I co-direct the Irvine Lab for the Study of Space and Crime (ILSSC) with Charis Kubrin. Here’s a presentation about the lab.
The Metropolitan Futures Initiative (MFI) is an interdisciplinary project that I am heading up, involving five faculty members. The Metropolitan Futures Initiative aims to develop an improved understanding of communities and their potential for integrative and collaborative planning and action to ensure a bright future for the region. With initial focus on Orange County and its location within the larger Southern California area, The Metropolitan Futures Initiative is a commitment to build communities that are economically vibrant, environmentally sustainable, and socially just by partnering Social Ecology’s world class, boundary-crossing scholarship with expertise throughout Southern California.
The initial Regional Progress Report was released on June 14, 2012. Go here to see the MFI webpage, read the Regional Progress Report and view supplemental tables and information from the Report.
The second Regional Progress Report was released on June 11, 2014. Go here to see the MFI webpage, read the Regional Progress Report and view supplemental tables and information from the Report.
We have now begun a Quarterly Report series, starting in July 2016. Go here to see the MFI webpage, see videos that describe the results of the Quarterly Reports, use interactive web mapping applications that allow you to explore the data used for the Quarterly Reports, and also read the Quarterly Reports.
Cascades of network structure and function: Pathways to Adolescent Substance Use. This project I work on includes an interdisciplinary team of experts exploring dynamic social networks of adolescents. It uses stochastic actor based models to explore social networks in continuous time, even when the data has only been collected for just three discrete time points. We have published several substantive papers, as well as methodological papers showing the challenges of using this increasingly popular statistical technique. Here is a cool video describing some simulation work we published in the American Journal of Public Health showing that in hypothetical scenarios in which social influence is increased, smoking behaviors would, surprisingly, actually be expected to decrease. Some of our methodological work has shown the perils of ignoring missing social network data when using these techniques.
Stata code to create your own egohoods is here. This is an explicitly spatial approach that constructs overlapping neighborhoods, as opposed to the more traditional approach of constructing non-overlapping neighborhoods.
When computing rates for intergroup relations (for example, violent events between groups), it is important to correctly compute the denominator for such rates. Most prior work does this incorrectly. This article discusses this issue: 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. Here is some Stata code to create these measures to either use as the denominator when computing a rate (e.g., a crime rate) or as an exposure variable when estimating a Poisson model.
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. The SAS macro and documentation for ctanest1.mac for performing model fit for Structural Equation Models with non-continuous variables can be downloaded here.
This is based on the work in “Model Fit in Structural Equation Models with Censored, Ordinal, and Dichotomous Variables: Testing Vanishing Tetrads”. Sociological Methodology. 33: 267-305. (with Kenneth A. Bollen).
Hipp, John R. and Aaron Roussell. 2013. “Micro- and Macro-environment Population and the Consequences for Crime Rates.” Social Forces 92:563-595.
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. The online appendix for this paper is here.
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. The online appendix for this paper is here.
This is a video describing some of my work.
In this video I describe a research project using tweets to estimate the number of people at locations at time of day, and then assess its relationship to crime. This presentation was part of the SoCal Analytics Workshop on May 11 2018.
Here’s a presentation about the Irvine Lab for the Study of Space and Crime (ILCCS) that I co-direct with Charis Kubrin (March 11 2013)
Here is a cool video describing some social network simulation work I did with a team in public health. We show that in hypothetical scenarios in which social influence is increased, smoking behaviors would, surprisingly, actually be expected to decrease.
I was part of a presentation on Solving Societal Problems, Social Ecology Style.; this link has a photo show, as well as videos of the various presenters. Here’s the link to my presentation on “Foreclosures, Neighborhood Dynamics, and the Ecology of Communities”. Nov 4, 2011
Segregation Through the Lens of Housing Unit Transition. This study focuses on the racial/ethnic composition of households in the transition of housing units. It studies the extent to which the race/ethnicity of the new household depends on the race/ethnicity of the previous residents, the racial/ethnic composition of the local micro-neighborhood, and the racial/ethnic composition of the broader census tract. Here is a talk I gave on this at the UC Irvine Population, Society and Inequality Brownbag Series in May 2010.
Some early versions of systematic social observation!! These are film of: a trolley ride in New York City in the early 1900s, and a cable car ride in San Francisco in 1906.
Four papers of mine from 2018 that are favorites of mine:
1) Although much research has posited that residents in neighborhoods can impact the level of crime through informal social control action, very little research has been able to test the individual-level mechanisms of these theories. This paper is therefore an important contribution as it uses longitudinal data of residents nested in neighborhoods to assess whether perceptions of disorder impact residents’ perceptions of the level of collective efficacy in the neighborhood, and then whether that impacts actual behavior to improve the neighborhood.
2) This paper extends the collective efficacy literature by considering why residents in some neighborhoods disagree about the level of collective efficacy. The study shows that the level of social distance in the neighborhood (measured as egohoods) reduces this level of agreement. Importantly, it is a general measure of social distance (based on several socio-demographic measures) that reduces this agreement, whereas simply measuring difference based on income or race/ethnicity does not reduce agreement.
3) The co-location in space and time of offenders and targets is posited to increase the possibility of crime at a location, and yet measuring the presence of persons at a location is difficult and data intensive. In this paper, we use geolocated and temporally precise twitter information as a proxy for the number of persons at a location during a particular hour of the day, and show that this has a robust positive relationship with the level of different types of crime in a sample of blocks in Southern California.
4) Filtering theory from housing economics posits that as housing ages, it filters down to lower income households. In this paper we build on this basic insight of the aging of housing to posit that such aging housing will tend to become more dilapidated over time, and hence result in more physical disorder at the location, and potentially more crime. Our results show that indeed, street segments with older housing tend to have more crime than streets with newer housing, even controlling for the usual measures of locations, including socio-economic status. We find that this positive effect tends to level off at particularly older age ranges, implying that there may be a gentrification effect in which older housing is then renovated.
Four papers of mine from 2017 that are favorites of mine:
1) This paper co-authored with James Wo and Young-an Kim considered how the relationship between the micro-context and crime can vary across different macro contexts. Building on the insights of an earlier paper with Aaron Roussell, we chose four cities cross-classified based on population in the micro-environment, and population in the broader macro-environment. The results demonstrate that the assumption that micro-crime patterns will necessarily generalize across different macro environments does not seem to hold.
2) This paper co-authored with Nick Branic considered both fast and slow dynamics in neighborhoods, and the consequences for levels of crime. We use annual HMDA data to capture year-to-year changes in neighborhoods, and show that the pace of change in neighborhoods (based on changing racial composition or economic composition) has important consequences for changes in crime rates over the decade. We term this temporal nonlinearity to capture neighborhoods in which the change along a particular dimension occurs primarily in either the early or latter part of the decade. The velocity of this demographic change appears important for understanding changing crime levels.
3) This paper co-authored with Kevin Kane and Jae Hong Kim uses a recently developed technique— kernel regularized least squares (KRLS)—that allows for non-parametric estimation of relationships between various measures of mixing in neighborhoods and the change in average household income from 2000 to 2010 in Southern California. KRLS is a machine learning technique that also detects nonlinear interactions between measures in the model. We develop a new Stata ado package that allows us to plot the key detected nonlinear interactions in the model. We refer to these combinations as a “recipe” for economic growth in a neighborhood over the decade.
4) This paper co-authored with Kevin Kane extends the macro literature on city crime rates in several fashions. First, it adopts an explicitly longitudinal view in studying changes in city characteristics and changes in crime rates over decades. Second, it takes into account long-term change by estimating the models on four separate decades. Third, it takes into account the broader region in which these cities are located and shows that the population growth and economic vibrancy of the larger region has consequences for how crime changes in the cities within those regions. Thus, spatial scale is important even in macro criminology research.
Three papers of mine from 2016 that are favorites of mine:
1) This paper proposes a new general theory of the spatial patterning of crime. It explicitly incorporates offenders into the model. Rather than trying to model all movements of offenders, targets, and guardians, it utilizes the key insight of the principle of least effort in proposing that spatial patterns of persons will typically exhibit a distance decay effect. It uses this insight to build a model that helps understand the spatial distribution of crime.
2) This paper published with Young-an Kim raises cautionary insights about the recently popular “law of crime concentration”. First, it uses a large sample of cities in Southern California to demonstrate that there is empirically more variability in the level of concentration across cities than one would reasonably expect for such a law. Second, it raises the methodological question of whether concentration should be measured across macro units of widely varying sizes. Third, it highlights the statistical challenge of measuring crime concentration in that researchers often pose a baseline assumption of a uniform distribution of crime when in fact a Poisson distribution is more reasonable. Fourth, it highlights the crucial need to consider the temporal assumption employed when measuring high crime locations. And finally, it points out the peculiar theoretical implications if a law of crime concentration indeed exists, which have been given virtually no consideration by scholars.
3) A paper published with Rebecca Wickes (freely available) uses two innovative measures of 1) residents’ assessments of neighborhood ethnic minorities; and 2) the extent of social ties between members of the same ethnic group compared to chance. The measure of residents’ bias towards seeing more minorities in the neighborhood than actually exists was first developed in an earlier paper of ours looking at residents’ perceptions of disorder. This current paper views the relationship of this measure to residents’ perceptions of social capital (measured by social cohesion, place attachment and neighboring). The measure of proportion of ties within and across groups accounts for the ethnic composition of the neighborhood; prior research typically fails to account for this. We use insights from an earlier paper of mine on intergroup violence that adjusted for neighborhood racial/ethnic composition. We find that 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.
Three papers of mine from 2015 that are favorites of mine:
1) This paper theoretically considers that collective efficacy develops over time. It develops two key principles. First, the notion of updating: persons re-evaluate their perception of the level of collective efficacy regarding some task based on feedback information. In the neighborhoods literature, this implies that crime and disorder would be expected to impact residents’ perception of collective efficacy. Second, the notion of uncertainty: residents in neighborhoods with few incivilities will typically be uncertain about the level of collective efficacy. An implication is that an incivility event has the potential to greatly change the perceived level of collective efficacy in such neighborhoods, which has rarely been considered.
2) A paper published with Wouter Steenbeek considers how the dynamic processes of neighborhoods may operate differently for various types of crime. It considers three dimensions of crimes: the violent/nonviolent nature; the public/private nature; the relative frequency. The paper considers how the mechanisms of social disorganization theory likely operate differently for various types of crime. And it considers that the feedback effect on residents’ perceptions and behaviors likely will be different over various types of crime.
3) A paper published with Alyssa Chamberlain explores the spatial distribution of crime at a larger scale. Using data for neighborhoods (census tracts) in 79 cities, it asks whether relative inequality—measured as the difference in concentrated disadvantage between a neighborhood and the surrounding neighborhoods—impacts levels of crime. It also explores the effect of relative inequality measured by the ratio of concentrated disadvantage in a neighborhood to the city in which it is located, and finds that this larger context also has important effects.
A fun paper from 2014 that I worked on:
A paper that I published with colleagues down under (Rebecca Wickes and Jonathan Corcoran) explores the intersection between the physical environment and the social environment. We propose the notions of social holes and wedges, and suggest that they can impact the social interactions among residents. A consequence of these social holes in wedges is that they impact the social porosity within and between neighborhoods, which has consequences for the level of cohesion in neighborhoods. We demonstrate these principles with an empirical sample: read about it here [freely available through open access].
Three papers from 2013 that I worked on that are fun:
1) Adam Boessen and I proposed a new measure of neighborhoods: egohoods. This approach is a radical shift away from nearly all prior research that defines “neighborhoods” as having non-overlapping boundaries. We instead think of neighborhoods as being overlapping concentric circles. The paper is here. The code to make your own egohoods is here.
2) Measuring the networks of all residents in a neighborhood is difficult, much less the networks of all residents in a city. From a project I am working on with Carter Butts and other colleagues, we developed a novel approach that simulates the network of ties among all residents in a city. We use the approach to simulate the networks of five cities, and then construct several key network measures to capture the structure of the network. We then find that these simulated network properties actually do a good job predicting the micro-location of crime in cities! Sound fantasmagorical? Read about it here.
3) Understanding the spatial scale of population density and the consequences for crime has bedeviled researchers since the time of Louis Wirth. A challenge is distinguishing between population size and density. Aaron Roussell and I conceive of these as micro-population density and macro-population density. We then propose novel measures of each of these: population density exposure to capture micro-density, and a measure of population within a 20 mile radius to capture macro-density. We point out that implications of routine activities theory are that these should have nonlinear interaction effects on city level crime rates. We demonstrate that this is empirically the case in both 1990 and 2000: read the paper here. The online appendix is here.
The Orange Crush: The Squeezing of Orange County’s Middle Class. This study views trends in Orange County, CA cities and neighborhoods over a forty year period (1960-2000). This report was done for the Center on Inequality and Social Justice, and the full report can be found here.
Social Disparities in Health: Disproportionate toxicity proximity in minority communities over a decade. In this study, we look at the exposure of various demographic groups to toxic waste in the Southern California region over the 1990-2000 period. We find that Latinos and Asians are disproportionately exposed to such waste. We also find that neighborhoods with a high percentage of highly educated persons (with at least a bachelor’s degree) are near particularly few such sites. Look here for maps of sites, and other related information. Here is a UC Irvine news release of the study. Here is the abstract and a link to the study published in the peer-reviewed journal Health & Place.
The OC Register covered it in the Science Dude blog.
The OC Weekly covered it in a blog.
Planet Harmony covered it.
YubaNet covered it.
Health Justice Network covered it.
UC Health covered it.
The Examiner covered it.
The Press-Enterprise covered it.
Do returning parolees affect neighborhood crime? A case study of Sacramento. In this study, we look at the effect of released parolees on monthly crime rates in Sacramento over a four year period. Here is a UC Irvine news release of the study. Here is the abstract and a link to the study published in the peer-reviewed journal Criminology.
The OC Register wrote an article.
Intra- and inter-group violent crime among African-Americans and Latinos: A study of ethnically transforming neighborhoods in south Los Angeles. In this new study, we estimate the rates of intra- and inter-group violent crime between Latinos and African-Americans in south Los Angeles over the 2000-06 period. Preliminary results from this research have been getting some press:
They even picked up the story in China!
It was picked up by Celeste Fremon on the Witness LA blog.
Our results were published in the peer-reviewed journal Criminology.
Is there a seasonal effect of crime, and why? Here’s a synopsis of a full study that I did.
The citation for the complete study is: 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.
“If the thorn of a rose is the thorn in your side,
then you’re better off dead if you haven’t yet died”