Juan Aristizábal (p), Gustavo García

Elias Oikarinen

Air pollution has important negative effects on several socioeconomic variables (Sunyer, et al., 2015; He, Liu, and Salvo, 2019; Wei, et al., 2022) and is one of the main problems for homeowners in urban areas (EEA, 2000). Research on the effects of air pollution on the housing market is based on the theoretical hedonic price model proposed by Rosen (1974). In this study, we use this model as a starting point, but propose an extension that incorporates a combination of objective and subjective measures of air quality. The idea is that the rationality of households in making housing choices is limited by lack of information, errors in judgment, or information processing capacity, so that housing decisions are subject to perceptions of place (Simon, 1997; Berezansky, et al., 2010). In addition, the literature highlights the existence of a “neighborhood halo effect” or subjective immunity, which is understood as a positive evaluation of environmental air quality regardless of the actual pollution levels (Brody, et al., 2004). Based on this augmented hedonic price model, we apply it to the rental housing market in Medellín (Colombia). Using dwelling level data, we estimate endogenous spatial hedonic models that include a measure that combines objective and subjective variables of air quality. Empirical evidence on spatial hedonic estimation and the joint inclusion of objective and subjective indicators of air quality is very limited and inconclusive, even for developed countries (see, for instance, Chasco and Le Gallo (2015) and Montero, et al., (2017)). Therefore, this study contributes to the theoretical and empirical analysis of the impact of air quality on the rental housing market, including objective and subjective indicators in the analysis. To the best of our knowledge, this is the first study to include the role of air quality perceptions along with objective measures in a theoretical hedonic price model and to provide empirical evidence on the impact of air pollution on the housing market in the context of a city in a developing country.

Tommaso Piseddu (p)

Juan Aristizábal

The increase in number and intensity of natural disasters observed in the last years and expected to progress in the coming ones has recently attracted the focus and the attention from financial actors and regulators for the negative impacts that these could have on assets' values. The cascading effects on financial markets through a value decrease due to substantial damages to the real estate sector risk to generate negative spillovers throughout the entire economy. Some real estate assets in many parts of Europe are already known for being particularly exposed to these risks and, consistent to the economic theory, their prices should reflect this awareness.

This paper aims at investigating to what extent physical climate risk, here considered in the form of riverine floods, is reflected in the prices of the real estate assets that were exchanged in Stockholm during the 2013 - 2018 period. The identification of the assets that are exposed to extreme flood risk in northern Stockholm is performed by using maps that the Swedish Civil Contingency Agency (MSB) made available, for free, on its website in 2013. If this information is accounted for during the settlement of the prices, these should be found to be significantly lower for the buildings exposed at risk. The research is carried out through a hierarchical Bayesian approach which allows to account for the spatial and the temporal structures of the dataset. In particular, spatial random effects are introduced and modeled through an Intrinsic Conditional Auto-Regressive model (ICAR). A competition process may be in place among assets that are located close to each other, determining the presence of a spatial structure that a frequentist spatial econometrics approach may fail to account for and produce spatially auto-correlated residuals. The potential effect of being exposed to flood risk is assessed by controlling for other factors that are considered to be determinants of the final price, such as the number of the rooms and the energy rating.

The findings of this paper may question the assumption of the Efficient Market Hypothesis, that all the available information is reflected in the prices if the actors are fully rational and raise a warning about the lack of attention to some forms of climate risk that the real estate sector has overlooked.

Magdalena Szczepańska (p), Anna Gałecka-Drozda, Agnieszka Wilkaniec

Tommaso Piseddu

Awareness of the need for human contact with greenery is growing. Green areas positively affect our health. It applies in particular to greenery in a direct neighbourhood of the housings. When it comes to new housing investments, greenery is an important element of marketing, but during research it occurred that its quality is low. At the same time the residents can’t fulfill their needs to be surrounded by nature. Both when spending time in greenery outside near flat on recreation and while viewing nature from windows.
Thesis of our study is that even expensive flats do not necessarily have an access to good quality greenery, as the price isn’t the factor that makes an estate greener. Residents are excluded from close and direct contact with good quality greenery. We analysed new housing estates in Poznan, one of the biggest cities in Poland. The research included two stages. The first stage was to assess greenery quality according to developed factors, based on data about: 1) area of the greenery in comparison with the area covered by hardscapes within the site; 2) pre-existing greenery inventories; 3) new greenery inventories; 4) green area functions and accessibility. In the second stage of the research we compared data about greenery quality with information concerning economic value of the statistic flat in the estate.
The research showed that greenery is not a factor which affects price. The quality of the greenery in the new estates is on a similar level notwithstanding the price. Initial potential of the site resulting from pre-existing greenery is not used by developers as most of the trees are removed. Developers do not take actual actions in the field of environmental compensation. What leads to lowering the quality of greenery, public space and living conditions in the city.

Elias Oikarinen (p), Steven C. Bourassa, Martin Hoesli, Janne Engblom

Magdalena Szczepańska

This study contributes to the analysis of the relationship between house prices and income and regional heterogeneity in this relationship in several ways. We consider a standard spatial equilibrium model and conduct an empirical analysis that examines whether results using panel data from the 70 largest U.S. MSAs are in line with that model’s predictions – which they are. In line with the spatial equilibrium model, our empirical findings indicate that regional house price-income ratios are typically not stable even over the long run. In contrast, panel regression models that relate house prices to aggregate personal income and allow for regional heterogeneity yield stationary long-term relationships in most areas. The house price-income relationship varies significantly across locations, underscoring the importance of using estimation techniques that allow for spatial heterogeneity. The substantial regional differences are closely related to the elasticity of housing supply. Our analysis thus supports the argument that local supply constraints are related to greater increases in regional house prices relative to incomes, thereby generating a counterforce for regional growth through adverse effects on the affordability of housing (while on the other hand supporting wealth accumulation). Furthermore, we illustrate how the panel level cointegration, or unit root, tests can lead to misleading conclusions regarding the nature of the regional house price-income relationships.