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A model for spatially varying crime rates in English districts: the

effects of social capital, fragmentation, deprivation and

urbanicity

Peter Congdon, Queen Mary University of Londonp.congdon@qmul.ac.uk

http://www.geog.qmul.ac.uk/staff/congdonp.htmlhttp://webspace.qmul.ac.uk/pcongdon/

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Crime variations & urban structure

Geographic variations in crime are increasingly linked to aspects of urban social structure.

However, relatively limited synoptic evidence on geographic crime differences & potentially relevant urban structural characteristics.

Many studies partial, considering particular associations, e.g. crime-poverty or crime-inequality links, or have restricted spatial focus

Potentially relevant influences considered here: deprivation, urbanicity, social capital, social fragmentation, income inequality, and with England-wide focus

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Social capital

Social capital: norms of reciprocity & trust that promote civic participation, activity in social organizations or voluntary activity (Putnam, 1995).

Social disorganisation theory stresses neighbourhood effects on crime, and role of social capital in informal control, but main focus is crime variations within urban areas.

Seek here to consider more complete spectrum of urban-rural contexts, albeit at aggregated spatial scale

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Methodological aspects: latent variables

Some important methodological issues Typically relevant aspects of urban socio-

economic structure are latent constructs The constructs are not directly observed,

but instead proxied by set of observed indicators.

Examples: area deprivation “measured” by variables such as unemployment rate, level of welfare dependency, poverty rate; social capital measured by perceptions of local neighbourhood, participation in voluntary activity, etc.

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Methodological aspects: spatial units of analysis

Assume an area focus using area crime rates and area variables – this means that comprehensive administrative data can be used. Here, use notifiable offences recorded by police in 2009/10 for 324 English local authorities.

Need to allow for spatial structure/correlation in regression model (e.g. spatially correlated residuals) to obtain valid effect measures

Kubrin & Weitzer (2003) mention spatial dependencies “how adjacent neighborhoods may affect each other’s level of disorganization and crime”.

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Methodological aspects: effect mediation

Social capital may affect crime rates (negative effect expected).

However, social capital itself may be affected by other urban dimensions: deprivation, urbanicity and fragmentation.

So in a spatial crime regression, social capital may mediate effects on crime of deprivation, urbanicity and fragmentation

Quote from Kubrin/Weitzer: “Social ties and informal control are…mediating the effects of exogenous sources of social disorganization (e.g., poverty, residential instability, ethnic heterogeneity) on neighborhood crime”

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Study Data: Measuring Social Capital

Six indicators of neighbourhood perception & volunteering activity from 2008 UK Place Survey used to measure social capital.

For example, respondents asked whether 1. “they belong to their immediate

neighbourhood”, 2. “satisfied with their local area as a place to

live”,3. “given unpaid help at least once per month

over the last 12 months”. Principal component analysis shows leading

eigenvalue of 4.54, accounting for 76% of original variation. Supports concept of single latent variable

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Map of component

scores

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Social Capital by English RegionEast

Mid

lands

East

of

Engla

nd

London

Nort

h E

ast

Nort

h W

est

South

East

South

West

West

Mid

lands

York

shir

e a

nd T

he H

um

ber

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

Average Social Capital Scores by Region

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Study Data: Measuring Other Constructs

Measuring urbanicity: pop’n density, % land that is greenspace, access to services (primary health, schools, post offices, retail stores),% working in agriculture, flatted housing. Leading component explains 79.0% of variation  

Measuring social fragmentation (summarises residential stability/family structure): migrant turnover, one person households, private renting, % adults married. Leading component also explains 79% of variation in these indicators.

Measuring area deprivation: receiving income support, unemployment rate, professional and managerial, % adults with higher education.

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How social capital varies with the

other urban dimensions

Average social capital according to quintile

groupings of local authorities on deprivation,

fragmentation, urbanicity

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Study Model:Geographic Crime Variation via Spatial Regression

The response variables are crime rates (total, violent, property)

Crime rates are spatially correlated, unmeasured influences likely to remain. Regression residuals assumed spatially correlated (Conditional Autoregressive or CAR spatial)

Poisson log link regression is adopted (Osgood, 2000), adjusting for population at risk→ response is log relative risk of crime.

Winbugs package used (Bayesian MCMC estimation)

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Geographic Crime Variation: Spatial Regression

Area crime predictors: four constructs as above and income inequality

Income inequality is coefficient of variation within each local authority of middle level super output area income estimates, 2007-08

Modelling sequence: no predictors; predictors excluding social capital; all predictors

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Model Sequence

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Crime Variation Regression: Findings

If social capital not included as predictor (regression 2), deprivation is strongest influence on crime responses, whether β-coefficients or risk ratios between 5th and 95th percentiles considered.

Strongest effect of urbanicity is on violent crime.

Effects of income inequality in model 2 insignificant: inequality effect entirely mediated by deprivation, urbanicity and fragmentation

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Crime Variation Regression: Findings

Impacts of urbanicity and deprivation considerably reduced in regression 3, in line with their effects being partially or completely mediated by social capital.

In fact, deprivation no longer has a significant impact on property crime – so providing an example of complete mediation

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Crime gradient (rates per 1000) by decile of social capital score, controlling for other urban dimensions

(deprivation, fragmentation, urbanity set to zero)

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References

Kubrin C, Weitzer R(2003)New Directions in Social Disorganization Theory. J Research Crime Delinquency, 40 

Osgood D (2000) Poisson-based regression analysis of aggregate crime rates. J. Quant Criminology, 16.

Putnam R (1995)Bowling Alone: America's Declining Social Capital. J of Democracy, 6:65-78.