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Population projection for Germany 2015-2050 on grid level (RWI-GEO-GRID-POP-Forecast): FDZ Data description

Author

Listed:
  • Breidenbach, Philipp
  • Kaeding, Matthias
  • Schaffner, Sandra

Abstract

Existing nationwide population projections focus on highly aggregated spatial units. The most regionalized nationwide study is provided by the German Federal Institute for Building, Urban Affairs and Spatial Research (BBSR) and predicts population on county level up to 2035 (BBSR 2015). Projections of the German Federal Statistical Office – marking the benchmark approach for German population projections – are constraint to agglomerated projections for entire Germany or for federal states, provided by the state offices. Existing small scaled data e.g. the RWI-GEO-GRID impressively reveal the high heterogeneity of local socioeconomic traits within commonly applied county- or municipality-data. Based on these existing population data on the grid level (offering a resolution of 1×1km-grids), the presented RWI-GEO-GRID-POP-Forecast provides a population projection up to 2050. The applied methodological concept strongly follows the approach of the German Federal Statistical Office and the agglomerated results are in line with this projection. This article gives an overview on the provided dataset, the applied methods, some basic results and the access to the data for scientific purposes.

Suggested Citation

  • Breidenbach, Philipp & Kaeding, Matthias & Schaffner, Sandra, 2017. "Population projection for Germany 2015-2050 on grid level (RWI-GEO-GRID-POP-Forecast): FDZ Data description," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 177815.
    • Handle: RePEc:zbw:rwipro:177815
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    1. Rüdiger Budde & Lea Eilers, 2014. "Sozioökonomische Daten auf Rasterebene - Datenbeschreibung der microm-Rasterdaten," RWI Materialien, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, pages 19, 05.
    2. Carter, Lawrence R. & Lee, Ronald D., 1992. "Modeling and forecasting US sex differentials in mortality," International Journal of Forecasting, Elsevier, vol. 8(3), pages 393-411, November.
    3. Budde, Rüdiger & Eilers, Lea, 2014. "Sozioökonomische Daten auf Rasterebene: Datenbeschreibung der microm-Rasterdaten," RWI Materialien 77, RWI - Leibniz-Institut für Wirtschaftsforschung.
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    1. Breidenbach Philipp & Eilers Lea, 2018. "RWI-GEO-GRID: Socio-economic data on grid level," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 238(6), pages 609-616, October.

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