Abstract
The determinants of adoption of technologies are mostly focused on socio-economic and demographic characteristics of farmers, overlooking the impact of corruption and preferential treatments (partisanship, nepotism and tribalism). We extend technology adoption predictors to include preferential treatment, and the results are explained with Relative Deprivation Theory. We used survey data collected from participants and nonparticipants of Planting for Food and Jobs (PFJ) programme in 2019. Respondents were rice farmers from three regions (Northern, Savannah and North-East regions) of Northern Ghana. We analysed the data using Systematic Probit Regression model after satisfying variables differential and correlation assumptions. The results revealed that while partisanship and tribalism are significant inverse factors, corruption is an insignificant negative determinant of participation in PFJ. We find nepotism to have a strong positive correlation with participation in PFJ. We recommend that government should plug all the loopholes facilitating corruption and preferential treatment if it intends to increase participation and rice productivity effectively.
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