Flooding the Market

Horn, D. and McShane, M., 2013, Flooding the Market, Nature Climate Change, November Issue, 3:11, pp. 945-947

Posted: 8 Nov 2013  

Diane Horn

University of London - Birkbeck College

Michael K. McShane

Old Dominion University

Date Written: November 7, 2013

Abstract

A flood insurance market with risk-based prices in the UK will only stimulate climate change adaptation if it is part of a wider strategy that includes land-use planning, building regulations and water management.

The exposure and vulnerability of economic assets and the magnitude of losses are increasing as the climate changes and population and property values in flood hazard areas increase. Many countries are grappling with how best to cope with financial losses from floods, with insurance often mentioned as a key adaptation measure. Flood insurance can discourage development in flood-prone areas by charging risk-based rates or by restricting availability of cover. In addition, flood insurance pricing can provide financial incentives to encourage policyholders to increase the flood resilience of their property. A new flood insurance scheme, Flood Re, is being negotiated between the Association of British Insurers (ABI) and the UK government. The scheme has no precedents and is likely to attract attention once in place, but the proposed structure is quite complex. The scientific community will need to understand how Flood Re works before they can start investigating the role it will play, if any, in encouraging adaptation to climate change.

Keywords: Flood Insurance

JEL Classification: N50

Suggested Citation

Horn, Diane and McShane, Michael K., Flooding the Market (November 7, 2013). Horn, D. and McShane, M., 2013, Flooding the Market, Nature Climate Change, November Issue, 3:11, pp. 945-947. Available at SSRN: https://ssrn.com/abstract=2351253

Diane Horn (Contact Author)

University of London - Birkbeck College ( email )

Michael K. McShane

Old Dominion University ( email )

Norfolk, VA 23529-0222
United States

Paper statistics

Abstract Views
510