Risk to Residential Property Values from Climate Change-Related Flooding Hazards: A Mixed Methods Approach
71 Pages Posted: 27 Dec 2019
Date Written: November 16, 2019
Greater South Dunedin (GSD) has been identified as one of the most vulnerable areas to Climate Change-Related Flooding Hazards (CCRFH) in New Zealand, yet little is known about the magnitude of how CCRFH will impact property values. We address this issue by proposing a novel modelling strategy that links CCRFH, and in particular Sea Level Rise (SLR), to of residential property value, at fine geographical resolution. The strategy is both empirical and forward looking modelling. The empirical analysis reveals a significant negative price effect for houses associated with flooding risks in the local market (between 5.9% and 3.1%), which existed prior to the June 2015 South Dunedin flood and was exacerbated temporarily after this event. The forward modelling projections apply a “bathtub fill” approach to elevation data in a Geographical Information System (GIS) to identify the properties that will be inundated (using IPCC scenarios to 2100). Uncertainties arising from data error and long-term projection are modelled through Monte Carlo simulation. We find that, the risks of permanent inundation are currently limited and only become non-negligible in a “business-as-usual” pathway. The risks of periodic flooding, however, are strikingly large across all scenarios in the presence of extreme events. With high tides, the number of inundated properties may be as high as 39%. With extreme rainfalls, this number potentially increases to 41%. Taken together, CCFRH may affect property worth up to NZ$ 983 million in rateable value (37% of GSD property market). We conclude by acknowledging the limitations of our “bathtub fill” approach.
Keywords: Climate Change; Real Estate Valuation; Sea Level Rise; Flooding; Geographical Information Systems (GIS); Stranded Assets; Monte Carlo Simulation; Matching Estimators
JEL Classification: G17; Q51; Q54; R30; R32
Suggested Citation: Suggested Citation