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Estimating the Effect of Air Quality: Spatial versus Traditional Hedonic Price Models

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  • Helen R. Neill

    ()
    (Department of Environmental Studies, Greenspun College of Urban Affairs, University of Nevada)

  • David M. Hassenzahl

    ()
    (Department of Environmental Studies, Greenspun College of Urban Affairs, University of Nevada)

  • Djeto D. Assane

    ()
    (Department of Economics, College of Business, University of Nevada)

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    Abstract

    Empirical studies of hedonic housing prices show that the spatial maximum likelihood estimation (MLE) method is preferable to the traditional ordinary least squares (OLS) hedonic method. Current computing capabilities restrict the MLE method to relatively small data sets. This paper circumvents this limitation by coupling the spatial MLE method with block bootstrapping, a form of Monte Carlo simulation that accounts for spatially dependent data. Blocks are created based on monthly and census tract information for resampling. For each month, we obtained 50 resamples of 750 observations from a data set of 15,727 residential properties to compare OLS and MLE empirical results. We find that the spatial MLE method consistently outperforms the traditional OLS method under these simulated conditions and that air quality matters irrespective of the method used.

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    Bibliographic Info

    Article provided by Southern Economic Association in its journal Southern Economic Journal.

    Volume (Year): 73 (2007)
    Issue (Month): 4 (April)
    Pages: 1088–1111

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    Handle: RePEc:sej:ancoec:v:73:4:y:2007:p:1088-1111

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    Cited by:
    1. Kelley Pace, R. & LeSage, James P., 2008. "A spatial Hausman test," Economics Letters, Elsevier, vol. 101(3), pages 282-284, December.
    2. Morito Tsutsumi & Hajime Seya, 2009. "Hedonic approaches based on spatial econometrics and spatial statistics: application to evaluation of project benefits," Journal of Geographical Systems, Springer, vol. 11(4), pages 357-380, December.
    3. José-María Montero & Coro Chasco & Beatriz Larraz, 2010. "Building an environmental quality index for a big city: a spatial interpolation approach combined with a distance indicator," Journal of Geographical Systems, Springer, vol. 12(4), pages 435-459, December.
    4. Montero, José María & Larraz, Beatriz & Chasco, Coro, 2008. "Building an Environmental Quality Index for a big city: a spatial interpolation approach with DP2," MPRA Paper 10736, University Library of Munich, Germany.

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