Participation in own-account activities is certainly most popular across the board, with 74-89% of rural adults participating in farming. Agricultural wage labor participation is less common, with fewer than 10% of rural adults participating in Ethiopia, Tanzania and Malawi, and just 15% in Uganda. In all countries, the average agricultural wage laborer is much more likely to be male than the average farm worker. Agricultural wage workers have more education, on average, than farm workers in Ethiopia and Malawi, and less in Tanzania and Uganda. Because Ethiopia and Malawi surveys collect casual wage labor that cannot be matched to a sector, it is likely that low skill agricultural laborers are showing up in the “unknown” sector.

Within the industry sector, rural individuals are more likely to participate as own account workers everywhere but Uganda. However, in Malawi, 30% of rural individuals participate in own-account industry sector activities, most of which are related to manufacturing. The industrial sector comprises less than 10% of the labor force everywhere but Malawi, where it surpasses 30%. Industry wage laborers are very strongly male, while industry own-account workers are mostly female. Urban participation in industry sector activities is slightly higher than is rural participation everywhere except Malawi.

Participation in the services sector by urban and rural workers is much higher than participation in the industry sector in all countries. Participation as own account workers is higher than participation as wage laborers among all urban and rural workers except for in Ethiopian small town areas. Wage labor participants in the services sector are very strongly male and have higher education levels than own account service sector participants. Both wage and services sector participants supply similar numbers of hours per year except in Tanzania, where own account service sector workers supply far fewer hours than do wage laborers.

Table 4 breaks down wage and NFE activities by a more granular list of sectors. For the enterprise columns, the total number of households in the dataset is provided, along with the number of households that operate at least one enterprise, and the total number of firms present in the dataset (this final number is larger because some households operate more than one firm). Then the firms are categorized by ten sub-sectors of the economy. For the jobs columns, the total number of individuals of working age is provided, along with the total number who participate in wage labor, and the total number of jobs reported in the dataset. Again, because some individuals have more than one source of wage-earning income, this number is larger than the number of wage market participants. The industry sector is divided into mining, manufacturing, electricity and utilities, and construction. The services sector is comprised of commerce, transport and communication, general services, and finance. A summary of activities is provided separately for rural and urban areas (Tables 4a and 4b, respectively).

I use respondents’ free descriptions of their NFEs and jobs, along with the specific industry codes provided by enumerators, to examine carefully the kinds of non-farm activities in which respondents are involved. We do not observe the level of formality associated with household firms and wage-earning jobs because there is not enough comparability across survey questionnaires to describe formality of employment arrangements and/or firm registration.

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