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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.
In the study, the aim of the development of the hedonic office rental model, which takes into account the effects of spatial dependency in order to identify the factors that are effective in the determination of office rental values in the Istanbul Office Market. For this purpose, the spatial delay model, along with the spatial error and the spatial Durbin model were predicted and the model, which according to various criteria better explained the relationship than other spatial models, was determined to be the spatial delay model. Local models were estimated using the data set of 2348 offices obtained from the 28 districts of Istanbul during the first quarter of 2018. According to the forecast results of the spatial delay model identified as the appropriate model, the first three variables affecting office rent are the average space ratio in office buildings, the type of building and the view of the throat, respectively. Since the big size of the data set will cause misleading predictions in the prediction of the spatial delay model, the upper spatial matrix model has been predicted. When comparing the forecast results of both models, it was observed that the percentage forecasts were almost the same.
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.
Alan : Sosyal, Beşeri ve İdari Bilimler
Dergi Türü : Uluslararası
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