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Soc Sci Res. 2018 Nov;76:77-91. doi: 10.1016/j.ssresearch.2018.08.002. Epub 2018 Aug 2.

Growing pains or appreciable gains? Latent classes of neighborhood change, and consequences for crime in Southern California neighborhoods.

Author information

1
Department of Criminology, Law and Society and Department of Sociology, University of California, Irvine, CA, USA.
2
Department of Criminology, Law and Society and Department of Sociology, University of California, Irvine, CA, USA. Electronic address: john.hipp@UCI.edu.

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.

KEYWORDS:

Change; Crime; Neighborhoods; Spatial; Temporal

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