Segmentation of the housing market with internet data : evidence from Denmark

Jakob Feveile Adolfsen, Bjarke Mørch Mønsted, Adrian Michael Bay Schmith, Alessandro Tang-Andersen Martinello, Simon Gudiksen, Kasper Fredløv Sonberg

In this paper, we introduce a novel tool for housing market analysis developed on the basis of online listings data from the largest real estate listing site in Denmark. The tool uses a combination of machine learning techniques to provide a datadriven segmentation of the housing market into meaningful submarkets that differ from administrative classifications. We demonstrate how the tool can support monitoring and research of underlying housing market developments in Denmark.

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Year of publication:	[2022]
Authors:	Adolfsen, Jakob Feveile ; Mønsted, Bjarke Mørch ; Bay Schmith, Adrian Michael ; Tang-Andersen Martinello, Alessandro ; Gudiksen, Simon ; Sonberg, Kasper Fredløv
Publisher:	Copenhagen : Danmarks Nationalbank
Subject:	Housing market \| internet data \| neural network \| Dänemark \| Denmark \| Internet \| Wohnungsmarkt \| Immobilienpreis \| Real estate price \| Neuronale Netze \| Neural networks \| Immobilienmarkt \| Real estate market

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Extent:	1 Online-Ressource (circa 28 Seiten) Illustrationen
Series:	Working paper / Danmarks Nationalbank ; nr. 188 (11 August 2022)
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Graue Literatur ; Non-commercial literature
Language:	English
Other identifiers:	hdl:10419/296890 [Handle]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10013334776