Development and assessment of pro-poor financial soft policies for expanding earthquake-prone urban communities - ICASP14; Galasso, Carmine; Cremen, Gemma; Wang, Chenbo; Gentile, Roberto (My University, 2023)
Recent major earthquake disasters have highlighted the effectiveness of regional financial soft policies (e.g., earthquake insurance) in transferring seismic risk away from those directly impacted and complementing 'hard' disaster risk mitigation measures such as seismic retrofitting. However, the benefits of existing regional 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 populations in 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-centered, household-level, compulsory financial soft policies related to earthquake risk (including conventional earthquake insurance, disaster relief fund schemes, income-based tax relief scheme, or a combination of these) across typical city-size regions 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 through strong local engagement that democratizes the concept of risk. The framework specifically enables decision makers to strategically design and then assess the pro-poorness of mandatory financial soft policies, using innovative financial impact metrics that discriminate earthquake-disaster losses on the basis of income. We showcase the framework using "Tomorrowville", a hypothetical expanding city that reflects a global-south urban setting in terms of its socioeconomic and physical aspects. This case-study application highlights the importance of adopting a future-focused approach in the design of financial soft policies, by revealing that the optimum (i.e., most pro-poor) soft financial policy may depend on the exact configuration of the urban system (i.e., layout of the building portfolio as well as the underlying physical and social vulnerability) that evolves in time. Policies deemed sufficiently pro-poor today will not necessarily remain pro-poor in the future, because of changes to the physical and social fabric of a given urban extent (among other factors). Stakeholders such as urban planning authorities, community representatives, and researchers can use the proposed framework for informed decision making on the design of pro-poor financial soft policies for implementation in future (as well as present) earthquake-prone urban communities.
14th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP14)
PUBLISHED