Water label under credit restrictions
Understanding the relation between banking and the water label on flood risk price integration
K.C. van den Berg (TU Delft - Technology, Policy and Management)
T. Filatova – Graduation committee member (TU Delft - Technology, Policy and Management)
T. Chatzivasileiadis – Graduation committee member (TU Delft - Technology, Policy and Management)
O. Kammouh – Graduation committee member (TU Delft - Technology, Policy and Management)
A. Mutlu – Mentor (TU Delft - Technology, Policy and Management)
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Abstract
Many homes in the Netherlands are currently at risk of flooding, increasing the likelihood of defaulting among homeowners if such an event were to occur, while adaptations are also difficult to purchase due to their high costs. Homeowners and buyers are currently unaware of these risks, with the water label and climate banking aiming to address them. The water label will help inform the buyer, while climate banking can assist in paying for flood adaptations if there is a sufficient increase in value. Under increasing demand, the water label helps integrate flood risk into pricing; however, it is possible that once credit restrictions become significant, demand instead causes the opposite reaction, significantly slowing the integration of risk due to increasingly stringent credit restrictions. Climate banking solves this issue, with the interest rate increases reducing these maximum mortgage and loan-to-value (LTV) ratios, instead using these restrictions to reduce the overall price of the risky homes. It is therefore recommended to adopt both policies in tandem, to increase the speed of pricing integration in for example the Randstad, the area which is also most at risk of floods. The most important finding is related to the impact of lower income groups, which due to larger competition in their section of the market are more credit reliant, leading to higher LTV ratios. At the same time these groups are led towards the unsafe homes, causing an increase of credit risk in an already vulnerable category. It is therefore recommended that they are assisted in moving out of these unsafe homes and are given subsidies to improve access to adaptation measures. These can be done in conjunction with more stringent LTV caps on risky homes, reducing overall risk. Moreover, even if banks are slow to adopt these new credit management practices, it will have minimal actual effect on the integration speed. It is therefore recommended to focus on improving data quality rather than on data availability. Finally, it may be possible that these measures might create sufficient fiscal space to fund flood adaptation, especially in areas with higher demand.