Determinants of Risk Behaviour in Livestock Development Programs: Evidence from South Africa's Kaonafatso Yadikgomo (Kyd) Scheme

Risk plays a significant role in input use decisions and production of output in agricultural production. Understanding farmer risk attitudes and their responses to risk is significant in designing effective intervention programmes. Few studies have tried to identify how the introduction of a livestock programme has tended to influence farmer risk profile. The objective of the study was to highlight the determinants of risk behaviour in participants of a livestock development programme. The study was carried out in KwaZulu-Natal (KZN) Province of South Africa, utilising a purposive sample of 164 respondents who are part of the Kaonafatso Yadikgomo (KYD) Scheme. The cross-sectional survey collected data pertaining to the risk attitudes of the livestock farmers from an attitudinal scale as well as socio-economic and farm biophysical characteristics. Descriptive statistics and multiple linear regression were used to analyse the data. The results show that the livestock farmers were risk loving, with the risk attitude being influenced by the age of household head, monthly household income and experience in rearing cattle at the ð‘ < 0.1 level. Furthermore, the source of income, herd size, reason for slaughtering cattle distance to the nearest water source and access to a dip tank had significant influence of attitude towards risk at the ð‘ < 0.05 level. The study concludes that being part of a livestock development programme tends inflto uence the risk attitudes of the participants as the determinants were against a priori expectations.&nbsp

Does Urbanization Matter For Poverty Reduction in Nigeria: An Empirical Evidence From Autoregressive Distributed Lag (ARDL) Estimation

Urbanization has been argued to be having an impact on several other development challenges. To this end, this paper aims to contribute to the empirical literature by exploring the effect of urbanization and its' magnitude on poverty, both in the short run and long run in Nigeria. The macroeconomic analysis was conducted using data from 1982 to 2017 which was obtained from the World Bank. Bound Test and autoregressive distributed-lag (ARDL) estimation techniques were used to test the existence of a cointegration relationship and to estimate the short and long-run effect of urbanization and other variables on poverty reduction. Results from the study and an economic standpoint, provide strong evidence that urbanization remains an important factor in poverty reduction in Nigeria. The analysis further shows that while international remittances have a positive and significant effect, foreign aid and government expenditure have significant negative effects on poverty reduction in the long-term period. While findings from this study suggest that urbanization remains a valid tool in the fight against poverty, the need for sustainable urbanization policies and efforts by the Nigerian government is highly imperative

Local Farmers' Perceptions About Covid-19 Impact on Agriculture: Case of Selected Rural Areas in Ekiti State, Nigeria

The outbreak of the Corona virus that ravaged most parts of the globe including Nigeria had impacted all sectors in all economies. Understanding the perception of rural farmers about Covid-19 pandemic impacts on agricultural activities becomes imperative as it will help local government authorities identify possible vulnerabilities and prioritize interventions. This study therefore seeks 1) to know farmer perceptions of the probable impacts of Covid-19 pandemic on agricultural production process of rural farmers and 2) to examine if this perception varies by the population subgroups of farmers? Using selected rural areas in five local government areas in Ekiti state as case study, primary data obtained through the administered questionnaire were analysed using descriptive statistics and analysis of variance. Results indicated that the two most potential and identified possible vulnerabilities are agricultural output and access to finance, and income with respect to production process and welfare, respectively. ANOVA results indicated that both age and gender are not statistically significant at 5 percent in explaining perceived impact of covid-19 on agricultural output likewise others such as educational attainment, years of farming experience and marital status. Hence, none of the levels in each of the chosen categorical variables is found to be statistically different from the other ones in impacting agricultural production. It is therefore recommended that government policies aimed at stimulating agricultural production should not be gender bias and age driven. Similarly, other factors such as years of farming experience, educational attainment and marital status should be de-emphasized when initiating such policies