**Table 6. Difference in subjective poverty between the lean and non-lean season waves**

||Burkin|a Faso|M|ali|Nig|er|Sen|egal|All exce|pt Chad|
|---|---|---|---|---|---|---|---|---|---|---|
||No<br>controls|Full<br>controls|No<br>controls|Full<br>controls|No controls|Full<br>controls|No<br>controls|Full<br>controls|No<br>controls|Full<br>controls|
|Lean season<br>wave|0.0068|-0.0004|0.0622**|0.0465**|0.0561***|0.0499***|0.0558**|0.0567***|0.0435***|0.0405***|
||(0.0253)|(0.0216)|(0.0243)|(0.0203)|(0.0214)|(0.0172)|(0.0256)|(0.0192)|(0.0133)|(0.0097)|
|N|6993|6912|6582|6550|5999|5898|7102|7057|26676|26417|
|R-squared|0.0001|0.1438|0.0046|0.1256|0.0048|0.1512|0.0031|0.1627|0.0022|0.1776|

Note: * p<0.10, ** p<0.05, *** p<0.01. Standard errors clustered at the ‘grappe’ level in parentheses. Dependent variable is a dummy variable taking 1 if a household classified itself as ‘poor’ or ‘very poor’ and 0 otherwise. Individual-level sampling weights applied. ‘Full controls’ specifications include controls for the gender, age, and education level of the household head, household size, the dependency ratio, household walls material, household roof material, household floor material, access to electricity, access to improved drinking water, and access to improved sanitation as well as an urban-rural dummy and region fixed effects. Source: EHCVM and World Bank estimates.

# Section 5. Heterogeneity

This section explores heterogeneity in the main results. First, we demonstrate that non-farm enterprise work appears to be a coping mechanism deployed by the Sahelian households during the lean season; this in itself suggests there may be heterogeneity in the results, because such opportunities outside of agriculture may not be available to everyone.<sup>25</sup> Second, we show that the negative effects of the lean season on consumption appear to be concentrated in rural areas and, specifically, among those households that cultivate fields. Third, however, we show that even when households’ main income earners work outside of agriculture that may not offer insulation from the knock-on effects of seasonality.

## 5.1. Non-farm enterprise work as a coping mechanism

Before assessing heterogeneity in the main results directly, we first consider whether typical mechanisms for coping with seasonality – which may be more widely available to certain types of households – show up in the data. It emerges that work in non-enterprise work, which households could use to bolster waning agricultural production, is indeed more prevalent in the lean season. Pooling all EHCVM countries except Chad, both household heads and all household members are about 3.6 percentage points more likely to be engaged in non-farm enterprise work in the lean season than the non-lean season (Table 7). This difference is statistically significant at (at least) the 5 percent level and is robust to the inclusion of controls. Nevertheless, altering the mix of activities in this way is unlikely to be possible for all Sahelian households. Looking across the countries, the effects are much stronger in Senegal, where household heads are as much as 5.8 percentage points more likely to engage in non-farm enterprise work in the lean season. Yet the descriptive statistics in Section 3 also demonstrate how non-agricultural activities are generally far less prevalent in rural areas; rural households may therefore struggle to find such activities when faced with the effects of the lean season.

> 25 For a detailed description of some additional income-generating activities undertaken by young people in Central Mali, see Von Der Goltz et al. (2022).

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