The mission of FAO in the Near East and North Africa is to achieve sustainable food security for all and to help vulnerable communities cope with and recover from shocks and crises. To do this, FAO helps Member States work toward sustainable increases in agriculture production, minimize depletion and degradation of already scarce natural resources and boost rural development.
High quality data and evidence is lacking in the NENA region, including when it comes to assessing socio-economic vulnerability and adaptive capacity. The lack of information and robust evidence has affected the design and targeting of both FAO and non-FAO projects and programmes that aim to combat poverty and food insecurity while reducing risk and vulnerability in rural areas. In order to better design interventions to target the most vulnerable populations and focus on those facets that will have the greatest impact on overall resilience, the Regional Office is investing in resilience and vulnerability assessments. In the first phase, assessments based on primary and secondary data collection will be conducted in two countries: Jordan and Syria.
To support this effort the Regional Office is seeking a qualified specialist to oversee data collection and conduct data analysis, in line with FAO tools and methodologies, including but not limited to the Resilience Index Measurement and Analysis (RIMA) tool.
The Economist (Rural Vulnerably) will report the Regional Economist (Rural Development) and work under the general supervision of the Senior Programme Officer/Lead of RP1 on Rural Transformation.
Supporting the data collection and analysis in Jordan and Syria to assess various dimensions of rural vulnerability and resilience.
Tasks and responsibilities
• Review existing data and targeting tools already available for these countries (e.g., hand in hand typologies, RIMA, UNDFF surveys, climate vulnerability and adaptation indices, and indicators of interest);
• Develop questionnaires for Jordan and Syria in Arabic language, to include indicators for targeting livelihoods, agricultural, social protection and other climate adaptation interventions, based on a theory of change developed in conjunction with other members of this project;
• Develop a sampling methodology in accordance with country stakeholders;
• Support the design and implementation of the enumerator trainings in Jordan and Syria to ensure full understanding and contextualization of the survey questions;
• Oversee data collection efforts in both countries, including follow up with service providers to ensure clear protocols for quality assurance are in place;
• Analyze the two respective data sets in line with guidance from ESA and ESP, to understand who is most vulnerable and what are primary drivers of vulnerability, in order to inform targeting and programme design;
• Draft of final reports for Jordan and Syria based on the analysis of existing literature as well as analysis of primary and secondary data;
• Present results and revise documents according to countries’ stakeholders’ feedback;
• Other related duties as assigned.
CANDIDATES WILL BE ASSESSED AGAINST THE FOLLOWING
• University degree in social sciences, agriculture sciences, economics or statistics;
• At least 1 year of relevant experience (for category C), 5 years (for category B), 12 years (for COF category A)/ 15 years (for PSA category A) of relevant experience in data collection and analysis.
• Working knowledge (level C) of English, French or Spanish and limited knowledge (level B) of one of the other two or Arabic, Chinese, Russian. For PSA, working knowledge of English, French or Spanish.
FAO Core Competencies
• Results Focus
• Building Effective Relationships
• Knowledge Sharing and Continuous Improvement
• Work experience in more than one location or area of work
• Extent and relevance of experience in data analysis and econometric modelling
• Extent and relevance of experience in vulnerability, resilience or poverty assessments in the Near East and North Africa
• Familiarity with data analysis tools and relevant software