This article was written by UC Davis ARE PhD student Isaac Ahimbisibwe.  It is the seventh in a series of excellent articles written by students in my ARE 231 class this fall.

Agricultural land has expanded significantly in Sub-Saharan Africa (SSA) since the 1980s and has been the biggest driver of growth in agricultural production according to this FAO report (pg 64). Since 1990, agricultural land as percentage of the total land has increased by about 10% in SSA and has remained flat in the world as a whole.

The SSA population has increased by a factor of five since 1950, and it has doubled since 1990. The population increases occurring throughout the region. The world population has tripled since 1950 and increased 50% since 1990.

The value of agricultural production per capita has stayed relatively constant in SSA since 1960, yet it has increased by 50% in the rest of the world. Thus, agricultural production in SSA has kept pace with population, but there is scope for significant productivity increases. Moreover, because population has grown faster than agricultural land, farm sizes have decreased. For example, the same FAO report (page 60) states that 80% of farms in SSA are small holders.

 

Despite the lack of growth in per capita production, agriculture provides a livelihood for the most vulnerable populations, such as the poor, women, and youth.  Agriculture growth will play a critical role in achieving sustainable development goals. Moreover, this growth must come from productivity growth, in addition to land expansion, to meet the pace of population growth.

Three factors account for low production and productivity growth, which should be considered in government policy.

First, African farmers are affected more by globalization and risks from weather and price shocks. While these shocks are not unique to African farmers, they are more vulnerable because they are less shielded with limited access to agricultural insurance and risk management tools. 

Second, African farmers have limited access to capital, which limits investment in profitable, yet risky activities. Research shows many poor farmers do not offer their land as collateral in fear of losing it, while others who seek capital do not qualify due to a lack of collateral. Many development economics studies have carried out microfinance interventions across Africa but results and mechanisms remain largely inconclusive.

Third, agricultural productivity is limited by technology adoption. Fertilizer and drought resistant crop varieties have been shown to be helpful in dealing with unfavorable climate and weather conditions in SSA, but uptake remains low.

Recent findings in behavioral economics provide some explanations for suboptimal adoption of technology and risk management strategies in addition to market failures. Many small-scale farmers suffer from time inconsistent behavior.   For example, Esther Duflo and co-authors  show  West Kenyan farmers did not purchase fertilizer when they had cash after harvest, choosing instead to wait until later in the new growing season, at which time other expenses came due and they didn’t purchase fertilizer. This shows present biased farmers naively overestimate their ability and capacity to invest in the future.

To protect farmers against risk, innovative insurance products such as index or rainfall insurance, which solve moral hazard and asymmetric information problems, have been developed and shown to be effective. However, take up of such insurance products remains low, which can also be explained by present bias. In addition, insurance and new crop varieties are generally a new concept to many farmers in SSA. Research has shown that learning about technologies meant for responding to stochastic events is hard, especially in areas where such technologies are relatively new.

Governments and NGOs in SSA are working to reverse these trends. They could benefit from investing in and scaling up randomized controlled trials, which evaluate policies addressing both market failures and irrational farmer behavior. Governments need to be aggressive in developing policies, such as tractor and fertilizer subsidies, and correcting credit market failures. 

Those policies could be complemented by simple nudges that address behavioral inconsistences. For example, Casaburi and Willis offer insurance contracts to farmers where the premium is paid at the end of the growing season. The figure below from their paper shows that this adjustment to the contract increases take-up significantly in the treatment group (pay-at-harvest). Offering a menu of contracts with commitment from the farmers where the premium is paid at the end of the season might increase take up among present biased and liquidity constrained farmers. In addition, farmers who delay purchasing fertilizer could benefit from policies that offer subsidies and vouchers with deadlines.

The figures in this article were created using this R code.