revealed the limits of using standardized data sets in seeking to understand the heterogeneity of drought impacts across household types.

We find that consumption is reduced by 10-20 percent in the worst weather observations in our surveys (corresponding to about a 1 in 10-year drought event). We use the estimated vulnerability functions and the full hazard distribution in each household location to calculate the cost drought poses to welfare outcomes. The results indicate that risk is large. Poverty is 1–12 percent higher under the worst weather conditions relative to the best conditions observed in the last 13 years. This amounts to an increase in the total national poverty gap that ranges from US$4 million to US$2.4 billion (2011 PPP) across countries. Estimates are more precise for countries with a large share of production in maize, highland and pastoral areas. Potential biases in estimating impacts mean this is likely an underestimate of the true cost.

The cost of weather shocks on welfare provides an indication of the size of the increased need that would need to be met by adaptive social protection systems or access to financial services. The cost of weather shocks on consumption could be reduced by investments in adaptation policies such as soil management and tree cover or by other adaptive farming techniques. Investments in development that enable households to switch into less rainfall-dependent economic activities, either when droughts occur or as part of broader structural transformation, would also reduce the welfare cost of drought. Further work is needed to estimate how different investments would reduce the welfare cost of drought. This type of work is needed to help prioritize investments.

Statistical analyses that rely only on observed historical data are generally limited by their short observation periods. In the context of drought risk, patterns and severity of future drought events might differ from what has been observed historically. Stochastic data sets provide a synthetic view of all events that could occur in a given year, together with their likelihood of occurring. These data sets typically allow for a more reliable analysis of drought risk, especially for events that occur less frequently. Use of a stochastic data set for Malawi showed how such an analysis can be carried out, but further work is needed to produce and use more reliable analyses of spatial and temporal correlations of drought hazard. A further extension of this work would incorporate climate trends into the analysis of welfare impacts in order to estimate the costs of longer-run welfare impacts (Baquie and Foucault 2023).

# References

ABI (Association of British Insurers). 2011. _Industry Good Practice for Catastrophe Modelling_ . London: ABI. - <u>https://www.abi.org.uk/globalassets/sitecore/files/documents/publications/public/migrated/solvency ii/industry-good-practice-for-catastrophe-modelling.pdf.</u> Angrist, J. D., and J. S. Pischke. 2009. _Mostly Harmless Econometrics_ . Princeton, NJ: Princeton University Press. Anttila-Hughes, J., and M. Sharma. 2015. “Linking Risk Models to Microeconomic Indicators.” Policy Research Working Paper 7359, World Bank, Washington, DC. <u><mark>http://hdl.handle.net/10986/22235.</mark></u> <mark>Artuc. E., G. Porto, B. Rijkers. 2023. Crops, Conflict, and Climate Change. World Bank Mimeo.</mark>

- Auffhammer, Maximilian. 2018. “Quantifying Economic Damages from Climate Change.” Journal of Economic Perspectives 32 (4): 33–52. https://doi.org/10.1257/jep.32.4.33.

- Baez, Javier E., Varun Kshirsagar, and Emmanuel Skoufias. 2019. “Adaptive Safety Nets for Rural Africa : DroughtSensitive Targeting with Sparse Data.” Policy Research Working Paper Series, Policy Research Working Paper Series, , December. https://ideas.repec.org//p/wbk/wbrwps/9071.html.

- Baquie, S., and G. Foucault. 2023. “Background Note on Bringing Climate Change into Vulnerability Analysis.” Unpublished background paper. World Bank.

- Baquie, Sandra, and Habtamu Neda Fuje. 2020. “Vulnerability to Poverty Following Extreme Weather Events in Malawi.” Policy Research Working Paper Series, Policy Research Working Paper Series, , October. https://ideas.repec.org//p/wbk/wbrwps/9435.html.

- Bates, Paul D., James Savage, Oliver Wing, Niall Quinn, Christopher Sampson, Jeffrey Neal, and Andrew Smith. 2023. “A Climate-Conditioned Catastrophe Risk Model for UK Flooding.” _European Geosciences Union_ 23 (2): 891–908. <u>https://nhess.copernicus.org/articles/23/891/2023/.</u>

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