Abstract
There is exhaustive literature on technology adoption rates and the relationship between technology adoption and relevant socioeconomic and policy variables. Yet adoption estimates derived from the application of standard techniques such as the probit and tobit yield biased estimates. This paper applies the modern evaluation technique: the counterfactual outcome framework to data from about 400 households in Malawi to assess the patterns of diffusion and adoption of improved pigeonpea varieties and their determinants. We find the sample adoption rate of improved varieties to be 14 % while the potential adoption rate if the improved varieties were widely disseminated is estimated at 41 %. The adoption gap resulting from the incomplete exposure to the improved pigeonpea is 27 %. Moreover, adoption is also found to be high among female-headed households, older farmers and those with access to credit. The findings suggest that for increased adoption, there is need for increased involvement of extension workers is the dissemination of information about improved pigeonpea varieties, a robust pigeonpea seed system to increase seed availability to farmers as well as the need for improved access to credit.
Highlights
Technology adoption studies are mainly focused on estimating adoption rates and understanding the relationship between technology adoption, its intensity and relevant socioeconomic, and policy variables
While such studies are quite useful in explaining some of the bottlenecks to technology adoption, they yield biased estimates of both adoption rates as well as determinants of adoption when applied to a population that is not fully aware of the technology
In this paper we provide a micro-perspective of the potential adoption rates and the determinants of adoption of improved pigeonpea varieties among farmers from southern Malawi
Summary
Technology adoption studies are mainly focused on estimating adoption rates and understanding the relationship between technology adoption, its intensity and relevant socioeconomic, and policy variables While such studies are quite useful in explaining some of the bottlenecks to technology adoption, they yield biased estimates of both adoption rates as well as determinants of adoption when applied to a population that is not fully aware of the technology. This is because awareness is an important precondition for adoption to occur, farmer knowledge of the improved varieties is neither random nor universal and may suffer from selection bias.
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