Climate change threatens agricultural productivity, especially among smallholder maize farmers in Nigeria. Although climate change adaptation strategies (CCAS) are promoted, evidence on adoption dynamics and income effects remains limited. This study analyzes the determinants of CCAS adoption and its income impacts using advanced econometric methods. Data from 300 maize farmers, selected through multistage sampling across major producing regions, were used. Adoption decisions and intensity were estimated with a Hurdle Negative Binomial model, while income effects across the distribution were assessed using an Instrumental Variable Quantile Treatment Effect (IV-QTE) model to address endogeneity. Results show that gender, age, household size, income, awareness, and access to meteorological information significantly influence adoption decisions. Adoption intensity is mainly driven by household size, farm size, weather information, revenue, and extension access. IV-QTE estimates indicate that CCAS adoption significantly increases net farm income, with the largest gains among lower- and middle-income farmers. The findings highlight the importance of information and institutional support. The study recommends strengthening extension services, improving timely weather information access, and expanding credit-linked training programs to enhance adoption and farmer resilience.

The prevalence of credit constraints has a significant effect on the adoption of biofortified cassava; hence, low productivity on farms. This research, therefore, investigates the effect of credit constraints on the adoption of biofortified cassava (BC) among farming households. A multistage sampling procedure is employed to select 300 cassava farming households for this study. Data is analyzed using descriptive statistics, seemingly unrelated regression, and endogenous switching regression model. The results show that most of the household heads (78%) are not constrained by credit while 22% of respondents are constrained by credit. Out of the 22% that are constrained by credit, 7% are ‘quantity’ constrained (they receive partial credit) while 7.5% are both ‘risk’ (they choose not to submit their applications due to concerns about losing their collateral) and ‘price’ (they do not apply because of high interest rate) constrained. The seemingly unrelated regression model reveals that marital status, household size, years of education and farming experience significantly influenced quantity constraint status; while age, relationship with household head, farming experience and access to information are factors that contribute to the risk constraint status of farming households. The conditional treatment effect (ATT), which assesses the effect of credit constraints on the adoption of BC among farming households, is approximately -11.4 and is statistically significant at 1 %. The study finds that credit constraint has a negative impact on the adoption of BC among farming households in Nigeria after adjusting for both observable and unobserved factors. Therefore, the study recommends that innovative financing mechanisms should be leveraged to help promote the adoption of agricultural technologies such as BC. This will help to improve the nutrition, food security and income of farming households.

The Ordinary Least Squares (OLS) method is widely adopted in studies estimating net profit generation among farmers, despite its strong tendency to produce misleading estimates, particularly when one or more fundamental assumptions are violated. This study examined the determinants of farm income among smallholder cassava farmers in Osun State, Nigeria correcting for various assumptions violations of the classical regression model. Aside from the usual OLS estimator, we employed robust estimators such as Maximum Likelihood-type estimator (M-estimator), Monotone M-estimator (MM-estimator), and Scale estimator (S-estimator) to account for outliers. One hundred and one smallholder farmers in Osun state were randomly selected for the study. Analyses revealed that the major socioeconomic factors affecting farming household profit were access to credit, farm size, years spent in farmers’ associations, years of experience, and distance to the nearest market, which are the major determinants of net farm profit among the cassava-based farming households in the study area. On average, the return on investment (ROI) among cassava-based farming households was found to be ₦1.32 per naira invested. The research findings indicated that cassava cultivation is a profitable venture within the investigated area and recommended robust methodology for effectiveness and accurate information in future analysis.

Access to cash remittances has a positive impact on the food security of people living in developing countries. However, little is known about the impact of access to cash remittances concerning cocoa yield. Therefore, the study investigates the impact of access to cash remittances on cocoa yield. A multistage sampling technique was used to select 300 cocoa farming households for the study. The data were analysed using the exponential double hurdle model (Churdle) estimation process, inverse probability weighted regression adjustment (IPWRA), and endogenous switching regression model (ESRM). According to the ATU estimate, the average farmer would produce a yield of 0.824 times more when he/she has access to cash remittances. The conditional treatment effect (ATT), which assesses the impact of access to cash remittances on cocoa yield, was correspondingly approximately 0.828 and statistically significant at 1 %. As a result, the typical farmer who has access to cash remittances would produce a yield that is 0.828 times more than it would be if he/she did not have access to cash remittances. The study found that access to cash remittances has a positive impact on cocoa yield among farmers in rural Nigeria after adjusting for both observable and unobserved factors.

This research aims to enhance model predictions by introducing a novel approach that combines the Stein estimator technique with principal component regression (PCR) within the linear regression context. The study recognizes the challenges posed by multicollinearity in predictive modelling and addresses them by leveraging the strengths of the Stein estimator and PCR. We compared the novel estimator with other commonly used regression techniques to showcase its superiority theoretically. we investigate the impact of different parameter settings and sample sizes on the performance of the enhanced model predictions via simulation design. We analyzed two real-life data to validate the theoretical and simulation results. The mean squared error was employed to measure the performance gain achieved by the fusion of these techniques. The results show the benefits of combining the Stein estimator and PCR. It also provides valuable insights into advanced techniques for enhancing model predictions.

The relationship between microcredit and variances in profit efficiencies among smallholder poultry farmers has received little attention. This study therefore investigates the impact of microcredit on the profit efficiency of smallholder poultry farmers in Nigeria. A multistage sampling procedure was used to obtain data for the study. The novel, nehurdle estimation procedure of the double-hurdle model, stochastic profit frontier function, and endogenous switching regression models were used to analyze the data. The findings of the first hurdle show that interest rate, loan repayment, access to extension service, and membership in a farmers' organization have a significant impact on the ability of poultry farmers to obtain microcredit, whereas the findings of the second hurdle show that loan repayment period, access to extension service, and bird stock size have a significant impact on the amount of microcredit obtained by smallholder poultry farmers. The SPFF model shows that the average profit efficiency estimate is 73.6 percent, and that flock size, feed, labor, medications, and veterinary service cost have a significant impact on the profit efficiency of poultry farmers. The average ATT is 11.346, and it is statistically significant at 1%. This suggests that farmers who have access to microcredit are substantially more profitable than those who do not. This study is the first, to the best of authors’ knowledge, to establish that access to microcredit has a positive impact on the profit efficiency of poultry farmers. As a result, agricultural programs aimed at increasing the profit efficiency of poultry farmers should include measures that make it easier for them to obtain microcredit.

PurposeA correlation has been shown in the literature between credit constraints and the adoption of agricultural technologies, technical efficiencies and measures for adapting to climate change. The relationship between credit constraints, risk management strategy adoption and income, however, is not well understood. Consequently, the purpose of this study was to investigate how credit constraints affect the income and risk management practices adopted by Northern Nigerian maize farmers.Design/methodology/approachCross-sectional data were collected from 300 maize farmers in Northern Nigeria using a multi-stage sampling technique. Descriptive statistics, seemingly unrelated regression and double hurdle regression models were the analysis methods.FindingsThe results showed that friends and relatives, banks, "Adashe", cooperatives and farmer groups were the main sources of credit in the study area. The findings also revealed that the sources of risk in the study area included production risk, economic risk, financial risk, institutional risk, technological risk and human risk. In addition, the risk management strategies used to mitigate observed risks were fertilizer application, insecticides, planting of disease-resistant varieties, use of herbicides, practising mixed cropping, modern planning, use of management tools as well as making bunds and channels. Furthermore, we found that interest rate, farm size, level of education, gender and marital status were significant determinants of statuses of credit constraints while the age of the farmer, gender, household size, primary occupation, access to extension services and income from maize production affected the choice and intensity of adoption of risk management strategies among the farmers.Research limitations/implicationsThe study concluded that credit constrained status condition of farmers negatively affected the adoption of some risk management strategies and maize farmers' income.Practical implicationsThe study concluded that credit constrained status condition of farmers negatively affected the adoption of some risk management strategies and maize farmers' income. It therefore recommends that financial service providers should be engaged to design financial products that are tailored to the needs of smallholder farmers in the study area.Originality/valueThis paper incorporates the role of constraints in influencing farmers' decisions to uptake credits and subsequently their adoption behaviours on risk management strategies. The researcher approached the topic with a state-of-the-art method which allows for obtaining more reliable results and hence more specific contributions to research and practice.

Tomatoes are one of the most significant fruit and vegetable crops in Nigeria. This could be ascribed to the fact that it helps many farmers support their way of life and improve their financial status. However, due to ineffective production management techniques, restrictions on the supply of pesticides and fungicides, access to information, market fluctuations, and crop shelf life, the yield of tomatoes is low. There is a need for powerful institutions like agricultural cooperatives to increase tomato yield. Agricultural cooperatives have been promoted in Nigeria as an agricultural development strategy that will increase crop yield and farmer income. Therefore, this study investigates the impact of membership in agricultural cooperatives on the yields of smallholder tomato farmers in rural Nigeria. A multistage sampling procedure is used to collect data for the study. The Endogenous Treatment Regression model was used to analyze the data. According to the findings of the first regression (Probit regression), age, years of formal education, main occupation, years of farming experience, farm size, years of experience in tomato farming, aged dependents, distance to market, access to credit service and access to extension service have a positive and significant impact on the membership of farmers in the agricultural cooperative. The results of the endogenous treatment regression model reveal marital status, age, years of formal education, years of informal education, main occupation, years of farming experience, farm size, years of tomato farming, aged dependents, distance to market, access to credit services, cost of processing, access to extension service and agricultural cooperative membership are all statistically significant variables influencing tomato yield. According to the ATE estimate, the average farmer would produce 9.159 times more when he/she joined an agricultural cooperative. The conditional treatment effect (ATT), which assesses the impact of membership in agricultural cooperatives on tomato yield, was correspondingly approximately 9.447 and statistically significant at 1%. As a result, the typical farmer who is a member of an agricultural cooperative would produce a yield that is 9.447 times more than it would be if he/she was not a member of an agricultural cooperative. The study found that membership in agricultural cooperatives has a positive impact on tomato yield among smallholder farmers in rural Nigeria in contrast to what it would have been in the absence of being a member of agricultural cooperatives after adjusting for both observable and unobserved factors. Tomatoes farmers must be encouraged to join an agricultural cooperative to boost their yield.

Ghana is currently experiencing stagnant agricultural growth as a result of significant differences between actual and potential crop productivity. Village Savings and Loans Associations (VSLAs) are essential in bringing financial services to rural areas where access is scarce. The study investigates smallholder women groundnut farmers' participation in Village Savings and Loans Association (VSLA) programme and its impact on farm productivity and income in Northern Ghana. The data was collected from 384 smallholder women groundnut farmers using multistage sampling technique and analyzed using descriptive statistics, Endogenous switching regression (ESR), Propensity Score Matching (PSM) and Kendall's Coefficient of Concordance. The findings of the ESR showed that membership of Farmer Based Organization (FBO), radio ownership and dependency ratio positively influenced the probability of women groundnut farmers' participation in the VSLA programme. However, extension services, years of living in the community, groundnut farming experience, farm size and input cost have negative influence on women farmers' participation in the VSLA programme. In addition, the results of the ESR and PSM showed that VSLA programme participation significantly increased participants' farm productivity and income. The small amount of available loans and short-term loan period were major challenges faced by the VSLA programmes and these limited investments in long-term activities. The study therefore suggests that VSLAs should tailor their savings and lending modalities to the needs of the farmers. To overcome the delivery challenges of VSLA credit, women groundnut farmers should use part of their loans from the VSLA programme to start off-farm income generating activities.

Introduction Whilst the coronavirus disease 2019 (COVID-19) vaccination rollout is well underway, there is a concern in Africa where less than 2% of global vaccinations have occurred. In the absence of herd immunity, health promotion remains essential. YouTube has been widely utilised as a source of medical information in previous outbreaks and pandemics. There are limited data on COVID-19 information on YouTube videos, especially in languages widely spoken in Africa. This study investigated the quality and reliability of such videos. Methods Medical information related to COVID-19 was analysed in 11 languages (English, isiZulu, isiXhosa, Afrikaans, Nigerian Pidgin, Hausa, Twi, Arabic, Amharic, French, and Swahili). Cohen's Kappa was used to measure inter-rater reliability. A total of 562 videos were analysed. Viewer interaction metrics and video characteristics, source, and content type were collected. Quality was evaluated using the Medical Information Content Index (MICI) scale and reliability was evaluated by the modified DISCERN tool. Results Kappa coefficient of agreement for all languages was p < 0.01. Informative videos (471/562, 83.8%) accounted for the majority, whilst misleading videos (12/562, 2.13%) were minimal. Independent users (246/562, 43.8%) were the predominant source type. Transmission of information (477/562 videos, 84.9%) was most prevalent, whilst content covering screening or testing was reported in less than a third of all videos. The mean total MICI score was 5.75/5 (SD 4.25) and the mean total DISCERN score was 3.01/5 (SD 1.11). Conclusion YouTube is an invaluable, easily accessible resource for information dissemination during health emergencies. Misleading videos are often a concern; however, our study found a negligible proportion. Whilst most videos were fairly reliable, the quality of videos was poor, especially noting a dearth of information covering screening or testing. Governments, academic institutions, and healthcare workers must harness the capability of digital platforms, such as YouTube to contain the spread of misinformation.

Access to microcredit has received a lot of attention, but, its role in the adoption of climate change adaptation strategies and improvement of rice yield is not often debated. This study investigated the impacts of access to microcredit on the adoption of climate change adaptation strategies and the yield of rice farmers. A multistage sampling procedure was employed to select 320 rice farmers for the study. Data collected were analyzed using descriptive statistics, the Multivariate Probit regression model, the Poisson regression model with endogenous treatment, and the Endogenous Switching Regression Model. The descriptive results for the entire sample show mean values of 45 years for age, 9 people for household size, 20 years for farming experience, and 19 hectares for farm size. The result also showed that many of the rice farmers are male (94%), married (92%), educated (97%), and belong to rice farmer's associations (85%). Most of the rice farmers have access to microcredit (80%) and the farmers depend largely on their funds from other enterprises (100%). Many of the farmers mostly adopted high-quality-improved seeds (92%). Further findings reveal that age, educational status, household size, farm size, and years of farming experience are factors that largely determine the choice of climate change adaptation strategies adopted. The study also revealed that access to microcredit significantly affected the intensity of adoption of climate change adaptation strategies; and farmers' age, education, and farm size significantly affected rice yield. Hence, policies that can promote increased access to microcredit should be promoted.

This study investigated the effect of microcredit on profit efficiency of small-scale poultry farmers in Oyo State. Multistage sampling procedure was used to select two hundred poultry farmers for the study. Data collected were analysed using descriptive statistics, Heckman selection model, stochastic frontier and Tobit models. Result from descriptive statistics showed that men (78%) are predominantly involved in poultry production. The average age of poultry farmers in the area of study is approximately 43 years. Most of the farmers are married (77.5%) and literate (80.5%). Furthermore, most of the respondents (73.5%) had access to microcredit with 87.5% belonging to one farmer’s association or the other. Heckman two-stage selection model revealed that membership of cooperative/farmer’s association and contact with extension agent are the significant factors influencing farmer’s access to microcredit. The second stage of the model reveals that age, years of education, household size, years of farming experience, distance to source of microcredit, timeliness of microcredit and stock size are the significant factors influencing the amount of microcredit obtained by farmers. Results obtained from the stochastic frontier model showed that smallholder poultry farmers had an average profit efficiency of 54.0% in poultry production. Furthermore, the Tobit model (Model 1) results revealed that amount of microcredit, distance to source of microcredit, interest rate and loan repayment period significantly influenced farmer’s profit efficiency while in the second model, years of formal education, poultry farming experience and membership of cooperative/farmer’s association influenced farmer’s profit efficiency. The results of two-side censored Tobit model suggest that microcredit variables are the most favourable variables for line of action. This suggested that policy makers should ensure that microcredit available through the agricultural credit programmes get to the needy farmers.

Most studies on climate change adaptation strategies adoption have focused on economic factors with little or no attention to the impact of collective actions and social capital networks. This paper investigates how farmers' participation in social capital networks influenced climate change adaptation strategies adoption in Nigeria. This study was carried out in the South-western Nigeria. Data were analysed using descriptive statistics, binary probit regression, multinomial logit regression, endogenous switching regression and multinomial endogenous switching regression models. The results suggest that significant differences exist in the years of membership in the social capital networks, access to weather information and market between farm managers who adopted climate change adaptation strategies and those who did not. Plot managers who adopted climate change adaptation strategies are found to have obtained much mean yield and farm revenue than their counterparts. The results further show that participation in the social capital networks does not only significantly influence plot manager's decision to adopt but also influences the choice of climate change adaptation strategies adopted by farmers. The study concludes that a farmer who chooses to participate in social capital networks has a higher level of adopting climate change adaptation strategies than what a random farmer would have had in Nigeria. We recommend that policies aimed at increasing the adoption of climate change adaptation strategies among farmers should be channelled through locally organised farmers-based social capital networks.

This study examined how social capital networks contribute to rural households’ poverty status in Southwestern Nigeria. A multistage sampling procedure was used to select a total of 300 households for this study. A structured questionnaire was used to obtain information and data were analyzed using descriptive statistics, Foster, Greer and Thorbecke (FGT) poverty measure and Two-Stage Least Square model (2SLS). Results showed that poverty incidence, depth and severity were 60%, 46.70% and 20.10% respectively among the sampled households. The results indicated that forms of social capital networks in the study area include cooperative societies, family and friends, farmers’, professional career, religious, and microfinance groups. The results further showed that 66.00% of the households in the study area sourced microcredit from cooperative societies. The 2SLS estimate showed that the coefficient of the aggregate social capital index (β =730.83, p < 0.05) also showed a positive, significant relationship with household per capital expenditure. The result indicated that a unit increase in social capital network index of the household would increase household per capita expenditure in the study area by N730.83. The study concluded that membership of social capital networks positive influence households’ access to access to microcredit and poverty reduction.

Cocoa’s contribution to the economic development of Nigeria is enormous. However, in recent years, income of cocoa farming households has reduced tremendously due to a number of factors. Participation in social groups could increase the households’ income through its benefits, social capital dimensions. Therefore, the study investigated the effects of social capital dimensions on the income of cocoa farming households in Osun State. Multistage sampling procedure was used to select 100 respondents for the study. Data were analyzed using descriptive statistics, social capital indices, farm budgetary techniques and OLS regression model. The results of the study showed 49 years for age, 16 years for year of experience, 6 persons for household size and 6 hectares for farm size. The results also revealed that six dimensions of social capital namely cash contribution, labour contribution, decision-making, meeting attendance, heterogeneity and density of membership were available to the households. The estimated costs and return to cocoa farming households per hectare of land on the average were ₦243,671 and N540,306.4 per annum, while return per naira outlay was ₦2.217 and the benefit cost ratio was ₦2.71. OLS estimates showed that age, farming experience, and social capital dimensions such as decision making and meeting attendance significantly influenced the income of cocoa farming households. The study concluded that social capital dimensions are among important variables influencing the income of cocoa farming households. The study therefore recommends that members of cocoa farming households or household head should be encouraged to be members of farmers’ organization and also actively participate in the decision-making process of the organization. This can be achieved throughregular meeting attendance. Keywords: Cocoa, Farming households, Social capital, Income, Osun State

This study investigated the effects of the social capital on the adoption of improved technology, profitability and productivity among cassava farmers in Osun state. A Multistage sampling procedure was used to obtain information from 100 cassava farmers and the data collected were analyzed using descriptive statistics, tobit, budgetary analysis and stochastic production function models. Results from the study showed an average cassava farmer was young, very active and smallholder in nature. Cassava farmers who participated in social capital network benefitted tremendously from their group because they made more profit and were more efficient than those who did not participate in any social network. The study concluded that cassava farmers who participated in social capital networks were more efficient that those who did not participate in any social network. The study therefore recommended that cassava farmers in the study area should be encourage to participate in social capital networks in order to improve their profit level and productivity. Also in order to promote and facilitate the rate and intensity of adoption of improved technologies among farmers, social capital and group networks should be considered as appropriate channels to introduce and train farmers for maximum impact.

Biofortified (vitamin A) cassava was developed through convectional breeding similar to most other improved varieties cultivated by Nigeria farmers. Despite its potential in addressing the increasing food demand and malnutrition in the country, lack of empirical knowledge about its yield and return on investment has been a major barrier to the uptake of this technology among farmers in Nigeria. This study examined the socio-economic characteristics of vitamin A cassava farmers; analyzed farm level efficiency and return on investment from vitamin A cassava in the study area; determined the factors affecting farm level efficiency and productivity, and examined the constraint to productivity and profitability among vitamin A cassava farmers. A multistage random sampling was used to select a total of 100 vitamin A cassava farmers in the study area. The data collected were analyzed using descriptive statistics, stochastic frontier production function (SFPF), profitability ratio and regression analysis. The results indicated that investing in vitamin A cassava as a business was very profitable. The result showed that 82% of the respondents were male, the mean age of the farmers was 53.25, 49% had only primary school certificate education, 66% farmed on the land between 1-2 hectares. The result further showed that on the average, total revenue was N261511.90, the total variable cost was N87754, gross margin was N173757.9, total cost was N179828.8, and net income was N81683.05. Mean technical efficiency was 78.73%. The study concluded that vitamin A cassava production in the study area was efficient and profitable. These results have implications for the design of effective advocacy strategies to attract more farmers into vitamin A cassava production in Nigeria.

Profit is the driving force for any enterprises to thrive well, because it encourages more investment into an enterprise. One of the major barriers to investing in plantain value chain is inadequate information on return to investment. Thus, this paper investigated profitability of investors along plantain value chain in Osun state. A multistage sampling procedure was used to elicit information from 100 respondents for the study. Data were analysed using descriptive analysis, budgetary analysis, and multiple regression analysis. Descriptive statistics reveal that average age was 52.2 (±11.19) years for plantain farmers, 41.8 (±10.78) years for processors and marketers 33.42 (±11.99). While, average farming experience was 26.9 (±10.88) years for plantain farmers, 12.47 (±10.78) years for processors and marketers 5.84 (±19.12). About 6.7% farmers, 15.6% processors and 13.2% marketers had access to credit facilities. The budgetary analysis showed that benefit-cost ratios were $1.38, $1.30 and $1.19 for the farmers, processors and marketers, respectively. Multiple regression estimates revealed that insecticide used (p<0.1) and numbers of plantain harvested (p<0.01) significantly influenced the profitability of the plantain farmers, while age (p<0.1), level of formal education (p<0.05), amount invested into the business (p<0.01) and household size (p<0.05) significantly influenced the profitability of the plantain marketers. Only household size (p<0.01) significantly influenced the profitability of the plantain processor. In accordance with the findings of the study, we therefore recommend that subsidized cost of inputs and better access to credit among the investors along the value chain would increase the level of return to the investment.