Abstract
The dynamics of residential sorting have been previously explored using segregation models. In contrast with these models which emphasize resultant spatial distributions, this paper suggests an approach of assessing temporal income sorting trends through the analysis of residential mobility patterns. The approach is focused on ‘gains’ in neighborhood socioeconomic status experienced by movers as a result of residential relocation. The analysis of income sorting trends is based upon the analysis of inter-group differentials in these gains over time. Trends in income sorting are assumed to follow temporal variations in exogenous factors such as housing market circumstances. As different age groups are assumed to respond differently to these variations, income sorting is expected to evolve to some extent on the basis of age. An empirical example demonstrates the application of this approach to intra-metropolitan residential mobility data collected for the Tel-Aviv metropolitan area through the years 1997–2008.
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Notes
Based on disposable income, after taxes and transfers, OECD data.
As moves are carried out by households, records cannot be assumed to be independent of each other. Thus the analysis is restricted to methods that do not involve violation of such required assumption.
Income deciles were calculated based on national income distributions for each year respectively. Data was provided to CBS by the National Insurance Institute. As missing income decile may indicate unemployment, labor force nonparticipation, missing data, or undeclared income, we chose not to include these records. Mover income records from 1999 onwards include earnings from both employment and self-employment, while 1997–8 records include earnings from salaried employment only.
Age is top-coded at 65 and hence we defined age-groups to be used as a categorical variable.
New areas that were built between 1995 and 2008 and were missing 1995 attribute values were assigned estimated values based on 2008 values and variable predicted growth rates. Predictions were carried out using decision tree models, where the dependent variable was the neighborhood growth rate of the examined variable from 1995 to 2008, and independent variables were: average growth rate of the variable in the city quarter in which the tract is situated, demographic and geographic variables.
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Acknowledgments
This research was supported by the Azrieli Foundation, the Israel Foundations Trustees Program for the Advancement of Research in the Social Sciences, and the Shlomo Glass and Penny Balaban Fund. The authors thank two anonymous reviewers for their constructive comments.
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Modai-Snir, T., Plaut, P.O. Intra-metropolitan residential mobility and income sorting trends. Lett Spat Resour Sci 8, 291–305 (2015). https://doi.org/10.1007/s12076-014-0133-z
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DOI: https://doi.org/10.1007/s12076-014-0133-z