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Geographical Diversification Through Spatial Autocorrelation Analysis Of Paris Residential Market

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Date
2010
Dewey
Economie industrielle
Sujet
geographical diversification; spatial autocorrelation; market segmentation; real estate portfolio
JEL code
R31
Conference name
17th Annual ERES Conference
Conference date
06-2010
Conference city
Milan
Conference country
Italie
URI
https://basepub.dauphine.fr/handle/123456789/8125
Collections
  • DRM : Publications
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Author
Simon, Arnaud
Srikhum, Piyawan
Type
Communication / Conférence
Abstract (EN)
The development of information and communication technologies (Internet, databases...) reduces the barriers of investment. Consequently, investors now have a wealth of opportunities available for diversifying their real estate portfolio geographically. However, neighborhoods residential properties tend to have similar price evolution because they have the same structural characteristics and share location amenities. The previous studies often confirm a degree of spatial autocorrelation (positive or very positive autocorrelation) between neighboring properties. Hence, the real estate diversification between predefined regions, based on administrative boundary (arrondissement) is rarely optimal. Differences from the administrative segmentation, this study analyzes the relevance of a new segmentation of Paris housing markets that could improve the geographical diversification performance. By applying the spatial econometrics techniques based on the notary’s data of 35206 apartments’ transaction in Paris in 2007, we attempt to use residual spatial autocorrelation information to redefine new market segmentation. This geographical boundary allows the properties to determine their submarket structure and to eliminate the spatial autocorrelation problem between submarket. We find a low spatial autocorrelation of properties belonging to different submarkets. According to this study, the diversified portfolios based on this structure show probably more efficient than the previous literatures established on the traditional administrative segmentation.

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