Setting out this approach has also highlighted four areas of measurement work that would benefit a global measure of vulnerability. First, generating global spatially disaggregated measures of poverty. This work has used administrative data, but there is room to experiment with how to disaggregate further. Second, further innovations on the method used to overlay dimensions from different data sources. A simple method was used for social protection and financial inclusion data, but further work could be undertaken on this to implement survey to survey methods across a wider range of dimensions of vulnerability. Third, developing a method to impute and line-up estimates of non-monetary vulnerability as is done for the income measure using methods developed for the global poverty measurement work. Finally, we have relied on historical datasets to define the probabilities of extreme events. As such this analysis provides a picture of who is vulnerable today. In order to say something about the future, the impact of a changing climate on the risk faced will need to be taken into account (see Baquie and Foucault, 2023).

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