# 4. Consumption aggregate

The main welfare measure used in this and other analyses using SHFS data is per‐capita consumption, rather than income (Deaton and Zaidi, 2002). The SHFS collected data on realized consumption rather than the total money spent on consumption items, as this measured actual realized welfare in a utility‐ consistent way (Ravallion, 1994). This section discusses the various adjustments made to the SHFS data to construct the consumption aggregate using the Rapid Consumption Methodology. Section 6 discusses the use of the international poverty line and various aggregate poverty measures to perform poverty analysis on the SHFS data.

## 4.1. Cleaning of consumption data

Before deriving the consumption aggregate, the components of consumption –data on food consumption, nonfood consumption, and durable assets– must undergo a cleaning process to correct outliers and other mistakes (Deaton and Zaidi, 2002).

Food expenditure data are cleaned in a four‐step process. First, units for reported quantities of consumption and purchase are corrected. Typical mistakes include recorded consumption of 100 kg of a product (like salt) where the correct quantity is grams. These mistakes are corrected using generic rules (Table A.4). Then, a conversion factor to kg for all units is introduced. For example, a small piece of bread will likely have a different weight than a small piece of garlic. To avoid mistakes, enumerator trainings focused on units and introduced a common understanding of what each unit means for each food item. In addition, the conversion to kilograms was made explicit on the enumerators’ tablets (Table A.5). The third step consisted of correcting issues with the exchange rate selected (Table A.6). Finally, outliers in each component of consumption are detected using a set of cleaning rules to correct quantities and prices (see Appendix Cleaning rules for food consumption data). The non‐food data set only contains values without quantities and units. First, the same cleaning rules for currencies are applied (Table A.6), followed by a set of specialized cleaning rules (see Appendix Cleaning rules for nonfood consumption data). Likewise, for durables, the same cleaning rules for currencies are applied (Table A.6), and then a set of durables‐specific cleaning rules (see Appendix Cleaning rules for durable assets).

## 4.2. Consumption aggregate using the Rapid Consumption Methodology

The nominal household consumption aggregate is the sum of four components, namely expenditures on food items, expenditures on non‐food items, the value of the consumption flow from durable goods, and housing (Deaton and Zaidi, 2002). Without a housing market functioning well enough to derive credible estimates for the cost of housing, the SHFS consumption aggregate is based on the first three components: food consumption, nonfood consumption, and consumption of durable assets.

### _Food and nonfood consumption in the Rapid Consumption Methodology_

The SHFS used the Rapid Consumption Methodology to estimate the consumption aggregate. Pape and Mistiaen (2018) provide a detailed and general exposition of the Rapid Consumption Methodology including an ex‐post assessment of the methodology. The methodology is based on dividing food and nonfood consumption items in one core and several optional modules. With each household assigned the core module and one optional module, this methodology reduces the time spent on enumerating the consumption modules. Deriving the consumption aggregate with this methodology is a two‐step process. First, core and optional modules are constructed. Core items are selected based on their importance for consumption. The remaining items are partitioned into optional modules. Optional modules are assigned 17