Project-level Women’s Empowerment in Agriculture Index for Market Inclusion (Pro-WEAI+MI): Philippines Case Study
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| Release Year | 2017 |
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| Source | HARVARD Dataverse |
| Data collection period | - |
| Temporal coverage | - |
| Usage Rights | |
| Access | Open |
| License | CC-BY |
| Disclaimer | IFPRI adheres to the principle of unrestricted public access to its own final research outputs and will make such outputs freely available. The Institute encourages the use of this dataset; for detailed information on its use, please refer to IFPRI’s Intellectual Property Policy. The data files in this dataset are unit record or ‘raw’ data files. Information that would allow survey respondents to be identified has been deleted from the files, but all other information remains. IFPRI’s decision not to alter the contents of the data files means that the user of these files will need to take care in handling missing observations, outliers, and violations of logical consistency. The data are provided ‘as is’ and in no event shall IFPRI be liable for any damages resulting from the use of the data. While great effort was taken to obtain high-quality data, the accuracy or reliability of the data is not guaranteed or warranted in any way. |
| Methodology | |
| Instrument | Structured questionnaire |
| Sampling | In consultation meetings between IFPRI and the Philippine Compact Development Team (CDT) held in December 2016, the CDT identified four target commodities that would be appropriate for value chain interventions under the MCC Compact in three priority regions. These commodities are abaca, coconut, seaweed (carrageenan) and swine, and the regions include Region 5 (Bicol), Region 7 (Central Visayas) and Region 8 (Eastern Visayas). The CDT’s interest in the WEAI survey is to use it as a diagnostic for identifying opportunities for narrowing empowerment gaps between women and men, and for mitigating any unintended negative consequences of potential interventions. Given this focus, the appropriate level of analysis is at the commodity-level, to allow for an assessment of women’s and men’s empowerment for each value chain. The target sample size is 400 households per stratum, which totals 1,600 households for four commodities. Note that this is the minimum sample size required to calculate the WEAI at the commodity-level, including an allowance for attrition in future rounds. Due to the increase in sample size required to cover four commodity strata (rather than the three region strata, originally proposed by IFPRI), the CDT prioritized the four provinces where the survey will take place to minimize field costs. Each commodity was collected from two provinces, to provide a basis for comparison. IFPRI contracted two field collaborators to administer the surveys, one team covering Sorsogon province in the Bicol region, and the other team covering the Cebu and Bohol provinces in the Central Visayas region and Leyte province in the Eastern Visayas region. The data collection was phased, starting with the smaller Bicol team in March 2017, followed by Visayas team in April 2017 (Figure 1). Sample barangays were selected purposively, ranked based on the production data from the 2012 Census of Agriculture and Fisheries (Philippine Statistical Authority). The CDT selected two provinces for each commodity based on their assessment of the presence of production and processing activities reported to be present in the province. For abaca and coconut, the provinces of Sorsogon (Region 5) and Leyte (Region 8) were selected. For seaweed and swine, provinces of Bohol (Region 7) and Cebu (Region 7) were selected. The target sample size for each province-commodity sample is 200 households, totaling 400 households per commodity, and 1,600 households for the entire survey. For each province-commodity sample, two hundred (200) households were selected. These households will be distributed into 10 barangays (or 20 households per barangay) in each of the two provinces for the commodities. These 10 barangays are those that have the highest production volume and/or land area devoted to the commodity in the province, based on data from the 2012 Census of Agriculture and Fisheries collected by the Philippine Statistical Authority. We use this criterion for selecting sample barangays because the areas where production is highest are also more likely to also have households engaged in various activities in the value chain. Before implementing the survey in a sample barangay, the team begins by conducting a courtesy call with the barangay leaders. At this visit, the team can identify key informants from cooperatives or other organizations that can provide a listing of households engaged in specific activities in the value chain. In addition to barangay leaders, the respondents themselves can also be used as key informants regarding the possible location of the processors and traders/marketers. The team may use any existing lists and other information provided by key informants as the starting point for conducting listing operations. Listing operations are conducted by implementing screening questions to verify membership in one of the cells above and identify eligible respondents (Figure 2). To minimize field time, the main questionnaires are administered as soon as an eligible respondent is identified. Once 20 households are identified and the six cells have non-zero entries, the listing operation will stop and implementation of the main questionnaire continues until all the eligible respondents are interviewed. The IFPRI team designed the WEAI4VC survey to collect data on key dimensions of empowerment across multiple activities in the value chain. The survey was implemented from March to July 2017. The screening questionnaire was conducted as a paper-based interview, while the household and individual questionnaires were conducted as computer-assisted personal interviews (CAPI) using SurveySolutions software on Android tablet computers. Skip patterns and consistency checks were included in the survey program to ensure data quality. The household listing exercise was designed to identify value chain participants for our sample and included only basic screening questions that would aid in sample selection. Data were collected on value chain activities in the target commodities and household identification only. This information was then used to populate the household survey among selected households. Given the purposive design of the survey, enumerators were instructed to seek information from barangay leaders, survey respondents, and other key informants for available lists and other information that can assist in identifying eligible producers, processors and traders/marketers. The main questionnaire may be administered immediately as soon as an eligible respondent is identified by the screening questionnaire. The WEAI4VC survey is composed of a household-level questionnaire administered to the value chain participant or other knowledgeable person in the household, and an individual-level questionnaire administered to the self-identified male and female decision makers regarding the relevant value chain activity. The household questionnaire included 10 modules covering various household-level information including demographics, agricultural production, employment, entrepreneurship, assets, transfers and shocks. The individual questionnaire included nine modules covering key dimensions of empowerment such as livelihoods, resources, income, leadership, time use, and intrahousehold relationships and access to information and extension |
| Unit of analysis | Commodity |
| Universe | Households growing abaca, coconut, seaweed, and swine. |
| Contact point | IFPRI-Data |
| DOI | https://doi.org/10.7910/DVN/UPKRKO |
| Funding Organisations | Millennium Challenge Corporation (MCC) |
| Providers | International Food Policy Research Institute (IFPRI) |
| Download All | Download all |
| full citation | International Food Policy Research Institute (IFPRI). 2023. Project-Level Women’s Empowerment in Agriculture Index for Market Inclusion (Pro-weai+MI): Philippines Case Study. Washington, DC: IFPRI [Dataset]. https://doi.org/10.7910/DVN/UPKRKO. Harvard Dataverse. Version 1. |
