The 2015 Ghana Agricultural Labor Survey interviewed 719 households, in 20 enumeration areas in four districts located in Ghana’s Ashanti and Brong Ahafo regions.<sup>14</sup> A major criterion for households selected was that they had at least one plot being cultivated at the time of the survey. Households were visited prior to the beginning of land preparation and again, at the end of the agricultural season.<sup>15</sup> In Ghana, as in the other two countries, maize is the most important staple crop and survey activities were timed as per the maize agricultural production cycle. The household member characteristics module (roster) captured, among other things, information about each household member’s current occupation and the intended use of the products obtained from the activity, that is, only for own use, mainly for own use, mainly for sale or only for sale. The end-of-season survey also included a standard LSMS labor module which asked each household member engaged in agriculture over the past seven days about the intended use of the products obtained from the activity, using the same four response categories described above. These questions in the member characteristics and labor modules are both examples of an _activity-level_ operationalization of the revised standards. In addition, the pre-planting survey included a short crop intention module, which asked a member of the household to report on the expected harvest and intended sales of each crop the household was expected to grow over the upcoming season. This is akin to a _productlevel_ operationalization of the 19th ICLS standards, with a focus on crops (i.e. no livestock products). The plot characteristics module also collected data on which members of the household were expected to work on each plot and the crops to be planted on each plot, which makes it possible to link crop-level reports on the intended use of output to the household members’ labor input.

The 2016/17 Malawi Agricultural Labor Survey interviewed about 850 households in 20 enumeration areas in the Ntcheu and Zomba districts of Malawi. Similar to the Ghana Agricultural Labor Survey, households were visited prior to the beginning of land preparation and again, at the end of the agricultural season.<sup>16</sup> For the purpose of this paper, we focus on the comparison of two randomly assigned groups of households. Both groups were administered short labor modules (modeled after a standard LSMS survey) that ask about each household members’ engagement in various types of economic activities over the past seven days. The two groups differ, however, with respect to how they capture the intended use of output for household members engaged in agriculture over the preceding seven days. In group one, the intended use of output was captured at the activity level (“Are the products obtained from [NAME's] farming/ fishing

> 14 The data were collected by the Institute of Statistical, Social and Economic Research (ISSER) of the University of Ghana. The four districts covered are Mampong Municipal, Ejura Sekyedumasi, Nkoranza South, and Pru. 15 A subsample of households was visited weekly during the agricultural season. These weekly visits, which collected data on plotspecific farm labor, were used to assess recall bias in farm labor data and are not used in this paper (see Gaddis et al, forthcoming). 16 Like the Ghana Agricultural Labor Survey, a subsample of households was visited weekly (the weekly visits were related to another part of the experimental design). The actual sample size differs across rounds due to the inclusion of replacement households in the pre-planting survey (to reduce possible attrition) and the addition of another random sample of households in the end-of-season survey. The data were collected by Wadonda Consult Limited.

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