Urban quality of life (QOL) is usually measured through an index defined as the estimated value of a set of urban amenities. However there is an increasing awareness that omitted variables might seriously undermine the method's ability to accurately estimate QOL. Here we extend the hedonic approach using a multivariate geostatistical model to address the omitted variable bias by identifying the latent common factors responsible for the spatial distribution of the amenities. A new QOL index is then defined as a function of the latent factors whose implicit prices are estimated through hedonic regressions. Our methodology is shown on a data set of individual-level property transactions from the city of Vicenza. As a result we obtain the spatial distribution of QOL calculated according to the new index.

Measuring urban quality of life using multivariate geostatistical models

FERRARI, Clarissa;MINOZZO, Marco
2011

Abstract

Urban quality of life (QOL) is usually measured through an index defined as the estimated value of a set of urban amenities. However there is an increasing awareness that omitted variables might seriously undermine the method's ability to accurately estimate QOL. Here we extend the hedonic approach using a multivariate geostatistical model to address the omitted variable bias by identifying the latent common factors responsible for the spatial distribution of the amenities. A new QOL index is then defined as a function of the latent factors whose implicit prices are estimated through hedonic regressions. Our methodology is shown on a data set of individual-level property transactions from the city of Vicenza. As a result we obtain the spatial distribution of QOL calculated according to the new index.
9788896025123
Hedonic prices; Housing market; Monte Carlo EM algorithm; Spatial factor model
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/385452
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