# 3.3. Welfare data

The main welfare measures examined are constructed from household consumption surveys. To provide a comparable measure of welfare across countries, the aggregate that is used for national poverty measures and that forms the basis for global poverty measurement is used. Consumption aggregates are converted into 2011 purchasing power parities (PPPs) for this analysis.<sup>11</sup> We selected nine countries representing geographic variation in SSA for the analysis of the relationship between droughts and monetary welfare (consumption). They include Ethiopia in Eastern Africa; Mauritania, Niger, and Nigeria in Western Africa; and Lesotho, Malawi, Mozambique, Zambia, and Zimbabwe in Southern Africa. For five of these countries data are available for multiple years. The countries, years, and outcome measures used in analysis are listed in Table 3.3. To allow for ease of matching rainfall patterns to consumption in the first analysis, the selected countries are all from parts of the continent where there is a clear main season of production. Selection was also designed to include countries that had multiple survey rounds that could be pooled for analysis and that would provide sufficient numbers for analysis across livelihood zones.

The empirical analysis is carried out by livelihood zone, which entails pooling these countries and estimating like areas of production within them. The zones used are those defined in Dixon et al. (2019). They allow for the required level of analysis. The authors provide gridded data for the livelihood zones estimated for 2015, which is within our analysis period. We further aggregated the zones estimated for 2015 into five zones. Table 3.4 indicates how the countries included match to the livelihood zones used in the analysis. Table 3.5 reports descriptive statistics for the variables used in the analysis by country and survey year.

**Table 3.3. Household surveys and welfare measures included in the analysis**

|**Country (years)**|**Welfare measure**|
|---|---|
|Ethiopia (2010/11, 2014/15)|Total expenditure per adult equivalent<br>Food expenditure per adult equivalent<br>Nonfood expenditureper adult equivalent|
|Lesotho(2017/18)|Total expenditureper capita|
|Malawi (2010/11, 2016/17,<br>2019/20)|Total expenditure per capita<br>Total food expenditure per capita<br>Total nonfood expenditure per capita<br>Household dietary diversity: based on 12 food categories<br>Household food consumption score: based on food types consumed and<br>frequencyof consumption in a seven-day period(maximum 120)|
|Mauritania(2014,2019/20)|Total expenditureper capita|
|Mozambique (2014)|Total expenditure per capita<br>Total food expenditure per capita<br>Total nonfood expenditureper capita|
|Niger (2018)|Total expenditure per capita<br>Total food expenditure per capita<br>Total nonfood expenditureper capita|
|Nigeria(2011,2013,2016)|Total expenditureper capita|
|Zambia(2015)|Total expenditureper capita|
|Zimbabwe(2017)|Total expenditureper capita|

_Source: World Bank._

> 11 In most countries, the aggregates take spatial variation in prices into account and where this is done, this is retained. In addition, if the consumption aggregate used for national poverty measurement uses per adult equivalent instead of per capita, this is also retained. This makes the aggregate different from the ones reported in the World Bank’s Poverty and Inequality Platform.

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