Dataset on Agro-Pastoral Youth Participation in Development Interventions in East and West Hararghe Zones, Oromia Regional State, Ethiopia
Description
The dataset contained in this data article comprises several sections. In all the sections, data were first presented for the full/pooled sample. Moreover, data were disaggregated by gender, Zone and Woreda. Data on socio-demographic characteristics were presented in Table 1 (for the full sample, male and female youth) and Figure 1 (for the two Zones and four Woredas). Data on youth employment and participation in the labour market for the full sample, male and female youth categories are given in Table 2. The Zonal and Woreda level data were presented in Figure 2. The engagement of youth in on-farm and non-/off-farm income-generating activities (IGAs) was given in Table 3 (for the pooled sample, male and female youth) and Figure 3 (for Zonal and Woreda comparisons). Concerning data on agricultural production, income and food security status, Table 4 presents a summary statistic on various aspects of livelihood activities and outcomes for the pooled sample and male and female youth categories. Whereas Figure 4 depicts the Zonal and Woreda level data on experience in farming, land holding size and livestock possessions, Figure 5 presents the status of land registration in the study Zones and Woredas. Likewise, Figure 6 depicts Zonal and Woreda level comparative data on expenditures for productive assets and farm income. Regarding food security, data on household dietary diversity score (HDDS) and food consumption score (FCS) were presented in Figure 7. Youth perception on whether agriculture can be a basic means of livelihood (Table 5 and Figure 8); whether agriculture can be a viable profession with a reasonable financial return (Table 6 and Figure 9); and level of satisfaction with current (agricultural) job (Table 7 and Figure 10) were all included herein. Data on youth access to basic services, infrastructure and facilities were given in Figure 11. Youth ownership of asset, control over use of income, and decision about credit is presented in Table 8 and Figure 12. Data on youth participation in public extension and advisory services, including farmer field schools (FFSs), farmer training centers (FTCs), and pastoral training centers (PTCs) is presented in Table 9 and Figure 13. Similarly, data on youth participation in microfinance institutions (MFI) and small and medium enterprise (SME) promotion activities is depicted in Table 10 and Figure 14. Concerning the participation of youth in community-based organizations (CBOs), networks and groups, data were presented in Table 11, Figure 15 and Figure 16. Furthermore, data on youth participation in the productive safety net program (PSNP) and cooperatives is given in Table 12 and Figure 17. The last part of this data article presents data on status of youth access to and participation in the activities of various NGOs operating in their vicinity (Table 13, Figure 18 and Figure 19).
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Primary data were collected by employing research assistants and local supervisors. A total of 12 research assistants/enumerators and 5 supervisors were provided an orientation training before they embark on pretesting the data collection instruments. The research assistants were selected based on their educational qualification, experience in socio-economic research, language competence, and experience in living/working in the study areas. The supervisors were instrumental in overseeing the process of data collection, together with the core research team, and provided feedback and technical support to the data collectors. Data collection process started by pretesting all the data collection tools with selected non-project participant respondents. Following the feedback gathered through this process, the data collection instruments were refined and adjusted for the main field survey and data collection. A range of data quality assurance mechanisms were implemented during the field-based data collection, analysis and reporting. To ensure the collection of high-quality data, the research team employed research assistants/enumerators with the required educational background and experience in survey and qualitative data collection tools. There was a continuous supervision by the research team and local supervisors tasked with follow up and provision of on-the-spot feedback to enumerators. There was also a daily debriefing session where enumerators shared their experiences and encounters and got support from the technical team. Quantitative data was checked regularly for completeness and consistency. Food Consumption Score (FCS) was measured using both the types of food groups consumed and the frequency of consumption of these food groups, and computed by employing the procedures indicated in the World Food Program (WFP) Technical Annex 2012 [8]. In order to capture the dietary habit of the sample households, seven days recall period was used which further reduces the risk of selection bias [3]. Frequency of consumption and weights attached to each food group are used for computing food consumption score [3]. The Household Dietary Diversity Score (HDDS) is a measure of food adequacy indicating the number of food groups consumed at household level, which is considered to be an indicator for economic ability of households [5]. Dietary diversity refers to the number of food groups (e.g., cereals, vegetables, milk, meat, legumes, eggs and fruits) consumed over 24 hours recall period [7]. The HDDS score ranges from 1 to 12. The minimum is consuming one food group over the reference period and the maximum is consuming twelve food groups [8; 5]. The data was partially analysed through descriptive (mean, frequency, and standard deviation) and inferential statistics. In all these processes, the research team exercised the highest level of scientific integrity and ethical procedures in gathering, processing, and analysing data.
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- Purdue University West LafayetteUnited StatesGrant ID: Purdue University Agreement No. F9002550402135 and USAID Prime Agreement No. 7200AA18CA00009