scholarly journals Socio-economic factors determining rural households access to credit and amount of loan utilization for proposed action: The case of Omo Micro Finance

2021 ◽  
Vol 13 (1) ◽  
pp. 58-63
Author(s):  
Jagiso Fonke Biruk
Keyword(s):  
Rural Households ◽  
Economic Factors ◽  
Access To Credit ◽  
Socio Economic Factors

scholarly journals Socio-economic factors influencing poverty among rural households in onicha local government area, ebonyi state, Nigeria

2019 ◽  
Vol 9 (1) ◽  
pp. 8-13
Author(s):  
VA Eze ◽  
NE Odoh ◽  
OE Igwe ◽  
CJ Mgbanya
Keyword(s):  
Local Government ◽  
Multiple Regression ◽  
Significant Influence ◽  
Rural Households ◽  
Farm Size ◽  
Economic Factors ◽  
Poverty Level ◽  
Factors Influencing ◽  
The Mean ◽  
Socio Economic Factors

The study examined the socio-economic factors influencing poverty among rural households in Onicha Local Government Area of Ebonyi state, Nigeria. The study adopted multistage random and purposive sampling techniques to select 120 household heads. Primary data used for the study were collected using structured questionnaire. The data were analysed with the aid of means, percentage and frequency count and OLS multiple regression model. The result indicated that the households spent an average of N31,250 monthly to take care of their families and other essential personal needs. The result of the socio-economic characteristics showed that majority (53.3) of the respondents were females. The mean age was 36 years with majority (64.2%) married while an average of 6 persons per household was recorded. The predominant occupations were farming (36.0%) and civil service (35.8%). The households cultivated a mean farm size of 3.8 hectares, the mean monthly income was N19,720 while their average monthly expenditure amounted to N31,250. Moreover, 73.3% of the respondents belonged to one social organization or the other with over 90.0% of them having acquired various forms of formal education. The multiple regression result showed the coefficient of determination (R2) was 0.644 or 64.4%. The overall model was statistically significant (P<0.05), signifying that the selected socio-economic characteristics of the households have significant influence on their poverty level. The coefficients of age, sex, educational attainment, household size, farm size, income and membership of social groups were statistically significant. The hypothesis tested led to the conclusion that the selected socio-economic characteristics have significant influence on the poverty level of the households. The study recommended improvement of socio-economic attributes that improve the poverty level of rural households. Int. J. Agril. Res. Innov. & Tech. 9 (1): 8-13, June, 2019

scholarly journals Influence of Socio-economic Factors of Rural Households on Fuelwood Consumption in Orlu Agricultural Zone of Imo State, Nigeria

2018 ◽  
pp. 1-6
Author(s):  
Egwuonwu, H. A. ◽  
A. P. Nweke
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Rural Households ◽  
Rural Household ◽  
Farm Size ◽  
Economic Factors ◽  
Household Heads ◽  
Fuelwood Consumption ◽  
Socio Economic Factors

The study analysed the influence of socio-economic factors of rural household on fuelwood consumption in Orlu Agricultural Zone of Imo State, Nigeria. Specifically, the study described the socio-economic characteristics of the households; determined the quantity (kg) of fuel wood consumed by household per week; identified coping measure in fuelwood scarcity among household and determined the influence of socio-economic characteristics of households on the quantity (kg) of fuelwood consumed. Data for the study were collected using structured questionnaire from 60 rural households through multi-stage sampling technique. Data were analysed using descriptive statistical tools and multiple regression analysis. Greater proportions (68.33%) were females. Mean age was 43.00 years. Majority (73.33%) were married with an average household size of 6 persons. The major occupation was farming (51.67%). Average farm size and farming experience of the rural household were 1.30 ha and 19 years respectively. Majority (56.67%) had primary education. Average fuelwood consumed by households weekly was 30.20 kg. The main coping measures for increasing fuelwood scarcity in the area were extinguish firewood after cooking (96.67%) and shifting to saw dust (88.33%). Estimated multiple regression analysis revealed that there was significant relationship between household heads socio-economic characteristic and quantity of fuelwood consumed weekly. The major determinants of the fuelwood collection and consumption in the area were age, sex, farm size, marital status, main occupation and educational level of household heads. The F-ratio was 5.125, indicating the overall significant of the regression model at 1% level of probability.

scholarly journals Logit analysis of socio-economic factors influencing people to become fishermen in the central region of Ghana

2011 ◽  
Vol 56 (1) ◽  
pp. 55-64 ◽  
Author(s):  
Henry Acquah ◽  
Isaac Abunyuwah
Keyword(s):  
Central Region ◽  
Weather Conditions ◽  
Structured Interview ◽  
Economic Factors ◽  
Logit Analysis ◽  
Access To Credit ◽  
The People ◽  
Study Results ◽  
Credit Lack ◽  
Socio Economic Factors

This study analyzes the socio-economic factors that influence people?s decision to become fishermen in the central region of Ghana. Using a well structured interview schedule, a random sample of 98 people from Elmina in the central region of Ghana was selected for the study. Results from the descriptive statistics analysis of respondents identified fishing as a family business, minimum skills requirement and ready market for fish demand as factors that motivated majority of the people into fishing. Lack of storage facilities, access to credit, lack of government assistance and unpredictable changes in weather conditions on sea were the main constraints to fishing activities. Results from the logistic regression model indicated that household size and access to credit were significant factors that positively influenced people?s decision to become fishermen. The regression analysis further revealed that engaging in other income generating activity and being educated significantly reduces the probability to start fishing business.

scholarly journals SOCIO ECONOMIC FACTORS AFFECTING BEAN PRODUCTION IN NORTHERN UGANDA

2017 ◽  
Vol 7 (1) ◽  
pp. 1009-1014
Author(s):  
Tekkara A. O ◽  
Kumakech A ◽  
Otim G ◽  
Alexandrina A ◽  
Wamani S ◽  
...  
Keyword(s):  
Smallholder Farmers ◽  
Descriptive Statistics ◽  
Northern Uganda ◽  
Local Market ◽  
Economic Factors ◽  
Factors Affecting ◽  
Access To Credit ◽  
Factors Influencing ◽  
Agricultural Mechanization ◽  
Socio Economic Factors

Beans is an important source of proteins and income for poor resource households. However the yied of beans has remained very low in comparion to yields obtained under ideal management conditions. This necessitated the examination of socio-economic factors influencing bean yields of smallholder farmers in eight districts of northern Uganda. A total of 1112 farmers were randomly selected from the study area and the data was subjected to descriptive statistics and regression analysis using IBM SPSS (version 20). The results indicated that 2.3% of variation in beans yield was attributed to amount of seed and acreage planted. The study further revealed that majority of the respondents (81.7%) were practicing farming and most of them were 31-40 years of age (31%). Also, 90.4% and 59.6% of the respondents had bean gardens ranging from 1 to 2 acres and sourced seeds for planting from local market respectively. While 90.4% of the farmers didn't have access to credit, 91.7% actually had access to market information. From the study, majority of the farmers (20.4%) attained yields of either 60 - 120kgs or above 240kgs per acre. It is recommended that, the government’s effort to support agricultural mechanization for increased acreage and productivity be strengthened through private public partnership to quickly reach the smallholder farmers.

Social Entrepreneurship and Microfinance in Kenya

2020 ◽  
Vol 11 (1) ◽  
pp. 256
Author(s):  
Haileslasie TADELE
Keyword(s):  
Social Entrepreneurship ◽  
Entrepreneurial Orientation ◽  
Least Square ◽  
Economic Factors ◽  
Microfinance Institutions ◽  
Credit Access ◽  
Access To Credit ◽  
Growth Constraints ◽  
Socio Economic Factors

This research examines the determinants of entrepreneurial orientation of individuals and investigates the role of microfinance in improving social entrepreneurship. The study uses survey data on a sample of 200 respondents from Kenya. The paper investigates the determinants of entrepreneurial orientation using socio-economic factors and microfinance borrowing as independent variables and entrepreneurial orientation as dependent variable. This model is estimated using an ordinary least square (OLS) regression model. The paper finds that higher educational level, greater access to credit, access to business skill trainings and microfinance borrowings tend to improve entrepreneurial orientation of individuals. The findings also indicate that microfinance borrowers tend to have higher risk taking and pro-active behavior indicating a higher entrepreneurial orientation than non-borrowers. The study thus confirms the role of microfinance in improving entrepreneurial orientation of borrowers and emphasizes the socio-economic factors that significantly affect entrepreneurial orientation of individuals. The findings have implications for further research on the growth constraints that impact microfinance institutions in promoting social entrepreneurship.  

scholarly journals Emerging Challenges in Rural Non-Farm Sector and Inequality in Rural India

2021 ◽  
Vol 3 (1) ◽  
pp. 88-101
Author(s):  
Bisla Devi ◽  
Thiagu Ranganathan
Keyword(s):  
Income Inequality ◽  
Rural Households ◽  
Household Head ◽  
Farm Income ◽  
Economic Factors ◽  
Inequality Decomposition ◽  
Absolute Deviation ◽  
Farm Sector ◽  
The Government ◽  
Socio Economic Factors

Purpose: This paper highlights the changing patterns of income diversification and the effects of various socio-economic factors influencing the non-farm (NF) income of rural households in India. The study also explores the inequality effects of the non-farm earnings of the households by using the Fields inequality decomposition.    Method: The study compares and evaluates the determinants and trends of inequality in 2004-2005 and 2011-2012 in the NF sector. It uses nationally representative data from two rounds of the Indian Household Development Survey (IHDS), which includes a panel of 36,278 households at all levels in India. The Censored Least Absolute Deviation (CLAD) model is used to estimate household determinants for non-farm income. The Fields decomposition decomposes total income inequality by considering the socio-economic factors. Results: The study finds that variations in non-farm earnings have increased. Field's Income Inequality Decomposition estimates show that income inequalities between households are significantly high due to factors such as education, level of the household head, land ownership, and population density, but also appear to be declining in 2011-12. Also, the earning gaps based on gender, age, and geographical zones have increased.  Implications: Overall, the non-farm income during the studied period was observed to be biased towards the better-off households. However, it opened up opportunities for underprivileged households as well. The non-farm sector has huge potential in augmenting incomes for unprivileged rural households. Therefore, the government should pay attention to this sector as a means of reducing income inequality and alleviating poverty.

scholarly journals Socio-economic Factors Affecting Uptake of Banana Value Addition among Smallholders in Chuka Sub-county, Tharaka Nithi County, Kenya

2021 ◽  
pp. 22-34
Author(s):  
Josphat K. Muigai ◽  
Geofrey K. Gathungu ◽  
Miriam Thogori
Keyword(s):  
Goodness Of Fit ◽  
Group Membership ◽  
Target Population ◽  
Economic Benefits ◽  
Economic Factors ◽  
Value Addition ◽  
Factors Affecting ◽  
Access To Credit ◽  
The Government ◽  
Socio Economic Factors

Banana farmers in most parts of Kenya have not embraced value addition despite its accrued economic benefits and emphasis by stakeholders. A study was done in Chuka Sub-County, Tharaka Nithi County to identify the socio-economic factors affecting uptake of banana value addition by farmers. The study was based on the diffusion of innovations theory to establish the relationship between farming experience, group membership, access to credit and uptake of banana value addition. The study adopted a descriptive research design whereby frequency tables were generated whilst both qualitative and quantitative data was collected. The target population was 20,180 banana farming households in Chuka Sub-County and 3 key informants. Purposive sampling, Random sampling and snowballing techniques were used to select the 156 banana farmers. A pilot study of 24 (15% of sample size) households was done in Imenti South and the questionnaire was found to be reliable (Cronbach alpha value, α˂0.785). With a 90% questionnaire return rate, the data collected was analyzed using SPSS version 25 and presented using frequency tables. Binary logistic regression was used to test the levels of significance of variables and the model through the Hosmer & Lemeshow test of the goodness of fit suggested that the it was good for fit to the data as p=0.480 (>0.05) while ANOVA analyses were used to check the presence of multicollinearity. It was observed that only 31.9% of farmers uptake banana value addition and there were no banana value addition technologies identified with 35.6% and 64.4% of those who uptake doing banana ripening for sale and bulk packaging respectively. The results [P=0.05] showed that group membership [p=0.019] and access to credit [p=0.004] had a positive and significant effect on the uptake of banana value addition by farmers at varying levels. It was observed that farming experience had a positive effect on the uptake, but was statistically insignificant. The study recommended that; farmers should be encouraged to form cooperatives on value addition and the government and other stakeholders in conjunction with financial institutions need to streamline policies to enhance farmer’s access credit for effective farming among others.

Food insecurity transitions among rural households in Nigeria

2020 ◽  
Vol 39 (1) ◽  
Author(s):  
Oluwakemi Adeola Obayelu ◽  
Emem Ime Akpan
Keyword(s):  
Food Security ◽  
Secondary Education ◽  
Food Insecurity ◽  
Primary Education ◽  
Rural Households ◽  
Farm Size ◽  
Dependency Ratio ◽  
Male Adult ◽  
Access To Credit ◽  
Food Expenditure

Food insecurity dynamics of rural households in Nigeria was assessed using a panel data. Results showed that 44.4% of households that were food secure in the first panel transited into food insecurity in the second panel, while 32.5% that were mildly food insecure transited into food security. Furthermore, 25.7% transited from moderate food insecurity to food security, while 38.2% transited from severe food insecurity to food security. About 35.1% of households were never food insecure; 11.4% exited food insecurity 28.0% entered food insecurity; while 25.48% remained always food insecure. Having primary education, secondary education, dependency ratio, household size, share of non-food expenditure and farm size explained food insecurity transition. However, the likelihood of a household being always food insecure was explained by gender, female-to-male-adult ratio, marital status, primary education, secondary education, dependency ratio, share of non-food expenditure, farm size, access to credit and access to remittance.

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