Modelling the impact of earthquake activity on real estate values: a multi-level approach

Abstract

Purpose This paper aims to explore the impact of a recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market. Design/methodology/approach The paper uses a multi-level approach within an event study framework to model changes in the pattern of house prices in Istanbul. The model allows the isolation of the effects of earthquake risk and explores the differential impact in different submarkets in two study periods – one before (2007) and one after (2012) recent earthquake activity in the Van region, which although in Eastern Turkey served to alter the perceptions of risk through the wider geographic region. Findings The analysis shows that there are variations in the size of price discounts in submarkets resulting from the differential influence of a recent earthquake activity on perceived risk of damage. The model results show that the spatial impacts of these changes are not transmitted evenly across the study area. Rather it is clear that submarkets at the cheaper end of the market have proportionately larger negative impacts on real estate values. Research limitations/implications The robustness of the models would be enhanced by the addition of further spatial levels and larger data sets. Practical implications The methods introduced in this study can be used by real estate agents, valuers and insurance companies to help them more accurately assess the likely impacts of changes in the perceived risk of earthquake activity (or other environmental events such as flooding) on the formation of house prices in different market segments. Social implications The application of these methods is intended to inform a fairer approach to setting insurance premiums and a better basis for determining policy interventions and public investment designed to mitigate potential earthquake risk. Originality/value The paper represents an attempt to develop a novel extension of the standard use of hedonic models in event studies to investigate the impact of natural disasters on real estate values. The value of the approach is that it is able to better capture the granularity of the spatial effects of environmental events than the standard approach.

Estimation and updating methods for hedonic valuation

“…To better account for spatial information in the data, the classical linear model can be extended to a hierarchical or multilevel (mixed effects) model by adding the municipality and possibly other higher-level administrative units as random intercepts in the model equation. Such models are, for example, applied by Brown and Uyar (2004), Ciuna et al (2017) and Keskin et al (2017) in the framework of hedonic price modeling. Numerous publications, such as Orford (2002), Goodman and Thibodeau (2003), Bourassa et al (2003), Case et al (2004) and Bourassa et al (2007, 2010), use related approaches in the context of market segmentation.…”

People or Systems: Does Productivity Enhancement Matter More than Energy Management in LEED Certified Buildings?

“…A multi-level model (MLM) is a widely used approach to deal with nested datasets, where variation across different clusters is assumed to be random and uncorrelated with the independent variables in the model [71]. This specification is a modified form of a hedonic pricing model since it has the same overall structure, which consists of fixed and random effects [72]. This model allows intercepts and slopes to have their own distributions across clusters, which can be summarised by a set of parameters, such as mean and variance.…”

Drivers of spatial change in urban housing submarkets

“…This includes the use of x, y co‐ordinates interacting with housing attributes (Fik et al., ; Pavlov, ) and his own use of the multi‐level modelling, again applied to Glasgow. The latter approach, he argues, can be used to reveal the changing spatial structure of the submarket system by allowing hedonic estimates to vary (estimated as random effects) at a finely grained spatial scale within submarkets and the housing market overall (see also Keskin & Watkins, ; Keskin et al., for an application to Istanbul).…”