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

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

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Series:	Danmarks Nationalbank Working Papers ; 188
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	1814181717 [GVK]
Source:	EconStor

Persistent link: https://www.econbiz.de/10014540934