Farm households’ livelihood diversification and its implications

Full title: Farm households’ livelihood diversification and its implications for young people’s engagement in agriculture, the case of Uasin Gishu County, Kenya

by Korir, L.K., Lagat, J.K. and Njehia, B.K.

In Kenya, the youth represent about 35.39% of the total population out of which a majority of them (61%) reside in the rural areas. There is widespread unemployment and poverty, especially among the youth. Farm households increasingly rely on non-farm income to supplement and stabilize their mainstream income. One form of this type of diversification is non-farm enterprise investments. Despite the potential benefits of this type of diversification, only some farmers have managed to diversify. In addition, the main avenues of livelihood diversification and the position of the youth in the diversification needed to be understood. This called for an investigation into the nature and extent of livelihood diversification, the position of the youth in the diversification as well as the constraints to this form of diversification. Implications for this diversification were drawn from the findings.

The study used primary data collected from 100 randomly selected farm households and used descriptive statistics to explain some of the questions. In addition, a logit model was used to identify the constraints to non-farm diversification. The study found that 67% of all the households had diversified into non-farm investments, only 23% of these were from the younger farmers’ category compared to 44% for the older farmer category. About 51% of the households had at least a member engaged in wage or salary earning activity, either in a rural or urban setting. Non-farm enterprises for the young farmers included diverse types of business activities with the major ones being agricultural trading, trading in household and consumer goods and motor cycle repair/transport services. The major types of businesses for the older farmers on the other hand were composed of agricultural trading, renting of property and maize milling. Young farmers’ households rely heavily on wage and non-farm investment income compared to older farmers who relied more on farm income (livestock and crop income). Logit model results showed gender, years of experience in farming, employment and farm income significantly determined non-farm investment decisions. Female headed households were more likely to diversify into non-farm businesses. The number of years of experience in farming and earning a wage or salary discourages this diversification. Initiatives that encourage the development of rural non-farm enterprises such as setting up infrastructure e.g. electricity, roads and communication in rural areas and credit targeted at rural based youth enterprises need to be sustained. Training in business and entrepreneurship as well as value addition is likely to position the youth strategically in the value chains where they can play an important role in contribution towards commercializing agriculture through linkage of rural farms with urban markets.

 

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In Kenya, the youth represent about 35.39% of the total population out of which a majority of them (61%) reside in the rural areas. There is widespread unemployment and poverty, especially among the youth. Farm households increasingly rely on non-farm income to supplement and stabilize their mainstream income. One form of this type of diversification is non-farm enterprise investments. Despite the potential benefits of this type of diversification, only some farmers have managed to diversify. In addition, the main avenues of livelihood diversification and the position of the youth in the diversification needed to be understood. This called for an investigation into the nature and extent of livelihood diversification, the position of the youth in the diversification as well as the constraints to this form of diversification. Implications for this diversification were drawn from the findings. The study used primary data collected from 100 randomly selected farm households and used descriptive statistics to explain some of the questions. In addition, a logit model was used to identify the constraints to non-farm diversification. The study found that 67% of all the households had diversified into non-farm investments, only 23% of these were from the younger farmers’ category compared to 44% for the older farmer category. About 51% of the households had at least a member engaged in wage or salary earning activity, either in a rural or urban setting. Non-farm enterprises for the young farmers included diverse types of business activities with the major ones being agricultural trading, trading in household and consumer goods and motor cycle repair/transport services. The major types of businesses for the older farmers on the other hand were composed of agricultural trading, renting of property and maize milling. Young farmers’ households rely heavily on wage and non-farm investment income compared to older farmers who relied more on farm income (livestock and crop income). Logit model results showed gender, years of experience in farming, employment and farm income significantly determined non-farm investment decisions. Female headed households were more likely to diversify into non-farm businesses. The number of years of experience in farming and earning a wage or salary discourages this diversification. Initiatives that encourage the development of rural non-farm enterprises such as setting up infrastructure e.g. electricity, roads and communication in rural areas and credit targeted at rural based youth enterprises need to be sustained. Training in business and entrepreneurship as well as value addition is likely to position the youth strategically in the value chains where they can play an important role in contribution towards commercializing agriculture through linkage of rural farms with urban markets.

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