A neighborhood-level analysis of immigration and crime in Vancouver, Canada

Author: 
Date created: 
2019-12-06
Identifier: 
etd20728
Keywords: 
Immigration
Crime
Spatial analysis
Local point pattern test
Decomposition model
Geographically weighted regression
Spatial non-stationarity
Abstract: 

In recent years, conflict and violence have propel the rate of displaced individuals to the highest levels since the Second World War, reigniting concerns on immigration and crime. Mass re-settlement initiatives have also changed the social and economic landscape of cities and neighborhoods, opening up an entirely new set of challenges for host nations. From an academic vantage, empirical inquiries are complicated by the dynamic, multifaceted and heterogeneous nature of immigration—complexities that also impact theory-based interpretations of the relationship. The polarization of sentiments complicate political and social perspectives. Advocates for restrictive immigration policies argue that immigrants are inextricably crime prone, while those in support of open immigration policies counter. Empirical research has proliferated in recent years, findings consistently show negative or null relationships between immigration and crime—yet researchers still know relatively little about why findings occur. As such, the current thesis aims to contribute to a better understanding of the immigration-crime link by addressing empirical and methodological gaps that help identify contextual mechanisms that underlie the relationship. Empirically, multi-dimensional, theoretically derived measures of immigration are analyzed—attending to the limitation of overly broad, single dimension, measures. Limitations also stem from a paucity of research that test the relationship at smaller aggregate units. This gap is addressed using census-tract level data and spatially referenced crime data to test immigration effects on disaggregated property crime types across neighborhoods in Vancouver, British Columbia, Canada, 2003-2016. Methodological limitations develop from the use of global analytic models in assessments of ecological spatial data. Accordingly, local-level spatial analytic techniques are utilized—the spatial point pattern test and geographically weighted regression and a decomposition model. Overall, findings importantly show significant spatial variation in the effect of immigration on property crime (spatial non-stationarity). Results also demonstrate significant variation across immigration measure, property crime classification, effects are also distinguished between and within neighborhoods. Findings therefore, illustrate the context dependent nature of immigration effects on crime. Therefore, in order to develop a better understanding of the immigration-crime link future research should move beyond monolithic expectations and adopt research strategies that account for contextual factors that help explain differential relationships between immigration and crime.

Document type: 
Thesis
Rights: 
This thesis may be printed or downloaded for non-commercial research and scholarly purposes. Copyright remains with the author.
File(s): 
Senior supervisor: 
Martin Andresen
Department: 
Arts & Social Sciences: School of Criminology
Thesis type: 
(Thesis) Ph.D.
Statistics: