Dealing with Data at Various Spatial Scales and Supports: An Application on Traffic Noise and Air Pollution Effects on Housing Prices with Multilevel Models

Julie Gallo () and Coro Chasco Yrigoyen
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Julie Gallo: Université de Franche-Comté

Chapter Chapter 14 in Defining the Spatial Scale in Modern Regional Analysis, 2012, pp 281-309 from Springer

Abstract: Abstract In empirical studies dealing with spatial data, researchers are frequently confronted with data available at different spatial scales. For instance, hedonic models on housing prices usually combine individual data pertaining to the price and structural characteristics of the dwelling and socio-economic neighbourhood characteristics that are available at some upper administrative levels. Another frequent issue is the change of support problem or misaligned regression problem (Gotway and Young 2002; Banerjee et al. 2004) when there is a spatial mismatch between the spatial supports of the variables. For instance, the measurement of air quality is based on regular sampling at a few stations in an area whereas socio-economic data are available for aggregate administrative.

Keywords: Housing Price; Census Tract; Multilevel Model; Floor Area; Noise Pollution (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/978-3-642-31994-5_14

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