The Matrix Exponential Spatial Specification Approach for Big Datasets: The Analysis of Istanbul Office Market

Yıl 2020, , 65 - 87, 25.01.2020

Sinem Kangallı Uyar

https://doi.org/10.17233/sosyoekonomi.2020.01.04

Cited By: 1

Öz

Our aim is to develop a hedonic office rent model considering the spatial dependency in order to determine the factors which have an impact on office rents. For this aim, spatial lag, spatial error, and spatial Durbin models were estimated and according to some criteria, the spatial lag model was selected as the best model which explains the relationship. Spatial models were estimated using the dataset obtained from 28 counties in Istanbul during the first quarter of 2018. According to the estimation results of the spatial lag model, the most effective independent variables are average vacancy rate, building type, and Bosporus view, respectively. Since the big dataset might cause some misleading estimations, the matrix exponential spatial specification model was estimated. It was observed that the estimated coefficients of both of the models are same.

Anahtar Kelimeler

Office Rents, Istanbul, Spatial Dependency, Matrix Exponential Spatial Specification, Big Data

Büyük Veri Setlerinde Üstel Mekânsal Matris Tanımı Yaklaşımı: İstanbul Ofis Piyasası Analizi

Öz

Çalışmada, İstanbul Ofis Piyasası’nda ofis kira değerlerinin belirlenmesinde etkili olan faktörleri tespit etmek amacıyla mekânsal bağımlılık etkisini dikkate alan hedonik ofis kira modelinin geliştirilmesi amaçlanmıştır. Bu amaçla, mekânsal gecikme modeli ile birlikte mekânsal hata ve mekânsal Durbin modeli tahmin edilmiş ve çeşitli kriterlere göre ilişkiyi diğer mekânsal modellere göre daha iyi açıklayan modelin mekânsal gecikme modeli olduğuna karar verilmiştir. Mekânsal modeller 2018’in ilk çeyreği boyunca İstanbul’un 28 ilçesinden elde edilen 2348 ofise ait veri seti kullanılarak tahmin edilmiştir. Uygun model olarak belirlenen mekânsal gecikme modelinin tahmin sonuçlarına göre, ofis kiraları üzerindeki en etkili ilk üç değişken sırasıyla ofis binalarındaki ortalama boşluk oranı, bina tipi ve boğaz manzarasıdır. Veri setinin büyük boyutlu olması mekânsal gecikme modelinin tahmininde yanıltıcı tahminlere neden olacağından, üstel mekânsal matris modeli tahmin edilmiştir. Her iki modelin tahmin sonuçları karşılaştırıldığında katsayı tahminlerinin neredeyse aynı olduğu gözlemlenmiştir.

Anahtar Kelimeler

Ofis Kiraları, İstanbul, Mekânsal Bağımlılık, Üstel Mekânsal Matris Tanımı, Büyük Veri

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