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OFFICE RENT MODELING IN ISTANBUL: A GEOADDITIVE APPROACH
Öz
The objective of this research is to develop a hedonic model for office space rent prices in Istanbul, using a data set consisting of 2348 office spaces. The data includes information on office building and office space characteristics, as well as features related to the lease, location, and neighborhood that impact office rents. To examine the connection between office rent and these factors, a semiparametric geoadditive model was utilized, which allows for flexibility in functional form and captures location effects through geographical smoothing functions instead of location dummies. The results indicate that the link between office rent determinants and office space rents is nonlinear. The vacancy rate, a measure of office space demand, is the determinant with the greatest impact on office rents. The second most important determinant of office rents is that the office space is in an A-class office building, and the third most influential factor is that the office spaces have a view of the Bosporus.
Anahtar Kelimeler
Kaynakça
- Ahamada, I., & Flacheir, E., (2010). Non-parametric econometrics. UK: Oxford University Press.
- Basile, R., Kayam, S., Mínguez, R., Montero, J. M., & Mur, J. (2015). Semiparametric spatial autoregressive geoadditive models. In P. Commendatore, S. Kayam, &, I. Kubin (Eds.), Complexity and Geographical Economics (pp. 73-98). Springer, Cham.
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- Bera, A. K. (2000). Hypothesis testing in the 20th century with a special reference to testing with misspecified models. Statistics Textbooks and Monographs.
- Bera, A. K., & Kangalli Uyar, S. G. (2019). Local and global determinants of office rents in Istanbul: The mixed geographically weighted regression approach. Journal of European Real Estate Research, 12(2), 227-249. https://doi.org/10.1108/JERER-12-2018-0052
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Ayrıntılar
Birincil Dil
İngilizce
Konular
Ekonomi
Bölüm
Araştırma Makalesi
Yazarlar
Erken Görünüm Tarihi
28 Ağustos 2023
Yayımlanma Tarihi
8 Eylül 2023
Gönderilme Tarihi
3 Mart 2023
Kabul Tarihi
6 Haziran 2023
Yayımlandığı Sayı
Yıl 2023 Sayı: 58
APA
Kangallı Uyar, S. G. (2023). OFFICE RENT MODELING IN ISTANBUL: A GEOADDITIVE APPROACH. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 58, 417-434. https://doi.org/10.30794/pausbed.1259880
AMA
1.Kangallı Uyar SG. OFFICE RENT MODELING IN ISTANBUL: A GEOADDITIVE APPROACH. PAUSBED. 2023;(58):417-434. doi:10.30794/pausbed.1259880
Chicago
Kangallı Uyar, Sinem Güler. 2023. “OFFICE RENT MODELING IN ISTANBUL: A GEOADDITIVE APPROACH”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, sy 58: 417-34. https://doi.org/10.30794/pausbed.1259880.
EndNote
Kangallı Uyar SG (01 Eylül 2023) OFFICE RENT MODELING IN ISTANBUL: A GEOADDITIVE APPROACH. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 58 417–434.
IEEE
[1]S. G. Kangallı Uyar, “OFFICE RENT MODELING IN ISTANBUL: A GEOADDITIVE APPROACH”, PAUSBED, sy 58, ss. 417–434, Eyl. 2023, doi: 10.30794/pausbed.1259880.
ISNAD
Kangallı Uyar, Sinem Güler. “OFFICE RENT MODELING IN ISTANBUL: A GEOADDITIVE APPROACH”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 58 (01 Eylül 2023): 417-434. https://doi.org/10.30794/pausbed.1259880.
JAMA
1.Kangallı Uyar SG. OFFICE RENT MODELING IN ISTANBUL: A GEOADDITIVE APPROACH. PAUSBED. 2023;:417–434.
MLA
Kangallı Uyar, Sinem Güler. “OFFICE RENT MODELING IN ISTANBUL: A GEOADDITIVE APPROACH”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, sy 58, Eylül 2023, ss. 417-34, doi:10.30794/pausbed.1259880.
Vancouver
1.Sinem Güler Kangallı Uyar. OFFICE RENT MODELING IN ISTANBUL: A GEOADDITIVE APPROACH. PAUSBED. 01 Eylül 2023;(58):417-34. doi:10.30794/pausbed.1259880