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Sampling Strategy

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Sampling Strategy Appendix B - Sampling Strategy Treatment Farmers Phase II of Africare’s project will be carried out in six districts: Jasikan, Kadjebi, Hohoe, Afadjato South, North Dayi, and Kpando. Africare’s project is targeted at those farmers who are (a) small/medium-sized landholders and (b) members of a farmer-based organization (FBO). While Africare sets targets for the number of farmers they plan to reach every quarter, the district MoFA offices decide which FBOs will receive training each month. Using a list of FBOs containing potential target FBOs for this project (as identified by MoFA’s district agricultural officers), we will draw a random sample of FBOs from these six districts as the treatment FBOs under the Africare project. FBOs thus constitute the primary sampling unit for this study. Based on Africare’s experience, we find that districts in the project coverage area have slightly different populations, while FBOs in these districts exhibit large variation in terms of size of membership, ranging from as few as 12 and as many as 100, with an average somewhere around 20-25 members. We will initially use an equal probability systematic selection approach that is designed to ensure that FBOs with smaller membership figures have the same probability of being selected as FBOs with larger membership figures. However, if there is concern that this approach will bias the sample toward districts with smaller populations or smaller numbers of FBOs, the alternative will be to explore a probability proportionate to size (PPS) approach. This method would ensure that districts with larger district populations or districts with larger numbers of FBOs have a greater chance of being selected into the sample. Household sampling weights would be calculated as the inverse of the probability of being selected in the sample, where the probability of being selected in the probability of begin selected into the sample (P) is P = D * F * H (1) where D denotes the probability of household’s district being chosen, F denotes the probability of household’s FBO being chosen, and H denotes the probability of household being selected from within the FBO. However, the use of a PPS approach raises certain issues for this project. First, because of recent redistricting in Volta Region, current or even recent population figures are unavailable on which to assign sampling weights. Second, and assuming that FBO members are the population of interest and that sampling weights can be assigned by the number FBO members per district, accurate figures on either are not available without an extensive FBO membership listing exercise. To make a determination of the appropriate sampling approach and (if necessary) to calculate weights, Africare will assist us in obtaining up-to-date figures on FBO membership and district populations. Once a random sample of FBOs and (if required) sampling weights are assigned, then 10 households will be randomly selected from each FBO to be surveyed at baseline and endline, with replacement. These households represent the secondary sampling units. See power calculations below. A tangential concern raised with AFricare and MoFA highlighted the possibility that sampled FBOs may not be engaged in maize, cowpea or cassava farming. This was argued not to be the case given that all three crops are food staples in Volta Region such that, by necessity, all small/medium-sized landholders are engaged in the production of at least one of these crops to meet their subsistence requirements. Control Farmers Given that the majority of all FBOs in the treatment districts are potential beneficiaries of the Africare project and that even non-beneficiary FBOs face a high probability of being indirectly treated by the project (though direct contamination or spillover effects), drawing a sample of control FBOs from the treatment districts was determined to be unviable. To draw a random sample of control farmers, a separate set of neighboring districts within Volta Region will be selected based on their agro-ecological and socioeconomic similarity and geographical proximity to the treatment districts. MoFA district directors and focal persons have suggested potential control districts corresponding to each treatment district (Table 1). IFPRI consultants based in Ghana, with the help of Africare staff will visit MoFA district offices in these districts to obtain an exhaustive list of FBOs (including information on FBO size). From this list, a random sample of FBOs will be chosen to serve as a control group. As with the treatment group, control group FBOs will also be sampled using PPS. Prior to the rollout of baseline, enumerators and ISSER hired supervisors will conduct a reconnaissance visit to each of the control communities to introduce themselves and collect FBO member lists for the FBOs selected to the sample. Table 1: Treatment and control districts Project (treatment) district Possible matching (control) districts Kpando Biakoye North Dayi South Dayi, Ho Central, Ho East Kadjebi Nkwanta South, Krache East Jasikan Biakoye, Ho East Afadjato South Ho West, South Dayi Hohoe Biakoye .
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