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• W2294435483 abstract "Summary. Several problems are noted in current approaches to the study of population turnover, especially the use of inadequate techniques and the dangers in using British census data. An alternative data source, and a method of analysis are briefly outlined. The study of population turnover has long been an integral part of urban studies. In the human ecology school associated with Burgess and Park, turnover was seen as the pulse of the community and more specifically, high turnover was seen as indicative of the breakdown or absence of community and social ties (Zorbaugh, 1929). More recent approaches to the study of turnover have moved away from this Wirthian-type framework and one avenue of recent research has been the analysis of the spatial covariance between turnover and selected ecological variables (Moore, 1969, 1971; Herbert, 1973). It is the aim of this paper to highlight some problems in this type of analysis, to pinpoint some dangers in the use of British mobility data, and finally to suggest a method for analysing turnover which overcomes these problems. Moore's analysis of turnover in Brisbane, Australia, consisted of defining a population turnover index which was then used as the dependent variable in a series of multiple and partial regressions. Herbert's analysis was less sophisticated, since the main aim was to focus on the behavioural aspects of residential mobility in Swansea, and consisted of an examination of the corre lation coefficients between the levels of intra-urban mobility and selected variables. There are three main problems associated with this type of analysis. First, to employ multiple regression with highly correlated independent variables-in Moore's seven by seven correlation matrix there were six cases where the correlation coefficients were greater than or equal to 0 70-entails multicollinearity which leads to high standard errors for, and imprecise esti mation of, the regression coefficients (Hauser, 1974). To overcome this problem it is necessary to use independent variables which are not highly correlated, and a convenient method is to subject the initial data set and/or other variables to a principal components analysis and then use the resultant component scores as independent variables. If this method is used, care has to be taken with the initial variable selection and component identification. Secondly, to use all the areas of the city as the data base in techniques of this kind, is to assume that the relationship between turnover values and any other variables is consistent, or ' holds up ' in all areas of the city. The relationship between turnover and other variables may not be linear and indeed may radi cally alter in different sub-areas of the city. High turnover figures are found in high status private renting areas, medium turnover figures are found in high status owner-occupier areas and low status private renting areas, while low turnover figures are associated with low socio-economic status public housing areas, medium status owner-occupier areas and low status owner-occupier areas. For any one variable or component-tenure, socio-economic status and stage in the life cycle-the relationship with population turnover does not" @default.
• W2294435483 created "2016-06-24" @default.
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• W2294435483 date "2016-01-01" @default.
• W2294435483 modified "2023-09-26" @default.
• W2294435483 title "Population turnover: problems in analysis and an alternative method" @default.
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