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Showing papers in "Applied Spatial Analysis and Policy in 2010"


Journal ArticleDOI
Paul Norman1
TL;DR: In this paper, the authors use the Townsend index to identify whether small areas have changed their level of deprivation over time and thereby be able to assess the impact of area-based planning initiatives.
Abstract: The measurement of area level deprivation is the subject of a wide and ongoing debate regarding the appropriateness of the geographical scale of analysis, the input indicator variables and the method used to combine them into a single figure index. Whilst differences exist, there are strong correlations between schemes. Many policy-related and academic studies use deprivation scores calculated cross-sectionally to identify areas in need of regeneration and to explain variations in health outcomes. It would be useful then to identify whether small areas have changed their level of deprivation over time and thereby be able to: monitor the effect of industry closure; assess the impact of area-based planning initiatives; or determine whether a change in the level of deprivation leads to a change in health. However, the changing relationship with an outcome cannot be judged if the ‘before’ and ‘after’ situations are based on deprivation measures which use different, often time-point specific variables, methods and geographies. Here, for the whole of the UK, inputs to the Townsend index obtained from the 1991 and 2001 Censuses have been harmonised in terms of variable detail and with the 1991 data converted to the 2001 Census ward geography. Deprivation has been calculated so that the 1991 scores are directly comparable with those for 2001. Change over time can be then identified. Measured in this way, deprivation is generally shown to have eased due to downward trends in levels of lack of access to a car, non-home ownership, household overcrowding but most particularly, to reductions in levels of unemployment. Despite these trends, not all locations became less deprived with gradients of deprivation largely persisting within the UK’s constituent countries and in different area types. For England, Wales and Scotland, the calculation of Townsend scores can readily be backdated to incorporate data from the 1971 and 1981 Censuses to create a 1971–2001 set of comparable deprivation scores. The approach can also be applied to the Carstairs index. Due to differences in data availability prior to 1991, incorporating small areas in Northern Ireland would be challenging.

127 citations


Journal ArticleDOI
TL;DR: In this paper, the temporal changes in levels of recorded poverty in Britain distinguishing between times of anecdotal reporting (1845-1901); the first national counts and geographical distribution descriptions (1895-1965); to the current era of an industry dedicated to poverty counting and cartography (1968-2008).
Abstract: This paper considers the temporal changes in levels of recorded poverty in Britain distinguishing between times of anecdotal reporting (1845–1901); the first national counts and geographical distribution descriptions (1895–1965); to the current era of an industry dedicated to poverty counting and cartography (1968–2008). The persistence to the geography of poverty over time is remarked upon and speculated over. In conclusion it is argued that it is important to understand the distribution of wealth to better understand poverty.

28 citations


Journal ArticleDOI
TL;DR: In this article, the effects of spatial location context on the odds of households being in poverty were examined using micro-data from the 2006 American Community Survey for households in the Texas Borderland and Mississippi Delta.
Abstract: This paper uses microdata from the 2006 American Community Survey for households in the Texas Borderland and Mississippi Delta to examine the effects of spatial location context on the odds of households being in poverty. We examine the micro-level and area-level effects of poverty among households located in the two regions. We estimate a series of multilevel regression models predicting the log odds of a household being in poverty. Our major contribution is the demonstration that areal context characteristics have statistically significant effects on the likelihood of households being in poverty. Spatial context matters when it comes to predicting poverty of the households in the Delta and Borderland.

25 citations


Journal ArticleDOI
TL;DR: In this paper, the association between cardiovascular disease and a pool of demographic and socioeconomic variables is analyzed, for a large Canadian city, by means of multivariate spatial regression analysis, which suggests that the spatial dependence observed in the disease prevalence is driven by the spatial distribution of senior citizens.
Abstract: The association between cardiovascular disease and a pool of demographic and socioeconomic variables is analyzed, for a large Canadian city, by means of multivariate spatial regression analysis. The analysis suggests that the spatial dependence observed in the disease prevalence is driven by the spatial distribution of senior citizens. A spatially autoregressive specification on a pool of solely socio-economic variables produces a model whose main predictors are family status, income, and educational attainments. This model can provide an effective analytical tool to support policy decisions, because it identifies a set of socioeconomic, not simply demographic predictors of disease. These socio-economic variables can be targeted by social policies much more effectively than demographic variables. A further analytical step recombines the significant explanatory variables based on their spatial patterns. Thus the model is used to identify areas of social and economic concern, and to enable the initiation of specifically localized preventative health measures. Owing to its generality, the method can be applied to other conditions and to analyze multivariate relationships involving not only socioeconomic variables, but also environmental factors.

19 citations


Journal ArticleDOI
TL;DR: In this paper, a model is formulated to estimate the strength of the relationship between household car ownership and income using cross-sectional data and the residual errors in the model are uncorrelated and hence allows for the estimation of parameters that are, in a statistical sense, the best available.
Abstract: In this paper a model is formulated to estimate the strength of the relationship between household car ownership and income using cross-sectional data. Whilst reports of such studies are not uncommon in the transport literature, this study is different in that it takes explicit account of the spatial distribution of the data. By incorporating this spatial element in the model formulation, the residual errors in the model are uncorrelated and hence allows for the estimation of parameters that are, in a statistical sense, the best available. These spatial models are fitted to a large data set provided by the United Kingdom Office for National Statistics, covering the area of England and Wales. The recommended model form is a Hierarchical Bayesian spatial regression model with the parameters in the model estimated using the technique of Markov Chain Monte Carlo (MCMC). A common feature of all the spatial models is that the estimate of the elasticity of car ownership with respect to income is seen to be larger than that from a non-spatial model.

13 citations


Journal ArticleDOI
TL;DR: In this article, the authors present a new method for monitoring the dynamic changes of functional urban regions (FURs) or metropolitan areas (MAs) boundaries throughout time, based on two elements: the population density and an index of transportation infrastructure supply, which are analyzed in two ways.
Abstract: The objective of this exploratory study is to present a new method for monitoring the dynamic changes of functional urban regions (FURs) or metropolitan areas (MAs) boundaries throughout time The suggested approach is based on two elements: the population density and an index of transportation infrastructure supply, which are analyzed in two ways First, we carry out exploratory analyses of those variables separately Next, the variables are combined using spatial analysis and spatial modeling techniques A case study in the state of Sao Paulo, Brazil, shows that the proposed methodology can be particularly useful for urban and regional planning in developing countries, because it stresses the relationship between land-use and transportation supply So, given the evidence that urban and regional development is strongly influenced by the level of transportation infrastructure supply, the approach can be further improved if considering other elements of transportation infrastructure, such as airports, railways, ports, as well as additional factors which may have effects on land use patterns such as distribution of services and jobs where data is available

13 citations


Journal ArticleDOI
TL;DR: In this article, a new technique that uses small administrative unit poverty maps is introduced to identify the territorial concentration of poverty and inequality, simulate the impact on poverty reduction of alternative land-based actions, engage different actors to discuss and agree on a plan of actions and thereby promote transparency and accountability in decision-making.
Abstract: This paper introduces a new technique that uses small administrative unit poverty maps. The paper shows a pilot application of the proposed technique using census-tract data of the medium-size city of Liberia, Costa Rica in four functions of urban planning: appraisal, simulation, decision-making and assessments. The piloting of the technique made possible to identify the territorial concentration of poverty and inequality, simulate the impact on poverty reduction of alternative land-based actions, engage different actors to discuss and agree on a plan of actions and thereby promote transparency and accountability in decision-making, and assess the impact on poverty reduction of the implementation of the social housing policy in Liberia. The technique may help to promote the development and use of timely and reliable census-tract data. It also incorporates a residential segregation approach to traditional poverty analyses, which proved to be helpful for poverty analyses at small administrative unit levels.

2 citations