South Sudan Poverty & Equity Assessment - Technical Annex - Annex A. Survey Sources, Comparability, Imputations

Jul 19, 2026

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This Technical Annex details how the South Sudan poverty assessment compares household survey sources and constructs comparable poverty and expenditure measures. It summarizes key design features across the 2022 Household Budget Survey (HBS), the High Frequency Survey wave 3 (HFS 2016–17), and the countrywide extended Food Security and Nutrition Monitoring System (FSNMS+). It further explains the SWIFT approach for rapid poverty estimation, including the imputation strategy used to infer FSNMS+ consumption expenditure and poverty statistics from shared poverty correlates when direct consumption data are absent.

LanguageEnglish

CategoryResearch & Report

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Pages21

Reading Time53 min

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Annex A. Survey Sources, Comparability, Imputations

A.1. Comparisons of the 2022 HBS, HFS wave 3 2016–17, and FSNMS+

A.2. The Survey of Well-Being via Instant and Frequent Tracking

A.3. Methodological Note: HBS 2022 to FSNMS+ Imputation

Public Disclosure Authorized Public Disclosure Authorized South Sudan Poverty & Equity Assessment June 2024 Technical Annex Annex A. Survey Sources, Comparability, Imputations A.1. Comparisons ofthe 2022 HBS, HFS wave 3 2016–17, and FSNMS+ The analysis in this poverty assessment mainly relies on data from three household surveys: the Household Budget Survey 2022 (2022 HBS); the High Frequency Survey 2015–17, wave 3 2016–17 (HFS wave 3 2016–17); and the countrywide extended Food Security and Nutrition Monitoring System (FSMNS+) . The key features of these three surveys are summarized in table A.1 . Table A.1. Comparison of HBS 2022, HFS wave 3 2016–27, and FSNMS+ | Feature | 2022 HBS (Household Budget and Poverty Survey 2022) | HFS wave 3 2016–17
(High Frequency Survey 2015–17, wave 3 2016–17) | FSNMS+
(Countrywide extended Food Security and Nutrition Monitoring System) | | --- | --- | --- | --- | | Data collection period | April 2022–June 2022; April: dry season; May–
June: wet season | September 2016–March 2017; September– October: wet season; November–April: dry season | Urban areas and camps: September 2021–November 2021;
Rural areas: November 2021 | | Coverage | Urban areas, rural areas, and camps; both urban
and rural areas are covered in all 10 states | Urban and rural areas (no camps); because of security issues, only seven states are covered: Central Equatoria, Eastern Equatoria, Lakes, Northern Bahr El Ghaza, Warrap, Western Bahr El Ghaza, and Western Equatoria; the three states not covered are Jonglei, Unity, and Upper Nile | Urban areas, rural areas, and camps; only urban areas in five states are covered: Central Equatoria, Jonglei, Unity, Upper Nile, and Western Bahr El Ghaza; the five states not covered are Eastern Equatoria, Lakes, Northern Bahr El Ghaza, Warrap, and Western Equatoria | | Sample size | 719 households (239 urban households; 240 rural households; 240 households in camps) | 1,846 households: 567 urban households;
1,279 rural households | 19,050 households: 3,255 urban households; 14,215 rural households; 1,580 households in camps | | Questionnaire | The questionnaire modules include a household roster; housing and household assets; subjective well-being and food security; food consumption; food expenditures; consumption of food and drinks; other expenditures Consumption expenditure modules are included | The questionnaire modules include a household roster; household head;
household characteristics; food consumption; nonfood consumption; livestock; durable goods; physical, psychological, and social well-being; enumerator conclusions
Although consumption expenditure modules are included, the HFS wave 3 consumption expenditure data are not exactly comparable to the HBS data because the HFS data were collected using a rapid data collection method | The questionnaire modules on urban areas and camps include demographics and vulnerabilities; displacement and mobility; shelter; health care; water, sanitation, and hygiene; and COVID- 19 Integrated Food Security Phase Classification (IPC); education; livelihoods and economic vulnerability; food consumption and food sources; coping; communication, social networks and community involvement; social protection; mental health and psychosocial support; humanitarian assistance and access to services; child nutrition and health; infant and young child feeding; nutritional status of girls and women; social support scale; and mental health; in addition, the camp questionnaire includes a module on return intentions No consumption expenditure modules are included | A.2. The Survey of Well-Being via Instant and Frequent Tracking SWIFT is a tool for the rapid estimation of poverty. It employs a combination of machine learning and traditional statistical modeling. The SWIFT methodology involves training models on a comprehensive household survey that encompasses both household expenditures and poverty correlates. Subsequently, i

FAQs

What three surveys underpin the South Sudan poverty assessment described in this annex?

The annex relies on the 2022 Household Budget Survey (2022 HBS), the High Frequency Survey wave 3 (HFS 2016–17), and the countrywide extended Food Security and Nutrition Monitoring System (FSNMS+).

How does the annex address differences across HBS 2022, HFS wave 3, and FSNMS+?

It compares survey design and key features such as data collection periods, coverage, sample sizes, and questionnaire modules, highlighting where measures are not directly comparable (e.g., consumption expenditure).

How is consumption expenditure imputed from HBS 2022 to FSNMS+ using SWIFT?

Because FSNMS+ lacks a consumption module, the annex states that SWIFT imputes expenditure using models trained on HBS 2022 with shared poverty correlates, separately for urban, rural, and camps, and then applies those models to infer FSNMS+ expenditure and poverty statistics.

Jul 19, 2026

Upload by Liam