Abstract :
[en] In line with the No Net Land Take (NNLT) doctrine from the European Commission (2011, p. 19), the Walloon Government (2019, pp. 46, 99) aims to limit land artificialization, while presenting significant ambitions concerning housing production to meet increasing demand.
However, experiences from European countries implementing compact city concepts for years shows a trend to liberalization of housing market. This, combined with land restrictions measures, exacerbate the pre-existing issues of housing affordability, such as property access, social exclusion, spatial segregation and spatial injustices (Bibby et al., 2020; Cavicchia, 2021).
Therefore and to ultimately develop effective policies, understanding current dynamics appears to be crucial. This requires, among other things, a detailed mapping of land values, enabling us to establish the respective shares of land and real estate values in the increase in housing prices, and to objectively assess, on the basis of the availability of developable land, whether or not a reduction in land supply has led to an increase in land values, and whether a further restriction in supply could yield similar outcomes.
Employing Multiscale Geographically Weighted Regression (MGWR) (Oshan et al., 2019), we model real estate and residential land prices across Belgium using 2008-2019 sales data. Initial findings will demonstrate MGWR's effectiveness in addressing heterogeneity and spatial segmentation in real estate markets, compared to traditional models. The methods used to distinguish land value from real estate value and to model the impact of land supply restrictions on prices will also be discussed.
Cavicchia, R. (2021). Are Green, dense cities more inclusive? Densification and housing accessibility in Oslo. Local Environment, 26(10), 1250–1266. https://doi.org/10.1080/13549839.2021.1973394.
Commission européenne. 2011. Feuille de route pour une Europe efficace dans l'utilisation des ressources, Bruxelles.
Gouvernement wallon. 2019. Schéma de Développement du Territoire. Une stratégie territoriale pour la Wallonie, Version rectificative du 14 mai 2019.
Oshan, T. M., Li, Z., Kang, W., Wolf, L. J., & Stewart Fotheringham, A. (2019). MGWR: A python implementation of multiscale geographically weighted regression for investigating process spatial heterogeneity and scale. ISPRS International Journal of Geo-Information, 8(6), 269. https://doi.org/10.3390/ijgi8060269.
