Attitudes to systemic risk: The impact of flood risk on the housing market in Dublin

Salem S. Gharbia, Owen Naughton, Vincent Farrelly, Ronan Lyons, Francesco Pilla
2016 2016 18th Mediterranean Electrotechnical Conference (MELECON)  
The concatenated effects of increased frequency of intense precipitations due to climate change and anthropogenic impacts in the form of construction in floodplains, channel straightening and increased presence of impermeable surfaces are increasing the incidence of floods in urban areas. This paper investigates behavioral responses to a natural hazard (flooding) by examining residential property values. The results of this investigation can be used to develop benefit/cost studies to assess the
more » ... economic merits of policies that mitigates the risk of floods by using the residential housing market as a proxy for estimating these values since the choice of where to live often includes the choice of hazard level. The methodology described here also provides a mechanism for testing consumer behavior under uncertainty. This study uses a hedonic property price function to estimate the effects of flood hazards on residential property values. The study utilizes data from 158,890 residential home sales in Dublin, Ireland between 2006 and 2015. This area experienced significant flooding in October 2011. GIS is used to spatially characterize the houses included in the analysis by linking them to the following set of parameters included into the baseline regression: house price, house type and size (number of bedrooms and bathrooms), when it was on the market, and its location. Once the baseline regression model is built, then the variables included in it are regressed against the flood-risk. The distance between a set of amenities and the properties is also calculated using GIS. Results show that a house located within a floodplain has a lower market value than an equivalent house located outside the floodplain. Finally, the benefits resulting from the use of GIS-based spatial indicators of properties in hedonic regression models to quantify the accessibility to amenities as network travel distances are also demonstrated.
doi:10.1109/melcon.2016.7495471 fatcat:eoaxb6vwbfd27j34g4l3ekaw4m