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Modelling hedonic residential rents for land use and transport simulation while considering spatial effects

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  • Löchl, Michael

    ()
    (IVT, ETH Zürich; Switzerland)

  • Axhausen, Kay W.

    (ETH Zürich; Switzerland)

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    Abstract

    The application of UrbanSim requires land or real estate price data for the study area. These can be difficult to obtain, particularly when tax assessor data and data from commercial sources are unavailable. The article discusses an alternative method of data acquisition and applies hedonic modeling techniques in order to generate the required data. Many studies have highlighted that ordinary least square (OLS) regression approaches lack the ability to consider spatial dependency and spatial heterogeneity, consequently leading to biased and inefficient estimations. Therefore, a comprehensive data set is used for modeling residential asking rents by applying and comparing OLS, spatial autoregressive, and geographically weighted regression (GWR) techniques. The latter technique performed best with regard to model fit, but the issue of correlated coefficients favored a spatial simultaneous autoregressive model. Overall, the article reveals that when housing markets are a particular concern in UrbanSim applications, significant efforts are needed for the price data generation and modeling. The study concludes with further development potentials for UrbanSim.

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    File URL: http://www.jtlu.org/index.php/jtlu/article/view/117/117
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    Bibliographic Info

    Article provided by Center for Transportation Studies, University of Minnesota in its journal The Journal of Tranport and Land Use.

    Volume (Year): 3 (2010)
    Issue (Month): 2 ()
    Pages: 39-63

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    Handle: RePEc:ris:jtralu:0030

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    Cited by:
    1. PHOLO BALA, Alain & PEETERS, Dominique & THOMAS, Isabelle, 2013. "Spatial issues on a hedonic estimation of rents in Brussels," CORE Discussion Papers 2013036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Sebastian Brandt & Wolfgang Maennig, 2012. "The impact of rail access on condominium prices in Hamburg," Transportation, Springer, vol. 39(5), pages 997-1017, September.
    3. Efthymiou, D. & Antoniou, C., 2013. "How do transport infrastructure and policies affect house prices and rents? Evidence from Athens, Greece," Transportation Research Part A: Policy and Practice, Elsevier, vol. 52(C), pages 1-22.
    4. Marko Kryvobokov & Aurélie Mercier & Alain Bonnafous & Dominique Bouf, 2013. "Simulating housing prices with UrbanSim: predictive capacity and sensitivity analysis," Letters in Spatial and Resource Sciences, Springer, vol. 6(1), pages 31-44, March.
    5. Nathalie Picard & Constantinos Antoniou, 2011. "Econometric guidance for developing UrbanSim models. First lessons from the SustainCity project," ERSA conference papers ersa11p1494, European Regional Science Association.

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