結合時空因子的大量估價模型應用：桃園蛋白、蛋黃、邊緣區的分析比較

Application of Mass Appraisal Models with Time and Space Factors: Analysis and Comparison of Core, Inner Suburbs, and Outer Suburbs of Residential Properties

周淑卿(Shu-Ching Chou)；王怡婷(Yi-Ting Wang)；江明珠(Ming-Chu Chiang)

房價 ； 空間異質性 ； 地理加權迴歸 ； 特徵估價模型 ； House prices ； Spatial heterogeneity ； Geographical weighted regression ； Hedonic model

住宅學報

32卷1期（2023 / 06 / 01）

75 - 98

繁體中文;英文

本文以桃園市中古住宅大樓2018年至2020年的房產交易資料為對象，應用地理加權迴歸時間數列法（geographical weighted regression-time series, GWR-TS）建立房價特徵模型（Fotheringham et al., 2015）。首先，觀察特徵的隱含價格在蛋白、蛋黃、邊緣區的時、空分佈差異，再預測桃園市未來的房價，與傳統的最小平方法（ordinary least square, OLS）估計之特徵估價模型比較，並檢驗兩模型的預測表現。研究結果發現，蛋黃區、蛋白區及邊緣區房價的差異主要是受區域因素的影響。其次，住宅特徵的隱含價格會隨時間而變化，並受住房市場景氣影響，數值在空間中出現收歛的漣漪現象。實證結果證實GWR-TS模型的預測能力及配適度均優於OLS模型。

This paper studies the real estate transaction data of Taoyuan City from 2018 to 2020 and applies geographic weighted regression with time series (GWR-TS) approach (Fotheringham, Crespo, & Yao, 2015) in modelling the hedonic housing price. This paper observes the temporal and spatial differences of the implied prices in the core, inner suburb, and outer suburb and forecasts the future housing prices. Then the prediction performance of hedonic model applying GWR-TS and OLS are compared. The empirical results show that, first, the difference in housing prices in the core, inner suburbs, and outer suburbs is mainly affected by regional factors. Second, the implicit price of the hedonic model changes over time. The values which may be related to the rapid cooling of the housing market appear to converge during study period, a phenomenon that is similar to ripples effect. Finally, the model prediction ability and goodness-of-fit of GWR-TS are superior to the traditional OLS hedonic model.

1. 李春長, C. C.,童作君, T. C.(2010)。住宅特徵價格模型之多層次分析。經濟論文叢刊，38(2)，289-325。
   連結：
2. 林祖嘉, C. C.,馬毓駿, Y. C.(2007)。特徵方程式大量估價法在台灣不動產市場之應用。住宅學報，16(2)，1-22。
   連結：
3. 林祖嘉, C. C.,馬毓駿, Y. C.(2012)。貝氏多層次模型在台灣不動產市場估價之應用─以台北市住宅建物為例。住宅學報，21(1)，1-18。
   連結：
4. 張怡文, Y. W.,江穎慧, Y. H.,張金鶚, C. O.(2009)。分量迴歸在大量估價模型之應用 - 非典型住宅估價之改進。都市與計劃，36(3)，281-304。
   連結：
5. 陳樹衡, S. H.,郭子文, T. W.,棗厥庸, C. Y.(2007)。以決策樹之迴歸樹建構住宅價格模型—台灣地區之實證分析。住宅學報，16(1)，1-20。
   連結：
6. 廖咸興, H. H.,張芳玲, F. L.(1997)。不動產評價模式特徵價格法與逼近調整法之比較。住宅學報，5，17-35。
   連結：
7. 賴碧瑩, P. Y.(2007)。應用類神經網路於電腦輔助大量估價之研究。住宅學報，16(2)，43-65。
   連結：
8. Basu, S.,Thibodeau, T. G.(1998).Analysis of Spatial Autocorrelation in House Prices.Journal of Real Estate Finance and Economics,17(1),61-85.
9. Bidanset, P. E.,Lombard, J. R.(2014).Evaluating Spatial Model Accuracy in Mass Real Estate Appraisal: A Comparison of Geographically Weighted Regression and the Spatial Lag Model.Cityscap,16(3),169-182.
10. Bitter, C.,Mulligan, G. F.,Dall’erba, S.(2007).Incorporating Spatial Variation in Housing Attribute Prices: a Comparison of Geographically Weighted Regression and the Spatial Expansion Method.Journal of Geographical Systems,9(1),7-27.
11. Brunsdon, C.,Fotheringham, A. S.,Charlton, M.(1999).Some Notes on Parametric Significance Tests for Geographically Weighted Regression.Journal of Regional Science,39(3),497-524.
12. Brunsdon, C.,Fotheringham, A. S.,Charlton, M.(1996).Geographically Weighted Regression: a Method for Exploring Spatial Nonstationarity.Geographical Analysis,28(4),281-298.
13. Cajias, M.,Ertl, S.(2018).Spatial Effects and Non-Linearity in Hedonic Modeling: Will Large Data Sets Change Our Assumptions?.Journal of Property Investment & Finance
14. Cao, K.,Diao, M.,Wu, B.(2018).A Big Data–Based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore.Annals of the American Association of Geographers,109(1),173-186.
15. Cebula, R. J.(2009).The hedonic pricing model applied to the housing market of the city of Savannah and its Savannah historic landmark district.Review of Regional Studies,39(1),9-22.
16. Chau, K. W.,Chin, T. L.(2003).A Critical Review of Literature on the Hedonic Price Model.International Journal for Housing Science and Its Applications,27(2),145-165.
17. Cliff, A. D.,Ord, J. K.,Haggett, P.,Versey, G. R.(1981).Spatial Diffusion: an Historical Geography of Epidemics in an Island Community.CUP Archive.
18. De Araujo, P.,Cheng, K.(2017).Do preferences for amenities differ among home buyers? A hedonic price approach.Review of Urban & Regional Development Studies,29(3),165-184.
19. Dombrow, J.,Knight, J. R.,Sirmans, C.(1997).Aggregation Bias in Repeat-Sales Indices.The Journal of Real Estate Finance and Economics,14(1),75-88.
20. Follain, J. R.,Malpezzi, S.(1980).Dissecting Housing Value and Rent: Estimates of Hedonic Indexes for Thirty-Nine Large SMSAs.Urban Institute Press.
21. Fotheringham, A. S.,Crespo, R.,Yao, J.(2015).Exploring, Modelling and Predicting Spatiotemporal Variations in House Prices.The Annals of Regional Science,54(2),417-436.
22. Fullerton, T. M.,Bujanda, A.(2018).Commercial Property Values in a Border Metropolitan Economy.Asia-Pacific Journal of Regional Science.,2(2),337-360.
23. Gardner, E. S., Jr.(2006).Exponential Smoothing: The State of the Art—Part II.International Journal of Forecasting,22(4),637-666.
24. Harris, P.,Fotheringham, A.,Crespo, R.,Charlton, M.(2010).The Use of Geographically Weighted Regression for Spatial Prediction: an Evaluation of Models Using Simulated Data Sets.Mathematical Geosciences,42(6),657-680.
25. Helbich, M.,Brunauer, W.,Vaz, E.,Nijkamp, P.(2014).Spatial heterogeneity in hedonic house price models: The case of Austria.Urban Studies,51(2),390-411.
26. Huang, B.,Wu, B.,Barry, M.(2010).Geographically and Temporally Weighted Regression for Modeling Spatio-Temporal Variation in House Prices.International Journal of Geographical Information Science,24(3),383-401.
27. Lancaster, K.(1966).A new approach to consumer theory.Journal of political economy,74(2),132-157.
28. Li, W.,Saphores, J.-D.(2012).A Spatial Hedonic Analysis of the Value of Urban Land Cover in the Multifamily Housing Market in Los Angeles, CA.Urban Studies,49(12),2597-2615.
29. Liou, F. M.,Yang, S. Y.,Chen, B.,Hsieh, W. P.(2016).The Effects of Mass Rapid Transit Station on the House Prices in Taipei: The Hierarchical Linear Model of Individual Growth.Pacific Rim Property Research Journal,22(1),3-16.
30. Lisi, G.(2019).Property valuation: the hedonic pricing model–location and housing submarkets.Journal of Property Investment & Finance,37(6),589-596.
31. Lu, B.,Charlton, M.,Harris, P.,Fotheringham, A. S.(2014).Geographically Weighted Regression With a non-Euclidean Distance Metric: a Case Study Using Hedonic House Price Data.International Journal of Geographical Information Science,28(4),660-681.
32. McCord, M.,Davis, P.,Haran, M.,McGreal, S.,McIlhatton, D.(2012).Spatial Variation as a Determinant of House Price: Incorporating a Geographically Weighted Regression Approach within the Belfast Housing Market.Journal of Financial Management of Property and Construction,17(1),49-72.
33. McMillen, D. P.,McDonald, J.(2004).Reaction of House Prices to a New Rapid Transit Line: Chicago’s Midway Line, 1983–1999.Real Estate Economics,32(3),463-486.
34. Osland, L.(2010).An Application of Spatial Econometrics in Relation to Hedonic House Price Modeling.Journal of Real Estate Research,32(3),289-320.
35. Pace, R. K.,Barry, R.,Gilley, O. W.,Sirmans, C. F.(2000).A Method for Spatial–Temporal Forecasting With an Application to Real Estate Prices.International Journal of Forecasting,16(2),229-246.
36. Rosen, S.(1974).Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition.Journal of Political Economy,82(1),34-55.
37. Sheppard, S.(1999).Hedonic analysis of housing markets.Handbook of Regional and Urban Economics,3,1595-1635.
38. Wang, D.,Li, V. J.(2019).Mass Appraisal Models of Real Estate in the 21st Century: A Systematic Literature Review.Sustainability,11(24),7006.
39. Wen, H.,Jin, Y.,Zhang, L.(2017).Spatial Heterogeneity in Implicit Housing Prices: Evidence From Hangzhou, China.International Journal of Strategic Property Management,21(1),15-28.
40. Yu, D.,Wei, Y. D.,Wu, C.(2007).Modeling Spatial Dimensions of Housing Prices in Milwaukee, WI.Environment and Planning B: Planning and Design,34(6),1085-1102.
41. 鄒克萬, K. W,鄭皓騰, H. T.,郭幸福, H. F.,楊宗名, T. M.(2013)。應用空間特徵價格模型評估高速鐵路對土地價格影響之時空特性—以臺灣高鐵為例。建築學報，14(1)，47-66。