudinal perspective in studying crime events. The spatial question focuses on why crime seems to occur more frequently in some locations than others, and the consequences of this for certain areas of cities, or neighborhoods. The longitudinal component focuses on how crime impacts, and is impacted by, characteristics of the environment. This book looks at where offenders, targets, and guardians might live, and where they might spatially travel throughout the environment, exploring how vibrant neighborhoods are generated, how neighborhoods change, and what determines why some neighborhoods decline over time while others avoid this fate.

Hipp’s theoretical model provides a cohesive response to the general question of the spatial scale of crime and articulates necessary future directions for the field. The book is essential for students and scholars interested in spatial-temporal criminology.

Paxton, Pamela; Hipp, John R. and Marquart-Pyatt, Sandra (2011). Nonrecursive Models: Endogeneity, Reciprocal Relationships, and Feedback Loops, Sage.

Nonrecursive Models is a clear and concise introduction to the estimation and assessment of nonrecursive simultaneous equation models. This unique monograph gives practical advice on the specification and identification of simultaneous equation models, how to assess the quality of the estimates, and how to correctly interpret results. It also discusses assessment techniques useful for structural equation modeling users.

Reports- MFI

Hipp, John R., Nene Osutei, Benjamin Forthun, Jae Hong Kim, Sugie Lee, and Donghwan Ki. 2022. “Irvine at 50: The changing landscape of housing, commuting, and amenities. MFI Report 2022_1” Metropolitan Futures Initiative (MFI), Irvine, CA.

This MFI report presents how Irvine has matured and transformed over the last several decades. The present report pays close attention to the city’s residents and their living environment (or the quality-of-life metrics). In Chapter 2, we explore the growth of Irvine’s boundaries and its villages. In Chapter 3 we describe the types of housing in Irvine, whether detached single family units, condominiums and townhomes, or various sized apartment complexes. Given these housing patterns, and the presence of so many jobs in Irvine, in Chapter 4 we explore the commuting patterns of residents in the city—both based on distance and time, as well as mode of commute—and compare them to the rest of the region. A feature of Irvine is the presence of many parks along with the small commercial districts in the Village model that the city has followed, and therefore in Chapter 5 we ask whether Irvine residents indeed live closer to parks and commercial areas compared to residents in the rest of the region. Chapter 6 will describe the demographic changes that have occurred within the neighborhoods of Irvine over its history. Finally, Chapter 7 will conclude by summarizing what we have learned in this Report, and consider what the future of Irvine might look like.

Hipp, John R., Jae Hong Kim, Sugie Lee, Benjamin Forthun, Nene Osutei, and Donghwan Ki. 2021. “Irvine at 50: From a Planned Community to a Growing Job Center. MFI Report 2021_2.” Metropolitan Futures Initiative (MFI), Irvine, CA.

This MFI Report presents the evolution of Irvine with a focus on its function as a job center. Although Irvine is well-known as a planned community with villages allowing for a comfortable suburban lifestyle, it nonetheless functions as a large job center to a degree that might surprise many people. Since 1980, it has retained the highest jobs/workers ratio in the Southern California region while also experiencing the fastest job growth in professional service industries throughout the region, particularly in computing and engineering occupations. As a consequence, the city has a much higher composition of high income jobs compared to the region—about 70% to 90% more than the region overall—and therefore fewer low and average income jobs. We explore how Irvine has grown and transformed over the last 50 years with a focus on the number and types of jobs that are located in the city. We also describe where the workers in these jobs are coming from.

Hipp, John R. and Romeo Ignacio. 2021. “Where Are the Highly Educated Moving? A Study of California: MFI Report 2021_1” Metropolitan Futures Initiative (MFI), Irvine, CA.

This Report explores residential mobility patterns among residents of California counties across four decades: 1985-90; 1995-2000; 2005-09, and 2015-19. We focus explicitly on highly educated residents (those with at least a Bachelor’s degree), and where they are moving to and from.

Hipp, John R. and Benjamin Forthun. 2020. “Inequality and Segregation in Southern California; Quarterly Report: 2020_2” Metropolitan Futures Initiative (MFI), Irvine, CA.

This Report studies the changes in inequality and racial composition and segregation in each of the counties in the Southern California region over a 50 year period. Many of the graphs display changes over a 50 year period since 1970, and some reach back even further in time. This Report extends the Report we did 10 years earlier that focused explicitly on Orange County: “The Orange Crush: The Squeezing of Orange County’s Middle Class.” This Report updates the data for the 10 most recent years, and includes information on the other counties in the region.

Kane, Kevin, John R. Hipp, and Benjamin Forthun. 2020. “Rising Inequality and Neighborhood Mixing: Comparing across Metropolitan Areas. Quarterly Report: 2020_1” Metropolitan Futures Initiative (MFI), Irvine, CA.

This Report provides new insights into some of the spatial relationships involved in both neighborhood mixing and regional inequality through an investigation of 381 metropolitan areas in the U.S. in 2010 using advanced measurement strategies and analysis methods.

The study uses a novel neighborhood unit—egohoods—to measure the degree of mixing that occurs within the neighborhoods of these metropolitan areas. It measures mixing based on income, occupational status, and educational achievement.

We compare the level of mixing on these three dimensions across all metropolitan areas in the U.S. in 2010.

John R. Hipp. 2018. “Typology of Southern California neighborhood home values from 1960-2015. Quarterly Report: 2018_1” Metropolitan Futures Initiative (MFI), Irvine, CA.

For our analyses, we use data from 5 U.S. Censuses: 1960, 1970, 1980, 1990, 2000; as well as the American Community Survey (ACS) 5-year data in 2005-09 and 2011-15. We adopt a statistical approach that allows us to create a typology of how neighborhoods change based on their home values over time. Our analyses yielded 16 different classes of neighborhoods. In this Report, we will describe these classes of neighborhoods based on their demographic composition over this period, and where they are located spatially.

In the Appendices, we present the profile of neighborhood types that exist in each of the cities in the region. That is, what percentage of neighborhoods in a city is classified into each class in our typology? We also present the profile of neighborhood types that exist in each of the zip codes in the region. Our neighborhoods (census tracts) are smaller than zip codes, and thus a zip code will be composed of several neighborhoods.

John R. Hipp. 2017. “The neighborhoods we live in: Comparisons by race and income in Southern California. Quarterly Report: 2017_4” Metropolitan Futures Initiative (MFI), Irvine, CA.

In this Report, we are particularly interested in how economic resources and racial/ethnic status might interact to affect access to various types of neighborhoods. Thus, whereas a particular racial/ethnic group may tend to live in a neighborhood with less favorable conditions compared to another group, the question we ask is whether economic resources can diminish this gap? Specifically, do greater economic resources for racial/ethnic groups that are typically more disadvantaged (e.g., Blacks, Latinos) similarly provide them access to similar neighborhoods as they might for more advantaged groups such as White residents?

Kane, Kevin, Jae Hong Kim, and John R. Hipp. 2017. “Business Relocations in Southern California: Which businesses move to (from) which neighborhood? Quarterly Report: 2017_3” Metropolitan Futures Initiative (MFI), Irvine, CA.

Business recruitment has long been one of the most popular strategies for state and local economic development in the US, but little is understood about the precise physical location of business moves, such as the surrounding neighborhoods and how far away a firm relocates. This Report takes a spatially precise approach toward analyzing business relocations in the seven-county Southern California region from 1997-2014. We analyze moves within cities and across city boundaries, as well as the characteristics of the neighborhoods which businesses leave – and move to.

Kevin Kane, Jae Hong Kim and John R. Hipp. 2017. “What makes housing accessible to everyday destinations in Southern California; Quarterly Report: 2017_2“. Metropolitan Futures Initiative (MFI). April 2017.

In this installment of the School of Social Ecology’s Metropolitan Futures Initiative Quarterly Report series, we explore the notion of urban accessibility, defined as the spatial separation between dwelling units and 32 types of destinations including shopping, open space, and public services. Using data on the roughly five million residential land parcels in Southern California, we use network analyses and multilevel regression modeling to determine what it is about homes that make them more or less accessible to a wide variety of destination types.

Hipp, John R., Kevin Kane, and Jae Hong Kim. 2017. “Jobs-housing balance in Egohoods in Southern California; Quarterly Report: 2017_1“. Metropolitan Futures Initiative (MFI). January 2017.

In this installment of the School of Social Ecology’s Metropolitan Futures Initiative Quarterly Report series, we study the relationship between the location of jobs and the residential location of potential workers. We distinguish between two related concepts. First, jobs-housing ratios capture locations that are particularly job-rich versus locations that are job deserts. Second, jobs-housing imbalance captures locations that have a big difference between the number of jobs and workers.

Kane, Kevin, Jae Hong Kim and John R. Hipp. 2016. “Understanding Mixing in Neighborhoods and its Relationship with Economic Dynamism; Quarterly Report: 2016_3.” Metropolitan Futures Initiative (MFI). October 2016.

This is the third installment of the School of Social Ecology’s Metropolitan Futures Initiative Quarterly Report series. This research aims to build a base of knowledge to guide policymakers in improving the overall quality of life in the Southland.

We typically think of neighborhoods as fairly homogeneous areas within cities. Nonetheless, some neighborhoods are highly mixed and others are not based on things like income, racial composition, age, land use, and the type of housing they contain. We analyze mixing across these dimensions in Southern California, then ask what are the consequences of mixing for economic dynamism in neighborhoods.

Kane, Kevin, Jae Hong Kim and John R. Hipp. 2016. “Detecting Job Density Over Time; Quarterly Report: 2016_2.” Metropolitan Futures Initiative (MFI). July 2016.

This is the second installment of the School of Social Ecology’s Metropolitan Futures Initiative Quarterly Report series. This research aims to build a base of knowledge to guide policymakers in improving the overall quality of life in the Southland.

The Los Angeles region is a classic example of a “polycentric metropolis” that is characterized by several centers of job density instead of a single, dominant downtown. This report examines how employment subcenters have been evolving since the 1990s in terms of their changing composition and spatial locations.

Kim, Jae Hong, Kevin Kane and John R. Hipp. 2016. “Understanding Business Churning Dynamics and their Spatial Variation; Quarterly Report: 2016_1.” Metropolitan Futures Initiative (MFI). July 2016.

This is the first installment of the School of Social Ecology’s Metropolitan Futures Initiative Quarterly Report series. This research aims to build a base of knowledge to guide policymakers in improving the overall quality of life in the Southland.

While job growth in a region is crucially important, the dynamic of business creation and business closure can reveal a lot about a region’s economy. Does churning lead to “creative destruction” and a more efficient economy in the long-run or might it have negative consequences, especially in certain neighborhoods? This report analyzes business churning at the neighborhood level across Southern California with an eye toward socio-demographic characteristics and local measures of well-being.

Hipp, John R., Jae Hong Kim, and Victoria Basolo. 2014. “Southern California Regional Progress Report: 2014.” Metropolitan Futures Initiative (MFI). June 2014.

The 2014 Southern California Regional Progress Report was prepared by researchers with the School of Social Ecology’s Metropolitan Futures Initiative, which aims to build a base of knowledge to guide policymakers in improving the overall quality of life in the Southland. It is the second installment in a biennial series of Regional Progress Reports.

Three faculty members, six graduate students and three undergraduates collected data from 17 sources on the region’s demographic, social and economic landscape. It allows for systematic statistical analyses at the county, city, neighborhood and street-block levels over a 20 year period: 1990-2012.

The report draws on this unprecedented data set to explore: 1) why do certain types of land use development occur in some locations rather than others; 2) which land use characteristics and demographic characteristics explain the neighborhoods across the region that exhibit the most economic vitality over time; 3) what land use characteristics around parks explain which parks have the most crime, and which land characteristics explain which blocks near parks have the most crime; 4) how can these statistical models help us understand the possible consequences of future development, using the Great Park area in Irvine as a test case.

The report is intended to serve as a catalyst for evidence-based dialogue that will inform planning for the future. Subsequent biennial reports will continue to monitor trends and expand the domain of coverage to include, for example, health and welfare.

Hipp, John R., Victoria Basolo, Marlon Boarnet, and Doug Houston. 2012. “Southern California Regional Progress Report: 2012.” Metropolitan Futures Initiative (MFI). June 2012.

The inaugural Southern California Regional Progress Report was prepared by researchers with the School of Social Ecology’s Metropolitan Futures Initiative, which aims to build a base of knowledge to guide policymakers in improving the overall quality of life in the Southland.

Five faculty members, 10 graduate students and six undergraduates collected data from 14 sources on the region’s demographic, social and economic landscape. It allows for systematic statistical analyses at the county, city, neighborhood and street-block levels.

The report draws on this unprecedented data set to examine the interrelationships among such community factors as racial/ethnic demographics, employment and economic welfare, housing density and availability, crime and public safety, and land use.

Reports – ILSSC Crime Reports

Hipp, John R., Charis E. Kubrin, and Benjamin Forthun. 2021. “Irvine at 50: A Tale of Continuity and Change.” Irvine Lab for the Study of Space and Crime (ILSSC), Irvine, CA.

The city of Irvine has experienced significant change over its 50-year history, and yet one constant is that crime has remained at a low level, and, if anything, has been declining in the most recent decade. Why is that? In this report, we explore some of the possible factors that may help account for this phenomenon. Although Irvine contains some characteristics that criminologists typically identify in cities with higher crime rates–such as population growth, racial and ethnic diversity, a relatively high concentration of rental housing units, and the presence of a large industrial area–nonetheless, the city has maintained a relatively low level of crime. In fact, for 15 straight years Irvine has been named America’s safest city of its size, based on FBI Uniform Crime Reporting statistics from 18,000 jurisdictions.

Hipp, John R, Charis Kubrin, and ILSSC. 2019. “Crime Report for Southern California 2019.” Irvine Laboratory for the Study of Space and Crime (ILSSC). January 2019.

This is the 5th annual Report describing crime across the cities of the Southern California region. It includes a forecasting component of expected city crime rates in 2019.

Hipp, John R, Charis Kubrin, and ILSSC. 2018. “Crime Report for Southern California 2018.” Irvine Laboratory for the Study of Space and Crime (ILSSC). December 2017.

This is the 4th annual Report describing crime across the cities of the Southern California region. It includes a forecasting component of expected city crime rates in 2018.

Hipp, John R, Charis Kubrin, and ILSSC. 2017. “Crime Report for Southern California 2017.” Irvine Laboratory for the Study of Space and Crime (ILSSC). December 2016.

This is the 3rd annual Report describing crime across the cities of the Southern California region. It includes a forecasting component of expected city crime rates in 2017.

Hipp, John R, Charis Kubrin, and ILSSC. 2016. “Crime Report for Southern California 2016.” Irvine Laboratory for the Study of Space and Crime (ILSSC). December 2015.

This is the 2nd annual Report describing crime across the cities of the Southern California region.

Hipp, John R, Charis Kubrin, and ILSSC. 2015. “Crime Report for Southern California 2015.” Irvine Laboratory for the Study of Space and Crime (ILSSC). December 2014.

This is the 1st annual Report describing crime across the cities of the Southern California region.

Reports – other

Hipp, John R., George E. Tita, Luis Daniel Gascon and Aaron Roussell. 2010. “Ethnically Transforming Neighborhoods and Violent Crime Among and Between African-Americans and Latinos: A Study of South Los Angeles.” Report to the Haynes Foundation, October 2010.

Abstract: ‘This research study examines the phenomena of interracial violence in South Los Angeles. We use the area that the Los Angeles Police Department (LAPD) designates as “South Bureau” to define our research boundaries and focus specifically on several communities within this larger designation for more detailed analysis. Despite the current demographic shift whereby Latinos are supplanting African Americans as the dominant resident racial/ethnic group, and contrary to popular media portrayals of an impending “race war” between these two groups, we find little evidence that interracial crime is a dominant trend in South LA. Instead, both lethal and non-lethal violence continues to concentrate within racial/ethnic groups: Latinos mainly victimize Latinos and blacks mainly victimize blacks. In South LA, the majority of intraracial crime continues to be concentrated among African Americans.”

Hipp, John R. (2009). The Orange Crush: The Squeezing of Orange County’s Middle Class, Center for Inequality and Social Justice.

Abstract: “Exploring data over a thirty year period, this study documents the demographic and economic changes in Orange County over that period. Orange County has grown dramatically since its days as a basin for the Valencia Orange—both in population and geography. There has been a boom of growth since the post WWII days of 1940. The bulk of the growth has taken place since the beginning of 1970, with the population more than doubling in size.

Many people came here to buy a home and find a good-paying job—in short—to realize the American Dream. However, over the past 35 years, that realization has become much less attainable due to policies that have shaped Orange County into an hourglass economy.

Most housing is no longer affordable to low- and middle-income families. The cost of housing in Orange County remains among the highest in the nation
Orange County’s population continues to increase, but affordable jobs are becoming harder to find. The jobs with the most openings are low-skilled and low-paying.”

Hipp, John R., George E. Tita, and Lyndsay N. Boggess. 2007. “Measuring Intra- and Inter-group violent crime for African Americans and Latinos in South Bureau, Los Angeles.” Report to the Los Angeles Police Department (LAPD), September 2007.

Abstract: “Does violent crime occur more frequently among same race individuals, or across different races? To hear recent media reports, one might suspect that inter-group violent crime (that is, violent events between individuals of different races) happen most frequently. Is this true? This report addresses this question.”

Hipp, John R. (2007). “Resident Perceptions of Crime: How Similar Are They to Official Crime Rates?” U.S. Census Bureau Center for Economic Studies (CES) Discussion Paper CES-WP-07-10:36.

Abstract: “This study compares the relationship between official crime rates and residents’ perceptions of crime in census tracts. Employing a unique dataset that links household level data from the American Housing Survey metro samples over a period of 25 years (1976-2000) with official crime rate data for census tracts in selected cities during selected years, this large sample provides considerable ability to generalize the findings. I find that residents’ perception of crime is most strongly related to official rates of tract violent crime. Models simultaneously taking into account both violent and property crime consistently found that property crime actually has a negative effect on perceived crime. Among types of violent crime, the robbery rate is consistently related to higher levels of perceived crime in the tract, whereas it appears a structural shift occurred in the mid-1980s in which aggravated assault and murder rates now impact perceptions of crime, even when taking into account the robbery rate.”

Neighborhoods/communities/crime papers

Hipp, John R. and Cheyenne Hodgen. (2024). “The ecology of business environments and consequences for crime.” Criminology. Forthcoming.

Abstract: “Existing research typically focuses on how certain types of business establishments are associated with the location of crime on street blocks. However, studies in this genre often do not account for the general business context of the block on which a business is located. The present study uses a large sample of blocks in Southern California to test whether the context of businesses matter. We assess whether a nonlinear relationship exists between the total businesses on a block and crime, whether there are differences based on broad categories of businesses—consumer-facing businesses, blue collar businesses, and white collar businesses—and whether the mixing of businesses on a block impacts crime. The study finds strong evidence that blocks with more business mixing have higher levels of crime. A one standard deviation increase in business mixing is associated with 35 to 95 percent more crime. The relationship between business mixing and crime is moderated by the size of the population on the block. There is also evidence of differences in relationships with crime between consumer-facing and white- or blue-collar businesses. There is only modest evidence that specific business types are related to crime levels after accounting for this general business context.”

Lee, Sugie, Dong Hwan Ki, Jae Hong Kim, and John R. Hipp. (2024). “Analyzing Nonlinearity and Threshold Effects between Street-Level Built Environments and Local Crime Patterns: An Interpretable Machine Learning Approach.” Urban Studies. Forthcoming.

Abstract: “Despite the substantial number of studies on the relationships between crime patterns and built environments, the impacts of street-level built environments on crime patterns have not been definitively determined due to the limitations of obtaining detailed streetscape data and conventional analysis models. To fill these gaps, this study focuses on the nonlinear relationships and threshold effects between built environments and local crime patterns at the level of a street segment in the City of Santa Ana, California. Using Google Street View (GSV) and semantic segmentation techniques, we quantify the features of the built environment in GSV images. Then, we examine the nonlinear relationships and threshold effects between built environment factors and crime by applying interpretable machine learning (IML) methods. While the machine learning models, especially Deep Neural Network (DNN), outperformed negative binomial regression in predicting future crime events, particularly advantageous was that they allowed us to obtain a deeper understanding of the complex relationship between crime patterns and environmental factors. The results of interpreting the DNN model through IML indicate that most streetscape elements showed nonlinear relationships and threshold effects with crime patterns that cannot be easily captured by conventional regression model specifications. The non-linearities and threshold effects revealed in this study can shed light on the factors associated with crime patterns and contribute to policy development for public safety from crime.”

Kubrin, Charis E., Xiaoshuang Iris Luo, and John R. Hipp. (2024). “Immigration and Crime: Is the Relationship Nonlinear?” British Journal of Criminology. Online.

Abstract: “Research finds that immigration and crime are not related across neighbourhoods, contrary to social disorganization theory and consistent with the immigration revitalization thesis. This research, however, is largely silent as to any possible nonlinear effects. Yet social theory offers sound reasons for why the immigration–crime association may be nonlinear; explanations, including immigrant/ethnic enclave theory and immigrant victimization theory, underscore potential concentration effects—albeit in different ways. Using a novel dataset with information on crime in over 15,000 neighbourhoods across a diverse range of US cities, we examine whether or not the immigration–crime association is nonlinear. We find that for both violent and property crime, a nonlinear relationship best captures the relationship. In additional analyses, we determine the theoretical perspective with which the findings are most consistent.”

+Zheng, Huixin, Nicholas Marantz, Jae Hong Kim, and John R. Hipp. (2024). “Dissolving Districts: Did Property Values Fall When California Terminated Its Redevelopment Agencies?” Economic Development Quarterly. Online.

Abstract: “California pioneered the use of tax increment finance (TIF) to promote redevelopment, but in 2012 all redevelopment agencies in the state were simultaneously (and unexpectedly) dissolved, essentially eliminating TIF-supported redevelopment in California. This paper uses hedonic methods to analyze changes in residential property values associated with the dissolution of TIF districts in five cities in northern Orange County. If TIF is necessary for (re)development in the TIF districts, then the unexpected elimination of TIF-funded redevelopment should have reduced property values. The authors find that, within the study area, the elimination of TIF was not associated with decreases in residential values within TIF districts, and quality-adjusted home prices in and near former TIF districts continued to grow at a rate at least comparable to citywide rates in the aftermath of the dissolution. These findings raise the concern that TIF may function as a tool for revenue capture before the TIF districts reach the anticipated expiration dates. In the absence of significant regulatory safeguards, TIF may be used to capture revenue from overlapping governments, instead of serving as an engine of economic development.”

Hipp, John R. and Jae Hong Kim. (2024). “Persistent Racial Diversity in Neighborhoods across the U.S.: Where Does It Occur?” Population, Space and Place. Online.

Abstract: “While there is a long history of racial change in the United States, and how this plays out within neighbourhoods, a key recurring question is whether some neighbourhoods are able to achieve and maintain racial diversity, or whether they simply transition to dominance by a new racial group. We test and find evidence of 1631 neighbourhoods across the United States from 1980 to 2020 that exhibit persistent racial diversity (PRD), and assess where this PRD occurs. Our analysis shows that PRD neighbourhoods (PRDNs) are likely to be present in counties with more economic opportunities–that is, counties with higher socioeconomic status (SES). PRDNs themselves, however, tend to be relatively lower SES neighbourhoods within relatively higher SES counties, suggesting that affordable locations surrounded by more economic opportunities may have served as an environment in which diversity can persist over a long period of time in the United States.”

+Luo, Xiaoshuang Iris, John R. Hipp, and Adam Boessen. (2024). “Parolee Concentration, Parolee Embeddedness, and the Reciprocal Relationship with Crime Rates: A Longitudinal Study of Neighborhoods and Reentry.” Journal of Criminology. Online.

Abstract: “Drawing on recent scholarship on mass incarceration and prisoner re-entry, this study examines the reciprocal relationship between returning parolees and neighbourhood crime rates in five large cities in Texas. Besides the more common approach of counting the number of people on parole in communities (parolee concentration), we propose a novel approach for measuring people on parole by capturing their exposure in the community as parolee embeddedness (i.e., the cumulative number of days that people on parole resided in the neighbourhood). Results show that parolee concentration has a significant positive effect on both violent and property crime, but parolee embeddedness is significantly associated with reductions in violent and property crime. Our findings detect different effects depending on the measurement of people on parole and their community context, illustrating the need to better understand the dynamics of parolee re-entry in the era of mass incarceration.”

+Ha, Jaehyun, Sugie Lee, Jae Hong Kim, and John R. Hipp. (2024). “Do employment centers matter? Consequences for commuting distance in the Los Angeles region, 2002-2019.” Cities. 145: 1-15.

Abstract: “The presence of employment centers provides the potential for reducing commuting distance. However, employment centers have distinct attributes, which may lead to varied impacts on commuting outcomes. We examine how proximity to employment centers can influence commuting distance with consideration of the heterogeneity of employment centers and workers. Specifically, we consider various attributes of employment centers related to location, persistency, job density, industry diversity, and size and analyze their impacts on the commuting patterns of low- and high-income workers using panel (2002-2019) data. Our analysis of the Los Angeles region shows that increasing proximity to the nearest employment center decreases commuting distance even after controlling for the job attributes located in the neighborhood of workers. The results further suggest that employment centers are not equal in terms of their impact on commute distance and that their impact is different for commuters from different income groups. Our findings contribute to the literature by deciphering the location and attributes of employment centers that may exert a greater impact on commuting patterns.”

Kim, Young-An and John R. Hipp. (2023). “Does Street Social Activity Impact Crime? An Analysis in New York City.” Crime & Delinquency. Online.

Abstract: “The current study examines the relationship between the level of social activity and crime in place. We theoretically conceptualized the social activity as a combination of two essential elements of vitality and diversity. Our results suggest that level of social activity has a crime enhancing effect on both violent and property crime. We also found that there are positive interaction effects between the measures of vitality and diversity. This study contributes to the field by introducing a theoretically driven concept of social activity and empirically showing how the two dimensions of social activity—vitality and diversity—have independent effects that multiplicatively impact the level of crime at a location.”

Lakon, Cynthia M. and John R. Hipp. (2024). “Socio-Spatial Health Disparities in Covid-19 Cases and Deaths in U.S. Skilled Nursing Facilities over 30 Months.” American Journal of Infection Control. 52(1): 3-14.

Abstract: “Background
This study investigated whether socio-spatial factors surrounding United States skilled nursing facilities related to Covid-19 case counts among residents, staff, and facility personnel and deaths among residents.
Methods
With data on 12,403 United States skilled nursing facilities and Census data we estimated multilevel models to assess relationships between facility and surrounding area characteristics from June 2020 to September 2022 for cumulative resident and facility personnel case counts and resident deaths.
Results
Facilities with more Black or Latino residents experienced more cases incident rate ratios (IRR = 1.005; 1.004) and deaths (IRR = 1.008) among residents during the first 6 months of the pandemic but were no different thereafter. Facilities with more racial and ethnic heterogeneity and percent Black or Latino in the surrounding buffer experienced more Covid-19 cases and deaths in the first 6 months, but no such differences were observed in the subsequent 24 months. Facilities surrounded by higher percent Latino consistently experienced more cases among staff and facility personnel over the study period (IRR = 1.006; 1.001).
Conclusions
Findings indicated socio-spatial health disparities in cases among residents, staff, and facility personnel in the first 6 months of the pandemic, with some disparities fading thereafter. This pattern likely suggests the importance of the adoption and adherence to pandemic-related safety measures in skilled nursing facilities nationwide.”

Ramos, Javier, Sylwia Piatkowska, Young-An Kim, and John R. Hipp. (2024). “Immigrant-Ethnic Activity Space (IEAS), Ex-prisoner Concentration, and Recidivism.” Crime & Delinquency. 70(11): 3016-3050.

Abstract: “Prior research measures immigration by only accounting for where immigrants live. We argue that this approach misses the activity spaces of immigrants, which also impact crime but are not always located in their residential communities. The present study uses an alternative definition of immigration—immigrant-ethnic activity space (IEAS)—that accounts for both the residential location and routine activities of immigrants. Additionally, given the crime-reducing effects associated with immigration, including for high-risk populations, we consider whether IEAS protects against reoffending for ex-inmates. Using Cox hazards models, we examine the relationship between IEAS and recidivism across the communities of five ethnic groups. Results show that the IEAS of all groups are inversely associated with recidivism. However, ex-prisoner concentration amplifies the risk for recidivism in the IEAS of some groups.”

+Thomas, Loring J., Peng Huang, Xiaoshuang Iris Luo, John R. Hipp, and Carter T. Butts. (2024). “Marginal-preserving Imputation of Three-way Array Data in Nested Structures, with Application to Small Areal Units.” Sociological Methodology. 54(1): 157-191.

Abstract: “There is conflicting evidence in the literature regarding the relationship between residents’ social networks and their perceptions of neighborhood collective efficacy. This study proposes addressing this challenge with several theoretically motivated refinements using a large spatially stratified sample of residents in the Western United States. First, we consider various distinct types of social relationships, and find that our novel measure of neighborhood safety ties is much more strongly related to perceived collective efficacy than is a measure of socializing relationships. Second, we explicitly account for the spatial distribution of ties, and find that it is not just local neighborhood ties that increase a sense of cohesion or informal social control, but that more spatially distant ties also matter. Third, we make a distinction between urban and rural areas, finding that in rural areas, social ties from an even broader area are associated with stronger feelings of collective efficacy.”

Kim, Jae Hong, Dong Hwan Ki, Nene Osutei, Sugie Lee, and John R. Hipp. 2023. “Beyond visual inspection: Capturing neighborhood dynamics with historical Google Street View and deep learning-based semantic segmentation.” Journal of Geographical Systems Online.
Abstract: “While street view imagery has accumulated over the years, its use to date has been largely limited to cross-sectional studies. This study explores ways to utilize historical Google Street View (GSV) images for the investigation of neighborhood change. Using data for Santa Ana, California, an experiment is conducted to assess to what extent deep learning-based semantic segmentation, processing historical images much more efficiently than visual inspection, enables one to capture changes in the built environment. More specifically, semantic segmentation results are compared for (1) 248 sites with construction or demolition of buildings and (2) two sets of the same number of randomly selected control cases without such activity. It is found that the deep learning-based semantic segmentation can detect nearly 75% of the construction or demolition sites examined, while screening out over 60% of the control cases. The results suggest that it is particularly effective in detecting changes in the built environment with historical GSV images in areas with more buildings, less pavement, and larger-scale construction (or demolition) projects. False-positive outcomes, however, can emerge due to the imperfection of the deep learning model and the misalignment of GSV image points over years, showing some methodological challenges to be addressed in future research.”

Hipp, John R., Adam Boessen, Carter T. Butts, Nicholas N. Nagle, and Emily J. Smith. 2023. “The Spatial Distribution of Neighborhood Safety Ties: Consequences for Perceived Collective Efficacy?” Journal of Urban Affairs Forthcoming.

Kim, Jae Hong, Kevin Kane, Young-An Kim, and John R. Hipp. (2023). “Business churning and neighborhood instability: Is there a link?” International Regional Science Review. Online.

Abstract: “Much of the work concerning economic dynamism has focused on its aggregate-level implications, while there have been rising concerns about business displacement at the community or neighborhood level. In this article, we analyze this important (restructuring) process using detailed establishment-level business information and explore how it manifests itself across space within the Los Angeles—Long Beach—Santa Ana, CA Urbanized Area. We also investigate the association between business churning and neighborhood-level housing vacancy rates to understand the implications of dramatic changes in the business landscape. We find that housing vacancies are more likely to increase in urban neighborhoods with a higher establishment death rate, while the creation of new businesses can mitigate the association to some extent. We also detect substantial variation across decades not only in the spatial distribution of business churning but also in its association with housing vacancy rates, suggesting the evolving nature of business dynamics and their implications.”

Hipp, John R., Sugie Lee, Dong Hwan Ki, and Jae Hong Kim. (2022). “How concentrated disadvantage moderates the built environment and crime relationship on street segments in Los Angeles.” Criminology & Criminal Justice. Online.

Abstract: “Criminological theories have posited that the built environment impacts where crime occurs; however, measuring the built environment is difficult. Furthermore, it is uncertain whether the built environment differentially impacts crime in high-disadvantage neighborhoods. This study extracts features of the built environment from Google Street View images with a machine learning semantic segmentation strategy to create measures of fences, walls, buildings, and greenspace for over 66,000 street segments in Los Angeles. Results indicate that the presence of more buildings on a segment was associated with higher crime rates and had a particularly strong positive relationship with robbery and motor vehicle theft in low-disadvantage neighborhoods. Notably, fences and walls exhibited different relationships with crime. Walls, which do not allow visibility, were strongly negatively related to crime, particularly for robbery and burglary in high-disadvantage neighborhoods. Fences, which allow visibility, were associated with fewer robberies and larcenies, but more burglaries and aggravated assaults. Fences only exhibited a negative relationship with violent crime when they were located in low-disadvantage neighborhoods. The results highlight the importance of accounting for the built environment and the surrounding level of disadvantage when exploring the micro-location of crime.”

Hipp, John R., Lyndsay N. Boggess, and Alyssa W. Chamberlain. (2022). “Locating Offenders: Introducing the Reverse Spatial Patterning Approach.” Computers, Environment and Urban Systems. 98: 1-10.

Abstract: “Objectives: Current strategies for locating where offenders live either focus exclusively on individual suspects or generalize to entire neighborhoods. However, better estimates of where offenders are located may improve models of the ecological distribution of crime, and forecasts of the locations of future crime incidents.
Methods: We propose a novel reverse spatial patterning (RSP) strategy that estimates where offenders may live based on the spatial locations of crime events. We rely on a distance decay function – based on the consistent finding that offenders do not travel far to commit crime – and Hipp’s (2016) general theory of spatial crime patterns, to work backwards from the locations of actual crime events to make predictions about where offenders may live in subsequent years. We then use these estimates in models predicting crime locations. We create two versions of the RSP: one which assumes everyone is equally likely to offend, and another that creates an estimate assuming disproportionate offending across persons.
Results: We test the effectiveness of our proposed strategy for these two measures using offense and arrest data from St. Petersburg, FL, and assess how well they predict the location of offenders (proxied by arrestees) and future crime events. We find consistent evidence that our RSP strategy provides better predictions of the locations of where offenders are located and also future crime incidents across a variety of crime types compared to existing strategies.
Conclusion: The RSP approach is useful for creating estimates of where offenders live, which allow for better predictions of the locations of future crime incidents. These better forecasts will allow for more efficient allocation of police resources and targeted crime suppression efforts.”

Hipp, John R., Sugie Lee, Jae Hong Kim, and Benjamin Forthun. (2022). “Employment Deconcentration and Spatial Dispersion in Metropolitan Areas: Consequences for Commuting Patterns.” Cities. 131: 1-14

Abstract: “There is interest in understanding which characteristics of metropolitan areas impact the length of time or distance residents spend commuting. We utilize two measures recently introduced to the urban literature capturing distinct dimensions of employment decentralization –the level of employment deconcentration and employment spatial dispersion in metropolitan areas – to assess how they are related to commuting patterns across metropolitan areas. These two measures of urban/metropolitan spatial structure avoid challenges in identifying “job centers” and allow for a more systematic investigation of how employment decentralization affects commuting patterns. Furthermore, we detect key differences for the implications of these measures for commuting across 329 US metropolitan regions based on their population size. We find that greater employment deconcentration in very small MSAs is associated with longer commute times and distances, whereas greater employment deconcentration in large or very large MSAs is associated with shorter commutes. And whereas spatial dispersion is not related to commute times in very small MSAs, greater spatial dispersion is associated with longer commutes in very large MSAs. This study also shows that the spatial pattern of employment in regions, captured by these new measures, is associated with the proportion of very short and very long duration commutes.”

Kim, Young-An, James Wo, and John R. Hipp. (2023). “Estimating Age-graded Effects of Businesses on Crime in Place.” Justice Quarterly. Online

Abstract: “Although prior studies have examined the association between the presence of various types of business facilities and crime in place, less attention has been paid to how the effects of businesses can be temporally different based on their age. We focus on four consumer-facing business types: 1) retail, 2) service, 3) restaurant, and 4) food and drug stores. For each type, we construct block level measures of the number of businesses, the average business age, and the standard deviation of business age. We estimate fixed-effects negative binomial regression models to test the effects of these measures on crime in blocks, controlling for a range of factors known to be associated with crime rates. The average age of businesses was robustly associated with lower crime rates and such pattern was most pronounced in blocks with a greater business presence.”

Hipp, John R. and Alyssa W. Chamberlain. (2022). “Who Leaves and Who Enters? Flow Measures of Neighborhood Change and Consequences for Neighborhood Crime.” Journal of Research in Crime & Delinquency. Forthcoming.

Abstract: “Objectives: Longitudinal studies of the relationship between neighborhood change and changes in crime typically focus exclusively on the net level of change in key socio-demographic characteristics.
Methods: We instead propose a demographic accounting strategy that captures the composition of neighborhood change: our measures capture which types of people are more likely to leave, stay, or enter the neighborhood. We use data for 3,325 tracts in the Southern California region over nearly two decades of 2000-2010 and 2010-2017 and construct flow measures based on race/ethnicity; the length of residence of owners and renters; the age structure.
Results: These flow measures improve the predictive power of the models—implying important theoretical insights. Neighborhoods with higher percentages of middle-aged residents who recently entered the neighborhood exhibit larger increases in violent and property crime. The relative stability of those in the highest crime-prone ages (aged 15-29) is associated with the largest increases in violent and property crime. The loss of Black and Asian residents decreased crime while moderate outflows of Latinos increased crime. The mobility of long- and short-term renters was related to crime changes.
Conclusions: This new technique will likely encourage further theoretical innovation for the neighborhoods and crime literature.”

Hipp, John R. and Xiaoshuang Iris Luo. (2022). “Improving or Declining: What are the Consequences for changes in local crime?” Criminology. Forthcoming.

Abstract: “Whereas existing ecology of crime research frequently uses a cross-sectional design, an open question is whether theories underlying such studies will operate similarly in longitudinal research. Using latent trajectory models and longitudinal data from the Southern California region over a 10-year period (2000-2010), we explore this question and assess whether the changes in key measures of social disorganization theory are related to changes in violent or property crime through three possible relationships: 1) a monotonic relationship; 2) an asymmetric relationship; 3) one in which any change increases crime. We find evidence that measures can exhibit any of these three possible relationships, highlighting the importance of not assuming monotonic relationships. Most frequently observed are asymmetric relationships, which we posit are simultaneously capturing more than one theoretical process of neighborhood and crime. Specific findings include asymmetric relationships between concentrated disadvantage, residential instability, population, change in racial/ethnic minority composition and crime. We consider how this strategy opens a needed area of future research assessing how measures for other theories operate as neighborhoods change.”

Kim, Young-an, John R. Hipp, and Charis E. Kubrin. (2022). “Immigrant Organizations and Neighborhood Crime.” Crime & Delinquency. Forthcoming.

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.”

Hipp, John R. and Jae Hong Kim. (2022). “Persistent Racial Diversity in Neighborhoods: What Explains it and what are the Long-term Consequences?” Urban Geography. Forthcoming.

Abstract: “We explore neighborhoods in Southern California from 1980-2010 that exhibit persistent racial diversity (PRD) and the consequences of this PRD. Initial exploratory analyses show that the racial composition of the area surrounding the neighborhood in 1980 is associated with which neighborhoods become PRDs. Our primary analyses compare how PRD neighborhoods change over time (1980-2010) based on several socio-demographic measures to a matched group of non-PRD neighborhoods that had similar characteristics in 1980. The key finding is that PRD neighborhoods improved more on per capita income and percent in poverty compared to their matched tracts from 1980-2010. We also found that there was not a single route to persistent diversity, but rather a myriad of pathways through which racial/ethnic diversity can persist over a long time period at the neighborhood level.”

Kim, Young-an and John R. Hipp. (2021). “Density, Diversity, and Design: Three Measures of the Built Environment and the Spatial Patterns of Crime in Street Segments.” Journal of Criminal Justice. Forthcoming.

Abstract: “Purpose: The current study simultaneously examines the effects of three different characteristics of the built environment based on the theoretical conceptualizations of density, diversity, and design (3D).
Methods: By using data of 211,155 street segments in the Southern California metropolitan region across 130 cities, we estimated a set of negative binomial regression models including the 3D measures of the built environment, while accounting for the effects of social structural characteristics of place. Furthermore, the current study examines the potential moderating effects of each 3D feature on crime.
Results: We found that higher levels of business density are consistently associated with higher levels of crime. The diversity measure is associated with moderately higher levels of crime, whereas the design measure consistently exhibited a negative relationship with crime. Furthermore, we found that the diversity and design measures moderated the business density relationship with crime.
Conclusion: The results of the current study suggest that it is necessary to examine the different types of physical environment simultaneously to understand the effects of physical environment and the spatial patterns of crime.”

+Luo, Xiaoshuang Iris, John R. Hipp, and Carter T. Butts. (2021). “Does the Spatial Distribution of Social Ties Impact Neighborhood and City Attachment? Differentials among Urban/Rural Contexts.” Social Networks. Forthcoming.

Abstract: “Using social network data from the American Social Fabric Project (ASFP), this study examines how the distance to social alters may lead to different perceptions of neighborhood and city attachment among urban versus rural residents, and considers which types of relations play influential roles in shaping attachment. Overall, a key finding is that having more local neighborhood ties is positively associated with attachment at both the neighborhood level and city level, holding for any social relationship in our sample and for urban and rural environments. Notably, long distance ties are not irrelevant for attachment; rather, we see that long distance ties are associated with greater neighborhood and city attachment. Among different social relations measured, neighborhood safety ties consistently show the strongest positive relationship with neighborhood and city attachment. Surprisingly, we find that the spatial distribution of social ties appears more consequential for attachment in the rural sample than it does in the urban sample. Further, geographically dispersed ties also matter for urban versus rural settings: physically close and midrange core ties are associated with weaker attachment for urban residents, whereas they do not affect rural residents’ perceptions of attachment.”

+Williams, Seth A. and John R. Hipp. (2021). “The Shape of Neighborhoods to Come: Examining Patterns of Gentrification and Holistic Neighborhood Change in Los Angeles County, 1980 – 2010.” Environment and Planning A: Economy and Space. Forthcoming.

Abstract: “The present study examines holistic neighborhood change in Los Angeles County across three decades between 1980 and 2010. Using Census tract data, we conduct a latent class analysis to identify classes of neighborhood change for each decade according to housing dynamics, age structure, racial-ethnic composition and churning, and socioeconomic characteristics, and describe latent classes indicative of gentrification. Further, we assess the degree to which tracts experience sustained or repeated gentrification over the 30 year period. In line with more recent conceptualizations of gentrification as a broad urban process, we find that gentrification occurs in a wide range of neighborhoods, and manifests itself differently according to shifts in population characteristics, with many tracts experiencing more than one successive period of gentrification over the 30 year period.”

Kubrin, Charis E., Nicholas Branic, and John R. Hipp. (2021). “(Re)conceptualizing Neighborhood Ecology in Social Disorganization Theory: From a Variable-Centered Approach to a Neighborhood-Centered Approach.” Crime & Delinquency. Forthcoming.

Abstract: “Shaw and McKay advanced social disorganization theory in the 1930s, kick-starting a large body of research on communities and crime. Studies emphasize individual impacts of poverty, residential instability, and racial/ethnic heterogeneity by examining their independent effects on crime, adopting a variable-centered approach. We use a “neighborhood-centered” approach that considers how structural forces combine into unique constellations that vary across communities, with consequences for crime. Examining neighborhoods in Southern California we: (1) identify neighborhood typologies based on levels of poverty, instability, and heterogeneity; (2) explore how these typologies fit within a disorganization framework and are spatially distributed across the region; and (3) examine how these typologies are differentially associated with crime. Results reveal nine neighborhood types with varying relationships to crime.”

Kim, Jae Hong, Sugie Lee, John R. Hipp, and Dong Hwan Ki. (2021). “Decoding Urban Landscapes: Google Street View and Measurement Sensitivity.” Computers, Environment and Urban Systems 88.

Abstract: “While Google Street View (GSV) has been increasingly available for large-scale examinations of urban landscapes, little is known about how to use this promising data source more cautiously and effectively. Using data for Santa Ana, California, as an example, this study provides an empirical assessment of the sensitivity of GSV-based streetscape measures and their variation patterns. The results show that the measurement outcomes can vary substantially with changes in GSV acquisition parameter settings, specifically spacing and direction. The sensitivity is found to be particularly high for some measurement targets, including humans, objects, and sidewalks. Some of these elements, such as buildings and sidewalks, also show highly correlated patterns of variation indicating their covariance in the mosaic of urban space.”

Boessen, Adam and John R. Hipp. (2021). “The network of neighborhoods and geographic space: Implications for joblessness while on parole.” Journal of Quantitative Criminology. Forthcoming.

Abstract: “Objectives: Few studies have examined the consequences of neighborhoods for job prospects for people on parole. Specifically, networks between neighborhoods in where people commute to work and their spatial distributions may provide insight into patterns of joblessness because they represent the economic structure between neighborhoods. We argue that the network of neighborhoods provides insight into the competition people on parole face in the labor market, their spatial mismatch from jobs, as well as their structural support.
Methods: We use data from people on parole released in Texas from 2006 to 2010 and create a network between all census tracts in Texas based on commuting ties from home to work. We estimate a series of multilevel models examining how network structures are related to joblessness.
Results: The findings indicate that the structural position of neighborhoods has consequences for people on parole’s joblessness. Higher outdegree, reflecting neighborhoods with more outgoing ties to other neighborhoods, was consistently associated with less joblessness, while higher indegree, reflecting neighborhoods with more incoming ties into the neighborhood, was associated with more joblessness, particularly for Black and Latino people on parole. There was also some evidence of differences depending on geographic scale.
Conclusions: Structural neighborhood-to-neighborhood networks are another component to understanding joblessness while people are on parole. The most consistent support was shown for the competition and structural support mechanisms, rather than spatial mismatch.”

Hipp, John R., Sugie Lee, Dong Hwan Ki, and Jae Hong Kim. (2021). “Measuring the Built Environment with Google Streetview and Machine Learning: Consequences for Crime on Street Segments.” Journal of Quantitative Criminology. Forthcoming

Abstract: “Objectives: Despite theoretical interest in how dimensions of the built environment can help explain the location of crime in micro-geographic units, measuring this is difficult.
Methods: This study adopts a strategy that first scrapes images from Google Street View every 20 meters in every street segment in the city of Santa Ana, CA, and then uses machine learning detect features of the environment. We capture eleven different features across four main dimensions, and demonstrate that their relative presence across street segments considerably increases the explanatory power of models of five different Part 1 crimes.
Results: The presence of more persons in the environment is associated with higher levels of crime. The auto-oriented measures—vehicles and pavement—were positively associated with crime rates. For the defensible space measures, the presence of walls has a slowing negative relationship with most crime types, whereas fences did not. And for our two greenspace measures, although terrain was positively associated with crime rates, vegetation exhibited an inverted-U relationship with two crime types.
Conclusions: The results demonstrate the efficacy of this approach for measuring the built environment.”

Wickes, Rebecca, John R. Hipp, and Jacqueline Laughland-Booy. (2022). “Ethnic diversity, social identity, and social withdrawal: Investigating Putnam’s constrict thesis.” The Sociological Quarterly. 63(3): 516-540

Abstract: “Since Putnam introduced his constrict thesis in 2007, many researchers have established that ethnic diversity lowers perceptions of social cohesion, at least in the short term. The connection between ethnic diversity and social behavior, however, is less certain. In this paper we draw on social distance and social identity theories to empirically test if ethnic diversity encourages behaviors linked to social withdrawal. Using data from a longitudinal panel study of urban communities in Australia, we examine the influence of social distance on neighborhood ties, neighborly exchange, and civic engagement and assess if an individual’s social identity (ethnic or civic) strengthens or weakens these relationships. We find individuals that endorse an ethnic identity are more likely to engage in social withdrawal behaviors. Withdrawal is also more likely in neighborhoods where individuals distort the presence of minorities.”

Kim, Young-An and John R. Hipp. (2021). “Small local versus Non-Local: Examining the Relationship between Locally Owned Small Business and Spatial Patterns of Crime.” Justice Quarterly. Forthcoming.

Abstract: “In the current study, we theorized that businesses in place are subject to two processes: a crime generator effect in which they heighten crime due to increased opportunities and a crime inhibition effect in which certain types of businesses can increase guardianship capability. We explicitly compare the different effects of local vs. non-local and small vs. large businesses on crime in street segments using the data in cities across the Los Angeles metropolitan region by estimating a set of negative binomial regression models for small local, large local, small non-local, and large non-local consumer facing businesses (Retail, Restaurants, Food/Drug Stores, and Services) for violent and property crime. Although we found that most of the business coefficients were positive, local businesses, and particularly small local businesses, have considerably smaller crime-enhancing effects for both violent and property crime.”

Hipp, John R., Jae Hong Kim, and Benjamin Forthun. (2021). “Proposing New Measures of Employment Deconcentration and Spatial Dispersion across Metropolitan Areas in the U.S.” Papers in Regional Science. 100(3): 815-841.

Abstract: “A well-known challenge is measuring employment concentration across metropolitan areas and analysing the evolving spatial structure. We introduce a new approach that avoids identifying “job centres” and conceptualizes the distribution of employment based on two dimensions: (1) employment deconcentration; and (2) spatial dispersion of high employment locations. We apply this framework to study 329 US metropolitan regions based on 1 sq km. grid cells. We find diverse trajectories of metropolitan restructuring between 2000 and 2010, and substantial variation across regions in employment concentration. The new framework enables researchers to compare metropolitan regions to gain insights into the dynamic nature of metropolitan spatial structure.”

John R. Hipp. (2021). “Typology of Home Value Change Over Time: Growth Mixture Models in Southern California Neighborhoods from 1960-2010” Journal of Urban Affairs. Forthcoming.

Abstract: “This study uses U.S. Census data on average home values in Southern California census tracts from 1960 to 2010. Using growth mixture modeling (GMM), 26 unique groups are detected capturing nonlinear change in neighborhood relative home values over this study period. There were seven broad patterns of changing home values: (1–3) decline and then rise (at high, mid, and low portions of the home value distribution); (4) rise and then decline; (5–6) a monotonic increase (either above or below the region average); and (7) a monotonic decrease. Multinomial regression models found that covariates exhibited a much stronger effect for distinguishing between the average level of home values in neighborhoods over the study period, rather than how home values changed over time.”

+Kim, Young-an and John R. Hipp. (2021). “Both sides of the street: Introducing Measures of Physical and Social Boundaries Based on Differences across Sides of the Street, and Consequences for Crime” Journal of Quantitative Criminology. Forthcoming.

Abstract: “Objectives: Although previous studies have theorized the importance of physical and social boundaries (edges) in understanding crime in place, the relationship between edges and the level of crime has been less studied empirically. The current study examines the effects of physical and social boundaries on crime in street segments.

Methods: To empirically measure boundaries, we introduce an approach of looking at the differences of land use (physical boundary), socioeconomic status, or racial composition (social boundaries) on both sides of a street segment. We estimated a series of negative binomial regression models in which measures of the physical and social boundaries are included while controlling for the effects of structural characteristic and the conventional physical boundary measures of highways, parks, and rivers.

Results: We observed that there are positive relationships between all three of these boundary measures and violent and property crimes. The results indicated that physical and social boundaries are important to consider in understanding the spatial patterns of crime. Moreover, the current study confirmed the moderating effects between social and physical boundaries.

Conclusions: Our results indicate that although much empirical research focuses solely on physical boundaries, our measures of social and physical boundaries have important consequences for the spatial location of crime, and therefore are worthy of further research.”

Hipp, John R. and Seth A. Williams (2020). “Accounting for Meso- or Micro-Level Effects When Estimating Models using City-level Crime Data: Introducing a Novel Imputation Technique” Journal of Quantitative Criminology.

Abstract: “Objectives: Criminological scholars have long been interested in how macro-level characteristics of cities, counties, or metropolitan areas are related to levels of crime. The standard analytic approach in this literature aggregates constructs of interest, including crime rates, to the macro geographic units and estimates regression models, but this strategy ignores possible sub-city-level processes that occur simultaneously.
Methods: One solution uses multilevel data of crime in meso-level units within a large number of cities; however, such data is very difficult and time intensive to collect. We propose an alternative approach which utilizes insights from existing literature on meso-level processes along with meso-level socio-demographic measures in cities to impute crime data from the city to the smaller geographic units. This strategy allows researchers to estimate full multilevel models that estimate the effects of macro-level processes while controlling for sub-city level factors.
Results: We demonstrate that the strategy works as expected on a sample of 91 cities with meso-level data, and also works well when estimating the multilevel model on a sample of cities different from the imputation model, or even in a different time period.
Conclusions: The results demonstrate that existing studies aggregated to macro units can yield considerably different (and therefore potentially problematic) results when failing to account for meso-level processes.”

Hipp, John R. (2020). “Simulating Spatial Crime Patterns: What do we Learn in Standard Ecological Studies of Crime?” Journal of Criminal Justice. 70.

Abstract: “Objectives: Given the spatial nature of offender and target behavior, what do standard ecological studies of crime aggregating measures to different geographic units actually tell us?
Methods: This study used a simple stylized simulation model of crime patterns based on offenders, an exponential distance decay function based on Euclidean distance to capture their typical mobility patterns when committing offenses, and immobile targets.
Results: There were four key results. First, although a measure of targets can explain much of the variance in micro-level models, knowing where offenders live, and their typical distances traveled to offending, greatly improved the model performance. Second, accounting for the typical spatial movement of offenders before aggregating to larger units produces better results based on explanatory power. Third, the explanatory power of targets alone was much weaker when aggregating to larger units despite the fact that the simulated model of crime events was entirely based on micro processes, highlighting that variance explained is distinct from causal processes. Fourth, knowing how offenders behave in target-rich versus target-poor environment impacts the results considerably.
Conclusions: The findings demonstrated the consequences of a spatially explicit model of offender and target behavior for ecological studies of crime that aggregate measures to geographic units that are either at the micro-, meso-, or macro-level.”

+Thomas, Loring J., Peng Huang, Fan Yin, Junlan Xu, Zack W. Almquist, John R. Hipp, and Carter T. Butts. (2022). “Geographical Patterns of Social Cohesion Drive Disparities in Early COVID Infection Hazard.” Proceedings of the National Academy of Sciences 119(12).

Abstract: “The uneven spread of COVID-19 has resulted in disparate experiences for marginalized populations in urban centers. Using computational models, we examine the effects of local cohesion on COVID-19 spread in social contact networks for the city of San Francisco, finding that more early COVID-19 infections occur in areas with strong local cohesion. This spatially correlated process tends to affect Black and Hispanic communities more than their non-Hispanic White counterparts. Local social cohesion thus acts as a potential source of hidden risk for COVID-19 infection.”

+Thomas, Loring J., Peng Huang, Fan Yin, Xiaoshuang Iris Luo, Zack W. Almquist, John R. Hipp, and Carter T. Butts. (2020). “Spatial Heterogeneity Can Lead to Substantial Local Variations in COVID-19 Timing and Severity.” Proceedings of the National Academy of Sciences. Aug 18, 2020

Abstract: “Standard epidemiological models for COVID-19 employ variants of compartment (SIR) models at local scales, implicitly assuming spatially uniform local mixing. Here, we examine the effect of employing more geographically detailed diffusion models based on known spatial features of interpersonal networks, most particularly the presence of a long-tailed but monotone decline in the probability of interaction with distance, on disease diffusion. Based on simulations of unrestricted COVID-19 diffusion in 19 U.S. cities, we conclude that heterogeneity in population distribution can have large impacts on local pandemic timing and severity, even when aggregate behavior at larger scales mirrors a classic SIR-like pattern. Impacts observed include severe local outbreaks with long lag time relative to the aggregate infection curve, and the presence of numerous areas whose disease trajectories correlate poorly with those of neighboring areas. A simple catchment model for hospital demand illustrates potential implications for health care utilization, with substantial disparities in the timing and extremity of impacts even without distancing interventions. Likewise, analysis of social exposure to others who are morbid or deceased shows considerable variation in how the epidemic can appear to individuals on the ground, potentially affecting risk assessment and compliance with mitigation measures. These results demonstrate the potential for spatial network structure to generate highly non-uniform diffusion behavior even at the scale of cities, and suggest the importance of incorporating such structure when designing models to inform healthcare planning, predict community outcomes, or identify potential disparities.”

+Gerlinger, Julie and John R. Hipp (2020). “Schools and Neighborhood Crime: The Effects of Dropouts and High-Performing Schools on Juvenile Crime” The Social Science Journal. Forthcoming.

Abstract: “Most scholars have focused on the simple presence of schools when examining their influence on neighborhood crime. This paper instead examines two school characteristics that might affect local juvenile crime. More specifically, this study uses negative binomial and logistic regression models to estimate the effects of high school dropouts and high-performing schools on juvenile violent crime in Orange County, CA. An integrated theoretical approach based on social bond and routine activity theories is utilized to guide this research. Findings from this study suggest that dropouts are associated with increases in aggravated assault and robbery incidents, but high-performing schools do not significantly affect these crime types. Finally, the models predicting juvenile crime are compared with models predicting all crime (both juveniles and adults), supporting our argument that juvenile crime is the theoretically appropriate crime measure.”

Hipp, John R., Young-An Kim, and James Wo (2020). “Micro-scale, meso-scale, macro-scale, and temporal scale: Comparing the relative importance for robbery risk in New York City” Justice Quarterly. Forthcoming.

Abstract: “We compare the relative importance of four dimensions for explaining the micro location of robberies: 1) the micro spatial scale of street segments; 2) the meso spatial scale surrounding the street segment; 3) the temporal pattern, and 4) the macro-scale of the surrounding 2.5 miles. This study uses crime, business, and land use data from New York City and aggregates it to street segments and hours of the day. Although the measures capturing the micro-scale of the street segment explained the largest amount of unique variance, the measures capturing temporal scale across hours of the day (and weekdays) explained the next largest amount of unique variance. The measures of the characteristics in the 2.5 miles macro scale explained the next largest amount of unique variance, and combined with the measures at the meso-scale explained nearly as much of the variance as the street segment measures.”

Hipp, John R. (2020). “Neighborhood Change from the Bottom Up: What are the Determinants of Social Distance between New and Prior Residents?” Social Science Research. 86.

Abstract: “An important source of neighborhood change occurs when there is a turnover in the housing unit due to residential mobility and the new residents differ from the prior residents based on socio-demographic characteristics (what we term social distance). Nonetheless, research has typically not asked which characteristics explain transitions with higher social distance based on a number of demographic dimensions. We explore this question using American Housing Survey data from 1985 to 2007, and focus on instances in which the prior household moved out and is replaced by a new household. We focus on four key characteristics for explaining this social distance: the type of housing unit, the age of the housing unit, the length of residence of the exiting household, and the crime and social disorder in the neighborhood. We find that transitions in the oldest housing units and for the longest tenured residents result in the greatest amount of social distance between new and prior residents, implying that these transitions are particularly important for fostering neighborhood socio-demographic change. The results imply micro-mechanisms at the household level that might help explain net change at the neighborhood level.he street network configuration and crime in street segments.”

+Kim, Young-an and John R. Hipp. (2019). “Pathways: Examining Street Network Configurations, Structural Characteristics and Spatial Crime Patterns in Street Segments.” Journal of Quantitative Criminology. Forthcoming.

Abstract: “Objectives: Although theories suggest that street network configurations (pathways) are important factors for understanding the spatial patterns of crime, relatively less attention has been paid to the association between the physical configuration of the street network and the level of crime in place. Consequently, we employed the concept of betweenness centrality in the context of the street network to empirically measure the potential foot traf-fic passing through a given street segment.
Methods: We introduce a methodological refinement by accounting for the characteristics of origin and destination of each potential trip (where travelers are from and tend to go) using residential population in origins and destinations and the number of various types of business employees in destinations. Moreover, we posit that the effect of potential foot traf-fic into a given street segment will be moderated by certain social environmental character-istics such as socioeconomic status of place. By using data on a sample of 300,000 street segments in the Southern California region across 130 cities, we estimate a set of negative binomial regression models including the betweenness measures.
Results: Our results show that betweenness centrality has a curvilinear relationship with violent and property crime: At lower levels, increases in betweenness results in increased crime, yet the pattern becomes crime-reducing at higher values of the betweenness meas-ure. We also found that the pattern is moderated by the socioeconomic status of the street segment.
Conclusions: The current study highlights that there is an important relationship of the physical environment in terms of the street network configuration and crime in street segments.”

+Kim, Young-an, John R. Hipp, and Charis E. Kubrin. (2019). “Where They Live and Go: Immigrant Ethnic Activity Space and Neighborhood Crime in Southern California.” Journal of Criminal Justice. 64(1): 1-12.

Abstract: “The current study advances the literature by simultaneously accounting for the geographic location of immigrant residences and the location of ethnic businesses, and considers their proximity to one another. We argue our alternative measure, which we term Immigrant Ethnic Activity Space (IEAS), more fully captures the ecology of immigrant communities. Using data from several sources to capture neighborhoods in the Southern California region, we constructed IEAS measures for the seven largest ethnic groups in the region, including groups from Mexico, China, Korea, Vietnam, Philippines, Armenia, and El Salvador. These measures reflect where immigrants live and where they go for various ethnic-related routine activities, as well as the distance between the two. We estimated a set of negative binomial regression models to examine the effects of the IEAS measures on neighborhood violent and property crime rates. We find that our IEAS approach is distinct from traditionally-employed measures of immigrant neighborhoods. We also find that IEAS measures have negative associations with both violent and property crime, in general. The current study proposes and develops an alternative approach to conceptualizing immigrant neighborhoods, which more closely aligns with extant theory and should be considered in future research on the immigration-crime nexus.”

Hipp, John R. and Seth A. Williams. (2019). “Advances in Spatial Criminology: The Spatial Scale of Crime.” Annual Review of Criminology. Forthcoming.

Abstract: “This essay takes stock of recent advances, as well as enduring and emerging challenges, in the area of spatial criminology. Although the notions of place and space are fundamentally intertwined, spatial criminology is distinct in its attempt to measure and theorize explicitly spatial processes and relationships. This essay highlights three key themes. First, the use of increasingly smaller geographic units in recent research creates even greater need to account for spatial behavior of persons when studying the location of crime. Second, although the explosion of spatially precise data in recent years presents exciting possibilities, we argue that theory is falling behind in guiding us in analyzing these new forms of data, and explicitly inductive approaches should be considered to complement existing deductive strategies. Third, an important direction for spatial criminology in the next decade is considering the extent to which micro- and meso-level processes operate invariantly across different macro contexts.”

Hipp, John R., Seth A. Williams, Young-an Kim, and Jae Hong Kim. (2019). “Fight or Flight? Crime as a Driving Force in Business Failure and Business Mobility.” Social Science Research. 82: 164-180.

Abstract: “A growing body of research has documented the consequences of neighborhood crime for a myriad of individual, household, and community outcomes. Given that neighborhood businesses figure into the link between neighborhood structure and crime as sources of employment or sites for neighbor interaction, the present study examines the extent to which neighborhood crime is associated with the survival, mobility, and destination locations of businesses in the subsequent year. Using business data from Reference USA (Infogroup 2015) and crime data from the Southern California Crime Study (SCCS) we assess this question for neighborhoods across cities in the Southern California region. We find that in general, higher violent and property crime are significantly associated with both business failure and mobility, and that higher crime in a destination neighborhood reduces the likelihood that a business locates there. We also present findings specific to industries, and discuss the implications of our findings for future research.”

Kane, Kevin and John R. Hipp. (2019). “Rising Inequality and Neighborhood Mixing in U.S. Metro Areas.” Regional Studies. Forthcoming.

Abstract: “Superstar cities with high-paying creative-class jobs, venture capital, and innovation are thought to be more unequal. We analyze mixing in neighbourhoods by income, education and occupation, relating this intra-urban measure with regional productivity indicators. Using non-overlapping census units and a machine-learning estimation technique that iterates over all combinations of economic, business, housing and cultural indicators, we identify ‘ingredients’ associated with economically and socially diverse neighbourhoods. Broad support is not found that neighbourhoods in superstar regions are less mixed; however, overrepresentation in creative occupations stymies mixing as does a combination of weak economic fundamentals with high shares of new housing.”

+Kim, Young-an and John R. Hipp. (2019). “Street Egohood: A New Perspective of Measuring Neighborhood Based on Urban Streets.” Journal of Quantitative Criminology. Forthcoming.

Abstract: “Objectives: The current study proposes an approach that accounts for the importance of streets while at the same time accounting for the overlapping spatial nature of social and physical environments captured by the egohood approach. Our approach utilizes overlapping clusters of streets based on the street network distance, which we term street egohoods.

Methods: We used the street segment as a base unit and employed two strategies in clustering the street segments: (1) based on the First Order Queen Contiguity; and (2) based on the street network distance considering physical barriers. We utilized our approaches for measuring ecological factors and estimated crime rates in the Los Angeles metropolitan area.

Results: We found that whereas certain socio-demographics, land use, and business employee measures show stronger relationships with crime when measured at the smaller street based unit, a number of them actually exhibited stronger relationships when measured using our larger street egohoods. We compared the results for our three-sized street egohoods to street segments and two sizes of block egohoods proposed by Hipp and Boessen (Criminology 51(2):287–327, 2013) and found that two egohood strategies essentially are not different at the quarter mile egohood level but this similarity appears lower when looking at the half mile egohood level. Also, the street egohood models are a better fit for predicting violent and property crime compared to the block egohood models.

Conclusions: A primary contribution of the current study is to develop and propose a new perspective of measuring neighborhood based on urban streets. We empirically demonstrated that whereas certain socio-demographic measures show the strongest relationship with crime when measured at the micro geographic unit of street segments, a number of them actually exhibited the strongest relationship when measured using our larger street egohoods. We hope future research can use egohoods to expand understanding of neighborhoods and crime.”

Hipp, John R. and Young-an Kim. (2019). “Temporal and Spatial Dimensions of Robbery: Differences across Measures of the Physical and Social Environment.” Journal of Criminal Justice. 60(1): 1-12.

Abstract: “Objectives: Given the evidence that crime events exhibit both a spatial and a temporal pattern, we explore whether certain social and physical environment characteristics have varying relationships with crime at different times of day.
Methods: We assess this temporal question using a flexible nonlinear parametric approach on a large sample of street segments (and surrounding spatial area) in Southern California.
Results: There are different temporal and spatial patterns for key measures. The presence of total employees in the surrounding area is associated with a reduced robbery risk during the daytime, but not at night. The risk of a robbery is elevated on a high retail segment on weekends during the daytime, and on high restaurant segments into the early evening on weekends. Furthermore, the presence of retail and restaurants in the surrounding area (evidence of shopping districts) was associated with elevated robbery risk in the afternoon and well into the evening.
Conclusion: These different temporal patterns indicate the possibility of different mechanisms in operation.”

+Williams, Seth and John R. Hipp. (2018). “How Great and How Good? Third Places, Neighbor Interaction, and Cohesion in the Neighborhood Context.” Social Science Research. 77(1): 68-78.

Abstract: “Though Ray Oldenburg’s (1989) notion of “third places”, or places conducive to sociality outside of the realms of home and work, has received both scholarly and popular attention over the past several decades, many of the author’s central claims remain empirically untested. The present study considers the association between neighborhood third places, cohesion and neighbor interaction. Drawing on various literatures regarding interaction in public space and neighborhood use-value, we consider how the role of third places might vary according to neighborhood socioeconomic context. Using data from Wave I of the Los Angeles Family and Neighborhood Study (LAFANS) and data on third places from the point-based business data of ReferenceUSA, we test the effect of third places on cohesion and neighbor interaction across neighborhood poverty strata. We find support for the hypothesis that third places are associated with greater cohesion and neighbor interaction, and that neighbor interaction mediates the relationship between third places and cohesion in poor neighborhoods.”

Boessen, Adam and John R. Hipp (2018). “Parks as Crime Inhibitors or Generators: Examining Parks and the Role of their Nearby Context”. Social Science Research. 76(1): 186-201.

Abstract: “Although neighborhood studies often focus on the presence of some particular entity and its consequences for a variety of local processes, a frequent limitation is the failure to account more broadly for the local context. This paper therefore examines the role of parks for community crime, but contributes to the literature by testing whether the context of land use and demographics nearby parks moderate the parks and crime relationship. A key feature of our approach is that we also test how these characteristics explain crime in the park, nearby the park, and in other neighborhoods in the city with data from nine cities across the United States (N= 109,808 blocks). We use multilevel Poisson and negative binomial regressions to test our ideas for six types of street crime. Our findings show that nearby land uses and socio-demographic characteristics are a key driver of crime being located within the park or nearby the park. Our results also show a clear distance decay pattern for the impact of various land uses and socio-demographics nearby parks. The results emphasize a need for research to consider the broader socio-spatial context in which crime generators/inhibitors are embedded.”

+Contreras, Christopher and John R. Hipp. (2019). “Drugs, Crime, Space, and Time: A Spatiotemporal Examination of Drug Activity and Crime Rates.” Justice Quarterly. Forthcoming.

Abstract: “To take stock of the neighborhood effects of drug activity, we combined theoretical insights from the drugs and crime and communities and place literatures in examining the longitudinal relationship between drug activity and crime rates at more spatially and temporally precise levels of granularity, with blocks as the spatial units and months as the temporal units. We found that drug activity on a block one month “pushes” assaultive violence into surrounding blocks the next month. Integrating perspectives form social disorganization theory with Zimring and Hawkins’ (1997) contingency causation theory, we also found that the economic resources and residential stability of the “the larger social environment”—that is, the surrounding quarter-mile egohood area—moderate drug activity’s block-level relationship to crime. These results suggest that drug activity increases assaultive violence and serious acquisitive crime rates on structurally advantaged blocks, producing a significant ecological niche redefinition for such blocks relative to others in Miami-Dade County, Florida.”

Kubrin, Charis, Young-an Kim, and John R. Hipp. (2019). “Institutional Completeness and Crime Rates in Immigrant Neighborhoods.” Journal of Research in Crime and Delinquency Forthcoming.
Abstract: “A growing body of research finds that immigration has a null or negative association with neighborhood crime rates. We build on this important literature by investigating the extent to which one theory, institutional completeness theory, may help explain lower crime rates in immigrant communities across the Sothern California region. Specifically, we test whether the two key measures of institutional completeness—the presence of immigrant/ethnic voluntary organizations in the community and the presence and diversity of immigrant/ethnic businesses in the community—account for lower crime rates in some immigrant communities. Compiling a tract-level dataset utilizing various data sources, we estimate negative binomial regression models predicting violent and property crime levels that include measures of institutional completeness while controlling for a range of neighborhood correlates of crime. We also account for possible endogeneity by estimating instrumental variable models. The results reveal very limited support for institutional completeness theory. Several possible explanations for these findings are discussed.”

+Branic, Nicholas and John R. Hipp. (2018). “Growing Pains or Appreciable Gains? Latent Classes of Neighborhood Change, and Consequences for Crime in Southern California Neighborhoods.” Social Science Research. Forthcoming.

Abstract: “This study explored the dynamic nature of neighborhoods using a relatively novel approach and data source. By using a nonparametric holistic approach of neighborhood change based on latent class analysis (LCA), we have explored how changes in the socio-demographic characteristics of residents, as well as home improvement and refinance activity by residents, are related to changes in neighborhood crime over a decade. Utilizing annual home mortgage loan data in the city of Los Angeles from the years 2000–2010, we 1) conducted principle components factor analyses using measures of residential in-migration and home investment activities; 2) estimated LCA models to identify classes of neighborhoods that shared common patterns of change over the decade; 3) described these 11 classes; 4) estimated change-score regression models to assess the relationship of these classes with changing crime rates. The analyses detected six broad types of neighborhood change: 1) stability; 2) urban investors; 3) higher-income home buyers; 4) in-mover oscillating; 5) oscillating refinance; 6) mixed-trait. The study describes the characteristics of each of these classes, and how they are related to changes in crime rates over the decade.”

Wickes, Rebecca, Renee Zahnow, John R. Hipp, and Jonathan Corcoran. (2019). “Neighbourhood Social Conduits and Resident Social Cohesion.” Urban Studies 56(1): 226-248.

Abstract: “Given the importance of the neighbourhood context for residents’ social cohesion, the current study examines the association between types of social and non-social places on three indicators of social cohesion: neighbour networks, social cohesion and neighbourhood attachment. We spatially integrate data from the census, topographic databases and a 2012 survey of 4132 residents from 148 neighbourhoods in Brisbane, Australia, and employ multilevel models to assess whether the variation in resident reports of social cohesion is attributable to land uses that function as neighbourhood social conduits. We also consider the degree to which neighbourhood fragmentation affects our indicators of social cohesion. Our findings reveal that even after controlling for the socio-demographic context of the neighbourhood and a range of individual and household control variables, residents’ reports of social cohesion are significantly associated with the types of social conduits, the diversity of land use and the degree of neighbourhood fragmentation.”

Hipp, John R., Young-an Kim, and Kevin Kane. (2019). “The effect of the physical environment on crime rates: Capturing housing age and housing type at varying spatial scales.” Crime & Delinquency. 65(11): 1570–1595.

Abstract: “This study introduces filtering theory from housing economics to criminology and measures the age of housing as a proxy for deterioration and physical disorder. Using data for Los Angeles County in 2009 to 2011, negative binomial regression models are estimated and find that street segments with older housing have higher levels of all six crime types tested. Street segments with more housing age diversity have higher levels of all crime types, whereas housing age diversity in the surrounding ½-mile area is associated with lower levels of crime. Street segments with detached single-family units generally had less crime compared with other types of housing. Street segments with large apartment complexes (five or more units) generally have more crime than those with small apartment complexes and duplexes.”

Hipp, John R. and Rebecca Wickes. 2018. “Problems, Perceptions and Actions: An Interdependent Process for Generating Informal Social Control.” Social Science Research 73:107-125.

Abstract: “Using two waves of survey data for residents in neighborhoods in Brisbane, this study explores the interdependent relationship between residents’ perceptions of neighboring, cohesion, collective efficacy, neighborhood disorder, and the actions they take to address these problems. Our longitudinal results show that residents’ perceived severity of a problem helps explain engaging in activity to address the problem. People loitering appeared to be the most galvanizing problem for residents, but had particularly deleterious effects on perceptions of cohesion and collective efficacy. We also find that residents who perceive more neighboring in their local area engage in more public and parochial social control activity and residents who live in collectively efficacious neighborhoods are more likely to engage in parochial social control action. Furthermore, residents who themselves perceive more collective efficacy in the neighborhood engage in more parochial or public social control during the subsequent time period. Importantly, we find strong evidence that residents update their sense of collective efficacy. Perceiving more problems in the neighborhood, and perceiving that these problems are increasing, reduced perceptions of neighboring and collective efficacy over time.”

Hipp, John R., Seth Williams, and Adam Boessen. 2018. “Disagreement in Assessing Collective Efficacy: The Role of Social Distance.” Socius 4: 1-16. [Freely available for download]

Abstract: “Whereas existing research typically treats variability in residents’ reports of collective efficacy and neighboring as measurement error, the authors consider such variability as of substantive interest in itself. This variability may indicate disagreement among residents with implications for the neighborhood collectivity. The authors propose using a general measure of social distance based on several social dimensions (rather than measures based on a single dimension such as racial/ethnic heterogeneity or income inequality) to help understand this variability in assessments. The authors use data from wave I (2001) of the Los Angeles Family and Neighborhood Survey (n = 3,570) to aggregate respondents into egohoods of two different sizes: quarter-mile and half-mile radii. Consistent with expectations, neighborhoods with higher levels of general social distance have higher variability in reports of neighboring and the two components of collective efficacy, cohesion and informal social control.”

Wickes, Rebecca and John R. Hipp. 2018. “The spatial and temporal dynamics of neighborhood informal social control and crime.” Social Forces. Forthcoming.

Abstract: “Social disorganization theory is one of the most widely tested theories in criminology, yet few studies consider the temporal and spatial dynamics of neighborhood composition, neighborhood informal social control, and crime. To better understand these relationships, we use census data, police data, and three survey waves of data from a unique longitudinal dataset with over 4,000 respondents living across 148 neighborhoods in an Australian city undergoing rapid population growth. We employ cross-lagged reciprocal feedback models to test the central tenets of social disorganization theory and its contemporary advances for three crime types: violent crime, property crime, and drug crime. Further, we examine the reciprocal relationship between neighborhood composition, three components of informal social control (neighborhood social ties, expectations for informal social control, and the exercise of informal social control), and crime and whether socio-demographic changes in nearby neighborhoods shape these relationships over time. We find that changes in the socio-demographic composition in both focal and nearby areas influence neighborhood informal social control; however, in contrast to cross-sectional studies of social disorganization theory, our results reveal little support that neighborhood informal social control significantly decreases crime over time.”

Lameris, Joran, John R. Hipp, and Jochem Tolsma. 2017. “Perceptions as the crucial link? The mediating role of neighborhood perceptions in the relationship between the neighborhood context and neighborhood cohesion.” Social Science Research 72(1):53-68.

Abstract: “This study examines the effects of neighborhood racial in-group size, economic deprivation and the prevalence of crime on neighborhood cohesion among U.S. whites. We explore to what extent residents’ perceptions of their neighborhood mediate these macro-micro relationships. We use a recent individual-level data set, the American Social Fabric Study (2012/2013), enriched with contextual-level data from the U.S. Census Bureau (2010) and employ multi-level structural equation models. We show that the racial in-group size is positively related to neighborhood cohesion and that neighborhood cohesion is lower in communities with a high crime rate. Individuals’ perceptions of the racial in-group size partly mediate the relationship between the objective racial in-group size and neighborhood cohesion. Residents’ perceptions of unsafety from crime also appear to be a mediating factor, not only for the objective crime rate but also for the objective racial in-group size. This is in line with our idea that racial stereotypes link racial minorities to crime whereby neighborhoods with a large non-white population are perceived to be more unsafe. Residents of the same neighborhood differ in how they perceive the degree of economic decay of the neighborhood and this causes them to evaluate neighborhood cohesion differently, however perceptions of neighborhood economic decay do not explain the link between the objective neighborhood context and neighborhood cohesion.”

Hipp, John R., Christopher J. Bates, Moshe Lichman, and Padhraic Smyth. (2019). “Using Social Media to Measure Temporal Ambient Population: Does it Help Explain Local Crime Rates?” Crime & Delinquency. 36(4): 718-748.

Abstract: “A challenge for studies assessing routine activities theory is accounting for the spatial and temporal confluence of offenders and targets given that people move about during the daytime and nighttime. We propose exploiting social media (Twitter) data to construct estimates of the population at various locations at different times of day, and assess whether these estimates help predict the amount of crime during two-hour time periods over the course of the day. We address these questions using crime data for 97,428 blocks in the Southern California region, along with geocoded information on tweets in the region over an eight month period. The results show that this measure of the temporal ambient population helps explain the level of crime in blocks during particular time periods. The use of social media data appear promising for testing various implications of routine activities and crime pattern theories, given their explicit spatial and temporal nature.”

Wickes, Rebecca, Lisa Broidy, and John R. Hipp. (2017). “Responding to neighborhood problems: Is the division of community labor gendered?” Crime & Delinquency. Published online.

Abstract: “Social disorganization theory positions informal social control as central to neighborhood crime reduction. Although neighborhood ties, fear of crime, and perceived disorder influence the exercise of informal social control, there are significant sex differences for these drivers that might differentially influence men and women’s informal social control actions. Furthermore, these differences may be exaggerated under conditions that activate gendered divisions of labor. We use survey data from 4,000 residents in 148 neighborhoods and employ multilevel logistic regression to examine the relationship between sex and informal social control actions. We find that men are more likely to take action than women; however, our three-way interactions reveal family arrangements moderate the relationship between ties, fear of crime, disorder, and these actions.”

Simpson, Rylan, John R. Hipp. (2017). “What Came First: The Police or the Incident? Bidirectional Relationships Between Police Actions and Police Incidents.” Policing & Society. Published online.

Abstract: “The present research examines the long-term, bidirectional relationships between calls for service, crime, and two police patrol strategies in Santa Monica, California: foot patrol and police stops. Using nine years of monthly data (2006–2014), we estimate two sets of block-level, longitudinal models to tease apart these relationships. In our first set of models, we use police actions and calls for service in the preceding month(s) to predict crime in the fsubsequent month. In our second set of models, we use calls for service and crime in the preceding month(s) to predict police actions in the subsequent month. We find that while changes in calls for service and crime often precede changes in police action, changes in crime also tend to follow them. For example, police stops appear to be particularly receptive to burglary: blocks with more burglaries receive greater numbers of police stops, and blocks with more police stops have reduced odds of experiencing burglary. We also find that the length of effects of predictors varies as a function of predictor and outcome: whereas some predictors exhibit short temporal effects (e.g. one month), other predictors exhibit much longer temporal effects (e.g. twelve months). Our results thus provide important insight into the spatial and temporal relationships between police actions and police incidents. Police actions must be neatly tailored to police incidents at precise levels if long-term deterrent effects at these levels are to be achieved.”

Hipp, John R., James Wo, and Young-an Kim. (2017). “Studying Neighborhood Crime Across Different Macro Spatial Scales: The Case of Robbery in Four Cities.” Social Science Research. 68(1): 15-29.

Abstract: “Whereas there is a burgeoning literature focusing on the spatial distribution of crime events across neighborhoods or micro-geographic units in a specific city, the present study expands this line of research by selecting four cities that vary across two macro-spatial dimensions: population in the micro-environment, and population in the broader macro-environment. We assess the relationship between measures constructed at different spatial scales and robbery rates in blocks in four cities: 1) San Francisco (high in micro- and macro-environment population); 2) Honolulu (high in micro- but low in macro-environment population); 3) Los Angeles (low in micro- but high in macro-environment population); 4) Sacramento (low in micro- and macro-environment population). Whereas the socio-demographic characteristics of residents further than ½ mile away do not impact robbery rates, the number of people up to 2.5 miles away are related to robbery rates, especially in the two cities with smaller micro-environment population, implying a larger spatial scale than is often considered. The results show that coefficient estimates differ somewhat more between cities differing in micro-environment population compared to those differing based on macro-environment population. It is therefore necessary to consider the broader macro-environment even when focusing on the level of crime across neighborhoods or micro-geographic units within an area.”

Hipp, John R. and Nicholas Branic. (2017). “Fast and slow change in neighborhoods: Characterization and consequences in Southern California.” International Journal of Urban Sciences. 21(3): 257-281.

Abstract: “Due to data limitations, most studies of neighborhood change within regions assume that change over the years of a decade is relatively constant from year-to-year. We use data on home loan information to construct annual measures of key socio-demographic measures in neighborhoods (census tracts) in the Southern California region from 2000-10 to test this assumption. We use latent trajectory modeling to describe the extent to which neighborhood change exhibits temporal nonlinearity, rather than a constant rate of change from year to year. There were four key findings: 1) we detected nonlinear temporal change across all socio-demographic dimensions, as a quadratic function better fit the data than a linear one in the latent trajectories; 2) neighborhoods experiencing more nonlinear temporality also experienced larger overall changes in percent Asian, percent black, and residential stability during the decade; neighborhoods experiencing an increase in Latinos or a decrease in whites experienced more temporal nonlinearity in this change; 3) the strongest predictor of racial/ethnic temporal nonlinearity was a larger presence of the group at the beginning of the decade; however, the racial and SES composition of the surrounding area, as well as how this was changing in the prior decade, also affected the degree of temporal nonlinearity in the current decade; 4) this temporal nonlinearity has consequences for neighborhoods: greater temporal nonlinear change in percent black or Latino was associated with larger increases in violent and property crime during the decade, and the temporal pattern of residential turnover or changing average income impacted changes in crime. The usual assumption of constant year-to-year change when interpolating neighborhood measures over intervening years may not be appropriate.”

Corcoran, Jonathan, Rebecca Wickes, Renee Zahnow, and John R. Hipp. (2017). “Neighbourhood land use features, collective efficacy and local civic actions.” Urban Studies. Forthcoming.

Abstract: “This paper explores the association between neighbourhood land use features and informal social control. More specifically, we examine the extent to which such features in combination with the socio-demographic context of the neighbourhood facilitate or impede collective efficacy and local civic actions. We achieve this through spatially integrating data from the census, topographic databases and a 2012 survey of 4,132 residents from 148 neighbourhoods in Brisbane, Australia. The study creates a new classification of a neighbourhood’s physical environment by creating novel categories of land use features that depict social conduits, social holes and social wedges. Social conduits are features of the neighbourhood that facilitate interaction between individuals, social holes are land uses that create situations where there is no occupancy, and social wedges are features that carve up neighbourhoods. We find some evidence to suggest that residents’ reports of collective efficacy are higher in neighbourhoods with a greater density of social conduits. Density of social conduits is also positively associated with local civic action. However, in neighbourhoods with more greenspace, residents are less likely to engage in local civic actions.”

Hipp, John R., Kevin Kane, and Jae Hong Kim. (2017). “Recipes for Neighborhood Development: A Machine Learning Approach toward Understanding the Impact of Mixing in Neighborhoods.” Landscape and Urban Planning. 164: 1-12.

Abstract: “Scholars of New Urbanism have suggested that mixing along various dimensions in neighborhoods (e.g., income, race/ethnicity, land use) may have positive consequences for neighborhoods, particularly for economic dynamism. A challenge for empirically assessing this hypothesis is that the impact of mixing may depend on various socio-demographic characteristics of the neighborhood and takes place in a complex fashion that cannot be appropriately handled by traditional statistical analytical approaches. We utilize a rarely used, innovative estimation technique—kernel regularized least squares—that allows for nonparametric estimation of the relationship between various neighborhood characteristics in 2000 and the change in average household income in the neighborhood from 2000 to 2010. The results demonstrate that the relationships between average income growth and both income mixing and racial/ethnic mixing are contingent upon several neighborhood socio-demographic “ingredients”. For example, racial mixing is positively associated with average income over time when it occurs in neighborhoods with a high percentage of Latinos or immigrants, high population density, or high housing age mixing. Income mixing is associated with worsening average household income in neighborhoods with more poverty, unemployment, immigrants, or population density. It appears that considering the broader characteristics of the neighborhood is important for understanding economic dynamism.”

Hipp, John R. and Kevin Kane. (2017). “Cities and the Larger Context: What explains changing levels of crime?” Journal of Criminal Justice. 49(1): 32-44.

Abstract: “This study explores whether the broader context in which a city is located impacts the change in crime levels over the subsequent decade. This study uses a wide range of cities (those with a population of at least 10,000), over a long period of time (from 1970 to 2010). We test and find that although cities with larger population and those surrounded by a county with a larger population typically experience larger increases in crime over the subsequent decade, cities experiencing an increase in population during the current decade experience crime decreases. The study finds that cities with higher average income experience greater subsequent crime decreases, and those surrounded by counties with larger unemployment increases experience crime increases. Higher levels of income inequality and racial/ethnic heterogeneity are associated with increasing crime rates, and increasing inequality and racial/ethnic heterogeneity in the surrounding county are associated with further increases. Furthermore, this relationship has strengthened since 1970, suggesting that both scales of inequality are even more important from a public safety perspective. Finally, we tested the time invariance of these relationships, and showed that the magnitude of the relationship between city-level inequality and increasing crime has increased over the study period.”

Boessen, Adam, John R. Hipp, Carter T. Butts, Nicholas N. Nagle, and Emily J. Smith. (2017). “The built environment, spatial scale, and social networks: Do land uses matter for personal network structure?” Environment & Planning B. Forthcoming.

Abstract: “In this study, we examine how different features of the built environment – density, diversity of land uses, and design – have consequences for personal networks. We also consider whether different features of the built environment have consequences for the spatial location of persons to whom one is tied by considering their distribution in local area, broader city region, and a more macro spatial scale. We test these ideas with a large sample of the Western United States for three different types of ties. Our findings suggest that the built environment is crucial for personal network structure, both in the number of social ties and where they are located.”

Kim, Young-an and John R. Hipp. (2016). “Physical boundaries and City boundaries: Consequences for Crime Patterns on Street Segments?” Crime & Delinquency. Forthcoming.

Abstract: “Scholars have theorized how spatial boundaries (edges) can be important for understanding the location of crime, yet the empirical relationship between spatial boundaries in the environment and levels of crime is relatively less explored compared to other features of the environment. The current study extends the literature by not only studying three types of physical boundaries—rivers, parks, and interstate highways—but also one non-physical and relatively less visible boundary—city boundaries. We analyze the relationship between crime in street segments and nearness to these four types of edges in the Southern California area. We measure nearness to these boundaries in two manners: 1) whether or not the segment is adjacent to the feature; and 2) how far in physical distance the segment is to the feature. Additionally, this study examines the possible moderating effect of retail land use of a segment and nearness to these boundaries.”

Kim, Jae Hong, John R. Hipp, Victoria Basolo, and Harya S. Dillon. (2017). “Land Use Change Dynamics in Southern California: Does Geographic Elasticity Matter?” Journal of Planning Education and Research. Forthcoming.

Abstract: “This article examines how municipal planning contexts can shape urban land use dynamics by investigating the parcel-level land use changes in a five-county Southern California metropolitan area between 1990 and 2005. An analysis, based on a multinomial logit model, shows that land use change patterns significantly vary by municipalities that were situated in heterogeneous planning contexts. More specifically, cities with limited ability to expand their jurisdictional boundaries are found to provide more recreational areas and urban open spaces, while restricting non-conventional land uses. However, no evidence of a shift from single-family to multi-family residential development is detected for such cities.”

Boessen, Adam, John R. Hipp, Emily J. Smith, Carter T. Butts, and Nicholas N. Nagle. (2017). “Social Fabric and Fear of Crime: Considering Spatial Location and Time of Day.” Social Networks. 51(1): 60-72.

Abstract: “Criminologists have long noted that social networks play a role in influencing residents’ fear of crime, but findings vis a vis the exact nature of that role have been mixed. More social ties may be associated with less fear of crime through their role in collective action, trust, and emotional support, but also with more fear of crime because of their role in the diffusion of information on local crime patterns. In what follows, we suggest temporal and spatial distinctions in how social ties matter for fear of crime with respect to these different mechanisms. Analysis of data from a large scale egocentric network study in Southern California provides evidence for these claims.”

Jose, Rupa and John R. Hipp (2016). “Mental Illness as an Ecological Factor of Neighborhood Crime”. Criminology, Criminal Justice, Law & Society. Forthcoming

Abstract: “Based on prior research, the presence of more residents diagnosed with mental illness in a neighborhood may indicate more offenders or more targets. We suggest that it may also indicate reduced guardianship and lower informal social control. Using data from blocks in 108 cities in Southern California, we examine the association between two types of mental disorders (affective disorders and substance use disorders) and crime rates. Even after controlling for more traditional predictors of neighborhood crime, we find a strong positive relationship between certain mental disorders and aggravated assault and motor vehicle theft rates. We also tested nonlinear interactions with economic disadvantage and found that a higher proportion of mentally ill residents in a zip code is associated with higher crime rates in zip codes with lower levels of concentrated economic disadvantage. The findings suggest that mental illness is a unique ecological factor by which to understand neighborhood crime.”

Kane, Kevin; John R. Hipp, and Jae Hong Kim. (2016). “Analyzing Accessibility using Parcel Data: Is there Still an Access-Space Tradeoff in Long Beach, California?” The Professional Geographer. 69(3): 486-503.

Abstract: “This article analyzes the impact of changing housing and neighborhood characteristics on the accessibility of neighborhood businesses using Long Beach, California as a case study. While advocates of smart growth and New Urbanism encourage land use mixing, aggregate-level analysis can be too coarse to pick up on fine-grained aspects of urban streetscapes. This study uses assessor parcel records and a point-based business establishment dataset to analyze citywide patterns of accessibility from individual dwelling units to 31 types of neighborhood businesses including grocery stores, service shops, drug stores, doctor’s offices, and banks. Regression results compare parcel-level and neighborhood-level drivers of accessibility between 2006 and 2015 to gauge the aggregated effect of recent economic, demographic, and built environment changes on this aspect of urban spatial structure. Larger homes in older, multi-unit buildings and higher-income neighborhoods show substantial increases in accessibility to most establishment types, suggesting a trend toward both greater accessibility and larger dwelling units – despite the traditional tradeoff between access and space. While gradual increases in home and business density increased overall accessibility over this period, weaker neighborhoodlevel results indicate this trend is less pronounced in high-poverty and nonwhite areas.”

Hipp, John R. and Young-an Kim (2016). “Measuring Crime Concentration across Cities of Varying Sizes: Complications Based on the Spatial and Temporal Scale Employed.” Journal of Quantitative Criminology. 33(3): 595-632.

Abstract: “Objectives: We argue that assessing the level of crime concentration across cities has four challenges: 1) how much variability should we expect to observe; 2) whether concentration should be measured across different types of macro units of different sizes; 3) a statistical challenge for measuring crime concentration; 4) the temporal assumption employed when measuring high crime locations.

Methods: We use data for 42 cities in southern California with at least 40,000 population to assess the level of crime concentration in them for five different Part 1 crimes and total Part 1 crimes over 2005-12. We demonstrate that the traditional measure of crime concentration is confounded by crimes that spatially locate due to random chance. We also use two measures employing different temporal assumptions: a historically adjusted crime concentration measure, and a temporally adjusted crime concentration measure (a novel approximate solution that is simple for researchers to implement).

Results: There is much variability in crime concentration over cities in the top 5% of street segments. The standard deviation across cities over years for the temporally adjusted crime concentration measure is between 10% and 20% across crime types (with the average range typically being about 15% to 90%). The historically adjusted concentration has similar variability and typically ranges from about 35% to 100%.

Conclusions: The study provides evidence of variability in the level of crime concentration across cities, but also raises important questions about the temporal scale when measuring this concentration. The results open an exciting new area of research exploring why levels of crime concentration may vary over cities? Either micro- or macro- theories may help researchers in exploring this new direction.”

Kubrin, Charis E., John R. Hipp, and Young-an Kim (2016). “Different than the Sum of its Parts: Examining the Unique Impacts of Immigrant Groups on Neighborhood Crime Rates.” Journal of Quantitative Criminology. Forthcoming.

Abstract: “There has been a veritable explosion of studies on the relationship between immigration and crime. The literature has produced one of the most robust findings in the field: neighborhoods with greater concentrations of immigrants have lower rates of crime. One drawback of this research is that it typically treats immigrants as a homogeneous population and fails to account for significant variation among immigrants. Examining the immigration-crime nexus across neighborhoods in the Southern California metropolitan region, this study builds on existing literature by unpacking immigration and accounting for the rich diversity that exists between immigrant groups. We capture this diversity using three different approaches, operationalizing immigrant groups by similar racial/ethnic categories, areas or regions of the world that immigrants emigrate from, and where immigrants co-locate once they settle in the U.S. We also account for the heterogeneity of immigrant populations by constructing measures of immigrant heterogeneity based on each of these classifications. We compare these novel approaches with the standard approach, which combines immigrants together through a single measure of percent foreign born. The results reveal that considerable insights are gained by distinguishing between diverse groups of immigrants. In particular, we find that all three strategies explained neighborhood crime levels better than the traditional approach. The findings underscore the necessity of disaggregating immigrant groups when exploring the immigration-crime relationship.”

Kane, Kevin; John R. Hipp, and Jae Hong Kim. (2016). “Los Angeles Employment Concentration in the Twenty-First Century.” Urban Studies. Forthcoming.

Abstract: “This paper is an empirical analysis of employment centers in the Los Angeles region from 1997-2014. Most extant work on employment centers focuses on identification methodology or their dynamics during a period of industrial restructuring from 1980-2000. This timely study examines hypotheses derived from more recent perspectives on urban concentration and dispersion including New Urbanism, Smart Growth, sustainable cities, and the recent Global Financial Crisis. We use point-based, rather than census tractbased employment data to analyze concentration across five key industries: knowledge-intensive business services (KIBS), retail, creative, industrial, and high-tech, emphasizing changes in center composition and boundaries. While using point data necessitates slight changes to the nonparametric identification method typically used, results show far greater change across centers than previous longitudinal studies. Only 43% of the land area that is in an employment center is part of one in both 1997 and 2014. Using a persistence score, centers range from stable to highly fluctuating, but emerging, persisting, and dying centers are found in core and fringe areas alike. KIBS are most associated with stable centers, while high tech employment is attracted toward emerging areas and retail exists throughout. Emerging centers are more likely to have greater accessibility, while industrial employment becomes far more concentrated in centers by 2014.”

Hipp, John R. and Rebecca Wickes. (2016). “Violence in Urban Neighborhoods: A Longitudinal Study of Collective Efficacy and Violent Crime.” Journal of Quantitative Criminology. 33(4): 783-808.

Abstract: “Objectives: Cross-sectional studies consistently find that neighborhoods with higher levels of collective efficacy experience fewer social problems. Particularly robust is the relationship between collective efficacy and violent crime, which holds regardless of the socio-structural conditions of neighborhoods. Yet due to the limited availability of neighborhood panel data, the temporal relationship between neighborhood structure, collective efficacy and crime is less well understood.

Methods: In this paper, we provide an empirical test of the collective efficacy-crime association over time by bringing together multiple waves of survey and census data and counts of violent crime incident data collected across 148 neighborhoods in Brisbane, Australia. Utilizing three different longitudinal models that make different assumptions about the temporal nature of these relationships, we examine the reciprocal relationships between neighborhood features and collective efficacy with violent crime. We also consider the spatial embeddedness of these neighborhood characteristics and their association with collective efficacy and the concentration of violence longitudinally.

Results: Notably, our findings reveal no direct relationship between collective efficacy and violent crime over time. However, we find a strong reciprocal relationship between collective efficacy and disadvantage and between disadvantage and violence, indicating an indirect relationship between collective efficacy and violence.

Conclusions: The null direct effects for collective efficacy on crime in a longitudinal design suggest that this relationship may not be as straightforward as presumed in the literature. More longitudinal research is needed to understand the dynamics of disadvantage, collective efficacy, and violence in neighborhoods.”

Hipp, John R. (2016). “General theory of spatial crime patterns.” Criminology. 54(4): 653-679.

Abstract: “I propose a general theory for examining the spatial distribution of crime by specifically addressing and estimating the spatial distribution of the residences of offenders, targets, guardians, and their respective movement patterns across space and time. The model combines information on the locations of persons, typical spatial movement patterns, and situational characteristics of locations to create estimates of crime potential at various locations at various points in time and makes four key contributions. First, the equations make the ideas involved in the theory explicit, and highlight points at which our current state of empirical evidence is lacking. Second, by creating measures of spatial “potentials” of offenders, targets, and guardians, this theory provides an explicit grounding for operationalizing spatial effects in studies of place and crime. Third, the equations provide an explicit consideration of offenders and where they might travel, and therefore incorporates offenders into crime and place research. Fourth, these equations suggest ways that researchers could use simulations to predict stable patterns, as well as changes, in the levels of crime at both micro and macro scales. Finally, I provide an empirical demonstration of the added explanatory power provided by the theory to a study of place and crime.”

Hipp, John R. and Charis E. Kubrin. (2017). “From Bad to Worse: How Changing Inequality in Nearby Areas Impacts Local Crime.” RSF: The Russell Sage Foundation Journal of the Social Sciences. Special Issue: Spatial Foundations of Inequality. 3(2): 129-151.

Abstract: “There is growing recognition that criminogenic neighborhood effects may not end at the borders of local communities, that neighborhoods are located relative to one another in ways that shape local crime rates. Inspired by this insight, this research explores the changing spatial distribution of race and income around a location and determines how such changes are associated with crime patterns and trends in neighborhoods in the southern California region. We examine how changes from 2000 to 2010 in the income composition, the racial composition, and the intersection of these two constructs are linked with changes in levels of crime across local areas. We find that neighborhoods experiencing greater increases in spatial inequality in a broader area (2.5 miles around the neighborhood) experience greater increases in crime levels in the focal area over the decade, and that this pattern is strongest for neighborhoods that are simultaneously experiencing increasing average household income or increasing inequality. We also find that neighborhoods simultaneously experiencing increases in inequality and racial/ethnic heterogeneity experience increases in crime.”

Hipp, John R. (2016). “Collective Efficacy: How is it Conceptualized, How is it Measured, and Does it Really Matter for Understanding Perceived Neighborhood Crime and Disorder?” Journal of Criminal Justice. 46(1): 32-44.

Abstract: “Building on the insights of the self-efficacy literature, this study highlights that collective efficacy is a collective perception that comes from a process. This study emphasizes that 1) there is updating, as there are feedback effects from success or failure by the group to the perception of collective efficacy, and 2) this updating raises the importance of accounting for members’ degree of uncertainty regarding neighborhood collective efficacy. Using a sample of 113 block groups in three rural North Carolina counties, this study finds evidence of updating as neighborhoods perceiving more crime or disorder reported less collective efficacy at the next time point. Furthermore, collective efficacy was only associated with lower perceived disorder at the next time point when it occurred in highly cohesive neighborhoods. Finally, neighborhoods with more perceived disorder and uncertainty regarding collective efficacy at one time point had lower levels of collective efficacy at the next time point, illustrating the importance of uncertainty along with updating.”

Hipp, John R. and Rebecca Wickes. (2016). “Minority Status Distortion and Preference for In-group Ties: Consequences for Social Capital.” Socius. 2: 1-18. [freely available online]

Abstract: “To assess residents’ perceptions of social capital (social cohesion, place attachment and neighboring), we create innovative measures of residents’ assessments of neighborhood ethnic minorities and the extent of social ties between members of the same ethnic group compared to chance. We use a sample of nearly 10,000 residents nested in 297 neighborhoods in two Australian cities. Residents who perceive more minorities in their neighborhood, who have more or fewer ties with members of the other ethnic group than expected by chance, or who live in neighborhoods with more inter-group ties than would be expected report lower levels of social capital.”

Hipp, John R. and Adam Boessen. (2016). “The Shape of Mobility: Measuring the Distance Decay Function of Household Mobility” The Professional Geographer. 69(1): 32-44.

Abstract: “A well-known challenge to studies examining the distance of residential mobility patterns is that the estimates are often constrained to only patterns within a particular metro area or between metro areas. Thus, studies are unable to estimate of the entire distance decay functional form. Using a unique dataset on the distance of the most recent move for a large sample of households in 23 metropolitan areas in the U.S. over three waves, we flexibly estimate the distance decay function for the entire sample, as well as for a series of subpopulations based on key demographic information.”

Wickes, Rebecca, John R. Hipp, Elise Sargeant, and Lorraine Mazerolle. (2016). “Neighborhood Social Ties and Shared Expectations for Informal Social Control: Do They Influence Informal Social Control Actions?” Journal of Quantitative Criminology. 33(1): 101-129.

Abstract: “Objectives: Social disorganization theories state that neighborhood social ties and shared expectations for informal social control are necessary for the exercise of informal social control actions. Yet this association is largely assumed rather than empirically examined in the literature. This paper examines the relationship between neighborhood social ties, shared expectations for informal social control and actual parochial and public informal social control actions taken by residents in response to big neighborhood problems.

Methods: Using multi-level logistic regression models, we integrate Australian Bureau of Statistics census data with the Australian Community Capacity Study survey data of 1,310 residents reporting 2,614 significant neighborhood problems across 148 neighborhoods to examine specific informal social control actions taken by residents when faced with neighborhood problems.

Results: We do not find a relationship between shared expectations for informal social control and residents’ informal social control actions. Individual social ties, however, do lead to an increase in informal social control actions in response to ‘big’ neighborhood problems. Residents with strong ties are more likely to engage in public and parochial informal social control actions than those individuals who lack social ties. Yet individuals living in neighborhoods with high levels of social ties are only moderately more likely to engage in parochial informal social control action than those living in areas where these ties are not present. Shared expectations for informal social control are not associated with the likelihood that residents engage in informal social control actions when faced with a significant neighborhood problem.

Conclusions: Neighborhood social ties and shared expectations for informal social control are not unilaterally necessary for the exercise of informal social control actions Our results challenge contemporary articulations of social disorganization theory that assume that the availability of neighborhood social ties or expectations for action are associated with residents actually doing something to exercise of informal social control.”

Wo, James C., John R. Hipp, and Adam Boessen. (2016). “Voluntary Organizations and Neighborhood Crime: A Dynamic Perspective.” Criminology. 54(2):212-241.

Abstract: “Although numerous theories suggest that voluntary organizations contribute to lower crime rates in neighborhoods, the evidence for this proposition is weak. Consequently, we propose a dynamic perspective for understanding the relationship between voluntary organizations and neighborhood crime that involves longitudinal analyses and the measurement of the age of organizations. By using longitudinal data on a sample of census blocks (N = 87,641) located across 10 cities, we test the relationship between age-graded measures of different types of voluntary organizations and neighborhood crime rates. We use fixed-effects negative binomial regression models that focus on change within neighborhoods of the relationship between voluntary organizations and neighborhood crime. Our results show that although each type of voluntary organization is found to exhibit crime-reducing behavior in neighborhoods, we find that many of them are consistent with what we refer to as the “delayed impact scenario”—there is a pronounced delay between the placement of a voluntary organization and a neighborhood subsequently experiencing a reduction in crime. With protective effects of organizations typically not demonstrated until several years after being in the neighborhood, these patterns suggest a need for long-term investment strategies when examining organizations.”

Chamberlain, Alyssa W. and John R. Hipp. (2015). “It’s All Relative: Concentrated disadvantage within and across neighborhoods and communities, and the consequences for neighborhood crime.” Journal of Criminal Justice. 43(6): 431-443.

Abstract: “Purpose: Prior studies have largely been unable to account for how variations in inequality across larger areas might impact crime rates in neighborhoods. We examine this broader context both in terms of the spatial area surrounding neighborhoods as well as the larger, city-level context. Although social disorganization, opportunity and relative deprivation theories are typically used to explain variations in neighborhood crime, these theories make differing predictions about crime when the broader areas that neighborhoods are embedded in are taken into account.

Methods: We use data from the National Neighborhood Crime Study for 7956 neighborhoods in 79 cities. Multi-level models with spatial effects are estimated to explain the relationship between crime and city and neighborhood social and economic resources.

Results: Disadvantage in the focal neighborhood and nearby neighborhoods increase neighborhood violent crime, consistent with social disorganization theory. However, relative deprivation provides a more robust explanation for understanding variation in property crime, as the difference in disadvantage between a neighborhood and nearby neighborhoods (or the broader community) explains higher levels of property crime.

Conclusions: Criminologists need to account for the larger context of nearby neighborhoods, as well as the broader city, when understanding the effect of relative deprivation on neighborhood-level property crime rates.”

Hipp, John R. and Wouter Steenbeek. (2015). “Types of crime and types of mechanisms: What are the consequences for neighborhoods over time?” Crime & Delinquency. 62(9): 1203-1234.

Abstract: “Using a longitudinal dataset of 317 neighborhoods from 1996 to 2002 in Utrecht, The Netherlands, this study tests whether types of crime differentially impact a) the mechanisms of social disorganization theory, and b) residents’ mobility behavior and attitudes towards the neighborhood. Neighborhoods with more cohesion have less violence two years later. Also, neighborhoods perceiving more violence experience lower levels of cohesion two years later. Higher levels of perceived violence were most important for explaining who moves out of the neighborhood, as such neighborhoods had more nonwhites and more lower income households at the next time point. Burglaries (a crime that occurs in private space) appear to increase residents’ sense of feeling responsibility for the neighborhood.”

Jose, Rupa, John R. Hipp, Carter T. Butts, Cheng Wang, and Cynthia M. Lakon. (2015). “Network Structure, Influence, Selection and Delinquent Behavior: Unpacking a Dynamic Process.” Criminal Justice and Behavior. 43(2): 264-284.

Abstract: “This study uses National Longitudinal Study of Adolescent Health (Add Health) data to explore the co-evolution of friendship networks and delinquent behaviors. Using a stochastic actor-based (SAB) model, we simultaneously estimate the network structure, influence process, and selection process on adolescents in 12 small schools (N = 1,284) and one large school (N = 976) over three time periods. Our results indicate the presence of both selection and influence processes. Moderating effects were tested for density, centrality, and popularity, with only a weak interaction effect for density and delinquent peer influence in the small schools (p < .10). Contexts outside the school impacted school networks: adolescents in the large school were particularly likely to form ties to others from equally disadvantaged neighborhoods, and adolescents in the small schools with more outside of school ties increased their delinquency behavior over time. These findings support the importance of delinquency in peer selection and influence processes.”

Boessen, Adam and John R. Hipp. (2015). “Close-ups and the Scale of Ecology: Land Uses and the Geography of Social Context and Crime.” Criminology. 53(3): 399-426.

Abstract: “Whereas one line of recent neighborhood research has placed an emphasis on zooming into smaller and smaller units of analysis such as street blocks, another line of research suggests that even the meso-area of neighborhoods is too narrow and that the area surrounding the neighborhood is also important. Thus, there is a need to examine the scale at which the social ecology impacts crime. We use data from seven cities from around the 2000-decade to test our research questions. Our results suggest that although many neighborhood factors appear to operate on the micro scale of blocks, others appear to have a much broader impact. In addition, we find that racially/ethnically homogenous blocks within heterogeneous block groups have the most crime. Our findings also show the strongest results for a multitude of land use measures and that these measures sharpen some of the associations from social characteristics. Thus, we find that accounting for multiple scales simultaneously is important in ecological studies of crime.”

Hipp, John R. and Alyssa W. Chamberlain. (2015). “Foreclosures and crime: A City-level Analysis in Southern California of a Dynamic Process.” Social Science Research. 51(2): 219-232.

Abstract: “Although a growing body of research has examined and found a positive relationship between neighborhood crime and home foreclosures, some research suggests this relationship may not hold in all cities. This study uses city-level data to assess the relationship between foreclosures and crime by estimating longitudinal models with lags for monthly foreclosure and crime data in 128 cities from 1996 to 2011 in Southern California. We test whether these effects are stronger in cities with a combination of high economic inequality and high economic segregation; and whether they are stronger in cities with high racial/ ethnic heterogeneity and high racial segregation. One month, and cumulative three month, six month, and 12-month lags of foreclosures are found to increase city level crime for all crimes except motor vehicle theft. The effect of foreclosures on these crime types is stronger in cities with simultaneously high levels of inequality but low levels of economic segregation. The effect of foreclosures on aggravated assault, robbery, and burglary is stronger in cities with simultaneously high levels of racial heterogeneity and low levels of racial segregation. On the other hand, foreclosures had a stronger effect on larceny and motor vehicle theft when they occurred in a city with simultaneously high levels of racial heterogeneity and high levels of racial segregation. There is evidence that the foreclosure crisis had large scale impacts on cities, leading to higher crime rates in cities hit harder by foreclosures. Nonetheless, the economic and racial characteristics of the city altered this effect.”

Kubrin, Charis E. and John R. Hipp. (2014). “Do Fringe Banks Create Fringe Neighborhoods? Examining the Spatial Relationship between Fringe Banking and Neighborhood Crime Rates.” Justice Quarterly. 33(5): 755-784.

Abstract: “In the aftermath of one of the worst recessions in U.S. history, high unemployment has placed millions of Americans in precarious financial positions. More than ever Americans are opting out of traditional financial services, relying instead on “fringe lenders” such as check cashers, payday lenders, and pawnshops to manage their finances. Given their tremendous growth and the concern that consumers who are least able to pay for high-cost, high-risk financial products are most likely to use them, fringe lenders have been the subject of controversy and the focus of much research. Largely unknown, however, are the effects of fringe lenders on the communities where they are located. Given their spatial concentration in low-income neighborhoods with greater concentrations of racial and ethnic minorities—areas with typically more crime—of concern is whether fringe lenders themselves are criminogenic. We consider this by examining the impact of several types of fringe lenders on neighborhood crime rates in Los Angeles. Our findings reveal that the presence of fringe banks on a block is related to higher crime levels, even after controlling for a range of factors known to be associated with crime rates. The presence of a fringe bank also impacts crime, particularly robbery, on adjacent blocks. Whereas we find that pawnshops have little impact on crime levels, payday lenders and check cashers have a much stronger impact. Finally, we discover there are moderating effects, as the fringe lender-crime relationship is considerably reduced if the lender is located in a higher population density area.”

Boggess, Lyndsay N. and John R. Hipp. (2016). “The spatial dimensions of gentrification and the consequences for neighborhood crime.” Justice Quarterly. 33(4): 584-613.

Abstract: “This study examines neighborhood economic improvement, what is occurring in nearby neighborhoods, and the consequences for neighborhood crime rates. Negative binomial regression models are estimated to explain the relationship between the increase in average home values (a component of gentrification) and crime in Los Angeles between 1990 and 2000. We find that the spatial context is important, as gentrifying neighborhoods located on the “frontier” of the gentrification process have significantly more aggravated assaults than gentrifying neighborhoods surrounded by neighborhoods also undergoing improvement. Furthermore, this effect is stronger in neighborhoods that began the decade with the highest average home values. Our findings indicate that the extent to which neighborhoods are more or less embedded in a larger process of economic improvement, and where the neighborhood is at in the economic development process, has differential effects on neighborhood crime.”

Hipp, John R. and Amrita Singh. (2014). “Changing Neighborhood Determinants of Housing Price Trends in Southern California, 1960-2009.” City & Community. 13(3): 254-274.

Abstract: “Research has generally failed to explore whether the effect of neighborhood characteristics on home values has changed over time. We take a long-range view and study decadal changing home values in the southern California region over a 50 year period, from 1960 to 2009. We focus on the effects of racial composition and measures associated with the New Urbanism on changing home values. We find that whereas neighborhoods with more racial/ethnic minorities and racial mixing experienced relative decreases in home values in the earlier decades, this effect has effectively disappeared in the most recent decade and actually became positive for some measures. We also found that certain characteristics associated with the New Urbanism—population density, older homes, a lack of concentration of single family units—show stronger positive effects on home values in the most recent decades.”

+Boessen, Adam, John R. Hipp, Emily J. Smith, Carter T. Butts, Nicholas N. Nagle, and Zack Almquist. (2014). “Networks, Space, and Residents’ Perception of Cohesion.” American Journal of Community Psychology. 53(3-4): 447-461.

Abstract: “Community scholars increasingly focus on the linkage between residents’ sense of cohesion with the neighborhood and their own social networks in the neighborhood. A challenge is that whereas some research only focuses on residents’ social ties with fellow neighbors, such an approach misses out on the larger constellation of individuals’ relationships and the spatial distribution of those relationships. Using data from the Twin Communities Network Study, the current project is one of the first studies to examine the actual spatial distribution of respondents’ networks for a variety of relationships and the consequences of these for neighborhood and city cohesion. We also examine how a perceived structural measure of cohesion—triangle degree—impacts their perceptions of neighborhood and city cohesion. Our findings suggest that perceptions of cohesion within the neighborhood and the city depend on the number of neighborhood safety contacts as well as on the types of people with which they discuss important matters. On the other hand, kin and social friendship ties do not impact cohesion. A key finding is that residents who report more spatially dispersed networks for certain types of ties report lower levels of neighborhood and city cohesion. Residents with higher triangle degree within their neighborhood safety networks perceived more neighborhood cohesion.”

Hipp, John R., Jonathan Corcoran, Rebecca Wickes, and Tiebei Li. (2014). “Examining the social porosity of environmental features on neighborhood sociability and attachment.” PLOS: One. 9(1): 1-13. [freely available]

Abstract: “The local neighborhood forms an integral part of our lives. It provides the context through which social networks are nurtured and the foundation from which a sense of attachment and cohesion with fellow residents can be established. Whereas much of the previous research has examined the role of social and demographic characteristic in relation to the level of neighboring and cohesion, this paper explores whether particular environmental features in the neighborhood affect social porosity. We define social porosity as the degree to which social ties flow over the surface of a neighborhood. The focus of our paper is to examine the extent to which a neighborhood’s environmental features impede the level of social porosity present among residents. To do this, we integrate data from the census, topographic databases and a 2010 survey of 4,351 residents from 146 neighborhoods in Australia. The study introduces the concepts of wedges and social holes. The presence of two sources of wedges is measured: rivers and highways. The presence of two sources of social holes is measured: parks and industrial areas. Borrowing from the geography literature, several measures are constructed to capture how these features collectively carve up the physical environment of neighborhoods. We then consider how this influences residents’ neighboring behavior, their level of attachment to the neighborhood and their sense of neighborhood cohesion. We find that the distance of a neighborhood to one form of social hole—industrial areas—has a particularly strong negative effect on all three dependent variables. The presence of the other form of social hole—parks—has a weaker negative effect. Neighborhood wedges also impact social interaction. Both the length of a river and the number of highway fragments in a neighborhood has a consistent negative effect on neighboring, attachment and cohesion.”

Hipp, John R., Carter T. Butts, Ryan M. Acton, Nicholas N. Nagle, and Adam Boessen. (2013). “Extrapolative Simulation of Neighborhood Networks based on Population Spatial Distribution: Do They Predict Crime?” Social Networks. 35(4): 614-615.

Abstract: “Objectives: Previous criminological scholarship has posited that network ties among neighborhood residents may impact crime rates, but has done little to consider the specific ways in which network structure may enhance or inhibit criminal activity. A lack of data on social ties has arguably led to this state of affairs. We propose to avoid this limitation by demonstrating a novel approach of extrapolatively simulating network ties and constructing structural network measures to assess their effect on neighborhood crime rates.

Methods: We first spatially locate the households of a city into their constituent blocks. Then, we employ spatial interaction functions based on prior empirical work and simulate a network of social ties among these residents. From this simulated network, we compute network statistics that more appropriately capture the notions of cohesion and information diffusion that underlie theories of networks and crime.

Results: We show that these network statistics are robust predictors of the levels of crime in five separate cities (above standard controls) at the very micro geographic level of blocks and block groups.

Conclusions: We conclude by considering extensions of the approach that account for homophily in the formation of network ties.”

Hipp, John R. and Aaron Roussell (2013). “Micro- and Macro-environment Population and the Consequences for Crime Rates.” Social Forces. 92(2): 563-595.

Abstract: “Few studies have explored Louis Wirth’s propositions regarding of the independent effects of population size and density due to the conceptual difficulty in distinguishing between them. We directly address this conundrum by conceptualizing these as micro-population density and macro-population density. We propose two novel measures for these constructs: population density exposure to capture micro-density, and a measure of population within a 20 mile radius to capture macro-density. We combine the theoretical insights of Wirth with routine activities theory to posit and find strong nonlinear effects of micro-density on crime rates, as well as the moderating effect of macro-density. We find strong evidence of macro social processes for population size including: 1) its strongest effect occurred for crimes generally between strangers (robberies and motor vehicle thefts); 2) virtually no effect for homicides, a type of crime that often occurs among non-strangers. For micro-density, our findings include: 1) strong curvilinear effects for the three types of property crime; 2) diminishing positive effects for robbery and homicide; and 3) a strikingly different pattern for aggravated assault. The effects for micro-density are stronger than for macro-density, a finding unexplored in the extant literature. We discuss the implications of these results within the context of Wirth’s theoretical framework as well as routine activities theory, and suggest ways to extend these findings.”

Wickes, Rebecca, John R. Hipp, Renee Zahnow, and Lorraine Mazerolle. (2013). “’Seeing’ Minorities and Perceptions of Disorder: Explicating the Mediating and Moderating Mechanisms of Social Cohesion.” Criminology. 51(3): 519-560.

Abstract: “Research shows that residents report high levels of disorder in places with greater concentrations of minorities even after controlling for objective indicators of crime or disorder. Less understood, however, are the mechanisms that explain this relationship. Drawing on a survey of nearly 10,000 residents nested within 297 neighborhoods across two cities, we use a multiple indicators–multiple causes model to examine the cues that lead individuals to distort the presence of minorities in neighborhoods. We then employ multilevel models to test whether these distortions influence perceptions of disorder. Furthermore, we assess whether living in a socially cohesive neighborhood mediates and/or moderates the relationship between “seeing” minorities and perceiving disorder. We find that when residents overestimate the proportion of minorities living in their neighborhood, perceptions of disorder are heightened. Yet social cohesion moderates and partially mediates this relationship: Residents living in socially cohesive neighborhoods not only report less disorder than those living in less cohesive communities, but also they “see” fewer minorities when compared with residents living in less socially cohesive neighborhoods. These results suggest that social cohesion is an important mechanism for explaining how residents internalize the presence of minorities in their neighborhoods and how this then leads to perceived neighborhood disorder.”

Hipp, John R., and Adam Boessen (2013). “Egohoods as waves washing across the city: A new measure of ‘neighborhoods’”. Criminology. 51(2): 287-327.

Abstract: “Defining “neighborhoods” is a bedeviling challenge faced by all studies of neighborhood effects and ecological models of social processes. Although scholars frequently lament the inadequacies of the various existing definitions of “neighborhood”, we argue that previous strategies relying on non-overlapping boundaries such as block groups and tracts are fundamentally flawed. The approach taken here instead builds on insights of the mental mapping literature, the social networks literature, the daily activities pattern literature, and the travel to crime literature to propose a new definition of neighborhoods: egohoods. These egohoods are conceptualized as waves washing across the surface of cities, as opposed to independent units with non-overlapping boundaries. This approach is illustrated using crime data from nine cities: Buffalo, Chicago, Cincinnati, Cleveland, Dallas, Los Angeles, Sacramento, St. Louis, and Tucson. The results show that measures aggregated to our egohoods explain more of the variation in crime across the social environment than do models with measures aggregated to block groups or tracts. Results also suggest that measuring inequality in egohoods provides dramatically stronger positive effects on crime rates than when using the non-overlapping boundary approach, highlighting the important new insights that can be obtained by utilizing our egohood approach.”

MacDonald, John M., John R. Hipp, and Charlotte Gill. (2013). “The Effects of Immigrant Concentration on Changes in Neighborhood Crime Rates.” Journal of Quantitative Criminology. 29(2): 191-215.

Abstract: “Objectives. This study investigated the extent to which immigrant concentration is associated with reductions in neighborhood crime rates in the City of Los Angeles.

Methods. A potential outcomes model using two-stage least squares regression was estimated, where immigrant concentration levels in 1990 were used as an instrumental variable to predict immigrant concentration levels in 2000. The instrumental variables design was used to reduce selection bias in estimating the effect of immigrant concentration on changes in official crime rates between 2000 and 2005 for census tracts in the City of Los Angeles, holding constant other demographic variables and area-level fixed effects. Non-parametric smoothers were also employed in a two-stage least squares regression model to control for the potential influence of heterogeneity in immigrant concentration on changes in crime rates.

Results. The results indicate that greater predicted concentrations of immigrants in neighborhoods are linked to significant reductions in crime. The results are robust to a number of different model specifications.

Conclusions. The findings challenge traditional ecological perspectives that link immigrant settlement to higher rates of crime. Immigration settlement patterns appear to be associated with reducing the social burden of crime. Study conclusions are limited by the potential for omitted variables that may bias the observed relationship between immigrant concentration and neighborhood crime rates, and the use of only official crime data which may under report crimes committed against immigrants. Understanding whether immigrant concentration is an important dynamic of changing neighborhood patterns of crime outside Los Angeles will require replication with data from other U.S. cities.”

Hipp, John R. and Adam Boessen (2012). “Immigrants and social distance: Examining the social consequences of immigration for Southern California neighborhoods over 50 years.” The ANNALS of the American Academy of Political and Social Science. 641(1): 192-219.

Abstract: “This project studied the effect of immigrant in-mobility on the trajectory of socio-economic change in neighborhoods. We suggest that immigrant inflows may impact neighborhoods due to the consequences of residential mobility and the extent these new residents differ from the current residents. We use southern California over a nearly 50-year period (1960 to 2007) as a case study to explore the short- and long- term impact of these changes. We find no evidence that immigrant inflow has negative consequences for home values, unemployment, or vacancies over this long period of time. Instead, we find that a novel measure that we develop—a general measure of social distance–is much better at explaining the change in the economic conditions of these neighborhoods. Tracts with higher levels of social distance experienced a larger increase in the vacancy rate over the decade. The effect of social distance on home values changed over the study period: whereas social distance decreased home values during the 1960’s, this completely reversed into a positive effect by the 2000’s.”

Hipp, John R. (2012). “Segregation through the lens of housing unit transition: What roles do the prior residents, the local micro-neighborhood, and the broader neighborhood play?” Demography. 49(4): 1285-1306.

Abstract: “This study focuses on segregation as it plays out at the micro-level of housing unit transition. Employing a unique sample that places housing units into micro-neighborhoods and census tracts, this study tests whether the characteristics of the previous residents of the unit, the local micro-neighborhood, or the broader tract best explain the race/ethnicity of the new residents in a housing unit. The results show that the racial/ethnic composition of the local micro-neighborhood has even stronger effects on the race/ethnicity of the new residents than does the racial/ethnic composition of the broader census tract. The results also reveal that even when the racial/ethnic composition of these two contexts are accounted for, the race/ethnicity of the prior residents has a very strong effect on the race/ethnicity of the new residents. I consider possible explanations for this household-level effect. One new theoretical explanation I put forward is that prospective residents use the race/ethnicity of the prior residents as a signal regarding the neighborhood’s appropriateness for them; I test and find that this hypothesized signaling effect is even stronger in certain micro-neighborhood, neighborhood, and county contexts.”

Hipp, John R., Robert W. Faris, and Adam Boessen (2012). “Measuring ‘neighborhood’: Constructing network neighborhoods.” Social Networks. 34(1): 128-140.

Abstract: “This study tests the effect of the composition and distribution of economic resources and race/ethnicity in cities, as well as how they are geographically distributed within these cities, on crime rates during a 30-year period. Using data on 352 cities from 1970 to 2000 in metropolitan areas that experienced a large growth in population after World War II, this study theorizes that the effect of racial/ethnic or economic segregation on crime is stronger in cities in which race/ethnicity or income are more salient (because of greater heterogeneity or inequality). We test and find that higher levels of segregation in cities with high levels of racial/ethnic heterogeneity lead to particularly high overall levels of the types of crime studied here (aggravated assaults, robberies, burglaries, and motor vehicle thefts). Similarly, higher levels of economic segregation lead to much higher levels of crime in cities with higher levels of inequality.”

Butts, Carter T., Ryan M. Acton, John R. Hipp, and Nicholas N. Nagle (2012). “Geographical Variability and Network Structure.” Social Networks. 34(1): 631-665.

Abstract: “In this paper, we explore the potential implications of geographical variability for the structure of social networks. Beginning with some basic simplifying assumptions, we derive a number of ways in which local network structure should be expected to vary across a region whose population is unevenly distributed. To examine the manner in which these effects would be expected to manifest given realistic population distributions, we then perform an exploratory simulation study that examines the features of large-scale interpersonal networks generated using block-level data from the 2000 U.S. Census. Using a stratified sample of micropolitan and metropolitan areas with populations ranging from approximately 1000 to 1,000,000 persons, we extrapolatively simulate network structure using spatial network models calibrated to two fairly proximate social relations. From this sample of simulated networks, we examine the effect of both within-location and between-location heterogeneity on a variety of structural properties. As we demonstrate, geographical variability produces large and distinctive features in the “social fabric” that overlies it; at the same time, however, many aggregate network properties can be fairly well-predicted from relatively simple spatial demographic variables. The impact of geographical variability is thus predicted to depend substantially on the type of network property being assessed, and on the spatial scale involved.”

Hipp, J. R. and A. Chamberlain (2011). “Community Change and Crime.” Oxford Bibliographies.

Introduction: “Community change and crime employs a dynamic perspective, linking ecological changes to changes in crime. More specifically, geographic places are considered entities that can change over time, and these changes can have important implications for various social and economic processes. Changes in a variety of structural characteristics have been linked to changes in crime, including economic and social resources, residential stability, immigration, and racial composition. Ecological changes are examined at both a micro and a macro level. Micro-level research may involve examining changes in an area as small as a street segment or as large as a neighborhood or police precinct area. Macro-level research may involve evaluating the impact of changes that occur across an entire city, county, or region. The issue of community change is further complicated when considering the fact that communities not only change over time, but the areas within which these communities are embedded are also changing, and these changes occur simultaneously. Variations in these surrounding areas may have a direct impact on levels of crime in a particular area. The growing evidence suggesting a link between neighborhood change and crime has also been applied to several policy initiatives. Programs such as Moving to Opportunity and Gautreaux are examples of such policies, in which inner-city residents are relocated to suburban areas with ample social and economic resources. The range of issues examined in the community change and crime literature is vast, but these studies provide a unique insight into understanding the role that the ecology of place plays in the amplification of crime.”

Hipp, John R. and Daniel K. Yates (2011). “Ghettos, thresholds, and crime: Does concentrated poverty really have an accelerating increasing effect on crime?” Criminology. 49(4): 955-990.

Abstract: “Theories make varying predictions regarding the functional form of the relationship between neighborhood poverty and crime rates, ranging from a diminishing positive effect, to a linear positive effect, to an exponentially increasing or even threshold effect. Nonetheless, surprisingly little empirical evidence exists testing this functional form. The present study estimates the functional form of the relationship between poverty and various types of serious crime in a sample of census tracts for 25 cities, and finds that a diminishing positive effect most appropriately characterizes this relationship whether estimating the models nonparametrically or parametrically. Only for the crime of murder is there some evidence of a threshold effect, although this occurs in the range of 20 to 40% in poverty, with a leveling effect on crime beyond this point of very high poverty. Thus, there is no evidence here in support of the postulate of William Julius Wilson that neighborhoods with very high levels of poverty will experience an exponentially higher rate of crime compared to other neighborhoods. We discuss the implications of these findings for the effect of the distribution of poverty throughout cities on overall levels of crime in cities.”

Hipp, John R. (2011). “Violent crime, mobility decisions, and neighborhood racial/ethnic transition.” Social Problems. 58(3): 410-432.

Abstract: “Numerous studies have observed a positive cross-sectional relationship between racial/ethnic minorities and crime and posited that this relationship is entirely due to a causal effect of minorities on crime rates. We posit that at least some of this relationship might be due to the opposite effect: neighborhood crime increases the number of racial/ethnic minorities. This study employs a sample that allows nesting housing units within census tracts in a number of cities to test the effect of violent crime rates on residential mobility. We find that racial/ethnic transformation occurs due to two effects: first, white households are more likely to exit neighborhoods with higher rates of violent crime than are African American households. Second, whites are significantly less likely to move into a housing unit in a tract with more violent crime, particularly if this violent crime rate is increasing. On the other hand, African American and Latino households are more likely to enter neighborhoods with higher levels of violent crime. And Latinos are particularly likely to enter neighborhoods experiencing an increasing level of violent crime over the previous four years.”

Hipp, John R. (2011). “Spreading the Wealth: The Effect of the Distribution of Income and Race/ethnicity across Households and Neighborhoods on City Crime Trajectories.” Criminology. 49(3): 631-665.

Steenbeek, Wouter and John R. Hipp. (2011). “A Longitudinal Test of Social Disorganization Theory: Feedback Effects between Cohesion, Social Control and Disorder.” Criminology. 49(3): 833-871.

Abstract: “Social disorganization theory holds that neighborhoods with greater residential stability, higher socioeconomic status, and more ethnic homogeneity experience less disorder because these neighborhoods have higher social cohesion and exercise more social control. Recent extensions of the theory argue that disorder in turn affects these structural characteristics and mechanisms. Using a data set on 74 neighborhoods in the city of Utrecht in the Netherlands spanning 10 years, we tested the extended theory, which to date only a few studies have been able to do because of the unavailability of neighborhood-level longitudinal data. We also improve on previous studies by distinguishing between the potential for social control (feelings of responsibility) and the actual social control behavior. Cross-sectional analyses replicate earlier findings, but the results of longitudinal cross-lagged models suggest that disorder has large consequences for subsequent levels of social control and residential instability, thus leading to more disorder. This is in contrast to most previous studies, which assume disorder to be more a consequence than a cause. This study underlines the importance of longitudinal data, allowing for simultaneously testing the causes and consequences of disorder, as well as the importance of breaking down social control into the two dimensions of the potential for social control and the actual social control behavior.”

Hipp, John R. (2010). “Assessing Crime as a Problem: The Relationship between Residents’ Perception of Crime and Official Crime Rates over 25 Years.” Crime & Delinquency. 16(4): 674-683.

Abstract: “This study compares the relationship between official crime rates in census tracts and resident perceptions of crime. Employing a unique dataset that links household level data from the American Housing Survey metro samples over 25 years (1976-1999) with official crime rate data for census tracts in selected cities during selected years, this study finds that tract violent crime is the strongest predictor of residents’ perception of crime. This standardized coefficient was .71 on average over the seven waves. Models simultaneously taking into account both violent and property crime consistently found a strong positive effect for violent crime, but a consistently negative effect for property crime. Among types of violent crime, robbery and aggravated assault have the strongest effect on the perception of crime in the tract. Burglary showed a stronger effect on perceptions of crime in the 1970s, but a steadily weakening effect since then.”

Hipp, John R. and Cynthia M. Lakon. (2010). “Social Disparities in Health: Disproportionate toxicity proximity in minority communities over a decade.” Health & Place. 16(4): 674-683.

Abstract: “This study employs latent trajectory models measuring the level of toxic waste over a decade in the cities of six highly populated, ethnically diverse, counties in southern California from 1990-2000 in 3,001 tracts. We find that tracts with 15% more Latinos are exposed to 84.3% more toxic waste than an average tract over this time period and tracts with 15% more Asians are exposed to 33.7% more toxic waste. Conversely, tracts with one standard deviation more residents with at least a bachelor’s degree (15.5%) are exposed to 88.8% less toxic waste than an average tract. We also found that these effects were considerably weaker when using the raw pounds of toxic waste rather than the toxicity-weighted measure, suggesting that future research will want to account for the toxicity of the waste.”

Boggess, Lyndsay N. and John R. Hipp. (2010). “Violent crime, residential instability and mobility: Does the relationship differ in minority neighborhoods?” Journal of Quantitative Criminology. 26(3): 351-370.

Abstract: “This study examines the relationship between violent crime and residential instability. We test whether the form of stability matters by comparing two different measures of stability: a traditional index of residential stability and compare it to a novel approach focusing specifically on the stability of homeowners. We test whether the racial/ethnic composition in which this stability occurs affects the instability – violent crime relationship. We test the simultaneous relationship between residential mobility and crime by estimating a dual multivariate latent curve model of the change in the violent crime rate and the change in the rate of home sales while controlling for neighborhood socioeconomic and demographic characteristics using data from Los Angeles between 1992 and 1997. The use of trajectory models provides a more thorough examination of the years under study than other longitudinal methodology, and can more accurately account for the nonlinearity of change over time. Results indicate that the initial level of violent crime increases the trajectory of residential instability in subsequent years for both of our measures of residential stability, but that the level of residential instability in most neighborhoods has no impact on the trajectory of violent crime over time. The one exception we find is that stable highly Latino communities do exhibit a protective effect against violence.”

Lakon, Cynthia M., John R. Hipp, and David S. Timberlake. (2010). “The Social Context of Adolescent Smoking: A Systems Perspective.” American Journal of Public Health. 100(7): 1218-1228.

Abstract: “Objectives: We examined the context of adolescent cigarette smoking as a system of contextual structures including youths’ personal and school networks, and neighborhoods, which, via flows of emotional support and influence from friends’ smoking behavior, affect past month smoking at two time points.

Methods: Using public use data (N=6,504) from wave one, and one measure of past month smoking from wave two, of the National Longitudinal Study of Adolescent Health, a nationally representative sample of students in grades 7 through 12, we employ Structural Equation Modeling to test relationships.

Results: Personal network properties affected past month smoking at time two via the flow of emotional support. Friends smoking had an effect on past month smoking at both time points. We found evidence of a partial feedback loop, from personal network properties to emotional support and then to past month smoking at time two. Past month smoking at time one fed back to positively affect in-degree centrality.

Conclusions: Findings suggest that personal and school networks and neighborhoods were important structures in the system, via flows of emotional support, in positively affecting past month smoking.”

Hipp, John R. (2010). “A dynamic view of neighborhoods: The reciprocal relationship between crime and neighborhood structural characteristics.” Social Problems. 57(2): 205-230.

Abstract: “Prior research frequently observes a positive cross-sectional relationship between various neighborhood structural characteristics and crime rates, and attributes the causal explanation entirely to these structural characteristics. We question this assumption theoretically, proposing a household-level model showing that neighborhood crime might also change these structural characteristics. We test these hypotheses using data on the census tracts in 13 cities over a ten-year period, and our cross-lagged models generally find that, if anything, crime is the stronger causal force in these possible relationships. Neighborhoods with more crime tend to experience increasing levels of residential instability, more concentrated disadvantage, a diminishing retail environment, and more African Americans ten years later. Although we find that neighborhoods with more concentrated disadvantage experience increases in violent and property crime, there is no evidence that residential instability increases crime rates ten years later.”

Hipp, John R. (2010). “Micro-structure in Micro-Neighborhoods: A New Social Distance Measure, and its Effect on Individual and Aggregated Perceptions of Crime and Disorder.” Social Networks. 32(3): 148-159.

Abstract: “This study links social network methodology with the social disorganization literature to test the effect of block-level social distance on neighborhood perceived crime and disorder. Employing a unique study design that allows creating matrices of social distance (based on demographic characteristics) between 11 residents on each of over 650 blocks at three time points, we find that more socially distant residents perceive more disorder than their neighbors. Consistent with the bridging social capital literature, overall social distance in the block has a curvilinear relationship with perceived crime. And blocks with two cohesive subgroups, based on social distance, have lower levels of perceived disorder.”

Hipp, John R., Joan Petersilia, and Susan Turner. (2010). “Parolee Recidivism in California: The Effect of Neighborhood Context and Social Service Agency Characteristics.” Criminology. 48(4): 947-979.

Abstract: “We studied a sample of re-entering parolees in California in 2005-06 to examine whether the social structural context of the census tract, as well as nearby tracts, along with the relative physical closeness of social providers, affects serious recidivism resulting in imprisonment. We found a strong effect in which increasing the presence of nearby social service providers (within two miles) decreases the likelihood of recidivating 41%, and that this protective effect is particularly strong for African American and Latino parolees. It appears that this protective effect may be diminished by over-taxed services (as proxied by potential demand). We find that higher levels of concentrated disadvantage and social disorder (as measured by bar and liquor store capacity) in both the neighborhood and surrounding neighborhoods increase recidivism. The findings suggest that the social context to which parolees return, as well as the accessibility of social service agencies, plays an important role in their successful reintegration.”

Hipp, John R., Jesse Jannetta, and Susan Turner. (2010). “Are sex offenders moving into social disorganization? Analyzing the residential mobility of California parolees.” Journal of Research in Crime and Delinquency. 47(4): 558-590.

Abstract: “This study focuses on the relationship between returning offender residential mobility and neighborhood structural factors characteristic of socially disorganized neighborhoods. It utilizes a unique dataset that combines information on parolees released in the state of California during the 2005-06 time-period with their geocoded addresses to view the types of neighborhoods they are moving to. We find that sex offenders are entering neighborhoods with more concentrated disadvantage and residential instability upon re-entry from prison and upon subsequent moves. This effect for sex offender status is particularly strong for whites and Latinos, leading them into more socially disorganized neighborhoods. We also find that sex offenders are more likely to enter neighborhoods with more minorities as measured by Latinos and African Americans, and less likely to enter neighborhoods with more whites.”

Hipp, John R. (2010). “What is the “neighbourhood” in neighbourhood satisfaction?” Urban Studies. 47(12): 2517-2536.

Abstract: “Using the neighborhood sub-sample from the American Housing Survey for 1985, 1989, 1993, this study tests whether the social context of the local micro-neighborhood or of the broader census tract more strongly affects neighborhood satisfaction. We find that the local context of the micro-neighborhood generally has a stronger effect on residents’ reported satisfaction. In contrast to studies aggregating to larger units, we find that greater residential stability in the micro-neighborhood increases reported neighborhood satisfaction. Low SES of the local micro-neighborhood decreases neighborhood satisfaction more than does the SES of the surrounding tract, and this effect is amplified in low-income tracts. Whereas prior evidence is mixed when aggregating perceptions of crime to larger units, we find a robust negative effect on satisfaction when aggregated to the micro-neighborhood.”

Hipp, John R. (2010). “The role of crime in housing unit racial/ethnic transition.” Criminology. 48(3): 683-723.

Abstract: “Previous research frequently observes a positive cross-sectional relationship between racial/ethnic minorities and crime and generally posits that this relationship is entirely due to the effect of minorities on neighborhood crime rates. We posit that at least some of this relationship might be due to the opposite effect: neighborhood crime increases the number of racial/ethnic minorities. This study employs a unique sample (the American Housing Survey neighborhood sample) focusing on housing units nested in micro-neighborhoods over three waves from 1985 to 1993. This allows us to test and find that such racial/ethnic transformation occurs due to two effects: first, white households that perceive more crime in the neighborhood, or that live in micro-neighborhoods with more commonly perceived crime, are more likely to move out of such neighborhoods. Second, whites are significantly less likely to move into a housing unit in a micro-neighborhood with more commonly perceived crime, whereas African American and Latino households are more likely to move into such units.”

Hipp, John R.. 2010. “Resident perceptions of crime: How much is ‘bias’ and how much is micro-neighborhood effect?” Criminology. 48(2): 475-508.

Abstract: “This study attempts to disentangle the extent to which residents are systematically biased when reporting on the level of crime or disorder in their neighborhood. By utilizing a unique sample of households nested in household clusters, this study teases out the degree of systematic bias on the part of respondents when perceiving crime and disorder. Our findings are generally consistent with theoretical expectations of which types of residents will perceive more crime or disorder, and contrast with the generally mixed results of prior studies that utilize an inappropriate aggregate unit when assuming that residents live in the same social context of crime or disorder. Estimating ancillary models on a sample of respondents nested in tracts produces mixed results that mirror the existing literature. We find that whites consistently perceive more crime or disorder than their neighbors. We also found that females, those with children, and those with longer residence in the neighborhood perceive more crime or disorder than their neighbors.”

Hipp, John R. and Daniel K. Yates. 2009. “Do returning parolees affect neighborhood crime? A case study of Sacramento.” Criminology. 47(3): 619-656.

Abstract: “This study utilized a unique dataset that combines information on parolees in the city of Sacramento, CA over the 2003-06 time-period with information on monthly crime rates in Sacramento census tracts over this same period, providing us a fine-grained temporal and geographical view of the relationship between the change in parolees in a census tract and the change in the crime rate. We find that an increase in the number of tract parolees in a month results in an increase in the crime rate. We find that more violent parolees have a particularly strong effect on murder and burglary rates. We find that the social capital of the neighborhood can moderate the effect of parolees on crime rates: neighborhoods with greater residential stability dampen the effect of parolees on robbery rates, whereas neighborhoods with greater numbers of voluntary organizations dampen the effect of parolees on burglary and aggravated assault rates. Furthermore, this protective effect of voluntary organizations appears strongest for those organizations that provide services for youth. We show that the effect of single parent households in a neighborhood is moderated by the return of parolees, suggesting that these re-united families may increase the social control ability of the neighborhood.”

Hipp, John R., Jesse Jannetta, Rita Shah, and Susan Turner. 2009. “Parolees’ physical closeness to health service providers: A study of California Parolees.” Health & Place. 15(3): 679-688.

Abstract: “We studied a sample of parolees and health service providers in the state of California in 2005-06 to examine the relative physical closeness to health providers (and the potential demand of these providers) of parolees based on their demographic and prior offending characteristics. Although African-American and Latino parolees have more health providers nearby, these providers have considerably more potential demand. The health providers near long-term prisoners and sex offenders have more potential demand. The results suggest inequity in access to services, as minority parolees and those with greater needs may live near more impacted providers. The results also suggest some differences in access based on rural, suburban, or urban location.”

Hipp, John R., George E. Tita, and Robert T. Greenbaum. 2009. “Drive-bys and Trade-ups: The Impact of Crime on Residential Mobility Patterns in Los Angeles.” Social Forces. 87(4): 1777-1812.

Abstract: “Most prior research testing the hypothesis of the social disorganization theory that residential instability increases crime has used cross-sectional data. Using a unique dataset linking home sales geocoded to census tracts with crime data in Los Angeles, we test the direction of this relationship using a six-year panel data design. We also test whether crime acts as a generator of transition and decline in neighborhoods by testing its effect on property values the following year. Our findings suggest little evidence that home sales volatility in one year leads to more property or violent crime the following year. Instead, higher levels of tract property and violent crime in one year lead to more home sales the following year. This effect of high crime rates is exacerbated in tracts with high levels of racial/ethnic heterogeneity, suggesting that such tracts may engender a distinct combination of fear and uncertainty in their residents, leading to more turnover. We also find that tracts with more violent crime one year have lower property values the following year, suggesting a general process of decline.”

Hipp, John R. 2009. “Specifying the Determinants of Neighborhood Satisfaction: A Robust Assessment in 24 Metropolitan Areas over Four Time Points.” Social Forces. 88(1):395-424.

Abstract: “Using a sample of households nested in census tracts in 24 metropolitan areas over four time points, this study provides a robust test of the determinants of neighborhood satisfaction taking into account the census tract context. Consistent with social disorganization theory, the presence of racial/ethnic heterogeneity and single parent households consistently reduced neighborhood satisfaction. Those perceiving more social or physical disorder were considerably less satisfied with the neighborhood, and perceiving more crime showed an accelerating negative effect on satisfaction. Furthermore, the effect of perceiving crime was exacerbated in tracts with a distressed labor market or the presence of disengaged youth. There was consistent evidence that those with more economic investment (homeowners) or social investment (married residents and parents) in the neighborhood are more satisfied. On the other hand, there was no evidence that longer-term residents report more satisfaction, nor that general residential stability in the tract will increase satisfaction.”

Hipp, John R., George E. Tita, and Lyndsay N. Boggess. 2009. “Inter- and Intra-group violence: Is violent crime an expression of group conflict or social disorganization?” Criminology. 47(2): 521-564.

Abstract: “The impact of residential turnover and compositional change at the neighborhood level on local patterns of crime lies at the center of most ecological studies of crime and violence. Of particular interest is how racial and ethnic change impacts intra-group and inter-group crime. Though many studies have examined this using city-level data, few have looked at it using neighborhood-level data. Using incident level data for the South Bureau Policing Area of the Los Angeles Police Department aggregated to Census tracts, we utilize a novel methodology to construct intra- and inter-group rates of robbery and assaults. The South Bureau has experienced dramatic demographic change as it has transitioned from a predominately African-American area to a predominately Latino area. We find support for the social disorganization model, as racial/ethnic transition in nearby tracts leads to greater levels of inter-group violence by both groups, as well as more intra-group violence by Latinos. Such neighborhoods appear to experience a breakdown in norms leading to higher levels of all forms of violence. Particularly noteworthy is that intra-group crime is highest in all settings, including the most heterogeneous tracts. We also find support for the consolidated inequality theory, as greater inequality across the two groups leads to more violence by the disadvantaged group.”

Hipp, John R., Jesse Jannetta, Rita Shah, and Susan Turner. 2011. “Parolees’ physical closeness to social services: A study of California Parolees.” Crime and Delinquency. 57(1): 102-129.

Abstract: “This study examines the proximity of service providers to recently released parolees in California over a 2-year period (2005-2006). The addresses of parolee residences and service providers are geocoded, and the number of various types of service providers within 2 miles (3.2 km) of a parolee are measured. “Potential demand” is measured as the number of parolees within 2 miles of a provider. Although racial and ethnic minority parolees have more service providers nearby, these providers appear to be particularly impacted based on potential demand. It is also found that the parolees arguably most in need of social services—those who have spent more time in correctional institutions, have been convicted of more serious or violent crimes in their careers, or are sex offenders—live near fewer social services, or the providers near them appear impacted.”

Hipp, John R. and Andrew J. Perrin. 2009. “The Simultaneous Effect of Social Distance and Physical Distance on the Formation of Neighborhood Ties.” City & Community. 8(1): 5-25.

Abstract: “Prior studies have separately suggested the importance of physical distance or social distance effects for the creation of neighborhood ties. This project adopts a case study approach and simultaneously tests for propinquity and homophily effects on neighborhood ties by employing a full-network sample from a recently-developed New Urbanist neighborhood within a mid-sized southern city. The authors find that physical distance reduces the likelihood of weak or strong ties forming, suggesting the importance of accounting for propinquity when estimating social tie formation. The authors simultaneously find that social distance along wealth reduces the likelihood of weak ties forming. Social distance on life course markers—age, marital status, and the presence of children—reduces the formation of weak ties. Consistent with the systemic model, each additional month of shared residence in the neighborhood increases both weak and strong ties. An important innovation is this study’s ability to directly compare the effects of physical distance and social distance, placing them into equivalent units: a ten percent increase in home value difference is equivalent to a 5.6 percent increase in physical distance.”

Hipp, John R. 2007. “Block Tract, and Levels of Aggregation: Neighborhood Structure and Crime and Disorder as a Case in Point.” American Sociological Review. 72(5): 659-680.

Abstract: “This paper highlights the importance of seriously considering the proper level of aggregation when estimating neighborhood effects. Using a unique non-rural sub-sample from a large national survey (the American Housing Survey) at three time points that allows placing respondents in blocks and census tracts, this study tests the appropriate level of aggregation of the structural characteristics hypothesized to affect block-level perceived crime and disorder. A key finding is that structural characteristics differ in their effects based on the level of aggregation employed. While the effects of racial/ethnic heterogeneity were fairly robust to geographical level of aggregation, the stronger effects when measured at the level of the surrounding census tract suggest more far-flung networks are important for perceived crime and disorder. In contrast, economic resources showed a particularly localized effect only evident when aggregating to the block-level and differed based on the outcome: higher average income reduced disorder, but increased crime, likely by increasing the number of attractive targets. And the presence of broken households had a localized effect for social disorder, but a more diffuse effect for perceived crime. These findings suggest the need to consider the mechanisms involved when aggregating various structural characteristics in neighborhood studies of crime rates, as well as the broader neighborhood effects literature.”

Hipp, John R. 2007. “Income Inequality, Race, and Place: Does the Distribution of Race and Class within Neighborhoods affect Crime Rates?” Criminology. 45(3): 665-697.

Abstract: “This study tests the effects of neighborhood inequality and heterogeneity on crime rates. Using a large sample of census tracts in 19 cities in 2000, the results provide strong evidence of the importance of racial/ethnic heterogeneity for the amount of all types of crime generally committed by strangers, even controlling for the effects of income inequality. Consistent with the predictions of several theories, greater overall inequality in the tract was associated with higher crime rates, particularly for violent types of crime. There was also strong evidence that within racial/ethnic group inequality increases crime rates: only the relative deprivation model predicted this association. An illuminating finding is that the effect of tract poverty on robbery and murder becomes non-significant when taking into account the level of income inequality, suggesting that past studies failing to take into account income inequality may have inappropriately attributed causal importance to poverty. This large sample also provides evidence that it is the presence of homeowners, rather than residential stability (as measured by the average length of residence), that significantly reduces the level of crime in neighborhoods.”

The online Appendix for this article is here

Lakon, Cynthia M., Dionne C. Godette, and John R. Hipp. 2007. “Network-Based Approaches for Measuring Social Capital.” Pp. 63-81 in Social Capital and Health, edited by I. Kawachi, S. V. Subramanian, and D. Kim. New York: Springer.

Abstract: “Despite the burgeoning literature on social capital that spans numerous disciplines, little is known about network measures of this construct. Prior studies within the fields of Sociology and Communications have explored how network measures of social capital account for the structural, positional, and functional measures of network actors. Hence, the goal of this chapter is to define key terminology relating to social networks and to discuss how social networks may be used to measure social capital in Public Health. The chapter provides a general overview of basic network measures of social capital, including structural, positional, and functional measures of network ties, in relation to both egocentric and whole networks. The chapter closes with a glossary of relevant social network terms (see Appendix 1), and a brief orientation to egocentric networks and sociometric networks (see Appendix 2)—readers unfamiliar with social network methodology may wish to consult these appendices before reading the main text.”

Hipp, John R. and Andrew J. Perrin (2006). “Nested Loyalties: Local Networks’ Effects on Neighborhood and Community Cohesion.” Urban Studies. 43(13): 2503-2523.

Abstract: “Recent scholarship has suggested that cohesion at the neighborhood level may not translate into greater cohesion for the broader community, and may even have detrimental effects. Employing a sample from a recently-developed New Urbanist community within a southern city, we simultaneously explore the determinants of perceived cohesion with the local neighborhood and with the broader community. We find that there is indeed a positive relationship between the two in this sample. However, we find that the determinants of the two differ: while both strong and weak informal ties in the neighborhood increase perceived neighborhood cohesion, only weak ties foster perceived cohesion with the broader community. We find no effect of residents’ structural positions within local networks on perceived cohesion beyond the effect of strong and weak ties. We discuss the implications of our findings for the broader literature viewing the effects of bridging and bonding social capital.”

Beyerlein, Kraig and John R. Hipp* (2006). “A Two-Stage Model for a Two-Stage Process: How Biographical Availability Matters for Social Movement Mobilization.” Mobilization. 11(3): 219-240.

Abstract: “This paper contributes to the social movement literature on differential participation by modeling protest activism as a two-stage mobilization process: willingness to engage in protest action and conversion of protest willingness into actual protest participation. We demonstrate how modeling protest activism as a two-stage mobilization process resolves one of the more puzzling empirical findings to emerge from the social movement literature on differential participation: the lack of constraining effects for biographical unavailability. Drawing on a nationally representative sample of individuals in the United States, we find that while our measures of biographical unavailability have no effect on the second stage of the mobilization process (conversion of protest willingness to actual protest behavior), they show striking robust negative effects on the first-stage of the mobilization process, removing people from the pool of willing protest participants. We also find that gender moderates the relationship between some of our measures of biographical unavailability-particularly marital status-and protest willingness. Our results suggest that future researchers would benefit from specifically modeling the distinct stages of social movement mobilization.”

* Order of authorship is alphabetical to denote equal contribution

Beyerlein, Kraig and John R. Hipp* (2006). “From Pews to Participation: The Effect of Congregation Activity and Context on Bridging Civic Engagement.” Social Problems. 53(1): 97-117.

Abstract: “This article identifies two important conditions under which participation in religious congregations influences active involvement in civic organizations that provide charitable services to and establish other types of linkages with residents in the wider community. We find that while the frequently employed measure of religious service attendance has minimal effects on participation in bridging types of civic organizations, congregation activity beyond religious service attendance has a substantial positive effect on participation in charitable and linking types of civic organizations. In addition, our findings demonstrate that religious tradition significantly moderates the extent to which congregation activity channels bridging civic engagement. While active involvement in black Protestant, mainline Protestant, and Catholic congregations predicts participation in substantially more bridging civic organizations, active involvement in evangelical Protestant congregations has little effect on this participation.”

* Order of authorship is alphabetical to denote equal contribution

Beyerlein, Kraig and John R. Hipp*. 2005. “Social capital, too much of a good thing? American religious traditions and community crime.” Social Forces. 84 (2): 995-1013.

Abstract: “Using American religious traditions as measures of bonding and bridging social capital in communities, we empirically test how these different forms of social capital affect crime rates in 3,157 U.S. counties in 2000. Our results suggest that the bonding networks evangelical Protestants promote in communities explain why counties with a greater percentage of residents affiliated with this tradition consistently have higher crime rates. Conversely, our results suggest that the bridging networks mainline Protestants and Catholics foster in communities explain why counties with a greater percentage of residents affiliated with these traditions generally have lower crime rates. This article provides empirical corroboration for recent theoretical discussions that focus on how the social capital groups cultivate in communities need not always benefit communities as a whole.”

* Order of authorship is alphabetical to denote equal contribution

The online Appendix for this article is here

Hipp, John R., Daniel J. Bauer, Patrick J. Curran, and Kenneth A. Bollen. 2004. “Crimes of Opportunity or Crimes of Emotion: Testing Two Explanations of Seasonal Change in Crime.” Social Forces. 82:1333-1372.

Abstract: “While past research has suggested possible seasonal trends in crime rates, this study employs a novel methodology that directly models these changes and predicts them with explanatory variables. Using a nonlinear latent curve model, seasonal fluctuations in crime rates are modeled for a large number of communities in the United States over a three-year period with a focus on testing the theoretical predictions of two key explanations for seasonal changes in crime rates: the temperature/aggression and routine activities theories. Using data from 8,460 police units in the United States over the 1990 to 1992 period, we found that property crime rates are primarily driven by pleasant weather, consistent with the routine activities theory. Violent crime exhibited evidence in support of both theories.”

Pastor, Manuel Jr., Jim Sadd, and John Hipp. 2001. “Which Came First? Toxic Facilities, Minority Move-in, and Environmental Justice.” Journal of Urban Affairs. 23:1-21.

Abstract: “Previous research suggests that minority residential areas have a disproportionate likelihood of hosting various environmental hazards. Some critics have responded that the contemporary correlation of race and hazards may reflect post-siting minority move-in, perhaps because of a risk effect on housing costs, rather than discrimination in siting. This article examines the disproportionate siting and minority move-in hypotheses in Los Angeles County by reconciling tract geography and data over three decades with firm-level information on the initial siting dates for toxic storage and disposal facilities. Using simple t-tests, logit analysis, and a novel simultaneous model, we find that disproportionate siting matters more than disproportionate minority move-in in the sample area. Racial transition is also an important predictor of siting, suggesting a role for multiracial organizing in resisting new facilities.”

Social Networks papers

Wang, Cheng, John R. Hipp, Carter T. Butts, and Cynthia M. Lakon. (2021). “The Moderating Role of Context: Relationships between Individual Behaviors and Social Networks.” Sociological Focus. 55(2): 191-212

Abstract: “A social context can be viewed as an entity or unit around which a group of individuals organize their activities and interactions. Social contexts take such diverse forms as families, dwelling places, neighborhoods, classrooms, schools, workplaces, voluntary organizations, and sociocultural events or milieus. Understanding social contexts is essential for the study of individual behaviors, social networks, and the relationships between the two. Contexts shape individual behaviors by providing an avenue for non-dyadic conformity and socialization processes. The co-participation within a context affects personal relationships by acting as a focus for tie formation. Where participation in particular contexts confers status, this effect may also lead to differences in popularity within interpersonal networks. Social contexts may further play a moderating role in within-network influence and selection processes, providing circumstances that either amplify or suppress these effects. In this paper we investigate the joint role of co-participation via social contexts and dyadic interaction in shaping and being shaped by individual behaviors with the context of a U.S. high school. Implications for future study of social contexts are suggested.”

Wang, Cheng, John R. Hipp, Carter T. Butts, and Cynthia M. Lakon. (2021). “Insight into Selecting Adolescents for Drinking Intervention Programs: A Simulation Based on Stochastic Actor-Oriented Models.” Prevention Science Forthcoming.

Abstract: “Adolescent drinking remains a prominent public health and socioeconomic issue in the United States with costly consequences. While numerous drinking intervention programs have been developed, there is little guidance whether certain strategies of participant recruitment are more effective than others. The current study aims at addressing this gap in the literature using a computer simulation approach, a more cost-effective method than employing actual interventions. We first estimate Stochastic Actor-Oriented models for two schools from the National Longitudinal Study of Adolescent to Adult Health (Add Health). We then employ different strategies for selecting adolescents for the intervention (either based on their drinking levels or their positions in the school network) and simulate the estimated model forward in time to assess the aggregated level of drinking in the school at a later timepoint. The results suggest that selecting moderate or heavy drinkers for the intervention produces better results compared to selecting casual or light drinkers. The intervention results are improved further if network position information is taken into account, as selecting drinking adolescents with a higher in-degree or higher eigenvector centrality values for intervention yields the best results. Results from this study help elucidate participant selection criteria and targeted network intervention strategies for drinking intervention programs in the U.S.”

+Jose, Rupa, John R. Hipp, Carter T. Butts, Cheng Wang, and Cynthia M. Lakon. (2021). “A Multi-Contextual Examination of Non-School Friendships and their Impact on Adolescent Deviance and Alcohol Use.” PLOS One. [Freely available online]

Abstract: “Despite decades of research on adolescent friendships, little is known about adolescents who are more likely to form ties outside of school. We examine multiple social and ecological contexts including parents, the school, social networks, and the neighborhood to understand the origins and health significance of out of school ties using survey data from the National Longitudinal Study of Adolescent to Adult Health (N = 81,674). Findings indicate that out of school (more than in-school) friendships drive adolescent deviance and alcohol use, and youth with such friends tend to be involved in school activities and are central among their peer group. This suggests that intervention efforts aimed at reducing deviance and underage drinking may benefit from engaging youth with spanning social ties.”

Wang, Cheng, Carter T. Butts, John R. Hipp, Rupa Jose, and Cynthia M. Lakon. (2020). “Model Adequacy Checking/Goodness of Fit Testing for Behavior in Joint Dynamic Network/Behavior Models, with an Extension to Two-Mode Networks” Sociological Methods & Research. Forthcoming.

Abstract: “The recent popularity of models that capture the dynamic co-evolution of both network structure and behavior has driven the need for summary indices to assess the adequacy of these models to reproduce dynamic properties of scientific or practical importance. Whereas there are several existing indices for assessing the ability of the model to reproduce network structure over time, to date there are few indices for assessing the ability of the model to reproduce individuals’ behavior patterns. Drawing on the widely used strategy of assessing model adequacy by comparing index values summarizing features of the observed data to the distribution of those index values on simulated data from the fitted model, we propose four goals that a researcher could reasonably expect of a joint structure/behavior model regarding how well it captures behavior, and describe indices for assessing each of these. These reasonably simple and easily implemented indices can be used for assessing model adequacy with any dynamic network models jointly working with networks and behavior, including the Stochastic Actor-Based models implemented within software packages such as RSiena. We demonstrate the use of our indices with an empirical example to show how they can be employed in practical settings, with an additional extension to modeling affiliation dynamics in two-mode networks.”

Wang, Cheng, John R. Hipp, Carter T. Butts, and Cynthia M. Lakon. (2018). “The interdependence of cigarette, alcohol, and marijuana use in the context of school-based social networks.” PLOS One. July 20, 2018. [Freely available online]

Abstract: “The concurrent or sequential usage of multiple substances during adolescence is a serious public health problem. Given the importance of understanding interdependence in substance use during adolescence, the purpose of this study is to examine the co-evolution of cigarette smoking, alcohol, and marijuana use within the ever-changing landscape of adolescent friendship networks, which are a primary socialization context for adolescent substance use. Utilizing Stochastic Actor-Based models, we examine how multiple simultaneous social processes co-evolve with adolescent smoking, drinking, and marijuana use within adolescent friendship networks using two school samples from early waves of the National Longitudinal Study of Adolescent to Adult Health (Add Health). We also estimate two separate models examining the effects from using one substance to the initiation and cessation of other substances for each sample. Based on the initial model results, we simulate the model forward in time by turning off one key effect in the estimated model at a time, and observe how the distribution of use of each substance changes. We find evidence of a unilateral causal relationship from marijuana use to subsequent smoking and drinking behaviors, resulting in the initiation of drinking behavior. Marijuana use is also associated with smoking initiation in a school with a low substance use level, and smoking cessation in a school with a high substance use level. In addition, in a simulation model excluding the effect from marijuana use to smoking and drinking behavior, the number of smokers and drinkers decreases precipitously. Overall, our findings indicate some evidence of sequential drug use, as marijuana use increased subsequent smoking and drinking behavior and indicate that an adolescent’s level of marijuana use affects the initiation and continuation of smoking and drinking.”

Lakon, Cynthia M., Wang, Cheng, Carter T. Butts, Rupa Jose, and John R. Hipp. (2017). “Cascades of Emotional Support in Friendship Networks and Adolescent Smoking.” PLOS One. June 29, 2017. [Freely available online]

Abstract: “Social support from peers and parents provides a key socialization function during adolescence. We examine adolescent friendship networks using a Stochastic Actor-Based modeling approach to observe the flow of emotional support provision to peers and the effect of support from parents, while simultaneously modeling smoking behavior. We utilized one school (n = 976) from The National Longitudinal Study of Adolescent to Adult Health (AddHealth) Study. Our findings suggest that emotional support is transacted through an interdependent contextual system, comprised of both peer and parental effects, with the latter also having distal indirect effects from youths’ friends’ parents.”

Wang, Cheng, John R. Hipp, Carter T. Butts, Rupa Jose, and Cynthia M. Lakon. (2017). “Peer Influence, Peer Selection and Adolescent Alcohol Use: A Simulation Study Using a Dynamic Network Model of Friendship Ties and Alcohol Use.” Prevention Science. 18(4): 382-393.

Boessen, Adam, John R. Hipp, Emily J. Smith, Carter T. Butts, and Nicholas N. Nagle. (2016). “Social Fabric and Fear of Crime: Considering Spatial Location and Time of Day.” Social Networks. 51(1): 60-72.

Wang, Cheng, John R. Hipp, Carter T. Butts, Rupa Jose, and Cynthia M. Lakon. (2016). “Co-Evolution of Adolescent Friendship Networks and Smoking and Drinking Behaviors with Consideration of Parental Influence.” Psychology of Addictive Behaviors. 30(3): 312-324.

Abstract: “Friendship tie choices in adolescent social networks coevolve simultaneously with youths’ cigarette smoking and drinking. We estimate direct and multiplicative relationships between both peer influence and peer selection with salient parental factors affecting both friendship tie choice and the use of these two substances. We utilized one sample of 12 small schools and a single large school extracted from the National Longitudinal Study of Adolescent to Adult Health. Using a Stochastic Actor-Based modeling approach over three waves, we found: 1) a peer selection effect, as adolescents nominated others as friends based on cigarette and alcohol use levels, across samples; 2) a peer influence effect, as adolescents adapted their smoking and drinking behaviors to those of their best friends across samples; 3) reciprocal effects of cigarettes and alcohol in the small schools sample; 4) a direct effect of parental support and the home smoking environment on adolescent friendship tie choice in the small school sample; 5) a direct effect of the home smoking environment on smoking across samples; 6) a direct effect of the home drinking environment on alcohol use across samples and 7) a direct effect of parental monitoring on alcohol use across samples. We observed an interaction between parental support and peer influence in affecting drinking, and an interaction between the home drinking environment and peer influence on drinking, in the small schools sample. Our findings suggested the importance of delineating direct and synergistic pathways linking network processes and parental influences as they affect concurrent cigarette and alcohol use.”

Lakon, Cynthia M., John R. Hipp, Cheng Wang, Carter T. Butts, and Rupa Jose. (2015). “Simulating a Dynamic Network Model of Adolescent Smoking: Varying Peer Influence and Selection.” American Journal of Public Health. 105(12): 2438-2448.

A video describing the project and the research team can be found here.

Abstract: “We used a stochastic actor-based approach to examine the effect of peer influence and peer selection—the propensity to choose friends who are similar—on smoking among adolescents. Data were collected from 1994 to 1996 from 2 schools involved in the National Longitudinal Study of Adolescent to Adult Health, with respectively 2178 and 976 students, and different levels of smoking. Our experimental manipulations of the peer influence and selection parameters in a simulation strategy indicated that stronger peer influence decreased school-level smoking. In contrast to the assumption that a smoker may induce a nonsmoker to begin smoking, adherence to antismoking norms may result in an adolescent nonsmoker inducing a smoker to stop smoking and reduce school-level smoking.”

Wang, Cheng, Cynthia M. Lakon, John R. Hipp, Carter T. Butts, and Rupa Jose. (2015). “Alcohol Use among Adolescent Youths: The Role of Friendship Networks and Family Factors in Multiple School Studies.” PLOS One. March 2015. [freely available]

Abstract: “This study examines the co-evolution of friendship networks and alcohol use behaviors for 1,284 adolescents from 12 schools from the National Longitudinal Study of Adolescent Health Study over three time periods. We apply a stochastic actor-based model to explore network dynamics and social influences simultaneously, net of other socio-demographic, family, and network factors. Findings indicate that adolescents with similar alcohol use levels were more likely to form connections or friendships than their peers with more dissimilar alcohol use levels. Moreover, adolescents adjusted their alcohol use behaviors to match the alcohol use behaviors of their peers. In predicting similarity in alcohol use behaviors, peer influence processes played a more significant role than peer selection processes. A unilateral rather than a reciprocal effect is confirmed from drinking frequency to popularity in the network. Findings suggest that the peer network and familial context provide key avenues for intervention targeting the reduction of alcohol use among adolescents.”

Lakon, Cynthia M. and John R. Hipp. (2014). “On Social and Cognitive Influences: Relating Adolescent Networks, Generalized Expectancies, and Adolescent Smoking.” PLOS:ONE. December 2014. [freely available]

Abstract: “Although stochastic actor-based models (e.g., as implemented in the SIENA software program) are growing in popularity as a technique for estimating longitudinal network data, a relatively understudied issue is the consequence of missing network data for longitudinal analysis. We explore this issue in our research note by utilizing data from four schools in an existing dataset (the AddHealth dataset) over three time points, assessing the substantive consequences of using four different strategies for addressing missing network data. The results indicate that whereas some measures in such models are estimated relatively robustly regardless of the strategy chosen for addressing missing network data, some of the substantive conclusions will differ based on the missing data strategy chosen. These results have important implications for this burgeoning applied research area, implying that researchers should more carefully consider how they address missing data when estimating such models.”

Lakon, Cynthia M., Cheng Wang, Carter T. Butts, Rupa Jose, David S. Timberlake, and John R. Hipp. (2015). “A Dynamic Model of Adolescent Friendship Networks, Parental Influences, and Smoking.” Journal of Youth and Adolescence. 44(9): 1767-1786.

Abstract: “Peer and parental influences are critical socializing forces shaping adolescent development, including the co-evolving processes of friendship tie choice and adolescent smoking. This study examines aspects of adolescent friendship networks and dimensions of parental influences shaping friendship tie choice and smoking, including parental support, parental monitoring, and the parental home smoking environment using a Stochastic Actor-Based model. With data from three waves of the National Longitudinal Study of Adolescent Health of youth in grades 7 through 12, including the In-School Survey, the first wave of the In-Home survey occurring 6 months later, and the second wave of the In-Home survey, occurring one year later, this study utilizes two samples based on the social network data collected in the longitudinal saturated sample of sixteen schools. One consists of twelve small schools (n = 1,284, 50.93 % female), and the other of one large school (n = 976, 48.46 % female). The findings indicated that reciprocity, choosing a friend of a friend as a friend, and smoking similarity increased friendship tie choice behavior, as did parental support. Parental monitoring interacted with choosing friends who smoke in affecting friendship tie choice, as at higher levels of parental monitoring, youth chose fewer friends that smoked. A parental home smoking context conducive to smoking decreased the number of friends adolescents chose. Peer influence and a parental home smoking environment conducive to smoking increased smoking, while parental monitoring decreased it in the large school. Overall, peer and parental factors affected the coevolution of friendship tie choice and smoking, directly and multiplicatively.”

Smith, Emily J., Carter T. Butts, Christopher Marcum, John R. Hipp, Zack Almquist, Nicholas N. Nagle, and Adam Boessen. (2014). “The Relationship of Age to Personal Network Size, Relational Multiplexity, and Proximity to Alters in the Western United States.” Journal of Gerontology: Social Sciences. 70(1): 91-99.

Abstract: “Objectives. This study examines the association of age and other sociodemographic variables with properties of personal networks; using samples of individuals residing in the rural western United States and the City of Los Angeles, we evaluate the degree to which these associations vary with geographical context. For both samples, we test the hypothesis that age is negatively associated with network size (i.e., degree) and positively associated with network multiplexity (the extent of overlap) on 6 different relations: core discussion members, social activity participants, emergency contacts, neighborhood safety contacts, job informants, and kin. We also examine the relationship between age and spatial proximity to alters.

Method. Our data consist of a large-scale, spatially stratified egocentric network survey containing information about respondents and those to whom they are tied. We use Poisson regression to test our hypothesis regarding degree while adjusting for covariates, including education, gender, race, and self-reported sense of neighborhood belonging. We use multiple linear regression to test our hypotheses on multiplexity and distance to alters.

Results. For both rural and urban populations, we find a nonmonotone association between age and numbers of core discussants and emergency contacts, with rural populations also showing nonmonotone associations for social activity partners and kin. These nonmonotone relationships show a peak in expected degree at midlife, followed by an eventual decline. We find a decline in degree among the elderly for all relations in both populations. Age is positively associated with distance to nonhousehold alters for the rural population, although residential tenure is associated with shorter ego-alter distances in both rural and urban settings. Additionally, age is negatively associated with network multiplexity for both populations.

Discussion. Although personal network size ultimately declines with age, we find that increases for some relations extend well into late-midlife and most elders still maintain numerous contacts across diverse relations. The evidence we present suggests that older people tap into an wider variety of different network members for different types of relations than do younger people. This is true even for populations in rural settings, for whom immediate access to potential alters is more limited.”

Conclusions: We conclude by considering extensions of the approach that account for homophily in the formation of network ties.”

Hipp, John R., Robert W. Faris, and Adam Boessen (2012). “Measuring ‘neighborhood’: Constructing network neighborhoods.” Social Networks. 34(1): 128-140.

Butts, Carter T., Ryan M. Acton, John R. Hipp, and Nicholas N. Nagle (2012). “Geographical Variability and Network Structure.” Social Networks. 34(1): 631-665.

Lakon, Cynthia M., John R. Hipp, and David S. Timberlake. (2010). “The Social Context of Adolescent Smoking: A Systems Perspective.” American Journal of Public Health. 100(7): 1218-1228.

Hipp, John R. and Andrew J. Perrin. 2009. “The Simultaneous Effect of Social Distance and Physical Distance on the Formation of Neighborhood Ties.” City & Community. 8(1): 5-25.

Hipp, John R. and Andrew J. Perrin (2006). “Nested Loyalties: Local Networks’ Effects on Neighborhood and Community Cohesion.” Urban Studies. 43(13): 2503-2523.

Methodological papers

Simpson, Rylan and John R. Hipp. (2017). “A Typological Approach to Studying Policing.” Policing & Society. Published online.

Abstract: “Policing in the United States has experienced immense change throughout the past quarter-century. Although police agencies have shared their goals of preserving life and protecting property, their philosophies and practices for achieving these goals have differed. The present research, therefore, explores patterns in policing via a novel, typological approach. Using six waves of data (1993, 1997, 2000, 2003, 2007, and 2013) from the Law Enforcement Management and Administrative Statistics (LEMAS) data series, we first employ factor analyses to generate indices for six important policing dimensions: (1) officer diversity, (2) community policing, (3) patrol strategy diversity, (4) militancy, (5) technology, and (6) staffing rigor. Using these indices, we then employ latent class analyses to construct typologies of police agencies, and examine the distribution of such typologies across space at various points in time. Our results reveal several key findings. We detect consistent patterns in typologies across time, including classes with high militancy, high diversity, or low staffing rigor (among others). Within these sets of classes, we also detect micro-heterogeneity amongst patterns of index values: for example, subsets of classes which all score high on one dimension but score high versus low on other dimensions. Finally, we find evidence to suggest spatial convergence of typologies in one large geographic region: Southern California. By offering a multidimensional classification scheme over a 20-year period, we contribute to the policing literature by highlighting the importance and implications of studying multiple policing dimensions simultaneously.”

Wang, Cheng, Carter T. Butts, John R. Hipp, Rupa Jose, and Cynthia M. Lakon. (2016). “Multiple Imputation for Missing Edge Data: A Predictive Evaluation Method with Application to Add Health.” Social Networks. 45(1): 89-98.

Abstract: “Recent developments have made model-based imputation of network data feasible in principle, but the extant literature provides few practical examples of its use. In this paper, we consider 14 schools from the widely used In-School Survey of Add Health (Harris et al., 2009), applying an ERGM-based estimation and simulation approach to impute the network missing data for each school. Add Health’s complex study design leads to multiple types of missingness, and we introduce practical techniques for handing each. We also develop a cross-validation based method – Held-Out Predictive Evaluation (HOPE) – for assessing this approach. Our results suggest that ERGM-based imputation of edge variables is a viable approach to the analysis of complex studies such as Add Health, provided that care is used in understanding and accounting for the study design.”

Hipp, John R., Cheng Wang, Carter T. Butts, Rupa Jose, and Cynthia M. Lakon. (2015). “Research Note: The consequences of different methods for handling missing network data in Stochastic Actor Models.” Social Networks. 41(1): 56-71.

Hipp, John R., George E. Tita, and Lyndsay N. Boggess. (2011). “A new twist on an old approach: A random-interaction approach for estimating rates of inter-group interaction.” Journal of Quantitative Criminology. 27(1): 27-51

Abstract: “There are numerous instances in which researchers wish to measure the rate of intra- or inter-group interactions (whether positive or negative). When computing such measures as rates there is great uncertainty regarding the appropriate denominator: we analytically illustrate how the choice of the denominator when calculating such rates is not trivial and that some existing strategies create a built-in relationship between the computed rate and the group composition within the entity. Another strand of prior work only focused on the relative occurrence of intra- versus inter-group events, which does not account for the important theoretical possibility that both types of events might increase in certain social contexts. Our approach provides an advance over these earlier strategies as it allows taking into account the relative frequency of interaction between members of different groups, but then translates this into per capita rates. We also provide an empirical example using data on inter- and intra-group robbery and aggravated assault events for block groups in a section of the city of Los Angeles to illustrate how our procedure works and to illustrate how other approaches can appear to imply dramatically different conclusions.”

Hipp, John R. and Daniel J. Bauer (2006). “Local Solutions in the Estimation of Growth Mixture Models.” Psychological Methods. 11 (1): 36-53.

Abstract: “Finite mixture models are well known to have poorly behaved likelihood functions featuring singularities and multiple optima. Growth mixture models may suffer from fewer of these problems, potentially benefiting from the structure imposed on the estimated class means and covariances by the specified growth model. As demonstrated here, however, local solutions may still be problematic. Results from an empirical case study and a small Monte Carlo simulation show that failure to thoroughly consider the possible presence of local optima in the estimation of a growth mixture model can sometimes have serious consequences, possibly leading to adoption of an inferior solution that differs in substantively important ways from the actual maximum likelihood solution. Often, the defaults of current software will need to be overridden to thoroughly evaluate the parameter space and obtain confidence that the maximum likelihood solution has in fact been obtained.”

Hipp, John R., Daniel J. Bauer, and Kenneth A. Bollen. 2005. “Conducting Tetrad Tests of Model Fit and Contrasts of Tetrad-Nested Models: A New SAS Macro.” Structural Equation Modeling. 12 (1): 76-93.

Abstract: “This article describes a SAS macro to assess model fit of structural equation models by employing a test of the model-implied vanishing tetrads. Use of this test has been limited in the past, in part due to the lack of software that fully automates the test in a user-friendly way. The current SAS macro provides a straightforward method for researchers to use the vanishing tetrads implied by models to assess the fit of (a) structural equation models containing continuous endogenous variables; (b) structural equation models containing continuous endogenous variables nested for vanishing tetrads; and (c) structural equation models containing dichotomous, ordinal, or censored endogenous variables. Besides providing an alternative assessment of model fit to the usual likelihood-ratio test (LRT), the vanishing tetrads test occasionally provides a statistical assessment of competing models nested for vanishing tetrads but not nested for the LRT. The macro permits formal comparisons between tetrad-nested structural equation models containing dichotomous, ordinal, or censored endogenous variables.”

Guo, Guang and John R. Hipp. 2004. “Analysis of Linear Longitudinal Data.” Pp. 347-368 in New Handbook on Data Analysis, edited by M. A. Hardy. London: Sage.

Abstract: “This chapter primarily compares and contrasts two approaches to modeling longitudinal data: the random effects growth curve model and the latent trajectory model. Our primary purpose is didactic, as we explicitly show how to construct these models and include syntax in the Appendix. We also show that while these two approaches begin from very different assumptions, in the case of continuous longitudinal data they provide identical parameter estimates and very similar standard errors. Employing an example with NLSY data, we show how these two approaches can model the within-case error structure in various fashions. We also illustrate how each of these approaches can handle predictors that are either time-invariant, or predictors that change over time, and that handling missing data on the dependent variable is straightforward. The similar results from each approach suggest that the researcher can obtain reliable parameter estimates from the method which he or she is most familiar with. However, we conclude by pointing out that the latent trajectory model has an additional advantage of allowing the researcher to assess the overall fit of the model, something that isn’t currently feasible using a random effects growth curve strategy.”

Hipp, John R. and Kenneth A. Bollen. 2003. “Model Fit in Structural Equation Models with Censored, Ordinal, and Dichotomous Variables: Testing Vanishing Tetrads.” Sociological Methodology. 33:267-305.

Abstract: “Though the methodology for handling ordinal and dichotomous observed variables in structural equation models (SEMs) is developing rapidly, several important issues are unresolved. One of these is the optimal test statistic to apply as a test of overall model fit. We propose a new “vanishing tetrad” test statistic for such models. We build on Bollen’s (1990) simultaneous test statistic for testing multiple vanishing tetrads and on Bollen and Ting’s (1993) Confirmatory Tetrad Analysis (CTA) for hypothesis testing of model structures. These and other works on vanishing tetrads assume continuous observed variables and do not consider observed categorical variables. In this paper we present a method to test models when some or all of the observed variables are collapsed or categorical versions of underlying continuous variables. The test statistic that we provide is an alternative “overall fit” statistic for SEMs with censored, ordinal or dichotomous observed variables. Furthermore the vanishing tetrad test sometimes permits us to compare the fit of some models that are not nested in the traditional likelihood ratio test. We illustrate the new test statistic with examples and a small simulation experiment comparing it with two other tests of model fit for SEMs with ordinal or dichotomous endogenous variables.”

Bollen, Kenneth A., Sharon L. Christ, and John R. Hipp. 2003. “Growth Curve Models.” Pp. G35-G38 in Encyclopedia of Social Science Research Methods, edited by M. Lewis-Beck, A. Bryan, and T. F. Liao. Thousand Oaks, CA: Sage.

Abstract: “.”