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Das Analysepotenzial georeferenzierter Daten

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  • Ramstein, Axel

Abstract

Seit 2013 ist es gesetzlich möglich, Erhebungsmerkmale der amtlichen Statistik dauerhaft zu geografischen quadratischen Gitterzellen von mindestens 100 Metern Kantenlänge zu verorten. Dadurch ergeben sich Analysemöglichkeiten in großer räumlicher Tiefe. Der Artikel untersucht auf Basis von Daten des Mikrozensus 2018 sowie der Zusatzerhebung "Wohnen", ob sich auf Haushaltsebene raumbezogene Charakteristika finden lassen, die einen Teil der Varianz der Nettokaltmiete erklären. Anhand der identifizierten räumlichen Variablen wird anschließend ein Indikator abgeleitet, der als ein Ansatz zur qualitativen Abbildung des Einflusses des Merkmals "Lage" auf Wohnkosten vorgeschlagen wird. Allerdings bedarf dieser Indikator weiterer Untersuchungen und ist daher als experimentelle Statistik zu betrachten.

Suggested Citation

  • Ramstein, Axel, 2022. "Das Analysepotenzial georeferenzierter Daten," WISTA – Wirtschaft und Statistik, Statistisches Bundesamt (Destatis), Wiesbaden, vol. 74(3), pages 39-52.
    • Handle: RePEc:zbw:wistat:260631
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    References listed on IDEAS

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    2. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    3. José-María Montero & Román Mínguez & Gema Fernández-Avilés, 2018. "Erratum to: Housing price prediction: parametric versus semi-parametric spatial hedonic models," Journal of Geographical Systems, Springer, vol. 20(1), pages 107-109, January.
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