Creating Small Area Measures of Urban Deprivation

Abstract

In recent years, the scale and pace of urban change have been associated with fine-scale fragmentation of the lifestyles of urban populations. One manifestation of this is that households of diverse means and circumstances may be found living in proximity to one another, particularly in urban areas. In this paper we argue that in these changed circumstances conventional deprivation indicators fail adequately to detect within and between small area variations in socioeconomic and environmental conditions. Using a case study of Bristol, England, we develop an analysis around Gordon and Forrest's Breadline Britain indicator in order to reveal the diversity of economic conditions that exist within wards that might be labelled as either affluent or deprived. We argue that adequate representation of diversity requires a greater sensitivity to difference at fine scales. In this context, we begin to evaluate the claims of marketeers who use commercial sources of data to model incomes at unit postcode and even household scales. We undertake an evaluation of such data and extend their application to calculation of Breadline Britain index scores. The results suggest some potential for using unconventional sources of data to ‘freshen up’ census information and provide direct, meaningful, measures of deprivation.

Spatial Dependence and Heterogeneity in Patterns of Hardship: An Intra-Urban Analysis

“…The broader merits of using income data from lifestyles surveys to supplement less frequent or coarser scale surveys are summarized by Harris and Longley (2002). In short, they provide a central ingredient of small-area hardship measures, yet there is also a clear need to cross-validate small-area income estimates with respect to external data sources.…”

“…Taken together, it remains unclear how meaningful indicators of social conditions can be adequately specified, or whether generalized representations can be sufficiently sensitive to place. A critical issue is thus to understand the scales at which both income, and the variables that are used to predict it, vary (see also Rees 1998;Harris and Longley 2002). There are geographies of the informal economy and unmeasured incomes (e.g., Williams and Windebank 2001), as well as mismatches between the spatial distribution of earned income and unearned income and wealth (e.g., Ball 1994), yet it is clear that deprivation and hardship are inextricably linked to measurable incomes derived from earnings and transfer payments.…”

“…In the same spirit as Gordon and Pantazis (1995), we thus think it necessary to retain some linkage to population census data-but in a way which is much more sensitive to spatial context. A critical issue is thus to understand the scales at which both income, and the variables that are used to predict it, vary (see also Rees 1998;Harris and Longley 2002). In our empirical analysis we examine a number of the facets of this issue through our detailed empirical case study.…”

Museums, schools and geographies of cultural value

“…Jordan, Roderick, Martin, & Barnett, 2004;Martin, Roderick, Diamond, Clements, & Stone, 1998) and social deprivation/exclusion (e.g., Carstairs & Morris, 1990, 1991aHarris & Longley, 2002;Kearns, Gibb, & Mackay, 2000;McLoone & Boddy, 1994;Pacione, 2004). Postcodes are seen as particularly useful in that they provide a system of georeferencing that "can be accurately and readily recalled by subjects" (Hyndman et al, 1995(Hyndman et al, , p. 1116, and can hence be obtained through research instruments such as questionnaires, and also because they are smaller spatial units than those used to disseminate most social statistics.…”

Geodemographic classifications, the digital divide and understanding customer take-up of new technologies

“…Developing a market picture, or for addressing issues of social cohesion, requires aggregation, however, and thus it may be appropriate to aggregate individuals into households or small neighbourhood units. This is also useful for viewing patterns of IT adoption relative to statistical information of the sort that is included in the current Index of Multiple Deprivation (see, for example, Senior [8], Harris and Longley [9]). Finally, aggregation can be helpful for evaluation purposes, and in our own evaluation initiative outlined below we have chosen to aggregate the classification to the unit postcode scale.…”