Scholarly works in Agricultural Economics
Permanent URI for this collectionhttps://repository.ui.edu.ng/handle/123456789/454
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Item Risk coping behaviour of small scale poultry farmers in Ogun State, Nigeria(Academic Journals Inc., 2013) Adepoju, A. O.; Timothy, O. A.; Oyekale, A. S.Poultry farmers in Nigeria are faced with diverse forms of risks. In the absence of any form of insurance and the almost inexistent credit markets, households have devised strategies to at least mitigate the effect of these risks on their livelihoods. This study analyzed the risk-coping strategies and potential of 116 small scale poultry farmers in Ogun State. The analytical techniques used included descriptive statistics, Mean Absolute Deviation (MAD) and the Ordinary Least Square (OLS) regression model. Results revealed that the major idiosyncratic risks faced by the farmers were death of birds, high costs of inputs and low poultry production. On the other hand, the major types of covariate risks faced by the poultry farmers include outbreak of diseases, rainfall shocks and hard economic times. Coping methods that were mostly used included drawing from personal savings, rearing of resistant breeds and restocking of birds. Econometric analysis revealed that factors such as number of years of formal education of the household head, initial capital outlay and proportion of non-farm to the total monthly income had positive impacts on the risk-coping potentials of the poultry farmers. The negative impacts of factors such as household size on the potential of the poultry farmers to cope with risks were also noted. Thus, the risk behavior of farmers and the factors influencing such behavior should be considered in the design and development of effective programs for the farmers.Item Determinants of poverty among riverine rural households in Ogun State, Nigeria(Kamla-Raj, 2012) Oyekale, A. S.; Adepoju, A.O.; Balogun, A.M.This paper analyzed the poverty status of rural households in Ogun Waterside Local Government Area of Ogun State. Data were collected from 125 households using multistage sampling procedure. Descriptive and Probit regression analytical approaches were used for data analysis. Results show that 28.8 percent of the households were poor. Poverty was perceived to be driven by unemployment, low-investment and neglect by government. Probit results revealed that having farming as primary occupation and household size significantly increased poverty (p<0.10), while amount of credit/loan obtained, educational attainments and monthly expenditure of household significantly reduced it (p<0.10). To alleviate rural poverty, the study concluded that households should have adequate access to affordable and easily accessible credit facilities, among others.Item Factors influencing domestic energy choice of rural households in Ogun State, Nigeria(Friends Science Publishers, 2012) Adepoju, A. O.; Oyekale, A. S.; Aromolaran, O.Choices of domestic energy that are made by rural households are able to influence environmental conservation and sustainable development. This study determined the factors influencing choice of energy by rural households. Data were collected from randomly sampled households. Analysis was done with descriptive statistics and Logit regression. Result showed that the largest proportion of the respondents used kerosene oil for cooking and lighting. Logit regression results showed that there was gender influence in fuel wood choice. Also, illiterate household heads had higher likelihood of choosing charcoal. Choices of kerosene oil and electricity were influenced by proximity. It was recommended that efforts to address energy problem in rural areas should take cognizance of ensuring availability and affordability of cleaner energy sources, among others.Item Household’s willingness to pay for malaria medical treatment in Ibarapa East local government area of Oyo State, Nigeria(Rushing Water Publishers Ltd., 2012-12) Adepoju, A. O.; Ogunmodede, A. S.; Oyekale, A. S.Malaria is a disease that has negatively affected livelihood of many households in Nigeria. This study analyzed the factors influencing households’ willingness to pay for medical treatment of malaria by selected rural households in Oyo state. The data were collected with structured questionnaires that were administered to households using multi-stage sampling method. Data analysis was done with descriptive statistics and Logit regression. Results show that 16.9% of the respondents are willing to pay below or exactly W500 for malaria treatment using insecticides, 18.1% of the respondents are willing to pay between N-1000Item Productivity of women farmers in the derived savannah zone of Nigeria:Panacea to food crisis(Journal of Research in Agriculture, 2010) Yusuf, T. M.; Okunmadewa, F. Y.; Adenegan, K. O.; Oyekale, A. S."There is food crisis in Nigeria. Food supply can no longer meet up with food demand. Since Women Farmers are the major food producers in Nigeria, it implies that their productivity is significantly low. This study therefore, explored the potential for improving productivity of women farmers in the Derived Savannah Zone of Nigeria. Primary data were collected using multi-stage random sampling technique. Kogi and Kwara states were randomly selected from the six states in the zone. Following this was a random selection of two ADP administrative zones from each slate. A random selection of four LGAs was then made, one from each ADP stratum from which four villages were selected per LGA. In the final stage 200 respondents were randomly selected from the villages on the basis of probability proportionate to size. Data were collected on socio-economic and demographic characteristics, institutional factors, quantities and prices of inputs and outputs. Data were analysed using Descriptive Statistics, Total Factor Productivity Analysis (IFP), and Ordinary Least Squares Regression (OLS) Analysis. The mean age and farming experience of the women farmers were 47.6 ± 9.5 and 20.4± 12.3years respectively. Their mean farm size and number of plots cultivated were 1.8 ± 1.18 acres and 2.0 ± 0.84 respectively. Total factor productivity index ranged from 2.7 to 1,J 04.6 with a mean of 489.9 indicating low productivity level. Factors found contributing to low productivity include; year of farming .extension and land fragmentation. A unit increase in years of education and MEO would increase productivity level by 0.8872 (p<0.01) and 0.1061 (p