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.
Abstract:The study determined the levels of New Rice for Africa (NERICA) technology adoption and identified the factors influencing the levels and intensity of technology adoption among the NERICA rice farmers with a view to improving NERICA production among rice farmers in the study area. A multi-stage sampling technique was used to select 200 NERICA rice farmers for the study. Primary data collected were analyzed using descriptive statistics and technology adoption index. Results showed that there were two main levels of NERICA technology adoption among the farmers based on the mean adoption index 0.9547. These were partial adopters with an index of <0.9547 and full adopters with an index of >0.9547. Partial adopters of the NERICA technology accounted for 50.5% of the farmers while full adopters accounted for 49.5%. The levels of adoption of NERICA technology was influenced by factors such as age, farming experience and quantity of fertilizer used while intensity was influenced by factors such as number of labour used, farming experience and quantity of fertilizer used. The study concluded that the adoption rate of NERICA technology in Ogun State could be improved by increasing the quantities of seed, number of labour and appropriate use of fertilizer.
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.
The study examined the determinants of farmers’ access to microcredit from cooperative societies in Ondo state. A multistage sampling technique was used to obtain data from 100 respondents. Primary data was collected for the purpose of the study. We used descriptive statistics and logit regression model to analyses the data collected. Result showed that the farmers were mostly male farmers (64%) while majority of the farmers had a mean age of 44.10 ± 14.70. It was also revealed that consumer cooperative society, producer cooperative society, marketing cooperative society, cooperative farming society and credit and thrift cooperative society were the major forms of cooperative used by the farmers. The result also shows that age, marital status, farm size, farming experience, credit from another source and number of years in the cooperative significantly influenced farmers’ access to microcredit from cooperative society. Int. J. Agril. Res. Innov. Tech. 11(2): 103-107, Dec 2021
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