Search results for "housing demand"
showing 5 items of 5 documents
Nature et impacts des effets spatiaux sur les valeurs immobilières : le cas de l'espace urbanisé francilien
2013
International audience
NEIGHBORHOOD EFFECTS IN SPATIAL HOUSING VALUE MODELS. THE CASE OF THE METROPOLITAN AREA OF PARIS (1999)
2009
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: social capital, social status and social externalities and consider the accessibility to the primary economic center as describing the urban spatial trend. Using spatial econometrics specifications of the hedonic equation, we estimate whether spatial effects impact the housing values. Our empirical case concerns the Metropolitan Area (MA) of Paris i…
Spatial effects of urban public policies on housing values
2009
International audience; Problems of spatial segregation have often stressed on the social status and social capital of a neighbourhood as main driving forces behind housing price formation. In this paper, it is assumed that spatial effects are additional variables worth considering since the impact of urban policies such as social housing policies and urban regeneration policies may permeate outside the areas where they are implemented. Our case study is of the urban area of Dijon (France), where these two types of urban policies have been implemented in the last three decades. Spatial effects are introduced in the hedonic model and a spatial error model is estimated, revealing a positive a…
Environmental spillovers and their impacts on housing prices: A spatial hedonic analysis
2015
This paper investigates the spatial dimension of environmental factors on housing prices. We develop spatial hedonic models to estimate the implicit prices of various environmental attributes. The spatial dimension can be interpreted in terms of local or global spillovers. We conduct an empirical study in the Loire estuary (France). We focus on natural areas and more artificialized ones (ocean frontage, wetlands, rivers, and noisy roads). We show that, depending on the spatial model used, the implicit price is more than just the estimated coefficient value and combines both a feedback effect and a propagation effect.
Qualitative analysis of housing demand using Google trends data
2019
Big data analytics often refer to the breakdown of huge amounts of data into a more readable and useful format. This study utilises Google Trends big data as a proxy for an analysis of housing demand. We employ a qualitative method (fuzzy set/Qualitative Comparative Analysis, fsQCA), instead of a quantitative method, for our estimate and forecast. The empirical results show that fsQCA successfully forecasts seasonal time series, even though the dataset is small in size. Our findings fill the gap in the qualitative and time series forecasting literature, and the forecasting procedure herein also offers a good standard for industry.