National governments, especially in sub-Saharan Africa, have limited budgets and are forced to make difficult funding decisions regarding the provision of social services and the support of agricultural programs. These provisions can play a critical role in rural incomes and agricultural production but due to data constraints, the effects of different types of social services on agricultural productivity in this region have not been analyzed in detail.
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.