In agricultural-dependent economies, extension programmes have been the main conduit for disseminating information on farm technologies, support rural adult learning and assist farmers in developing their farm technical and managerial skills. It is expected that extension programmes will help increase farm productivity, farm revenue, reduce poverty and minimize food insecurity. In this study, we estimate the effects of extension services on farm productivity and income with particular reference to agricultural extension services delivered by Association of Church-based Development NGOs (ACDEP). The study used cross-sectional data collected from 200 farm households from two districts in the Northern region of Ghana. The robustness of the estimates was tested by the use of regression on covariates, regression on propensity scores and Heckman treatment effect model. The study found positive economic gains from participating in the ACDEP agricultural extension programmes. Apart from the primary variable of interest (ACDEP agricultural extension programme), socio-economic, institutional and farm-specific variables were estimated to significantly affect farmers’ farm income depending on the estimation technique used. The study has reaffirmed the critical role of extension programmes in enhancing farm productivity and household income. It is, therefore, recommended that agricultural extension service delivery should be boosted through timely recruitment, periodic training of agents and provision of adequate logistics.

This study aims to identify the determinants of adoption of improved maize variety (IMV) among farmers in the northern region of Ghana and subsequently assess the factors influencing the intensity of IMV adoption. The study used two econometric techniques to address its objectives. Firstly, a multinomial logit was employed to identify factors affecting the adoption of IMV. Secondly, Tobit regression was used to analyze the determinants of the intensity of IMV adoption. A fractional regression model through the procedure proposed by Papke and Wooldridge was also used to test the robustness of the results obtained from the Tobit model. Results from the study revealed that variables such as the age of the household head, household size, level of experience, farm workshop attendance, the number of years in formal education, access to agricultural credit, membership of a farmer-based organization, availability of labor and extension contacts influence the adoption of IMV. Moreover, variables such as years in formal education, household size, distance to farm plots, attendance of demonstration fields, membership of a farmer-based organization, farm size, and previous income are significant determinants of the intensity of IMV adoption. The study has implications for achieving food security and poverty reduction through agricultural productivity growth.

This study explored the potential impact of rural non-farm income diversification on households' welfare and adoption of Zai-technology (a proxy for agricultural technology adoption) using primary data collected from agricultural households in the Upper East region of Ghana. We used Propensity Score Matching (PSM) and Inverse-Probability-weighted Regression Adjustment (IPWRA) techniques to estimate welfare and Zai-technology impacts of non-farm income diversification. After controlling for differences in covariates, the results show that non-farm income diversification increases the likelihood of Zai-technology adoption and contributes to significant household welfare gains. We therefore suggest that the activities of agricultural extension services and farmer-based organizations (FBOs) be enhanced as they facilitate the diversification of non-farm incomes, thereby increasing investment in productivity-enhancing technologies (Zai) and household welfare.

Climate change significantly impacts global agricultural productivity. Therefore, a more dynamic farming system is needed to enable farmers to better adapt to climate change while contributing to efforts to produce enough food to feed the growing world population. In the context of climate change, this study analyzed the empirical scientific literature on the link between climate-smart agriculture and farm productivity. To evaluate the relevant articles, the authors used the search term “climate-smart agriculture amidst climate change to enhance agricultural production (CSA-CCAP)” to find studies published between 2009 and March 2022 using innovative bibliometric techniques. One hundred and sixteen published papers in BibTeX format were downloaded for further analysis. The most successful selected CSA approaches in Africa, such as in the Congo Basin forest, including sustainable land management practices, water-efficient maize hybrids, and others, aim to counteract climate change with signs of 200 percent output gains. The findings showed an annual growth rate of about 19%, demonstrating that research on CSA-CCAP expanded over time during the study period. Nonetheless, the research output on CSA-CCAP varied, with 2021 accounting for 30%, followed by 2020 with 16% as of March 2022. The study concluded that boosting agricultural productivity in the face of climate change may be accomplished through CSA to end hunger, eradicate poverty, and improve people’s well-being.

This study explores smallholder cocoa farmers’ adoption decisions of agrochemical inputs in the Ghanaian cocoa industry using farm-level data collected from a sample of 838 farm households in four cocoa producing regions. Multivariate probit and Tobit models were used to examine the determinants of agrochemical inputs adoption and the extent of adoption, respectively. The result of the study showed that agrochemical management practices are complementary and thus the adoption of an agrochemical input is conditional on the adoption of others. Different household characteristics, household assets, institutional variables, and the perception of soil fertility status and the incidence of pests and diseases influence the adoption of individual agrochemical inputs. Furthermore, the result of the study showed that intensity (or extent) of agrochemical adoption (measured as farmers’ expenditure on agrochemicals) is also influenced by some socioeconomic and institutional variables such as extension services and farmers’ visits to demonstration farms. The implication of this result provides empirical guidelines necessary for farm-level programmes designed to improve adoption and intensity of adoption of agrochemical management practices in the Ghanaian cocoa sector.

The use of agricultural technology, such as high-yielding seed varieties in developing countries where the primary source of livelihood is agriculture is vital in reducing poverty, hunger, and promoting food security. This study examined the productivity impact of improved rice varieties (IRV) among smallholder farmers in South West, Nigeria, using cross-sectional data obtained from a sample of 250 rice farming households. The propensity score matching (PSM) technique was used to evaluate the impact of IRV adoption on rice productivity. The results of the study indicated that educational attainment, experience in rice farming, extension contact, access to credit, and access to IRV seeds had a positive and statistically significant influence on the adoption of IRV. Moreover, adopters of IRV gain 452 kg more rice grains per hectare of rice farms. The paper concludes that strengthening extension services using new strategies like electronic and social media may be more effective than the conventional method of extension delivery. Also, having an effective credit scheme and making the improved seeds physically accessible to farmers will increase adoption of IRVs, and subsequently boost farm productivity.