Testing the Waters: A Spatial Econometric Pricing Model of Different Waterfront Views

David Wyman, Norman Hutchison, Piyush Tiwari

    Research output: Contribution to journalArticle

    9 Citations (Scopus)

    Abstract

    This study contrasts the pricing of waterfront view amenities in a South Carolina lakefront community between the bubble and the post-bubble phases of the real estate cycle. Testing for spatial autocorrelation reveals the asymmetrical operation of spatial processes between the two periods. We find that empirical results for quality of view, view aspect orientation, and origin of buyer are affected by the recent recession. Specifically, prices for non-premium view properties suffer disproportionately. These results are confirmed by the construction of a spatial error model that provides an improved fit compared to a standard OLS spatial model.
    Original languageEnglish
    Pages (from-to)363-382
    Number of pages20
    JournalJournal of Real Estate Research
    Volume36
    Issue number3
    Publication statusPublished - Jul 2014

    Fingerprint

    Testing
    Bubble
    Spatial econometrics
    Water
    Spatial model
    Recession
    Empirical results
    Spatial autocorrelation
    Amenities
    Buyers
    Real estate
    Pricing

    Keywords

    • waterfront development
    • econometrics
    • CAPM
    • recessions

    Cite this

    Testing the Waters : A Spatial Econometric Pricing Model of Different Waterfront Views. / Wyman, David; Hutchison, Norman; Tiwari, Piyush.

    In: Journal of Real Estate Research, Vol. 36, No. 3, 07.2014, p. 363-382.

    Research output: Contribution to journalArticle

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    abstract = "This study contrasts the pricing of waterfront view amenities in a South Carolina lakefront community between the bubble and the post-bubble phases of the real estate cycle. Testing for spatial autocorrelation reveals the asymmetrical operation of spatial processes between the two periods. We find that empirical results for quality of view, view aspect orientation, and origin of buyer are affected by the recent recession. Specifically, prices for non-premium view properties suffer disproportionately. These results are confirmed by the construction of a spatial error model that provides an improved fit compared to a standard OLS spatial model.",
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