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Statistiques spatiales et étude immobilière

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  • Batsch, Laurent

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  • Srikhum, Piyawan
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    Abstract

    Geostatistics and spatial econometrics are two spatial statistical approaches used to deal with spatial dependence. Geostatistics estimates directly the variance-covariance matrix by assuming that the covariance among observations depends inversely on the distance between their locations, called the covariogram. Spatial econometrics defines and integrates the spatial interaction matrix in a hedonic regression model. In real estate, price estimation should take into account these spatial characteristics because property prices are correlated. Hence, these two approaches are commonly used to study the spatial dependence of the real estate prices in many contexts. However, a definite rule in selection these statistic approaches has not been established. This thesis examined these two approaches in order to distinguish the similarities, differences, advantages, and disadvantages of each methodology. Some examples of their applications in a real estate study. The geostatistics is used to analyze the stationarity of the variogram and its sensitivity depending on the parameters added in hedonic estimation. The spatial econometric is used to define econometrically the real estate market dominant area.

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    File URL: http://basepub.dauphine.fr/xmlui/bitstream/123456789/10864/1/These_PiyawanSrikhum_versioncomplet.pdf
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    This book is provided by Paris Dauphine University in its series Economics Thesis from University Paris Dauphine with number 123456789/10864 and published in 2012.

    Order: http://basepub.dauphine.fr/xmlui/handle/123456789/10864
    Handle: RePEc:dau:thesis:123456789/10864

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    Related research

    Keywords: Evaluation de biens immobiliers; Quartier dominant; Non stationnarité spatiale; Econométrie spatiale;

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    1. Mats Wilhelmsson, 2000. "The Impact of Traffic Noise on the Values of Single-family Houses," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 43(6), pages 799-815.
    2. Witte, Ann D & Sumka, Howard J & Erekson, Homer, 1979. "An Estimate of a Structural Hedonic Price Model of the Housing Market: An Application of Rosen's Theory of Implicit Markets," Econometrica, Econometric Society, vol. 47(5), pages 1151-73, September.
    3. 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.
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