Policy brief No. 1. In recent years, food consumers have become in- creasingly aware of and concerned about the sa- fety of food products. As a response, public and private actors have introduced different standards to ensure that food safety reaches the degree de- manded by consumers. Developing countries often lack the institutional capacities and financial and non-financial resources to comply with standards.
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.
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.