sources are not well diversified, especially in rural areas. Across the five countries, 55.5 percent of the population live in a household in which the main income earner engages primarily in agriculture, raising animals, or fishing. At the same time, relatively few Sahelians hold savings, and neither borrowing nor selling assets is widely used as a coping mechanism: 28.9 percent of the population live in a household in which any member held an account with a financial institution, just 16.1 percent of the population live in a household in which any member actually held savings, while livestock sales were not clearly associated with seasonality in the EHCVM sample. Despite this exposure and widespread poverty, government support for households is insufficient, with just 10.5 percent of Sahelians living in a household that received food during the 12 months prior to being interviewed, and 3.6 percent living in a household that received cash transfers.<sup>6</sup> Comparing the waves of the EHCVM data demonstrates the dramatic effects of seasonality on Sahelian households’ welfare. The share of the population living below the national poverty line in the wave corresponding to the lean season was 13.7 percentage points higher in Burkina Faso, 6.6 percentage points higher in Niger, and 8.1 percentage points higher in Senegal compared to the wave corresponding to the non-lean season. Pooling the data from these countries, mean real monetary consumption is estimated to be around 10.5 percent lower in the lean season. Controlling for region fixed effects and other household-level controls has little effect on these estimates. Moreover, this drop is concentrated in reduced consumption of staple foods (such as cereals), rather than the more ‘typical’ reduction in dietary diversity that might be observed as households try to adapt. Seasonality therefore brings about extreme forms of deprivation. Suggestive evidence also indicates that the welfare losses begin relatively early in the lean season, even as early as April.

Turning to heterogeneity, the effects of seasonality appear to be concentrated in rural households that rely on agriculture or pastoralism for their livelihoods, but other households may still be affected. Pooling the data from Burkina Faso, Niger, and Senegal, mean real monetary consumption is estimated to be about 13.5 percent lower in the lean season than the non-lean season in rural areas, a difference that is statistically significant at the 1 percent level. In urban areas, the difference is just 2.4 percent and is not statistically significant, even at the 10 percent level.<sup>7</sup> Within rural areas, it also appears that households cultivating fields are more affected by seasonality. Yet even households whose main income earners are engaged in services or industry appear to be at least partly impacted by seasonality, suggesting that leaving agriculture is not sufficient to escape the effects of seasonality fully.

The extent of seasonal swings in welfare, especially in rural areas, has clear implications for policy, and especially for Adaptive Social Protection (ASP) programs. Numerous studies have demonstrated that social safety nets boost consumption and reduce poverty.<sup>8</sup> Safety nets also help poor households to invest in productive assets and livestock holdings, diversify income-generating activities, and bolster savings. Yet despite safety nets’ demonstrated impact on poverty reduction and resilience building, their coverage is limited. Except for Mauritania and Senegal – where coverage of regular cash transfer programs reaches about 40 percent of the poor – coverage of poor households is below 10 percent in the rest of the Sahel.

> 6 In each country, the shares receiving such support are generally only slightly higher among those living below the national poverty line.

> 7 The difference between the effects of seasonality in rural and urban areas is formally tested using a regression with interaction terms. This is explained in detail in Section 2.

> 8 See, for example, Beegle, Coudouel, and Monsalve (2018).

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