10 | Sub-Saharan Africa (SSA) Report

          Between 1996-2005 (World Bank, 2006), fifteen SSA countries (Mozambique, Rwanda, Cape Verde, Uganda, Mali, Botswana, Ethiopia, Tanzania, Mauritania, Benin, Ghana, Senegal, Burkina Faso, Gambia and Cameroon) recorded annual growth rates of more than 4.5%. During the same period, thirteen SSA countries recorded growth rates of only 1.3% (Swaziland, Kenya, Lesotho, Eritrea, Comoros, Seychelles, Cote d’Ivoire, Burundi, Sierra Leone, central African republic, Guinea-Bissau, DRC Congo, and Zimbabwe) (World Bank, 2006).

Between 1998-2000, agricultural GDP averaged 29% of the total GDP and agricultural labor comprised 66.6% of the total labor force in SSA (Beintema and Stads, 2004). Rural livelihoods in SSA are diversified between farm and non-farm activities but are largely dependent on agriculture, either directly or indirectly as agriculture is both a source of income and means to food security (Pinstrup-Andersen and Cohen, 2001).

Agricultural research directly contributes to growth and development (IAC, 2004); stimulating agricultural growth in SSA can contribute significantly to economic growth and poverty reduction. By increasing food availability and incomes and contributing to asset diversity and economic growth, higher agricultural productivity and supportive pro-poor policies allow people to break out of the povertyhunger-malnutrition trap (Garner, 2006). Improving the productivity and the economic returns of agriculture can have immediate effects on poverty and hunger (Kydd, 2002).

A nation’s ability to solve problems and initiate and sustain economic growth depends partly on its capabilities in science, technology, and innovations (UN Millennium project, 2005). Scientific, technological, and innovation capacity are often associated with economic growth (IAC, 2004). SSA and South Asia have the lowest access to information and communication technologies (Pigato, 2001).
Poverty reduction requires a combination of economic growth and a reduction in inequality (Okojie and Shimeles, 2006). Recent studies have shown that both income and non-income inequalities are high in sub-Saharan Africa (Okojie and Shimeles, 2006; World Bank, 2006; Blackden et al., 2006) with the level of inequality lower in rural areas (Okojie and Shimeles, 2006; Table 1-3) Countries with high initial income inequality find economic growth to be less effective in reducing poverty (Okojie and Shimeles, 2006). For example, in Tanzania the pace of poverty reduction would have been substantial had it not been for the dampening effects of a rise in inequality in the wake of economic growth (Demombynes and Hoogeveen, 2004).

Gender inequalities also play a significant role in accounting for SSA’s poor growth and poverty reduction performance (Townsend, 1999; Blackden et al., 2006). Analysis


from Kenya suggests that giving women farmers the same education and inputs as men increases yields by as much as 22 percent. For Burkina Faso, analysis of household panel data suggests that farm output could be increased 6-20% through a more equitable allocation of productive resources between male and female farmers (World Bank, 2001).

The nature of farming is changing in many African countries because of demographic changes: the farm population is aging, rural male workers are migrating to urban areas, and many rural areas are becoming urbanized (IAC, 2004). These changes imply an increasingly diverse clientele for agricultural research and the need to give much more attention to women farmers and older farmers. Moreover, although most poor, rural Africans still depend heavily on agriculture for their livelihoods, many also have diversified into non-farm income sources, including small-scale, rural non-farm enterprises, non-farm employment and seasonal migration. As a result, many small farms may give lower priority to farming than non-farm activities and may not take up promising new technology options that compete for labor. On the other hand, more diversified households may have more capital of their own to invest in new agricultural technologies and resource improvements and be better able to withstand shocks and risks.

Smallholders dominate the agricultural sector and have shown a capability of adopting new technology options where the right incentives and market opportunities exist (IAC, 2004). Each 10% increase in smallholder agricultural productivity in SSA can move almost 7 million people above the dollar-a-day poverty line (IFPRI, 2006). Due to the growth multipliers between agriculture and the rural non-farm sector, the urban poor benefit along with the rural poor from broad-based agricultural productivity growth (IAC, 2004).

1.2.5 Agricultural R&D investments
Despite the evidence of high returns from agricultural research and its importance for agricultural development, growth in agricultural research and development (R&D) investments has stagnated in sub-Saharan Africa. In addition, due to political, social, and economic unrest as well as institutional changes (mergers, subdivisions, relocation, reshuffling and so on), research systems have experienced greater instability than those in other regions in the world. As a result public agricultural research spending has fluctuated in many countries (Beintema and Stads, 2006).

Most of the growth in sub-Saharan African agricultural R&D spending took place in the 1960s when real (inflationadjusted) investments in agricultural R&D increased by an average of 6.3% per year. Annual growth declined from 1.3% during the 1980s to only 0.8% in during the 1990s

Table 1-3. Measures of inequality for Africa relative to other world regions in the 1990s.

Inequality indicators Average Standard
Maximum Minimum East Asia
& Pacific
Gini Coefficient
Share of top 20%
Share of middle class
Share of bottom 20%

Source: UNECA, 1999.