License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GISCIENCE.2018.32
URN: urn:nbn:de:0030-drops-93608
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/9360/
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Inoue, Ryo ; Ishiyama, Rihoko ; Sugiura, Ayako

Identification of Geographical Segmentation of the Rental Apartment Market in the Tokyo Metropolitan Area (Short Paper)

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Abstract

It is often said that the real estate market is divided geographically in such a manner that the value of attributes of real estate properties is different for each area. This study proposes a new approach to the investigation of the geographical segmentation of the real estate market. We develop a price model with many regional explanatory variables, and implement the generalized fused lasso - a regression method for promoting sparsity - to extract the areas where the valuation standard is the same. The proposed method is applied to rental data of apartments in the Tokyo metropolitan area, and we find that the geographical segmentation displays hierarchal patterns. Specifically, we observe that the market is divided by wards, railway lines and stations, and neighbourhoods.

BibTeX - Entry

@InProceedings{inoue_et_al:LIPIcs:2018:9360,
  author =	{Ryo Inoue and Rihoko Ishiyama and Ayako Sugiura},
  title =	{{Identification of Geographical Segmentation of the Rental Apartment Market in the Tokyo Metropolitan Area (Short Paper)}},
  booktitle =	{10th International Conference on Geographic Information  Science (GIScience 2018)},
  pages =	{32:1--32:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Stephan Winter and Amy Griffin and Monika Sester},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/9360},
  URN =		{urn:nbn:de:0030-drops-93608},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.32},
  annote =	{Keywords: geographical market segmentations, rental housing market, sparse modelling, generalised fused lasso, Tokyo metropolitan area}
}

Keywords: geographical market segmentations, rental housing market, sparse modelling, generalised fused lasso, Tokyo metropolitan area
Collection: 10th International Conference on Geographic Information Science (GIScience 2018)
Issue Date: 2018
Date of publication: 02.08.2018

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