Design and assessment of pro-poor financial soft policies for expanding cities. (1st February 2023)

• Record Type: Journal Article
• Authors: Wang, Chenbo; Cremen, Gemma; Gentile, Roberto; Galasso, Carmine
• Is Part Of: International journal of disaster risk reduction. Volume 85(2023)
• Publication Date: 2023-02-01
• Subjects: Financial soft policies -- Pro-poor -- Decision support environment -- Urban expansion -- Natural-hazard risk; Emergency management -- Periodicals; Risk management -- Periodicals; Disaster relief -- Periodicals; Hazard mitigation -- Periodicals; 363.34
• DOI: 10.1016/j.ijdrr.2022.103500
• Languages: English
• ISSNs: 2212-4209

Abstract

Abstract: Recent major earthquake disasters have highlighted the effectiveness of financial soft policies (e.g., earthquake insurance) in transferring seismic risk away from those directly impacted and complementing 'hard' disaster risk mitigation measures (e.g., structural retrofit). However, the benefits of existing financial soft policies are often not guaranteed. This may be attributed to: (1) their low penetration rate (e.g., in the case of earthquake insurance); (2) the fact that they typically neglect the explicit needs of low-income sectors in (developed and developing) modern societies, who are often disproportionately impacted by natural-hazard driven disasters; and/or (3) their failure to consider the time-dependent nature of urban exposure. We contribute towards addressing these shortcomings by proposing a flexible framework for designing and assessing bespoke, people-centred, household-level, compulsory financial soft policies (including conventional earthquake insurance, disaster relief fund schemes, income-based tax relief schemes, or a combination of these) across cities under rapid urban expansion. The proposed framework leverages the Tomorrow's Cities Decision Support Environment, which aims to facilitate pro-poor disaster-risk-informed urban planning and design in developing country contexts. The framework specifically enables decision makers to strategically design and then assess the pro-poorness of mandatory soft policies, using financial impact metrics that discriminate losses on the basis of income. We showcase the framework using the hypothetical expanding city, "Tomorrowville", successfully identifying pro-poor seismic-risk-related financial soft policies for different instances in the lifetime of the urban system.