Table 1 - uploaded by Diègo Legros
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In hedonic housing models, the spatial dimension of housing values are traditionally processed by the impact of neighborhood variables and accessibility variables. In this paper we show that spatial effects might remain once neighborhood effects and accessibility have been controlled for. We notably stress on three sides of neighborhood effects: so...
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... average density on the MA is 8,669 hab/km² and remains high compare to other Metropolitan Areas in the world. The main figures of each département are presented in the Table 1 showing some specific profiles. For example, there are more young people, more non French households, more manual workers and more social housing in Seine Saint Denis than in others départements. ...
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Citations
... Spatial fixed effects and locational variables can be introduced into the linear hedonic model, but these attributes are not always observable and can be difficult to identify. Previous studies have shown that even after adding control variables for certain locational characteristics, spatial dependence can still remain (Baumont and Legros, 2009;Pace, Barry, and Sirmans, 1998). Moreover, Anselin and Arribas-Bel (2013) demonstrate that the removal of spatial autocorrelation by spatial fixed effects may be spurious when spatial lag or spatial error dependence exists. ...
... Pace, Barry, and Sirmans (1998) review a number of spatial applications on the real estate market and conclude that employing a spatial statistical estimator provides better predictions and inferences than OLS. Baumont and Legros (2009) examine the spatial effects in housing prices in the Paris Metropolitan Area and conclude that spatial models can better control for spatial effects than a hedonic housing price model that includes neighborhood attributes. Osland (2010) demonstrates that spatial hedonic models have significantly higher explanatory power than conventional hedonic models. ...
White Bear Lake, MN, has lost a large amount of water due to excessive groundwater extraction. Using a general nested spatial hedonic pricing model, this paper identifies and evaluates the impact of water loss in the lake on lakeshore properties. In addition to providing a quantitative estimate of property value loss, the results show that the marginal loss intensifies as water level persistently declines further. The findings of this study alert emerging urban areas to the negative externalities of failing to balance the tasks of meeting increased water demand as well as achieving sustainable water use.
... Housing attributes include building quality, space arrangement, and physical characteristics such as land size, building scale, and housing year as well as attributes like having a garage/fireplace, and the number of bedrooms and bathrooms [22][23][24]. Community attributes refer to neighborhood quality in terms of socioeconomic and environmental traits such as educational opportunities [25,26], income level, ethnicity, community facilities [27], and neighborhood redevelopment plans [28]. Environmental externality effects are also included in this category, such as traffic noise [29][30][31][32][33], air quality [34][35][36][37], water quality [38,39], and greenspaces and parks [40][41][42][43][44]. Locational attributes indicate accessibility and proximity to major public facilities such as the central business district [45], commercial malls [46], road infrastructure [47], transportation stations [48], and schools [49]. ...
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This study analyses the effect of location on price of
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using GIS, with a view to providing information for property
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residential or commercial advancement. However, the study
relates variations in land prices to the prices paid by prospective
buyers in the study area.
Dans cet article, nous montrons que l’influence des facteurs spatiaux sur la formation des prix immobiliers n’est pas totalement appréhendée par des variables explicatives d’attributs des voisinages et d’accessibilité. Nous avons considéré deux catégories d’attributs susceptibles d’impliquer des effets de voisinage : le statut socioéconomique des quartiers et les politiques de mixité. Notre étude empirique porte sur l’espace urbain comprenant la ville de Paris et la petite couronne qui comprend 2 636 aires de voisinage et sur lequel nous disposons de 21 098 transactions. Des effets spatiaux sont détectés, et l’estimation du modèle hédonique spatial de Durbin fournit les effets multiplicateurs. Nous montrons que la localisation dans les quartiers favorisés valorise les appartements et que les politiques de mixité ont un effet négatif. Dans chaque cas, les effets spatiaux accentuent ces impacts.
In a series of papers, Andrew
Oswald
(1996, 1999) has argued that a major explanation of unemployment in
Oecd
countries is the increase of home-ownership. In this work, we try to test the
Oswald
Hypothesis for French employment areas. We analyse the effect of home-ownership rate and other residential status on unemployment rate. We use a generalized spatial two-stage least squares (
Gs2sls
) procedure in order to account for two forms of spatial dependence in our data (a spatial autocorrelation in the dependent variable and a spatial autocorrelation in the error terms), but also endogeneity of residential status. Our findings are in contradiction with the
Oswald
hypothesis. Indeed, all other things being equal, a high home-ownership rate is associated with a low unemployment rate.
The issue of households’ residential choices is one of the key problem areas in urban economics today. While the first monocentric models focused on households’ tradeoffs between the costs involved in location and the costs of travel between home and workplace, which was assumed to be in the economic centre of the city, more recent studies attempt to look beyond this simplifying framework and take into account current urban changes and the differences observed between European and North American towns. In particular, taking account of the role of urban and natural amenities improves the explanatory power of these theoretical urban models. Widely used in the field of environmental evaluation, the hedonic price method can provide useful responses to this urban problem. Developed by Rosen (1974), it uses household behaviours to measure the value that households place on different intrinsic and extrinsic housing characteristics, particularly natural or built amenities. Estimation of these hedonic prices must take account of the dual spatial and endogenous nature of the characteristics of housing : simple estimates by the ordinary least squares method are potentially biased. To correct this bias, the FGS2SLS method proposed by Fingleton and Le Gallo (2008) must be used, combining instrumental variables and spatial autocorrelation correction. This method is applied to the case of the town of Angers : the town centre has many historic amenities, and it is indeed a typical European example. Beyond the predominant role given to the intrinsic features of the housing, the way households value “ green” amenities such as green spaces emphasises the complexity of the Angers urban space.
This paper employs the hedonic price method to examine whether the implicit value of the greenbelt is capitalized into apartment prices in the city of Vienna, Austria. We improve the traditional model using spatial econometric techniques and compare the estimates from different spatial models, namely the spatial lag model, the spatial error model, and the spatial Durbin model (SDM). While our use of spatial models addresses the common problem of omitted variable bias, the SDM specifically allows for controlling possible nearby proximity effects (i.e., small-scale neighborhood) that are rarely included in this type of analyses. Findings indicate that distance from the greenbelt is important in explaining apartment prices in Vienna and that the greenbelt exerts a centrifugal force. The SDM is found to be the best performing model indicating the existence of small-scale neighborhood effects and presenting a solid case for the consideration of this model in valuation of green amenities.
