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7.2.4 Off-farm activitiesIn the study area, a few households (13%) went into paid labour on other people‟sfarms. How it usually worked was the a person would get paid per acre and on thebasis of what type of work it entailed, whether ploughing or harvesting, andsometimes depending on what type of crop he/she was working with, a price per acrewould be bargained. For instance in some areas working on a farm which producedsim sim would pay more per acre than for instance maize.Table 33: Off-farm employment, Kilosa District, Tanzania, 2010Lunenzi Nyali Masugu TotalOff-farm employment*Use of off-farm labour*8725532320N = 180, * indicates significantly difference between locations (p < 0.051332As seen in Table 33, most of the households employed as off-farm labour are fromMasugu. The poorer households tend to be well represented within this activity,where also the size of the household matters. The bigger the households, the morethey will be engaged in off-farm labour (p = 0,036).When poorer households tends to be the employee, the less poor households will bethe managers (p = 0,030; p = 0,005) From this we therefore see that when Masuguwas most engaged as labour, Lunenzi hire more labour than people attend to. Thesevariations in activities and employment can reflect the natural capital in each village.In Masugu we did learn that the conditions for agriculture was challenging. This canthen in return lead to that more people turn to off-farm employment as an alternative.All in all, we see that almost all households are engaged in agriculture. This is alsothe case with forest environmental resources, where close to all households aredependent on collecting fuel wood to cover the daily energy needs. The forests werehowever also used for other purposes such as collecting NTFPs, producing charcoal,poles and timber. Such activities were mostly done in Masugu, and by the morewealthy households. Other activities include non-farm and off-farm activities. Ingeneral, this shows that more wealthy households diversify their livelihoods by theinvolvement in more activates than the poorer ones. By this their livelihood outcomewould most likely be better.193