Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/175073 
Erscheinungsjahr: 
2018
Schriftenreihe/Nr.: 
Discussion Paper No. 2018/2
Verlag: 
Freie Universität Berlin, School of Business & Economics, Berlin
Zusammenfassung: 
The transformation of area aggregates between non-hierarchical area systems is a standard problem of official statistics. We introduce a new method which is based on kernel density estimates. It is a modification of the SEM algorithm proposed by Gross et al. (2016), which was used for the transformation of totals on rectangular areas to kernel densities estimates. As a by-product of the routine one obtains simulated geo-coordinates for each unit. With the help of these geo-coordinates it is possible to calculate case numbers for a new area system. The method is applied to student resident figures from Berlin. These are known only at the level of ZIP codes but they are needed for administrative planning districts. Our method is evaluated on a similar, simulated data set with known exact geo-coordinates. In the empirical part results for changes in the student residential areas between 2005 and 2015 are presented. It is demonstrated that the transformation via kernel density estimates offers additional useful features to display concentration areas.
Schlagwörter: 
Choropleths
Grid Maps
Kernel Density Estimation
Geo-Coordinates
Dokumentart: 
Working Paper

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