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

Yıl 2020, Cilt: 28 Sayı: 43, 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

Kaynakça

• Anselin, L. (1988), “Model Validation in Spatial Econometrics: A Review and Evaluation of Alternative Approaches”, International Regional Science Review, 11(3), 279-316.
• Anselin, L. & A. K. Bera (1998), “Spatial Dependence in Linear Regression Models with an Introduction to Spatial Econometrics” in A. Ullah and D.E.A. Giles (eds.), Handbook of Applied Economic Statistics, New York: Marcel Decker, Inc., 237-289.
• Anselin, L., A. K. Bera, R. Florax & M. J. Yoon (1996), “Simple Diagnostic Tests for Spatial Dependence”, Regional Science and Urban Economics, 26(1), 77-104.
• Arbia, G. (2014), A Primer for Spatial Econometrics: With Applications in R, Palgrave Texts in Econometrics Series.
• Bell, K. P. & N. E. Bockstael (2000), “Applying the Generalized-Moments Estimation Approach to Spatial Problems Involving Micro-Level Data”, Review of Economics and Statistics, 82(1), 72-82.
• Burridge, P. (1980), “On the Cliff-Ord Test for Spatial Correlation”, Journal of the Royal Statistical Society. Series B (Methodological), 42(1), 107-108.
• Chegut, A. M., P. M. Eichholtz & P. J. Rodrigues (2015), “Spatial Dependence in International Office Markets”, The Journal of Real Estate Finance and Economics, 51(2), 317-350.
• Chiu, T. Y., T. Leonard & K. W. Tsui (1996), “The Matrix-Logarithmic Covariance Model”, Journal of the American Statistical Association, 91(433), 198-210.
• Cliff, A. & K. Ord (1972), “Testing for Spatial Autocorrelation among Regression Residuals”, Geographical analysis, 4(3), 267-284.
• Debrezion, G. & J. Willigers (2008), “The Effect of Railway Stations on Office Space Rent Levels: The Implication of HSL South in Station Amsterdam South Axis”, in F. Bruinsma, E. Pels, H. Priemus, P. Rietveld & B. van Wee (eds.), Railway Development: Impacts on Urban Dynamics, Heidelberg: Physica-Verlag, 265-293.
• Elhorst, J. P. (2014), Spatial Econometrics: From Cross-Sectional Data to Spatial Panels, New York: Springer.
• Kelejian, H. H. & I. R. Prucha (1998), “A Generalized Spatial Two-Stage Least Squares Procedure for Estimating A Spatial Autoregressive Model with Autoregressive Disturbances”, The Journal of Real Estate Finance and Economics, 17(1), 99-121.
• Kempf, S. (2015), Development of Hedonic Office Rent Indices: Examples for German Metropolitan Areas, Wiesbaden: Springer Gabler.
• Koster, H. R., J. van Ommeren & P. Rietveld (2014), “Is the Sky the Limit? High-Rise Buildings and Office Rents”, Journal of Economic Geography, 14(1), 125-153.
• LeSage, J. P., & R. K. Pace (2007), “A Matrix Exponential Spatial Specification”, Journal of Econometrics, 140(1), 190-214.
• LeSage, J. & Pace, R. K. (2009), Introduction to Spatial Econometrics, New York: Chapman and Hall/CRC.
• LeSage, J. & R. K. Pace (2010), “Spatial Econometrics Models”, in M. M. Fischer & A. Getis (eds.), Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications, Heidelberg: Springer-Verlag.
• Nappi‐Choulet Pr, I. & T. P. Maury (2009), “A Spatiotemporal Autoregressive Price Index for The Paris Office Property Market”, Real Estate Economics, 37(2), 305-340.
• Osland, L. (2010), “An Application of Spatial Econometrics in Relation to Hedonic House Price Modeling”, Journal of Real Estate Research, 32(3), 289-320.
• Öven, V. A., & D. Pekdemir (2006), “Office Rent Determinants Utilising Factor Analysis—A Case Study for Istanbul”, The Journal of Real Estate Finance and Economics, 33(1), 51-73.
• Ozus, E. (2009), “Determinants of Office Rents in The Istanbul Metropolitan Area”, European Planning Studies, 17(4), 621-633.
• Moran, P. A. (1950), “A Test for The Serial Independence of Residuals”, Biometrika, 37(1/2), 178-181.
• Pekdemir, D. & V. Dökmeci (2011), “İstanbul Ofis Kira Tahmin Modeli Geliştirilmesi”, ITU Journal Series A: Architecture, Planning, Design, 10(1), 51-60.
• Tobler, W. (1970), “A Computer Movie Simulating Urban Growth in The Detroit Region”, Economic Geography, 46(sup 1), 234-240.
• Tu, Y., S. M., Yu & H. Sun (2004), “Transaction‐Based Office Price Indexes: A Spatiotemporal Modeling Approach”, Real Estate Economics, 32(2), 297-328.