Fairtrade certification has recently gained in importance for various export crops produced in developing countries. One of Fairtrade's main objectives is to improve the social conditions of smallholder farmers. Previous research showed that Fairtrade has positive effects on farmers' sales prices and incomes in many situations. However, more detailed analysis of the effects on food security and other dimensions of household living standard is rare.
Many developing countries are experiencing a rapid expansion of supermarkets. New supermarket procurement systems could affect farming patterns and wider rural development. While previous studies have analyzed farm productivity and income effects, possible employment effects have received much less attention. Special supermarket requirements may entail intensified farm production and post-harvest handling, thus potentially increasing demand for hired labor. This could also have important gender implications, because female and male workers are often hired for distinct farm operations.
With the commercialization of agriculture, women are increasingly disadvantaged because of persistent gender disparities in access to productive resources. Farmer collective action that intends to improve smallholder access to markets and technology could potentially accelerate this trend. Here, we use survey data of small-scale banana producers in Kenya to investigate the gender implications of recently established farmer groups. Traditionally, banana has been a women’s crop in Kenya. Our results confirm that the groups contribute to increasing male control over banana.
In Sub-Sahara Africa, adoption rates of improved crop varieties remain relatively low, which is partly due to farmers’ limited access to information. In smallholder settings, information often spreads through informal networks. Better understanding of such networks could potentially help to spur innovation and farmers’ exposure to new technologies. This study uses survey data from Tanzania to analyze social networks and their role for the spread of information about improved varieties of maize and sorghum.
Labor saving innovations are essential to increase agricultural productivity, but they might also increase inequality through displacing labor. Empirical evidence on such labor displacements is limited. This study uses representative data at local and national scales to analyze labor market effects of the expansion of oil palm among smallholder farmers in Indonesia. Oil palm is labor-saving in the sense that it requires much less labor per unit of land than alternative crops.
This study analyse how agricultural extension can be made more effective in terms of increasing farmers’ adoption of pro-nutrition technologies, such as biofortified crops. In a randomised controlled trial with farmers in Kenya, the authors implemented several extension treatments and evaluated their effects on the adoption of beans biofortified with iron and zinc. Difference-in-difference estimates show that intensive agricultural training can increase technology adoption considerably.
Background
Weather risk is a serious issue in the African small farm sector that will further increase due to climate change. Farmers typically react by using low amounts of agricultural inputs. Low input use can help to minimize financial loss in bad years, but is also associated with low average yield and income. Increasing small farm productivity and income is an important prerequisite for rural poverty reduction and food security. Crop insurance could incentivize farmers to increase their input use, but indemnity-based crop insurance programs are plagued by market failures.
Classical innovation adoption models implicitly assume homogenous information flow across farmers, which is often not realistic. As a result, selection bias in adoption parameters may occur. We focus on tissue culture (TC) banana technology that was introduced in Kenya more than 10 years ago. Up till now, adoption rates have remained relatively low.
Most micro-level studies on the impact of agricultural technologies build on cross-section data, which can lead to unreliable impact estimates. Here, we use panel data covering two time periods to estimate the impact of tissue culture (TC) banana technology in the Kenyan small farm sector. TC banana is an interesting case, because previous impact studies showed mixed results. We combine propensity score matching with a difference-in-difference estimator to control for selection bias and account for temporal impact variability.