The geographies of perceived neighbourhood disorder: A small area estimation approachCitation formats

Standard

The geographies of perceived neighbourhood disorder: A small area estimation approach. / Buil-Gil, David; Medina, Juanjo; Shlomo, Natalie.

In: Applied Geography, Vol. 109, 2019.

Research output: Contribution to journalArticle

Harvard

APA

Vancouver

Author

Bibtex

@article{e5bb0ec64be4411c965098e66e885c91,
title = "The geographies of perceived neighbourhood disorder: A small area estimation approach",
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.",
keywords = "Antisocial behaviour, Model-based estimation, Subjective security, Mapping, Environmental criminology, EBLUP",
author = "David Buil-Gil and Juanjo Medina and Natalie Shlomo",
year = "2019",
doi = "10.1016/j.apgeog.2019.102037",
language = "English",
volume = "109",
journal = "Applied Geography",
issn = "0143-6228",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - The geographies of perceived neighbourhood disorder: A small area estimation approach

AU - Buil-Gil, David

AU - Medina, Juanjo

AU - Shlomo, Natalie

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Antisocial behaviour

KW - Model-based estimation

KW - Subjective security

KW - Mapping

KW - Environmental criminology

KW - EBLUP

U2 - 10.1016/j.apgeog.2019.102037

DO - 10.1016/j.apgeog.2019.102037

M3 - Article

VL - 109

JO - Applied Geography

JF - Applied Geography

SN - 0143-6228

ER -