Using Probabilistic Models to Appraise and Decide. Ley-Borrás and Fox revenues. While some work has been done on the macroeconomic impacts of natural catastrophes (e.g., Rose, 2007), there has been limited progress on applying this to governments. Recent initiatives have attempted to link estimates of government emergency loss requirements to direct physical damage estimates (e.g., see the Pacific Catastrophe Risk Assessment and Financing Initiative –PCRAFI–).

Since 1996 and the creation of its National Fund for Natural Disasters (Fondo Nacional de Desastres Naturales, FONDEN), the Mexican government has sought to implement an innovative sovereign disaster risk financing and insurance strategy, relying on a blend of risk‐retention and risk‐transfer instruments. A core part of this initiative is a probabilistic catastrophe risk assessment platform developed to estimate the government's contingent liability called R‐FONDEN. The model takes as input a detailed exposure database (including details of buildings, roads, and other public assets) and produces as outputs risk metrics including AAL and PMLs. This model is currently used by the Ministry of Finance, in combination with actuarial analysis of historic loss data, to monitor the disaster risk exposure of FONDEN's portfolio and to design disaster risk transfer strategies. One example of the value of R‐FONDEN in the SDRFI decision‐making process was in helping to inform the design of the second catastrophe bond issued to protect FONDEN from earthquake and hurricane risk in Mexico (MultiCat 2009 and later MultiCat 2012 with an even larger coverage area).

In order for the SDRFI evaluation process to be undertaken in a consistent way across territories, it requires consistent inputs (probabilistic risk modeling output, as defined earlier) – therefore it is imperative that all four components of a model be developed and applied for this purpose. While there are insights that decision makers can gain from the information inherent in an exposure database or hazard catalog in isolation, these would not provide the appropriate inputs into the SDRFI decision‐making process as outlined in this paper. This potentially poses challenges to its application in countries where there is limited information available to inform one or more of the risk model components; however this paper recommends that some effort must be applied to bridge these potential knowledge gaps. By way of example, in the case of a national exposure database containing individual geo‐referenced assets and their associated physical and economic characteristics not being available, efforts should be made to develop a proxy‐based alternative, perhaps at a coarser resolution – but nonetheless its existence would allow the production of preliminary risk modeling outputs.

# **2. Sovereign Disaster Risk Financing and Insurance (SDRFI)**

## **Instrumentation**

Governments have a range of sources of financing available following the occurrence of a severe natural disaster. Typically these financing sources are categorized as either ex‐post or ex‐ante instruments. In the case of ex‐post financing the instruments are not planned in advance and include budget reallocations, domestic credit, external credit, tax increases, and donor assistance. On the other hand, ex‐ante funding instruments do require advance planning and include reserve funds, budget contingencies, contingent debt facilities, and risk‐transfer mechanisms. The latter allow risk to be passed to external third parties such as national and international (re)insurance companies or the international capital markets

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