Exploring determinants of housing prices in Beijing: An enhanced hedonic regression with open access POI data

ISPRS International Journal of Geo-Information

Volumn 6, Issue 11, 2017, Pages

  Xiao, Yixiong ^a   Chen, Xiang ^b   Li, Qiang ^a   Yu, Xi ^a   Chen, Jin ^a   Guo, Jing ^a  

^a BEIJING NORMAL UNIVERSITY   (China)

^b ARKANSAS TECH UNIVERSITY   (United States)

Author keywords

Accessibility; Amenity value; Hedonic pricing model; Points of Interest (POIs); Spatial autocorrelation

Indexed keywords

EID: 85044507336     PISSN: None     EISSN: 22209964     Source Type: Journal    
DOI: 10.3390/ijgi6110358     Document Type: Article

References (75)

1. Cohen, B. Urbanization in developing countries: Current trends, future projections, and key challenges for sustainability. Technol. Soc. 2006, 28, 63–80. [CrossRef]
2. D’Acci, L. Monetary, subjective and quantitative approaches to assess urban quality of life and pleasantness in cities (hedonic price, willingness-to-pay, positional value, life satisfaction, isobenefit lines). Soc. Indic. Res. 2014, 115, 531–559. [CrossRef]
3. Jim, C.Y.; Chen, W.Y. External effects of neighbourhood parks and landscape elements on high-rise residential value. Land Use Policy 2010, 27, 662–670. [CrossRef]
4. Kaltenborn, B.P.; Andersen, O.; Nellemann, C. Amenity development in the Norwegian mountains. Landsc. Urban Plan. 2009, 91, 195–201. [CrossRef]
5. Yamagata, Y.; Murakami, D.; Yoshida, T.; Seya, H.; Kuroda, S. Value of urban views in a bay city: Hedonic analysis with the spatial multilevel additive regression (SMAR) model. Landsc. Urban Plan. 2016, 151, 89–102. [CrossRef]
6. Hui, E.C.M.; Chau, C.K.; Pun, L.; Law, M.Y. Measuring the neighboring and environmental effects on residential property value: Using spatial weighting matrix. Build. Environ. 2007, 42, 2333–2343. [CrossRef]
7. Kong, F.; Yin, H.; Nakagoshi, N. Using GIS and landscape metrics in the hedonic price modeling of the amenity value of urban green space: A case study in Jinan City, China. Landsc. Urban Plan. 2007, 79, 240–252. [CrossRef]
8. Clark, J.K.; McChesney, R.; Munroe, D.K.; Irwin, E.G. Spatial characteristics of exurban settlement pattern in the United States. Landsc. Urban Plan. 2009, 90, 178–188. [CrossRef]
9. Lin, D.; Allan, A.; Cui, J. Exploring differences in commuting behaviour among various income groups during polycentric urban development in China: New evidence and its implications. Sustainability 2016, 8, 1188. [CrossRef]
10. Wen, H.; Tao, Y. Polycentric urban structure and housing price in the transitional China: Evidence from Hangzhou. Habitat Int. 2015, 46, 138–146. [CrossRef]
11. Chiang, Y.H.; Peng, T.C.; Chang, C.O. The nonlinear effect of convenience stores on residential property prices: A case study of Taipei, Taiwan. Habitat Int. 2015, 46, 82–90. [CrossRef]
12. Jang, M.; Kang, C.-D. Retail accessibility and proximity effects on housing prices in Seoul, Korea: A retail type and housing submarket approach. Habitat Int. 2015, 49, 516–528. [CrossRef]
13. Dai, X.; Bai, X.; Xu, M. The influence of Beijing rail transfer stations on surrounding housing prices. Habitat Int. 2016, 55, 79–88. [CrossRef]
14. Zhang, M.; Meng, X.; Wang, L.; Xu, T. Transit development shaping urbanization: Evidence from the housing market in Beijing. Habitat Int. 2014, 44, 545–554. [CrossRef]
15. Xu, Y.; Zhang, Q.; Zheng, S. The rising demand for subway after private driving restriction: Evidence from Beijing’s housing market. Reg. Sci. Urban Econ. 2015, 54, 28–37. [CrossRef]
16. Peng, T.; Chiang, Y. The non-linearity of hospitals’ proximity on property prices: Experiences from Taipei, Taiwan. J. Prop. Res. 2016, 9916, 1–21. [CrossRef]
17. Wen, H.; Zhang, Y.; Zhang, L. Do educational facilities affect housing price? An empirical study in Hangzhou, China. Habitat Int. 2014, 42, 155–163. [CrossRef]
18. Nguyen-Hoang, P.; Yinger, J. The capitalization of school quality into house values: A review. J. Hous. Econ. 2011, 20, 30–48. [CrossRef]
19. Basu, S.; Thibodeau, T. Analysis of spatial autocorrelation in house prices. J. Real Estate Financ. Econ. 1998, 17, 61–85. [CrossRef]
20. Palm, R. Spatial Segmentation of the urban housing market. Econ. Geogr. 1978, 54, 210–221. [CrossRef]
21. Chau, K.W.; Chin, T.L. A critical review of literature on the hedonic price model. Int. J. Hous. Sci. Its Appl. 2003, 2, 145–165.
22. Kiel, K.A.; Zabel, J.E. Location, location, location: The 3L approach to house price determination. J. Hous. Econ. 2008, 17, 175–190. [CrossRef]
23. McMillen, D.P. The return of centralization to Chicago: Using repeat sales to identify changes in house price distance gradients. Reg. Sci. Urban Econ. 2003, 33, 287–304. [CrossRef]
24. Jim, C.Y.; Chen, W.Y. Value of scenic views: Hedonic assessment of private housing in Hong Kong. Landsc. Urban Plan. 2009, 91, 226–234. [CrossRef]
25. Wu, F. Changes in the structure of public housing provision in urban China. Urban Stud. 1996, 33, 1601–1628. [CrossRef]
26. Ta, N.; Chai, Y.; Zhang, Y.; Sun, D. Understanding job-housing relationship and commuting pattern in Chinese cities: Past, present and future. Transp. Res. Part D Transp. Environ. 2017, 52, 562–573. [CrossRef]
27. Huang, Y.; Jiang, L. Housing inequality in transitional Beijing. Int. J. Urban Reg. Res. 2009, 33, 936–956. [CrossRef]
28. Li, S.M.; Siu, Y.M. Residential mobility and urban restructuring under market transition: A study of Guangzhou, China. Prof. Geogr. 2001, 53, 219–229. [CrossRef]
29. Mathur, S.; Ferrell, C. Measuring the impact of sub-urban transit-oriented developments on single-family home values. Transp. Res. Part A Policy Pract. 2013, 47, 42–55. [CrossRef]
30. Ma Laurence, J.C.; MaCui, G. Administrative changes and urban population in China. Ann. Assoc. Am. Geogr. 1987, 77, 373–395. [CrossRef]
31. Chen, X.; Yang, X. Does food environment influence food choices? A geographical analysis through “tweets”. Appl. Geogr. 2014, 51, 82–89. [CrossRef]
32. Yue, Y.; Zhuang, Y.; Yeh, A.G.O.; Xie, J.-Y.; Ma, C.-L.; Li, Q.-Q. Measurements of POI-based mixed use and their relationships with neighbourhood vibrancy. Int. J. Geogr. Inf. Sci. 2016, 1–18. [CrossRef]
33. Liu, X.; Long, Y. Automated identification and characterization of parcels with OpenStreetMap and points of interest. Environ. Plan. B Plan. Des. 2016, 43, 341–360. [CrossRef]
34. Jiang, S.; Alves, A.; Rodrigues, F.; Ferreira, J.; Pereira, F.C. Mining point-of-interest data from social networks for urban land use classification and disaggregation. Comput. Environ. Urban Syst. 2015, 53, 36–46. [CrossRef]
35. Lancaster, K.J. A new approach to consumer theory. J. Polit. Econ. 1966, 74, 132. [CrossRef]
36. Malpezzi, S. Hedonic pricing models: A selective and applied review. In Housing Economics and Public Policy; Blackwell Science Ltd.: Oxford, UK; pp. 67–89, ISBN 9780470690680.
37. Conway, D.; Li, C.Q.; Wolch, J.; Kahle, C.; Jerrett, M. A spatial autocorrelation approach for examining the effects of urban greenspace on residential property values. J. Real Estate Financ. Econ. 2010, 41, 150–169. [CrossRef]
38. Anselin, L.; Le Gallo, J. Interpolation of air quality measures in hedonic house price models: Spatial aspects. Spat. Econ. Anal. 2006, 1, 31–52. [CrossRef]
39. Kim, C.W.; Phipps, T.T.; Anselin, L. Measuring the benefits of air quality improvement: A spatial hedonic approach. J. Environ. Econ. Manag. 2003, 45, 24–39. [CrossRef]
40. Anselin, L.; Rey, S. Properties of tests for spatial dependence in linear regression models. Geogr. Anal. 1991, 23, 112–131. [CrossRef]
41. Getis, A.; Griffith, D. A comparative spatial filtering in regression analysis. Geogr. Anal. 2002, 34, 130–140. [CrossRef]
42. Chun, Y. Analyzing space-time crime incidents using eigenvector spatial filtering: An application to vehicle burglary. Geogr. Anal. 2014, 46, 165–184. [CrossRef]
43. Chun, Y.; Griffith, D.A. Modeling network autocorrelation in space–time migration flow data: An eigenvector spatial filtering approach. Ann. Assoc. Am. Geogr. 2011, 101, 523–536. [CrossRef]
44. Diniz-Filho, J.A.F.; Bini, L.M. Modelling geographical patterns in species richness using eigenvector-based spatial filters. Glob. Ecol. Biogeogr. 2005, 14, 177–185. [CrossRef]
45. Helbich, M.; Griffith, D.A. Spatially varying coefficient models in real estate: Eigenvector spatial filtering and alternative approaches. Comput. Environ. Urban Syst. 2016, 57, 1–11. [CrossRef]
46. Rosen, S. Hedonic prices and implicit markets: Product differentiation in pure competition. J. Polit. Econ. 1974, 82, 34. [CrossRef]
47. Ottensmann, J.R.; Payton, S.; Man, J. Urban location and housing prices within a hedonic model. J. Reg. Anal. Policy 2008, 38, 19–35.
48. Cropper, M.L.; Leland, B.D.; McConnell, K.E. On the choice of funtional form for hedonic price functions. Rev. Econ. Stat. 1988, 70, 668–675. [CrossRef]
49. De Jong, P.; Sprenger, C.; van Veen, F. On extreme values of moran’s I and Geary’s c. Geogr. Anal. 1984, 16, 17–24. [CrossRef]
50. Tiefelsdorf, M.; Boots, B. The exact distribution of Moran’s I. Environ. Plan. A 1995, 27, 985–999. [CrossRef]
51. Griffith, D.A. A linear regression solution to the spatial autocorrelation problem. J. Geogr. Syst. 2000, 2, 141–156. [CrossRef]
52. Haining, R.P. Spatial Data Analysis: Theory and Practice; Cambridge University Press: Cambridge, UK, 2003; ISBN 0521774373.
53. Patuelli, R.; Griffith, D.A.; Tiefelsdorf, M.; Nijkamp, P. Spatial filtering and eigenvector stability: Space-time models for German unemployment data. Int. Reg. Sci. Rev. 2011, 34, 253–280. [CrossRef]
54. Tiefelsdorf, M.; Griffith, D.A. Semiparametric filtering of spatial autocorrelation: The eigenvector approach. Environ. Plan. A 2007, 39, 1193–1221. [CrossRef]
55. Beijing Municipal Environment Monitoring Center. Available online: http://www.bjmemc.com.cn/ (accessed on 13 November 2017).
56. Kay, S.; Zhao, B.; Sui, D. Can social media clear the air? A case study of the air pollution problem in Chinese cities. Prof. Geogr. 2015, 67, 351–363. [CrossRef]
57. Helbich, M.; Brunauer, W.; Vaz, E.; Nijkamp, P. Spatial heterogeneity in hedonic house price models: The case of Austria. Urban Stud. 2014, 51, 390–411. [CrossRef]
58. Helbich, M.; Brunauer, W.; Hagenauer, J.; Leitner, M. Data-driven regionalization of housing markets. Ann. Assoc. Am. Geogr. 2013, 103, 871–889. [CrossRef]
59. Kwan, M.-P. Space-time and integral measures of individual accessibility: A comparative analysis using a point-based framework. Geogr. Anal. 1998, 30, 191–216. [CrossRef]
60. Chen, X.; Kwan, M.-P. Choice set formation with multiple flexible activities under space–time constraints. Int. J. Geogr. Inf. Sci. 2012, 26, 941–961. [CrossRef]
61. Black, J.; Conroy, M. Accessibility measures and the social evaluation of urban structure. Environ. Plan. A 1977, 9, 1013–1031. [CrossRef]
62. Chen, X.; Clark, J. Interactive three-dimensional geovisualization of space-time access to food. Appl. Geogr. 2013, 43, 81–86. [CrossRef]
63. Wooldridge, J.M. Introductory Econometrics: A Modern Approach, 5th ed.; South Western Cengage Learning: Mason, USA, 2015; ISBN 1111531048.
64. Wang, R.; Yuan, Q. Parking practices and policies under rapid motorization: The case of China. Transp. Policy 2013, 30, 109–116. [CrossRef]
65. Wang, Y.L.; Wang, X.; Zhang, M.C. Current situation and analysis of parking problem in Beijing. Procedia Eng. 2016, 137, 777–785. [CrossRef]
66. Jayantha, W.M.; Lam, S.O. Capitalization of secondary school education into property values: A case study in Hong Kong. Habitat Int. 2015, 50, 12–22. [CrossRef]
67. Wu, Q.; Zhang, X.; Waley, P. Jiaoyufication: When gentrification goes to school in the Chinese inner city. Urban Stud. 2016, 53, 3510–3526. [CrossRef]
68. Zhao, P. Sustainable urban expansion and transportation in a growing megacity: Consequences of urban sprawl for mobility on the urban fringe of Beijing. Habitat Int. 2010, 34, 236–243. [CrossRef]
69. Miao, P. Deserted streets in a jammed town: The gated community in Chinese cities and its solution. J. Urban Des. 2003, 8, 45–66. [CrossRef]
70. Zhao, W.; Zou, Y. Un-gating the gated community: The spatial restructuring of a resettlement neighborhood in Nanjing. Cities 2017, 62, 78–87. [CrossRef]
71. Chattopadhyay, S. Estimating the demand for air quality: New evidence based on the Chicago housing market. Land Econ. 1999, 75, 22–38. [CrossRef]
72. Li, H.; Wei, Y.D.; Yu, Z.; Tian, G. Amenity, accessibility and housing values in metropolitan USA: A study of Salt Lake County, Utah. Cities 2016, 59, 113–125. [CrossRef]
73. Chen, X. Take the edge off: A hybrid geographic food access measure. Appl. Geogr. 2017, 87, 149–159. [CrossRef]
74. Zheng, S.; Hu, W.; Wang, R. How much is a good school worth in Beijing? Identifying price premium with paired resale and rental data. J. Real Estate Financ. Econ. 2016, 53, 184–199. [CrossRef]
75. Du, Z.; Zhang, L. Home-purchase restriction, property tax and housing price in China: A counterfactual analysis. J. Econom. 2015, 188, 558–568. [CrossRef]