Purpose – The purpose of this paper is to examine the impact of agricultural credit on technical efficiency of Ghanaian maize farmers using a unique dataset drawn from the database of Sub-Saharan Africa’s intensification of food crops agriculture (Afrint II) in 2008 period. Design/methodology/approach – In this study, a two-stage estimation procedure is employed to determine impact of agricultural credit on technical efficiency of Ghanaian maize farmers. The first stage utilized probit model while the second stage utilized stochastic frontier approach to estimate impact of credit on technical efficiency of Ghanaian maize farmers. Findings – The study found that farmers are producing below the frontier with average technical efficiency of 47 percent. Policy variables such as credit access; education, extension access and farm size played a stronger role in technical efficiency. Agricultural credit in particular increased technical efficiency by 3.8 percent. Research limitations/implications – The results should not be extended to the impact of agricultural credit on economic efficiency since the allocative efficiency component is not considered in this study. Also, caution should be taken in the interpretation of these results because the data could not permit the incorporation of all variables that might affect technical efficiency. Originality/value – The originality of the paper and its contribution to existing literature largely lies from the use of a unique dataset to find evidence of the impact of credit on efficiency in Ghana.

Purpose – This paper aims to investigate the determinants of the motivation to pay tax in Ghana. Traditionally, raising tax morale to ensure compliance is often tied to the level of prevailing enforcement. But beyond enforcement, why do citizens pay tax? Design/methodology/approach – This paper relied on the sixth wave of the World Values Survey data in determining the drivers of tax morale. It used the probit model with different specifications to determine robustness of the results. Findings – The findings remain robust to model specification and show a non-linear relationship between age and tax morale. The level of education, marital status, patriotism, sector of employment, satisfaction with democracy and one’s “fear of God” do not matter in tax morale. The economic class of a person per se is also far from being a significant driver and that people are intrinsically motivated to pay tax once they are satisfied with their financial situation, have trust in the government as well as confidence in the parliament. Originality/value – In addition to being a pioneering micro-econometric work on the determinants of tax morale in Ghana, the main contribution of the study lies in its investigation of a non-linear relationship between age and tax morale in Ghana.

Purpose The purpose of this paper is to investigate factors affecting the adoption of agricultural technologies in Sub-Saharan Africa, specifically the role of credit market inefficiency in adoption of agricultural technologies in the region. Design/methodology/approach Most importantly, the paper applies a 2SLS model on a unique data set on nine agrarian countries from Sub-Saharan Africa’s intensification of food crops agriculture (Afrint) to provide evidence on how credit market inefficiency affects adoption of technologies in the sub region. Findings The study finds that the relationship between credit and technology adoption is one-way causal relation (i.e. credit access leads to technology adoption) as opposed to a two-way relation (i.e. mutual dependent relation). Further, the results indicate that credit market inefficiency can be a major barrier to the adoption of yield enhancing technologies in Sub-Saharan Africa. Further, the study showed mixed results for household variables. The results give credence to studies that highlight the importance of infrastructure and risk control in the adoption of new technologies. Research limitations/implications The study is limited to only nine countries in Sub-Saharan Africa. Thus, the findings and interpretations should be considered as such. Further, there is the need for further research that considers all the region so as to establish whether or not there is a relationship between credit market inefficiencies and technology adoption in the region. Practical implications 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 technology adoption will be enhanced. Originality/value The main contribution of the study lies in its use of a unique data set from Sub-Saharan Africa’s intensification of food crops agriculture (Afrint) to investigation relationship between credit market inefficiency and technology adoption.

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.

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