A multifaceted sampling approach was implemented at three distinct levels to determine (i) the target enumeration areas, (ii) the target households per enumeration area (including subsistence farmers), and (iii) the target respondents per household. A combination of purposive and random sampling was employed to identify the farmers for the pilot interviews and the full surveys.

In each of the surveyed countries, we had the following sampling strategy for the full surveys: (i) more than 800 purposively selected contract farmers, and (ii) 400 randomly selected farmers. Our plan was to allocate the sample equally among cassava, maize, and sorghum farmers. However, given that, as opposed to maize, cassava and sorghum crops are not a staple for these countries, it was not possible to cover the crops equally.

**_<u>Table 1: Full Sample</u>_**

|**Country**|**Farmers**|**Buyers**|**Aggregators**|
|---|---|---|---|
|**Ghana**|1,294|17|25|
|**Kenya **|1,285|31|24|
|**Zambia**|1,356|8|11|
|**Total**|3,935|56|60|

The key objectives of our empirical research are to assess the impact of contracting arrangements—and ultimately value chain participation—and compare farmers participating in the value chain and/or specific contract arrangements with nonparticipating farmers. A major challenge was to identify contract farmers (an initial way to identify value chain participation), especially those growing sorghum. The pilot surveys taught us that in a random selection of farmers the prevalence of contract farmers is very low, unless the random selection happens to be in an area where a buying scheme was already set up. Based on this finding, our conclusion was that at the national level, only a minority of farmers participate in a scheme. This finding is in agreement with the findings of other studies, such as the Consultative Group to Assist the Poor’s National Survey and Segmentation of Smallholder Households in Tanzania which was conducted in May 2016 (Anderson et al. 2016). The survey found that only 3 percent of farmers in Tanzania are reported to have a contractual arrangement to sell any of their crops or livestock. Thus, we designed a sampling strategy that targets a sufficient number of contract farmers through a purposive selection of enumeration areas.

Identifying contract farmers requires a deep exploration of particular value chains, ranging from processors or other large consumers of the focus crops, to smaller players that aggregate farmers’ produce. From our pilot surveys, we also learned that a top-down approach would not yield sufficient leads to contract farmers. In preparing the full surveys, a team of research assistants undertook a scoping exercise to identify schemes of contract farmers, to ensure sufficient leads before deploying a full team of enumerators. The first few contacts were established by making calls, followed by a scoping trip to the regions where the focus crops are grown. The research assistants collected information on the size of the groups, crops grown, and contact details of the group leaders/representatives.

Contrary to our expectations, the initial investigation revealed that only a few large schemes could be identified in each country. Therefore, several smaller groups were included in the sample, with sample sizes of around 30 to 50 farmers per group. The “control group” is comprised of farmers who were interviewed in the same areas as the farmers operating in a scheme, but at a sufficient distance for them not to be affected by the schemes or programs. The details of the random and purposive sampling are presented in annex B.

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