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dc.contributor.authorLonghofer, Stanley D.
dc.contributor.authorRedfearn, Christian L.
dc.date.accessioned2022-11-14T17:35:47Z
dc.date.available2022-11-14T17:35:47Z
dc.date.issued2022-10-29
dc.identifier.citationLonghofer, S. D., & Redfearn, C. L. (2022). Estimating land values using residential sales data. Journal of Housing Economics, 101869. https://doi.org/https://doi.org/10.1016/j.jhe.2022.101869
dc.identifier.issn1051-1377
dc.identifier.urihttps://doi.org/10.1016/j.jhe.2022.101869
dc.identifier.urihttps://soar.wichita.edu/handle/10057/24209
dc.descriptionClick on the DOI to access this article (may not be free).
dc.description.abstractLand prices are at the heart of urban economics but are generally not observed directly. Though they are central to household and firm location choices, land-only sales in urban areas are rare and often outliers. Indeed, urban areas are in part defined by a largely contiguous area of high land-use intensity – those places in which developable land is scarce. In this paper, we make use of more-common market data to infer land prices: house sales. Using locally weighted regressions, we estimate the value of a standardized structure across two urban counties: Maricopa, Arizona and Sedgwick, Kansas. Because the value of the standardized structure should be invariant across different locations in a metropolitan area, any remaining variation in the value surface should reflect differences in land values. By pinning down this surface using vacant lot sales at the periphery, we are able to extract land values throughout the metropolitan area, even in locations where vacant land sales are rare.
dc.language.isoen_US
dc.publisherElsevier
dc.relation.ispartofseriesJournal of Housing Economics
dc.relation.ispartofseries2022
dc.subjectLand values
dc.subjectLocally weighted regressions
dc.titleEstimating land values using residential sales data
dc.typeArticle
dc.rights.holder© 2022 Elsevier Inc. All rights reserved.


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