GIS-Based Spatial Analysis for the Determinants of REIT-Owned Commercial Property Rents in Istanbul Metropolitan Area
||Erol, Isil; Aysegul Ozbakir, Buket
||GIS-Based Spatial Analysis for the Determinants of REIT-Owned Commercial Property Rents in Istanbul Metropolitan Area
||16th Annual European Real Estate Society Conference in Stockholm, Sweden
||Over the past decade, Istanbul Metropolitan Area has been the international center of Turkey’s various service sectors, including producer, distributive, and especially financial services. Today, foreign investors are heavily investing in high-rise office blocks and shopping centers in Istanbul. Having population of 12 million, Istanbul has more modern shopping centers than most European cities – 58 existing centers and 47 more are being built - and 40 per cent of the stores in shopping centers are either foreign-owned or franchises of foreign companies. The objective of this paper is, firstly, to carry out a spatial analysis of the physical, socio-economic and locational rent determinants of the offices and commercial (shopping centres) properties in Istanbul Metropolitan Area using the Principal Component Analysis (PCA) and Geographic Information Systems (GIS). Our data set includes a detailed survey of 500 financial and commercial properties particularly owned by the Turkish REITs. Turkey established its REIT structure in 1998, and currently there are 14 REITs listed in the Istanbul Stock Exchange. REITs own prestigious financial and commercial properties located mostly in the CBD, constituting the Historical Peninsula, Beyoglu, Sisli, Besiktas, and Sariyer where the sampling data for this study are also collected. Both an in-depth survey of the offices and shopping centers and their locational parameters derived from GIS are subjected to PCA. Results of the PCA show that each component is linked to a different meaning of the rent determination of a commercial property. Second, this study attempts to construct, for the first time in the literature, a cross-sectional Real Estate Valuation Index (REVI), based on a weighted combination of the PCA components using GIS. The spatial distribution of this index in Istanbul will also make significant contributions to a thorough analysis of the real estate market in Turkey."
||Rent Determinants, Commercial Property, Turkish REITs, Geographical Information Systems (GIS), Principal Component Analysis (PCA), Cross-sectional Real Estate Valuation Index (REVI)
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||Price and Rent Determination
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