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Title:
Geographically Varying Correlates of Car Non-Ownership in Census Output Areas of England, 2001
(Grid Enabled Spatial Regression Models)

Subject Categories:
Economic conditions and indicators - Economics
Population censuses - Population, vital statistics and censuses
Equality and inequality - Social stratification and groupings

Depositor(s):
Harris, R., University of Bristol. School of Geographical Sciences

Principal Investigator(s):
Harris, R., University of Bristol. School of Geographical Sciences
Grose, D., Lancaster University. Centre for e-Science

Sponsor(s):
Economic and Social Research Council

Grant Number:
RES-149-25-1041

Abstract:
Standard indexes of poverty and deprivation are rarely sensitive to how the causes and consequences of deprivation have different impacts depending upon where a person lives. More geographically minded approaches are alert to spatial variations but are also difficult to compute using desktop PCs.

The aim of the ESRC sponsored project was to develop a method of spatial analysis known as ‘geographically weighted regression’ (GWR) to run in the high power computing environment offered by ‘Grid computation’ and e-social science. GWR, like many other methods of spatial analysis, is characterised by multiple repeat testing as the data are divided into geographical regions and also randomly redistributed many times to simulate the likelihood that the results obtained from the analysis are actually due to chance. Each of these tests requires computer time so, given a large dataset such as the UK Census statistics, running the analysis on a standard machine can take a long time! Fortunately, the computational grid is not standard but offers the possibility to speed up the process by running GWR’s sequences of calibration, analysis and non-parametric simulation in parallel.

An output is a model of the geographically varying correlates of car non-ownership fitted for the 165,665 Census Output Areas in England. Specifically, a geographically weighted regression of the relationship between the proportion of households without a car (or van) in 2001 (the dependent variable), and the following predictor variables: proportion of persons of working age unemployed; proportion of households in public housing; proportion of households that are lone parent households; proportion of persons 16 or above that are single; and proportion of persons that are white British.

Note - the file does not contain Census 2001 data, only National Grid references and regression coefficients.

Further information is available from the ESRC Award web page.

Main Topics:
Investigating the spatially varying correlates of car non-ownership using GWR.

Coverage:
Dates of Fieldwork: 2001
Country: England
Spatial Units: National Grid references
Observation Units: Administrative units (geographical/political)
Kind of Data: Numeric data; Aggregate (macro) level

Universe Sampled:
Location of Units of Observation:National
Population:The geographically varying correlates of car non-ownership in England, 2001.

Methodology:
Time Dimensions: Cross-sectional (one-time) study
Sampling Procedures: No sampling (total universe)
Secondary analysis of Census 2001 data.
Number of Units: 165,665
Method of Data Collection: Compilation or synthesis of existing material
Weighting: No weighting used
Data Sources: Census 2001

Language(s) of Written Materials:
Study Description: English
Study Documentation: English

Access:
Access Conditions: The depositor has specified that registration is required and standard conditions of use apply. The depositor may be informed about usage. See terms and conditions for further information.
Availability: ESDS Access and Preservation, UK Data Archive
Contact: Help desk: help@esds.ac.uk

Date of Release:
First Edition: 2 April 2009

Copyright:
Copyright R. Harris

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