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.
Original language | English |
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Article number | 102037 |
Journal | Applied Geography |
Volume | 109 |
Early online date | 25 Jun 2019 |
DOIs | |
Publication status | Published - 25 Jun 2019 |
Keywords
- Antisocial behaviour
- Model-based estimation
- Subjective security
- Mapping
- Environmental criminology
- EBLUP
Research Beacons, Institutes and Platforms
- Cathie Marsh Institute
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Dive into the research topics of 'The geographies of perceived neighbourhood disorder: A small area estimation approach'. Together they form a unique fingerprint.Prizes
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ONS Early Career Researcher Award 2021
Buil Gil, David (Recipient), 13 Oct 2021
Prize: Prize (including medals and awards)
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Second Prize - “Rafael Bonet” award of policing studies
Buil Gil, David (Recipient), Nov 2018
Prize: Prize (including medals and awards)