The geographies of perceived neighbourhood disorder. A small area estimation approach. (August 2019)

• Record Type: Journal Article
• Authors: Buil-Gil, David; Medina, Juanjo; Shlomo, Natalie
• Is Part Of: Applied geography. Volume 109(2019)
• Publication Date: 2019-08
• Subjects: Antisocial behaviour -- Model-based estimation -- Subjective security -- Mapping -- Environmental criminology -- EBLUP; Geography -- Periodicals; Human geography -- Periodicals; Human ecology -- Periodicals; 910
• DOI: 10.1016/j.apgeog.2019.102037
• Languages: English
• ISSNs: 0143-6228

Abstract

Abstract: This research examines the geographical distribution of perceived neighbourhood disorder in Manchester, England, by using small area estimates. Sample surveys are the main source of information to analyse perceived disorder. However, most surveys are only representative of large areas, and direct estimates may be unreliable at small area level. Small area estimation techniques borrow strength from related areas to produce reliable small area estimates. This research produces Spatial Empirical Best Linear Unbiased Predictor (SEBLUP) estimates, which account for spatially correlated random area effects, of perceived neighbourhood disorder from the Manchester Resident Telephone Survey. The highest levels of perceived disorder are found in the city centre and some Northern and Central-Eastern areas. Perceived disorder is higher in areas with higher population churn, income deprivation and crime. Small area estimation techniques are a potential tool to map perceived disorder. Highlights: Direct estimators produce unreliable estimates at small area level. The SEBLUP produces the most reliable estimates at small area level. Disorder is perceived as higher in areas with higher population churn. Perceived disorder is also higher in economically deprived neighbourhoods. Perceived disorder is higher in the Manchester city centre and most Northern areas.