## **Table 9. Difference in total monetary consumption per capita between the lean season and non-lean season waves for rural households, split by whether households cultivated fields in the previous agricultural season**

## _Panel A: Did not cultivate fields_

||Burkin|a Faso|Nig|er|Sen|egal|All except C|had and Mali|
|---|---|---|---|---|---|---|---|---|
||No|Full|No|Full|No|Full|No|Full|
||controls|controls|controls|controls|controls|controls|controls|controls|
|Lean season<br>wave|0.0241|-0.1871*|-0.0478|-0.0643|-0.0212|-0.0167|-0.0126|-0.0527*|
||(0.1549)|(0.0946)|(0.0826)|(0.0432)|(0.0538)|(0.0383)|(0.0519)|(0.0276)|
|N|269|255|1024|966|920|904|2213|2125|
|R-squared|0.0003|0.5862|0.0018|0.4525|0.0005|0.3924|0.0001|0.4847|

## _Panel B: Cultivated fields_

||Burkina|Faso|Ni|ger|Sen|egal|All except Ch|ad and Mali|
|---|---|---|---|---|---|---|---|---|
||No controls|Full<br>controls|No<br>controls|Full<br>controls|No controls|Full<br>controls|No controls|Full<br>controls|
|Lean season<br>wave|-0.2001***|-0.1959***|-0.0841**|-0.0994***|-0.1086***|-0.1095***|-0.1310***|-0.1416***|
||(0.0429)|(0.0335)|(0.0325)|(0.0253)|(0.0381)|(0.0258)|(0.0253)|(0.0177)|
|N|3594|3547|3423|3393|2294|2290|9311|9230|
|R-squared|0.0334|0.3490|0.0084|0.3213|0.0129|0.3859|0.0160|0.3858|

Note: * p<0.10, ** p<0.05, *** p<0.01. Standard errors clustered at the ‘grappe’ level in parentheses. Sample restricted to rural households. Dependent variable is the log of total monetary consumption per capita. Individuallevel 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 region fixed effects. Source: EHCVM and World Bank estimates.

# 5.3. Differences by household head’s income-generating strategies

Even though welfare losses appear to be concentrated among rural, agricultural households, having household heads working outside of agriculture does not appear to guarantee avoiding the effects of the lean season. To verify this, we split the sample according to the main occupation of the household head and re-estimate Equation 1 for each sub-sample with the log of real per capita consumption as the dependent variable. While the coefficient on the lean season dummy variable is larger for households where the head primarily engages in agriculture or in livestock/fishing it is still signed negatively even when the household head is primarily engaged in industry/construction or in services/other sectors (Table 10). These effects in households where the head is engaged in industry/construction or in services/other sectors are only statistically significant at the 5 percent level in the specifications that include full controls, although we prefer these specifications here given the sample splits applied; the controls may help to address observed sample selection. These results may arise because, even if the household head engages in non-agricultural work, they may have secondary activities linked to agriculture, or other household members may engage in agriculture as their primary or secondary activity too. Using the household head’s occupation alone to determine who faces the effects of seasonality may therefore be misleading.

21