Published online by Cambridge University Press: 05 July 2022
It is possible to estimate the numbers of poor children and poor households at the community level (using the Breadline Britain definitions of poverty; see Gordon and Pantazis, 1997) by obtaining weightings for the best subset of deprivation indicator variables that were measured in both the 1991 Census and the Breadline Britain survey and by then using the multivariate statistical technique of logistic regression (Gordon and Forrest, 1995; Gordon, 1995).
Eleven variables, which have been used in one or more Censusbased indices, were examined to estimate the number living in poverty.
V1 Unemployment
V2 Lone parents
V3 Limiting long-term illness
V4 Low social class
V5 No access to a car
V6 Living in non-owner-occupier accommodation
V7 Single pensioners
V8 Divorced people
V9 Widows
V10 Lacking or sharing basic amenities
V11 Not self-contained accommodation
A step-wise logistic regression analysis allowed the best subset of variables to be selected that were proxies of poverty (as defined by the Breadline Britain survey) and provided weightings for each variable after allowing for the overlaps between variables (ie lone-parent households may also be likely to be of low social class or live in rented accommodation).
There was a considerable degree of overlap between single pensioners and widows and both variables were excluded because they were not good predictors of poverty. Divorced people were excluded because of their high overlap with single parenthood, which was a better predictor of poverty. ‘Lacking basic amenities’ and ‘not self-contained accommodation’ were dropped because they were found not to be additive, for example, households which contained someone with a limiting long-term illness and also lacked basic amenities were not likely to be poorer than a household with an ill person but with basic amenities. The reason for this is that many poor disabled people live in local authority accommodation which invariably have indoor toilets and bathrooms.
An estimate of the number of poor households in an area can be calculated as: 21.7% of the number of households with no access to a car + 20.3% of the number of households not in owner-occupied accommodation + 16% of the number of lone-parent households + 15.9% of the number of workers in social classes IV and V + 10.8% of the number of households containing a person with a limiting long-term illness + 9.4% of unemployed workers.
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