IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this article

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

Listed author(s):
  • Löchl, Michael

    ()

    (IVT, ETH Zürich; Switzerland)

  • Axhausen, Kay W.

    (ETH Zürich; Switzerland)

Registered author(s):

    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.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://www.jtlu.org/index.php/jtlu/article/view/117/117
    File Function: Full text
    Download Restriction: no

    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

    as
    in new window

    Handle: RePEc:ris:jtralu:0030
    Contact details of provider: Web page: http://www.jtlu.org/index.php/jtlu

    More information through EDIRC

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as
    in new window


    1. Steven Bourassa & Martin Hoesli, 2010. "Why Do the Swiss Rent?," The Journal of Real Estate Finance and Economics, Springer, vol. 40(3), pages 286-309, April.
    2. David C Wheeler, 2009. "Simultaneous Coefficient Penalization and Model Selection in Geographically Weighted Regression: The Geographically Weighted Lasso," Environment and Planning A, , vol. 41(3), pages 722-742, March.
    3. Chris Lloyd & Ian Shuttleworth, 2005. "Analysing commuting using local regression techniques: scale, sensitivity, and geographical patterning," Environment and Planning A, Pion Ltd, London, vol. 37(1), pages 81-103, January.
    4. Anglin, Paul M & Gencay, Ramazan, 1996. "Semiparametric Estimation of a Hedonic Price Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 633-648, Nov.-Dec..
    5. Ning Wang & Chang-Lin Mei & Xiao-Dong Yan, 2008. "Local linear estimation of spatially varying coefficient models: an improvement on the geographically weighted regression technique," Environment and Planning A, Pion Ltd, London, vol. 40(4), pages 986-1005, April.
    6. David C Wheeler, 2007. "Diagnostic tools and a remedial method for collinearity in geographically weighted regression," Environment and Planning A, Pion Ltd, London, vol. 39(10), pages 2464-2481, October.
    7. G. Stacy Sirmans & C.F. Sirmans & John D. Benjamin, 1989. "Determining Apartment Rent: The Value of Amenities, Services, and External Factors," Journal of Real Estate Research, American Real Estate Society, vol. 4(2), pages 33-44.
    8. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    9. Pace, R Kelley, 1993. "Nonparametric Methods with Applications to Hedonic Models," The Journal of Real Estate Finance and Economics, Springer, vol. 7(3), pages 185-204, November.
    10. Yan Kestens & Marius Thériault & François Des Rosiers, 2006. "Heterogeneity in hedonic modelling of house prices: looking at buyers’ household profiles," Journal of Geographical Systems, Springer, vol. 8(1), pages 61-96, March.
    11. David C Wheeler, 2009. "Simultaneous coefficient penalization and model selection in geographically weighted regression: the geographically weighted lasso," Environment and Planning A, Pion Ltd, London, vol. 41(3), pages 722-742, March.
    12. Dragana Djurdjevic & Christine Eugster & Ronny Haase, 2008. "Estimation of Hedonic Models Using a Multilevel Approach: An Application for the Swiss Rental Market," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(IV), pages 679-701, December.
    13. Halvorsen, Robert & Pollakowski, Henry O., 1981. "Choice of functional form for hedonic price equations," Journal of Urban Economics, Elsevier, vol. 10(1), pages 37-49, July.
    14. Carlos Martins-Filho & Okmyung Bin, 2005. "Estimation of hedonic price functions via additive nonparametric regression," Empirical Economics, Springer, vol. 30(1), pages 93-114, January.
    15. Cropper, Maureen L & Deck, Leland B & McConnell, Kenneth E, 1988. "On the Choice of Functional Form for Hedonic Price Functions," The Review of Economics and Statistics, MIT Press, vol. 70(4), pages 668-675, November.
    16. Clapp, John M, 2003. "A Semiparametric Method for Valuing Residential Locations: Application to Automated Valuation," The Journal of Real Estate Finance and Economics, Springer, vol. 27(3), pages 303-320, November.
    17. James Valente & ShanShan Wu & Alan Gelfand & C.F. Sirmans, 2005. "Apartment Rent Prediction Using Spatial Modeling," Journal of Real Estate Research, American Real Estate Society, vol. 27(1), pages 105-136.
    18. Andrea Baranzini & José V. Ramirez, 2005. "Paying for Quietness: The Impact of Noise on Geneva Rents," Urban Studies, Urban Studies Journal Limited, vol. 42(4), pages 633-646, April.
    19. David Wheeler & Michael Tiefelsdorf, 2005. "Multicollinearity and correlation among local regression coefficients in geographically weighted regression," Journal of Geographical Systems, Springer, vol. 7(2), pages 161-187, 06.
    20. Daniel J. Henderson & Christopher F. Parmeter & Subal C. Kumbhakar, 2007. "Nonparametric estimation of a hedonic price function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 695-699.
    21. Yefang Huang & Yee Leung, 2002. "Analysing regional industrialisation in Jiangsu province using geographically weighted regression," Journal of Geographical Systems, Springer, vol. 4(2), pages 233-249, 06.
    22. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132-132.
    23. Christopher Bitter & Gordon Mulligan & Sandy Dall’erba, 2007. "Incorporating spatial variation in housing attribute prices: a comparison of geographically weighted regression and the spatial expansion method," Journal of Geographical Systems, Springer, vol. 9(1), pages 7-27, April.
    24. R. Kelley Pace, 1998. "Appraisal Using Generalized Additive Models," Journal of Real Estate Research, American Real Estate Society, vol. 15(1), pages 77-100.
    25. David C Wheeler, 2007. "Diagnostic Tools and a Remedial Method for Collinearity in Geographically Weighted Regression," Environment and Planning A, , vol. 39(10), pages 2464-2481, October.
    26. John M. Clapp, 2004. "A Semiparametric Method for Estimating Local House Price Indices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 32(1), pages 127-160, 03.
    27. Won Kim, Chong & Phipps, Tim T. & Anselin, Luc, 2003. "Measuring the benefits of air quality improvement: a spatial hedonic approach," Journal of Environmental Economics and Management, Elsevier, vol. 45(1), pages 24-39, January.
    28. Ning Wang & Chang-Lin Mei & Xiao-Dong Yan, 2008. "Local Linear Estimation of Spatially Varying Coefficient Models: An Improvement on the Geographically Weighted Regression Technique," Environment and Planning A, , vol. 40(4), pages 986-1005, April.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:ris:jtralu:0030. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Arlene Mathison)

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.