This study examines the effect of fertiliser subsidy on application rates of fertiliser among maize farmers in Northern Region. The study uses cross-sectional data from 301 households in the northern region of Ghana. The Probit and Tobit models were respectively used to analyse the determinants of participation in the subsidy programme and the effect of participation on fertiliser application rates. The results of the study show that farm size, price of the subsidised fertiliser, distance to input dealers, amount of credit borrowed and off-farm income are key determinants of farmer's participation in the subsidy programme. Participation in the subsidy programme was found to exert a positive effect on the quantity of fertiliser farmers applied on their farms. The study recommends among other things, the inclusion of cash credit schemes in the subsidy programme as smallholders still found the down payment 79% of the cost of fertiliser high. The study also suggested restructuring in the subsidy programme to allow for channelling of fertiliser through farmer-based organisations (FBOs) in order to curb exploitation by politician and elite farmers.
Purpose The purpose of this paper is twofold: to determine the factors contributing to farm income in the Transitional and Savanna zones of Ghana and to ascertain variations between in the same and across the two locations; and to determine the impact of credit on farm income in each of the two zones and to ascertain the variation in impact of credit across the two locations. Design/methodology/approach In order to address endogeneity and sample selection bias, the authors draw from the theory of impact evaluation in nonrandom experiment, employing the endogenous switching regression (ESR) while using the propensity score matching (PSM) to check for robustness of the results. Findings The results show significant mean differences between some characteristics of households that have access to credit and those that did not have access. Further, the results revealed farm size, labor; gender, age, literacy, wealth and group membership as the significant determinants of both credit access and income in the two zones. With the ESR, credit access increases households farm income by GH¢206.56/ha and GH¢39.74/ha in the Transitional and Savanna zones, respectively, but with the PSM, credit increases farm income by GH¢201.50 and GH¢45.69 and in the Transitional and Savanna, respectively. Research limitations/implications The mean differences in characteristics of the households revealed the presence of selection bias in the distribution of household’s covariates in the two zones. The results further indicate the importance of productive resources, information and household characteristics in improved access to credit and farm income. Also, the results from both methods indicate that credit access leads to significant gains in farm income for households in both zones. However, differences exist in the results of PSM and that of the ESR results. Practical implications The presence of selection bias in the samples suggests that the use of ESR and PSM techniques is appropriate. Further, the results suggesting that enhanced credit access and farm income could be attained through improved access to household resources and information. The results also suggest the need for establishing and expanding credit programs to cover more households in both zones. The differential impact of credit between the two methods employed in each zone revealed the weakness of each model. The low values from PSM could indicate the presence of selection bias resulting from unobservable factors whiles the high values from the ESR could stem from the restrictive assumption of the model. This reinforces the importance of combining mixed methods to check robustness of results and to explore the weakness of each method employed. Originality/value The novelty of this study lies in the use of a very extensive and unique data set to decompose the determinants of credit access and farm income and as well as the impacts of credit into zones.
At the onset of climate change, the adoption of soil and water conservation (SWC) techniques in Africa sub of the Sahara has become even more crucial. The study aimed at estimating the determinants and effects of SWC adoption. The data was obtained from the Ghana Agriculture Production Survey (GAPS), a national level survey conducted by Ghana's Ministry of Food and Agriculture with technical and financial support from the International Food Policy Research Institute (IFPRI). A total sample size of 1,530 farm households selected from 20 districts across Ghana was used. The Poisson model was employed to estimate the determinants of adoption of SWC technology while the stochastic frontier model was used to analyze the effects of SWC technology adoption on technical efficiency. The study found that SWC adoption significantly affected technical efficiency in maize production. Significant policy variables that were found to positively influence the adoption of SWC techniques included credit, farm size, group membership and proximity to input sale points. Also, credit, education and extension services significantly influenced farmers' technical efficiency. There is the need for a holist approach to supporting farmers. In general, access to education, extension services and credit must be stepped up. Farmers must also be supported to form farm groups as a viable source of farm labour.
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