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Kodierung des Geburtsstaats in der Wanderungsstatistik: Ein Vergleich regelbasierter Signierung mit Verfahren des maschinellen Lernens

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  • Feuerhake, Jörg
  • Lange, Kerstin
  • Siegismund, Annelen
  • Vigneau, Elsa

Abstract

Seit dem Berichtsjahr 2008 enthalten die Datenlieferungen zur deutschen amtlichen Wanderungsstatistik Angaben zum Geburtsstaat von zu-, fort- und umziehenden Personen. Wegen unzureichender Qualität wurden diese Daten bislang nur für Schätzungen nach Geburtsstaatengruppen im Rahmen europäischer Lieferverpflichtungen genutzt. Künftig sollen auch Aussagen über die einzelnen Geburtsstaaten der Wandernden möglich sein. Daher wurden im Jahr 2019 verschiedene Methoden untersucht, um ein Verfahren zur automatisierten Plausibilisierung und Signierung des Merkmals zu entwickeln. Der Beitrag stellt zwei Ansätze vor und vergleicht sie miteinander: eine regelbasierte Geburtsstaatssignierung basierend auf Leitdateien und den Einsatz von maschinellen Lernverfahren.

Suggested Citation

  • Feuerhake, Jörg & Lange, Kerstin & Siegismund, Annelen & Vigneau, Elsa, 2020. "Kodierung des Geburtsstaats in der Wanderungsstatistik: Ein Vergleich regelbasierter Signierung mit Verfahren des maschinellen Lernens," WISTA – Wirtschaft und Statistik, Statistisches Bundesamt (Destatis), Wiesbaden, vol. 72(3), pages 98-110.
    • Handle: RePEc:zbw:wistat:220347
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    References listed on IDEAS

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    1. Wright, Marvin N. & Ziegler, Andreas, 2017. "ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i01).
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