This study set out to estimate baseline indicators of the drivers of vulnerability and adaptive capacity of the target communities to priority shocks or stresses as a basis for informing development of resilience dimensions and metrics so as to develop innovations that will result in improved resilience of the target communities in Uganda. Specifically the study aimed at; to assess dimension specific resilience factors in the RAN target communities in Uganda, to determine benchmark dimension-specific data for measuring success of resilience innovations in the RAN target communities, to assess the inter-relationships between the resilience dimensions so as to identify opportunities for leverage during innovation development in the RAN target communities

The Resilient Africa Network data asset includes both qualitative and quantitative data. The qualitative data are aimed at understanding the Dimensions of Vulnerability and Resilience (2015) in Uganda, Rwanda, Ghana, Senegal, South Africa, Malawi, Somalia and Ethiopia. The quantitative data were collected to understand resilience pathways in these communities, to highlight interventions and innovations that strengthen resilience developed by collaborative teams informed by this analysis across Africa.

The study set out to understand the extent to which households and systems are affected by shocks and stressors related to rapid urbanization, climate change and food insecurity identified in three qualitative study locations in Ghana in the regions of Ashaiman (Greater Accra region), Tamale (Northern region) and Navrongo (Upper East region)

The Partnership for Recovery and Resilience (PfRR) in South Sudan brings the UN’s “New Way of Working” together with the support of multiple donors and non-governmental partners in a commitment that shifts the focus from “meeting needs” to “reducing needs, risks, and vulnerability.” The PfRR is emerging as an all-encompassing, unified approach to reduce vulnerability and build resilience through a multi-actor and cross-sector collaboration. This data asset contains quantitative data collected from 7 Candidate Partnership Areas identified through the Partnership for Recovery and Resilience. The 7 CPAs are: Rumbek, Aweil, Yambio, Torit, Wau, Yei and Bor.

This data asset contains the data from the Graduation with Resilience to Achieve Sustainable Development (GRAD) endline beneficiary-based survey in selected four woredas. The evaluation used a multi-stage cluster sampling design. GRAD implementing partners (IPs) purposively chose woredas at baseline to include one woreda per region and implementing partner. These woredas were Endamehoni in Tigray region, Lay Gayint in Amhara, Ziway Dugda in Oromia, and Hawassa Zuria in Southern Nations, Nationalities and Peoples (SNNP) regions. At endline, the GRAD final Evaluation team used the baseline kebeles as clusters from which to randomly sample household respondents, using GRAD’s kebele-level beneficiary lists to identify the final sample. The sample size for the endline survey was 1602. The Feinstein International Center of Tufts University conducted the baseline survey 2012. Ethiopian Performance Monitoring and Evaluation Service’s (EPMES’) sub-contractor, Sub-Sharan Africa Research Center undertook the endline survey data collection. The survey included different sections: Household Socio-Demographics, PSNP and GRAD Participation, Livelihoods Shocks, Household Expenditure, Income Sources, Access to Input and Output Markets, Credit & Savings, Project Outcomes and Benefits, Food Security and Nutrition and Women’s Empowerment.

The objective of the PRIME project is to increase household incomes, enhance resilience, and bolster adaptive capacity to climate change among pastoral people in Ethiopia. Investigators use both qualitative and quantitative data to determine the impact of the project’s interventions on households’ resilience to shocks and, thus, on well-being outcomes, including poverty, food security, and children’s nutritional status.

In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully. This is the third spreadsheet of three in the Ethiopia Pastoralist Areas Resilience Improvement and Market Expansion (PRIME) Project IE--Household Information.

The endline household survey sampled beneficiaries of GRAD that the evaluation team designed to mirror the baseline survey of GRAD household beneficiaries conducted by the Feinstein International Center of Tufts University in 2012. The endline surveyed households in the same villages as the baseline and used the same data collection tool, with minor refinements to improve the flow and clarity of questions. The evaluation used a multi-stage cluster sampling design. GRAD implementing partners (IPs) purposively chose woredas at baseline to include one woreda per region and implementing partner. These woredas were Endamehoni in Tigray region, Lay Gayint in Amhara, Ziway Dugda in Oromia, and Hawassa Zuria in SNNPR . The baseline sample size was 1,584 households, and the endline sample size was 1,602

In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully. This is the second spreadsheet of three in the Ethiopia Pastoralist Areas Resilience Improvement and Market Expansion (PRIME) Project IE--Household Information.