2010
DOI: 10.2139/ssrn.1783627
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Commercial and Residential Land Prices Across the United States

Abstract: We use a national dataset of land sales to construct land price indexes for 23 MSAs in the United States and for the aggregate of those MSAs. We construct the price indexes by estimating hedonic regressions with a large sample of land transactions dating back to the mid-1990s. The regressions feature a flexible method of controlling for spatial price patterns within an MSA. The resulting price indexes show a dramatic increase in both commercial and residential land prices over several years prior to their peak… Show more

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Cited by 4 publications
(1 citation statement)
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“…Indeed, it is relatively easy to find information about the weights of the main locational attributes since they "are indeed capitalised in land values" (Kauko, 2003, p. 253). Accordingly, a rough estimation of the overall weight of locational features can be inferred by the ratio between the land value and the market value of a property (Davis & Heathcote, 2007;Davis & Palumbo, 2008;Oliner et al, 2010), a parameter that has been called "land leverage" (Bostic et al, 2007, p. 184). Equally, the weights of primary structural attributes can be approximated referring to cost data, namely, based on the construction costs of the building components (Davis & Heathcote, 2007;French & Gabrielli, 2007;Davis & Palumbo, 2008).…”
Section: Conceptual Frameworkmentioning
confidence: 99%
“…Indeed, it is relatively easy to find information about the weights of the main locational attributes since they "are indeed capitalised in land values" (Kauko, 2003, p. 253). Accordingly, a rough estimation of the overall weight of locational features can be inferred by the ratio between the land value and the market value of a property (Davis & Heathcote, 2007;Davis & Palumbo, 2008;Oliner et al, 2010), a parameter that has been called "land leverage" (Bostic et al, 2007, p. 184). Equally, the weights of primary structural attributes can be approximated referring to cost data, namely, based on the construction costs of the building components (Davis & Heathcote, 2007;French & Gabrielli, 2007;Davis & Palumbo, 2008).…”
Section: Conceptual Frameworkmentioning
confidence: 99%