of differences in household characteristics to productivity gaps by generating productivity measures for each sector-activity combination at the household level. This includes household farms, household-owned NFEs, and household wage labor in all sectors. Wages are not, of course, a productivity measure, especially in the presence of market frictions, of which the evidence is strongly suggestive (Dillon and Barrett 2014). They do offer a lower bound on the marginal revenue product of hired labor, and they also provide a benchmark against which individuals in an economy can evaluate self vs. own employment.

Figure 8 depicts these sector-activity productivity gaps based on mean returns to each sectoractivity compared with mean returns to farming. The labor inputs of hired workers are included alongside household workers whenever possible. As previously mentioned, the per-person farm productivity estimates do not include hired labor and therefore necessarily over-estimate output per farm worker. Firm level per-hour productivity estimates are not included for NFEs because good time input measures are not available for these firms.

The patterns here are similar to those observed with the sector level analysis. First, mean returns per participant per year are higher outside of farming in many cases – for wage laborers in Malawi, and for enterprise operators and industry and sector wage workers in Tanzania and Uganda. NFEs and wage laborers often each bring _lower_ returns per participant per year than do household farm workers. The unconditional (cross-household) and conditional (intra-household) productivity gaps are similar in magnitude to the sector productivity gaps. These gaps also shrink considerably, except in Tanzania, when labor inputs are considered.

Using the sector-activity productivity measures, I next calculate conditional productivity gaps, or within-household gaps between farming and other activities for farming households that also participate in an additional activity. Figure 9 depicts these conditional gaps – measured as the median across households of cross-sector gaps observed within households that participate in multiple activities. The conditional productivity gap for agricultural wages, for example, is based on a comparison between farm returns and agricultural wages only for households that participate in farming and agricultural wage labor.

In comparison with the unconditional productivity gaps, the conditional gaps are informative. If households are equating returns across sectors where we see them in multiple sectors simultaneously (i.e. the conditional productivity gap measures), then the differences in returns observed in the unconditional productivity gap measures reflect selection effects related to a household’s ability to participate in an activity. This is consistent with the idea of human capital heterogeneity across sectors. The observed small magnitude of intra-household gaps also suggests that structural barriers to improved household productivity that span across sectors may constrain households’ opportunities to raise their productivity levels.

# 4.2 _Jobs and Non-Farm Enterprises_

Table 3 summarizes individuals’ participation in own account and wage labor activities by sector, describing participation rates and basic characteristics of participants for both rural (Table 3a) and urban (Table 3b) populations. Additional analysis of the NFEs that occur in the LSMSISA datasets can be found in Nagler and Naudé (2014).

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