Effect of Income Diversification on Household’s Income in Rural Oyo State, Nigeria

Analysis of income diversification conceives of diversification in terms of strategies employed to earn cash income in addition to primary production activities from a variety of sources. It is often argued that this is a strategy primarily intended to offset risk. This study focused on analyzing the effects of diversification on household income in rural farming household in Oyo State, Nigeria. The result presented was based on primary data collected from a random sample of 120 households from two Agricultural zones (Ibadan/Ibarapa and Ogbomoso) of Oyo State. Descriptive statistics was used to describe the socioeconomic characteristics such as age, marital status and primary occupation of the respondents while two-stage least square (2 SLS) was employed to determine effect of diversification of income on per household income and income diversification of rural farming household. Results of descriptive statistics revealed that majority of the farmers were married with mean household size and age of 8 persons and 44 years respectively.2SLS showed that number of income source (NIS), share of off-farm income (OFS), Herfindahl Diversification Index (HDI), years of experience and farm size were positively significant to the per capita household income. Selected human capital variables such as years of education, years of vocational training and extension agent contacts have positive significant effect on income diversification of the farmers in the study area.  The study concluded that number of income source and years of education were the major factors affecting per household income and income diversification of rural farming household

Effect of Income Diversification on Household’s Income in Rural Oyo State, Nigeria

Analysis of income diversification conceives of diversification in terms of strategies employed to earn cash income in addition to primary production activities from a variety of sources. It is often argued that this is a strategy primarily intended to offset risk. This study focused on analyzing the effects of diversification on household income in rural farming household in Oyo State, Nigeria. The result presented was based on primary data collected from a random sample of 120 households from two Agricultural zones (Ibadan/Ibarapa and Ogbomoso) of Oyo State. Descriptive statistics was used to describe the socioeconomic characteristics such as age, marital status and primary occupation of the respondents while two-stage least square (2 SLS) was employed to determine effect of diversification of income on per household income and income diversification of rural farming household. Results of descriptive statistics revealed that majority of the farmers were married with mean household size and age of 8 persons and 44 years respectively.2SLS showed that number of income source (NIS), share of off-farm income (OFS), Herfindahl Diversification Index (HDI), years of experience and farm size were positively significant to the per capita household income. Selected human capital variables such as years of education, years of vocational training and extension agent contacts have positive significant effect on income diversification of the farmers in the study area. The study concluded that number of income source and years of education were the major factors affecting per household income and income diversification of rural farming household

What Drives Households’ Payment forWaste Disposal and Recycling Behaviours? Empirical Evidence from South Africa’s General Household Survey

Publication history: Accepted - 22 July 2020; Published - 1 October 2020.Safeguarding the environment and its citizens’ health remains one of the key policy priorities of the governments of many developing and emerging countries. Using the 2017 General Household Survey (GHS) dataset, this study examines the driving factors a ecting households’ recycling behaviour and payment for waste disposal in South Africa. The methods of data analysis were based on descriptive statistics and a Bivariate Probit regression model. The descriptive statistics results indicate that there are 56.29% male-headed and 43.71% female headed households, with an average age of 49 years. In addition, the study shows that 89.97% of household heads had formal education with a mean monthly income of 11,099.07 ZAR/650.504 USD. The study also revealed that 22% of the households sampled had access to social grants. The results from the Bivariate Probit regression model show that household’s income, access to social grants, formal educational attainment and the age of the household were significant (p < 0.01) driving factors a ecting households’ recycling behaviour and payment for waste disposal. The study concludes that the households’ socio-economic factors a ect their recycling behaviour and willingness to pay for waste management in South Africa. Actions targeted at poverty alleviation and environmental sensitization programmes are key for facilitating environmental conservation behaviours of households in South Africa in order to achieve the environmental sustainability Sustainable Development Goal (SDG) target of the United Nations