Annals of Economics and Statistics (2018), n°130, juin 2018, pp. 39-68
Présentation (FED) : Cet article estime les préférences des acheteurs pour les attributs de logement et les caractéristiques du quartier comme le bruit, la criminalité, la qualité de l'école, la distance des emplois, en utilisant la méthode des prix hédonistes. Les résultats, estimés sur le quartier Montmartre de Paris, montrent un consentement à payer marginal significativement positif pour l'accessibilité au travail et la qualité de l'école, et un consentement à payer marginal négatif pour un taux de criminalité plus élevé dans la région. Par contraste, le niveau de bruit ou l’accessibilité des transports en commun ont moins d’influence sur les prix des logements.
Abstract (authors) : This paper estimates buyers' preferences for dwelling attributes and neighbourhood characteristics. The collected data allows for the simultaneous consideration of a wide range of intrinsic characteristics, such as surface, floor, etc., and neighbourhood characteristics, including noise, crime, school quality, distance to jobs, etc. The marginal willingness to pay is identified from transaction data under the assumptions of the hedonic model described by Rosen (1974). We use very local fixed effects combined when possible with administrative boundaries as geographical discontinuities to isolate the effect of each amenity. Estimation is achieved by using flexible semi-parametric methods. Characteristics explain more than 90% of the variance of dwelling prices, showing a significant positive marginal willingness to pay for job accessibility and school quality, and a negative marginal willingness to pay for a higher crime rate in the area. By contrast, noise level or public transport accessibility have less influence on housing prices. These results are robust to the inclusion of census tract fixed-effects, which also drastically reduces the spatial correlation of the residual prices.
Lien : https://www.jstor.org/stable/10.15609/annaeconstat2009.130.0039#metadata_info_tab_contents