IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2020i1p24-d470316.html
   My bibliography  Save this article

Making the Third Dimension (3D) Explicit in Hedonic Price Modelling: A Case Study of Xi’an, China

Author

Listed:
  • Yue Ying

    (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands)

  • Mila Koeva

    (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands)

  • Monika Kuffer

    (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands)

  • Kwabena Obeng Asiama

    (Geodetic Institute, Gottfried Wilhelm Leibniz University of Hannover, Nienburger Strasse 1, 30167 Hannover, Germany)

  • Xia Li

    (School of Earth Science and Resources, Chang’an University, No. 126, Yanta Road, Xi’an 710064, China)

  • Jaap Zevenbergen

    (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands)

Abstract

Recent rapid population growth and increasing urbanisation have led to fast vertical developments in urban areas. Therefore, in the context of the dynamic property market, factors related to the third dimension (3D) need to be considered. Current hedonic price modelling (HPM) studies have little explicit consideration for the third dimension, which may have a significant influence on modelling property values in complex urban environments. Therefore, our research aims to narrow the cognitive gap of the missing third dimension by assessing both 2D and 3D HPM and identifying important 3D factors for spatial analysis and visualisation in the selected study area, Xi’an, China. The statistical methods we used for 2D HPM are ordinary least squares (OLS) and geographically weighted regression (GWR). In 2D HPM, they both have very low R 2 (0.111 in OLS and 0.217 in GWR), showing a very limited generalisation potential. However, a significant improvement is observed when adding 3D factors, namely view quality, sky view factor (SVF), sunlight and property orientation. The obtained higher R 2 (0.414) shows the importance of the third dimension or—3D factors for HPM. Our findings demonstrate the necessity to include such factors into HPM and to develop 3D models with a higher level of details (LoD) to serve more purposes such as fair property taxation.

Suggested Citation

  • Yue Ying & Mila Koeva & Monika Kuffer & Kwabena Obeng Asiama & Xia Li & Jaap Zevenbergen, 2020. "Making the Third Dimension (3D) Explicit in Hedonic Price Modelling: A Case Study of Xi’an, China," Land, MDPI, vol. 10(1), pages 1-26, December.
  • Handle: RePEc:gam:jlands:v:10:y:2020:i:1:p:24-:d:470316
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/1/24/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/10/1/24/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yu, Xu & Su, Yuehong, 2015. "Daylight availability assessment and its potential energy saving estimation –A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 494-503.
    2. Feng, Qu & Wu, Guiying Laura, 2015. "Bubble or riddle? An asset-pricing approach evaluation on China's housing market," Economic Modelling, Elsevier, vol. 46(C), pages 376-383.
    3. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    4. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    5. Jaehyun Ha & Sugie Lee & Cheolyeong Park, 2016. "Temporal Effects of Environmental Characteristics on Urban Air Temperature: The Influence of the Sky View Factor," Sustainability, MDPI, vol. 8(9), pages 1-15, September.
    6. Hu, Lirong & He, Shenjing & Han, Zixuan & Xiao, He & Su, Shiliang & Weng, Min & Cai, Zhongliang, 2019. "Monitoring housing rental prices based on social media:An integrated approach of machine-learning algorithms and hedonic modeling to inform equitable housing policies," Land Use Policy, Elsevier, vol. 82(C), pages 657-673.
    7. Gaetano Lisi, 2019. "Property valuation: the hedonic pricing model – location and housing submarkets," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 37(6), pages 589-596, August.
    8. W.J. McCluskey & M. McCord & P.T. Davis & M. Haran & D. McIlhatton, 2013. "Prediction accuracy in mass appraisal: a comparison of modern approaches," Journal of Property Research, Taylor & Francis Journals, vol. 30(4), pages 239-265, December.
    9. Tan, Ronghui & He, Qingsong & Zhou, Kehao & Xie, Peng, 2019. "The effect of new metro stations on local land use and housing prices: The case of Wuhan, China," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    10. Kara, Abdullah & van Oosterom, Peter & Çağdaş, Volkan & Işıkdağ, Ümit & Lemmen, Christiaan, 2020. "3 Dimensional data research for property valuation in the context of the LADM Valuation Information Model," Land Use Policy, Elsevier, vol. 98(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yue Ying & Mila Koeva & Monika Kuffer & Kwabena Obeng Asiama & Xia Li & Jaap Zevenbergen, 2022. "The Perception of the Vertical Dimension (3D) through the Lens of Different Stakeholders in the Property Market of China," Land, MDPI, vol. 11(2), pages 1-29, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jose Torres-Pruñonosa & Pablo García-Estévez & Josep Maria Raya & Camilo Prado-Román, 2022. "How on Earth Did Spanish Banking Sell the Housing Stock?," SAGE Open, , vol. 12(1), pages 21582440221, March.
    2. Sofia Vale & Felipa de Mello-Sampayo, 2021. "Effect of Hierarchical Parish System on Portuguese Housing Rents," Sustainability, MDPI, vol. 13(2), pages 1-17, January.
    3. Guiwen Liu & Jiayue Zhao & Hongjuan Wu & Taozhi Zhuang, 2022. "Spatial Pattern of the Determinants for the Private Housing Rental Prices in Highly Dense Populated Chinese Cities—Case of Chongqing," Land, MDPI, vol. 11(12), pages 1-22, December.
    4. Cankun Wei & Meichen Fu & Li Wang & Hanbing Yang & Feng Tang & Yuqing Xiong, 2022. "The Research Development of Hedonic Price Model-Based Real Estate Appraisal in the Era of Big Data," Land, MDPI, vol. 11(3), pages 1-30, February.
    5. Trojanek, Radoslaw & Huderek-Glapska, Sonia, 2018. "Measuring the noise cost of aviation – The association between the Limited Use Area around Warsaw Chopin Airport and property values," Journal of Air Transport Management, Elsevier, vol. 67(C), pages 103-114.
    6. Juergen Deppner & Marcelo Cajias, 2024. "Accounting for Spatial Autocorrelation in Algorithm-Driven Hedonic Models: A Spatial Cross-Validation Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 68(2), pages 235-273, February.
    7. Shimizu, Chihiro, 2014. "How Are Property Investment Returns Determined? : Estimating the Micro-Structure of Asset Prices, Property Income, and Discount Rates," HIT-REFINED Working Paper Series 12, Institute of Economic Research, Hitotsubashi University.
    8. Dan Horsky & Sanjog Misra & Paul Nelson, 2006. "Observed and Unobserved Preference Heterogeneity in Brand-Choice Models," Marketing Science, INFORMS, vol. 25(4), pages 322-335, 07-08.
    9. Ilir Nase & Jim Berry & Alastair Adair, 2016. "Impact of quality-led design on real estate value: a spatiotemporal analysis of city centre apartments," Journal of Property Research, Taylor & Francis Journals, vol. 33(4), pages 309-331, October.
    10. Laura Blow & Martin Browning & Ian Crawford, 2004. "Nonparametric methods for the characteristic model," CeMMAP working papers 18/04, Institute for Fiscal Studies.
    11. Marco Helbich & Wolfgang Brunauer & Eric Vaz & Peter Nijkamp, 2014. "Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria," Urban Studies, Urban Studies Journal Limited, vol. 51(2), pages 390-411, February.
    12. Frondel, Manuel & Kussel, Gerhard & Sommer, Stephan & Vance, Colin, 2019. "Local cost for global benefit: The case of wind turbines," Ruhr Economic Papers 791, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, revised 2019.
    13. Brockmeier, M., 1991. "Entwicklung und Aufhebung von Reinheitsgeboten im Nahrungsmittelbereich – Analyse und Bewertung," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 27.
    14. Erica L. Groshen & Brian C. Moyer & Ana M. Aizcorbe & Ralph Bradley & David M. Friedman, 2017. "How Government Statistics Adjust for Potential Biases from Quality Change and New Goods in an Age of Digital Technologies: A View from the Trenches," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 187-210, Spring.
    15. Celia Bilbao-Terol, 2009. "Impacts of an Iron and Steel Plant on Residential Property Values," European Planning Studies, Taylor & Francis Journals, vol. 17(9), pages 1421-1436, September.
    16. Can Zou & Jun Tai & Li Chen & Yue Che, 2020. "An Environmental Justice Assessment of the Waste Treatment Facilities in Shanghai: Incorporating Counterfactual Decomposition into the Hedonic Price Model," Sustainability, MDPI, vol. 12(8), pages 1-12, April.
    17. Ming Li & Guojun Zhang & Yunliang Chen & Chunshan Zhou, 2019. "Evaluation of Residential Housing Prices on the Internet: Data Pitfalls," Complexity, Hindawi, vol. 2019, pages 1-15, February.
    18. Buller, Virginia & Hudson, Darren & Parkhurst, Gregory M. & Whittington, Andrew, 2006. "The Impact of Hunting Package Attributes on Hunting Package Prices in Mississippi," Research Reports 15798, Mississippi State University, Department of Agricultural Economics.
    19. Matthias Staudigel & Aleksej Trubnikov, 2022. "High price premiums as barriers to organic meat demand? A hedonic analysis considering species, cut and retail outlet," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(2), pages 309-334, April.
    20. Smed, Sinne & Hansen, Lars Garn, 2018. "Consumer Valuation of Health Attributes in Food," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 43(2), May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:10:y:2020:i:1:p:24-:d:470316. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.