Tables 4.4 and 4.5 show results for pastoral and agropastoral areas respectively. The choice of hazard and functional form is influenced by in-depth work undertaken on Mauritania (Hill and Vinha 2022), one of the pastoral countries in the sample. This work highlights the importance of using Tropical Livestock Unit (TLU) ownership as a way of distinguishing between household types. It also highlights the importance of including households living in areas classified as urban, as many of these households were found to have significant TLU ownership. Also, given that especially many of the pastorals are in locations without growing season per se, the hazards are constructed over the whole rainy season. The results for pastoral areas show that poor weather impacts consumption much more strongly for households with fewer animals. Those with more animals are able to smooth their consumption in the face of poor weather. The results for agropastoralists are harder to interpret. The same pattern of worse impacts for households with fewer animals holds for agropastoralists, but weather shocks appear positive for landless households. Only results for NDVI are shown, but no measure provided sensible results. Further work, and probably additional data, are needed to better model and understand the impact of weather shocks on agropastoralist welfare in Sub-Saharan Africa, including considering cumulative impacts of rainfall losses across seasons and temperature impacts on cattle.

**Table 4.4. Results for pastoral zone in Western Africa**

|||**NDVI**<br>||**S**<br>|**oil moisture**<br>||**Tota**<br>|**l seasonal rai**<br>|**nfall**<br>|
|---|---|---|---|---|---|---|---|---|---|
||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|**(7)**|**(8)**|**(9)**|
|**No TLU**||||||||||
|Hazard|**0.069****|**0.065*****|**0.130*****|**0.120*****|0.050|0.014|0.014|0.019|0.111|
||**[2.463]**|**[2.966]**|**[3.510]**|**[2.809]**|[0.929]|[0.157]|[0.518]|[0.667]|[1.632]|
|Hazard<sup>2</sup>||0.004|**0.056***||0.079|0.022||-0.008|0.025|
|||[0.126]|**[1.832]**||[1.304]|[0.313]||[-0.227]|[0.662]|
|Hazard<sup>3</sup>|||**-0.037*****|||0.059|||**-0.049***|
||||**[-2.782]**|||[0.681]|||**[-1.659]**|
|**Few(less**|**than 2.1) TL**|**U**||||||||
|Hazard|**0.087*****|**0.065*****|**0.120*****|**0.110*****|**0.072****|**0.060**|**0.073****|**0.078****|**0.156****|
||**[2.899]**|**[3.656]**|**[4.102]**|**[2.841]**|**[2.378]**|**[1.233]**|**[2.432]**|**[2.579]**|**[2.552]**|
|Hazard<sup>2</sup>||0.024|**0.062*****||0.047|0.030||-0.013|0.005|
|||[1.049]|**[2.891]**||[1.185]|[0.506]||[-0.658]|[0.235]|
|Hazard<sup>3</sup>|||**-0.028*****|||0.016|||**-0.040***|
||||**[-3.379]**|||[0.375]|||**[-1.914]**|
|**Many (m**|**ore than 2.1)**|**TLU**||||||||
|Hazard|0.020|0.022|-0.011|0.016|**0.087****|0.078|0.001|0.009|0.028|
||[1.008]|[1.074]|[-0.382]|[0.433]|**[2.355]**|[1.592]|[0.047]|[0.330]|[0.520]|
|Hazard<sup>2</sup>||-0.009|-0.019||**-0.076***|-0.090||-0.027|-0.021|
|||[-0.954]|[-1.352]||**[-1.895]**|[-1.538]||[-1.522]|[-1.153]|
|Hazard<sup>3</sup>|||**0.013***|||0.013|||-0.005|
||||**[1.867]**|||[0.264]|||[-0.284]|
|Obs.|13,641|13,641|13,641|13,641|13,641|13,641|13,641|13,641|13,641|
|R-sq|0.417|0.418|0.422|0.415|0.416|0.416|0.415|0.415|0.416|

_Source:_ World Bank.

_Note:_ NDVI = Normalized Difference Vegetation Index; TLU = Tropical Livestock Unit. Results are from a weighted regression such that each household is assigned its survey-specific population weight. Countries and years included are Mauritania (2014, 2109/20) and Niger (2018). Dependent variable is the log of per capita (or adult equivalent) consumption. Other variables included and not shown are education of household head, gender of household head, whether the household location is remote, whether the household was surveyed during the lean season, survey year, country, country x survey year, and administrative fixed effects. Robust t-statistics are shown in parenthesis. Significance level: * = 10 percent, ** = 5 percent, *** = 1 percent.

23