Is labour a major determinant of yield gaps in sub-Saharan Africa? A study of cereal-based production systems in Southern Ethiopia

• Published in: Agricultural systems Vol. 174; pp. 39 - 51
• Main Authors: Silva, João Vasco, Baudron, Frédéric, Reidsma, Pytrik, Giller, Ken E.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2019
• Subjects: Extensification; Farm power; Frontier analysis; Intensification; Triticum aestivum L; Zea mays L; Frontier analysis; Triticum aestivum L; Intensification; Farm power; Extensification; Zea mays L
• ISSN: 0308-521X; 1873-2267
• DOI: 10.1016/j.agsy.2019.04.009

We investigated the role of labour in explaining the yield gap of cereals at both crop and farm levels on smallholder farms in Southern Ethiopia. A household survey containing detailed information of labour use at crop and farm level of ca. 100 farms in a maize-based system around Hawassa and ca. 100 farms in a wheat-based system around Asella was used for this purpose. Stochastic frontier analysis was combined with the principles of production ecology to decompose maize and wheat yield gaps. Actual maize and wheat yields were on average 1.6 and 2.6 t ha−1, respectively, which correspond to 23 and 26% of the water-limited yield (Yw) of each crop. For both crops, nearly half of the yield gap was attributed to the technology yield gap, indicating sub-optimal crop management to achieve Yw even for the farmers with the highest yields. The efficiency yield gap was ca. 20% of Yw for both crops; it was negatively associated with sowing date and with the proportion of women's labour used for sowing in the case of maize but with the proportion of hired labour used for sowing and weed control in the case of wheat. The resource yield gap was less than 10% of Yw for both crops due to small differences in input use between highest- and lowest-yielding farms. The contribution of capital and farm power availability to crop yields, input use and labour use was analysed at the farm level. Labour calendars showed that crops cultivated in Hawassa were complementary, with peak labour occurring at different times of the year. By contrast, crops cultivated in Asella competed strongly for labour during sowing, hand-weeding and harvesting months, resulting in potential trade-offs at farm level. Oxen ownership was associated with capital availability, but not farm power in Hawassa and with both capital availability and farm power in Asella. Farmers with more oxen applied more nitrogen (N) to maize in Hawassa and cultivated more land in Asella, which is indicative of an intensification pathway in the former and an extensification pathway in the latter. Differences in land:labour ratio and in the types of crops cultivated explained the different strategies used in the two sites. In both sites, although gross margin per unit area increased linearly with increasing crop yield and farm N productivity, gross margin per labour unit increased up to an optimal level of crop yield and farm N productivity after which no further response was observed. This suggests that narrowing the yield gap may not be economically rational in terms of labour productivity. We conclude that labour (and farm power) is not a major determinant of maize yield gaps in Hawassa, but is a major determinant of wheat yield gaps in Asella. •Labour calendars reveal competition for labour in Asella, but not in Hawassa.•Yield gaps for maize and wheat in Southern Ethiopia are around 80% of Yw.•The technology yield gap explains nearly half of the yield gap of both crops.•Lack of capital hinders maize intensification in Hawassa; access to farm power wheat intensification in Asella.•Labour is a major limiting factor in some African smallholder farming systems.