Book Description

A substantial amount of the literature has reported on the impact of access to credit on technology adoption, and many studies find that credit has a positive impact on adoption. However, most existing studies have failed to explicitly measure and analyze the amount of credit that farm households are able to borrow and whether they are credit constrained or not. They overlooked the fact that credit access can be a panacea for non-adoption only if it is targeted at households that face binding liquidity constraints. Guided by the frame work of a household model under credit market failure, this paper aims at investigating the impact of access to credit on the adoption of hybrid maize among households that vary in their credit constraints. The data used in the study is from Malawi collected by the International Food Policy Research Institute (IFPRI). Using the direct elicitation approach, households are classified into constrained and unconstrained regimes. We start by estimating the probability of being credit constrained, followed by an estimation of the impact of access to credit for the two categories of households (credit constrained and unconstrained), while accounting for selection bias. The impact of access to credit is estimated using a switching regression in a Double-Hurdle model. Results reveal that while access to credit increases adoption among credit constrained households, it has no effect among unconstrained households. Results also show that factors that affect adoption among credit constrained households are different from those that that affect adoption among unconstrained household. Landholding size, for example, has opposite effects on adoption in the two regimes of households. The policy implication is that microfinance institutions should consider scaling up their credit services to ensure that more households benefit from it, and in so doing maize adoption will be enhanced.