Effects of digital agriculture solutions on smallscale wage workers and employment

Abstract

The study examined how the use of digital agriculture solutions affected farm worker pay and on-farm employment. Data gathered, was from 1,199 randomly sampled Small-scale farmers in the Bono East Region of Ghana. To account for potential selection bias resulting from unobservable factors that can influence the adoption of digital agriculture solutions, an endogenous switching regression model was employed. The results show that farmer demographic characteristics (age), farm characteristics (farm size and contract with employees), and institutional support services (group membership, access to training, access to credit and access to agricultural extension services) influence the adoption of digital agricultural solutions by Small-scale farmers in the Bono East region. We provide evidence that a high household income, a large farm size, access to information and participation in FBOs encourage farmers to employ more farm workers and pay higher wages. The study reveals that digital agricultural solutions have the potential to reduce the number of farm workers employed by 52% as well as reduce the amount of wages paid farm workers by 2%. The findings suggest the need for government and development partners to devise strategies that would increase the financial endowment of households and Farmers by making credit more available, expanding the availability of farmers productive resources like land, and increasing household income through livelihood diversification strategies. This move can enhance the use of digital farming technologies and empower farmers to increase on-farm employment and wages.