# **1 Introduction**

Despite a slow decline in the poverty rate over the last decades, the number of poor continues to rise in Sub-Saharan Africa. Although the poverty rate has declined from 56% in 1990 to 40% in 2018, this progress has not been sufficient to keep up with population growth: it was estimated that 433 million Africans lived in extreme poverty in 2018, against 284 million in 1990.<sup>1</sup> Considering a higher poverty line (i.e. US$ 5.50 a day) reveals an even more fragile situation, with a poverty rate remaining almost constant and a doubling of the number of poor during the same period. These trends indicate that a large share of the population remains highly vulnerable to poverty and that the modest progress observed in terms of extreme poverty reduction could easily be reversed in the face of adverse shocks. Looking forward, climate change is expected to further exacerbate weather-related shocks and climate variability, which could worsen the current situation, especially in rural areas that concentrate 82% of the people living in extreme poverty in Sub-Saharan Africa and where livelihood means are heavily reliant on weather conditions (Beegle and Christiaensen, 2019).

There is already ample evidence on the impact of weather shocks on households’ consumption in Africa, not only in terms of short-term fluctuations but also for long-term consumption growth due to the lack of insurance and the adoption of adverse coping strategies (Baez et al., 2020; Dercon, 2004). Some studies have specifically focused on food consumption and found that rainfall variability had a significant impact (Demeke et al., 2011; Huho and Mugalavai, 2010; Lewis, 2017), identifying climate as a clear threat to the achievement of the second Sustainable Development Goal (SDG) of zero hunger. Most of those studies employ panel methods to quantify the impacts of specific events on poverty outcomes. However, to the best of our knowledge, no study has further exploited these results with the objective of effectively predicting the welfare impacts of weather shocks at sub-national levels. This is mainly due to data limitations for investigating a highly complex and heterogeneous relationship between environmental conditions and welfare. Moreover, it is now well-established that both idiosyncratic and covariate shocks, including weather shocks, induce some degree of inter-temporal variability in households’ welfare and measuring poverty at one point in time can be misleading; the non-poor today may be the poor of tomorrow (Hill and Porter, 2017; Skoufias et al., 2021). As a result, another strand of literature has moved the focus away from event-specific impacts to grasp a broader understanding of welfare volatility by developing methods for quantifying the risk of being poor, usually referred to as “vulnerability to poverty”<sup>2</sup> (see Gallardo

> 1Source: World Bank, World Development Indicators and World Bank (2020).

> 2In this paper, we revise the concept of vulnerability and provide a definition that is consistent with the notion of vulnerability used in catastrophe risk models. We define vulnerability at the household-level as the relationship between rainy season conditions and food consumption in the following lean season.

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