-
Economic Contributions of Jima Ganati Farmers’ Cooperative Union to Farmers: The Case of Maize Producer Farmers
Issue:
Volume 4, Issue 1, March 2019
Pages:
1-10
Received:
21 January 2019
Accepted:
21 February 2019
Published:
14 March 2019
Abstract: This article investigates the impact evaluation of Jima Ganati farmers’ cooperative union intervention in economic activities which is measured in terms of income and productivity as the best means to improve the living standard of farmers’ household. For this, cross-sectional data were collected from 280 households purposively selected from five kebeles consisting of 204 member farmers and 76 non-member farmers. The analytical procedure has involved two stages: in the first stage, descriptive analyses were used to detect existence of difference in various outcome indicators between member farmers and non-member farmers. In the second stage, I applied a semi-parametric impact evaluation method of propensity score matching with some matching algorithms to estimate the impact of the intervention on various impact indicators. Combined use of these alternative estimation techniques has enabled us to arrive at consistent results. Our results show that member farmers scored statistically significant higher maize crop income test score than non-member farmers and they are also identified with statistically significant higher total productivity. Although the crop income and productivity test scores show significant changes, some constraints were identifiedin the economic contributions of the cooperative union to farmersand theseinclude: high turnover of the union mangers, lack of skill in cooperative development, rent seeking behavior of the cooperative leaders, lack oftransparency, Accordingly, a number of recommendations are suggested.
Abstract: This article investigates the impact evaluation of Jima Ganati farmers’ cooperative union intervention in economic activities which is measured in terms of income and productivity as the best means to improve the living standard of farmers’ household. For this, cross-sectional data were collected from 280 households purposively selected from five k...
Show More
-
Review on Adoption of Improved Agricultural Technologies in Ethiopia
Issue:
Volume 4, Issue 1, March 2019
Pages:
11-19
Received:
26 November 2018
Accepted:
17 January 2019
Published:
15 March 2019
Abstract: The objective of this review was to assess the factors affecting adoption and intensity of agricultural new technologies. The adoptions of agricultural technologies were highly influenced by socio-economic factors, institutional, location factors as well as agro-ecological factors and the characteristics of the farmers were those factors affecting the adoption and intensity of agricultural new technologies. Also the review was focused on the probability of adoption of crop, feed improvement technologies and artificial insemination. The other objective of the review was the impact of the technology adoption on the small holder farmers’ welfare.
Abstract: The objective of this review was to assess the factors affecting adoption and intensity of agricultural new technologies. The adoptions of agricultural technologies were highly influenced by socio-economic factors, institutional, location factors as well as agro-ecological factors and the characteristics of the farmers were those factors affecting ...
Show More
-
Determinants of Crime in Nigeria from Economic and Socioeconomic Perspectives: A Macro-Level Analysis
Aduralere Opeyemi Oyelade
Issue:
Volume 4, Issue 1, March 2019
Pages:
20-28
Received:
17 January 2019
Accepted:
18 March 2019
Published:
8 April 2019
Abstract: The study examined the determinants of crimes in Nigeria from economic and socioeconomic perspectives: A macro-level analysis using a time series data covering the period of 1990 to 2014. Both economic and socio-economic factors that determinant crime were included in the model. The economic factors include GDP per capita; male unemployment rate; female unemployment rate and poverty rate while the socioeconomic-demographic factors include higher education enrolment; urban population and rural population. The study embraces the autoregressive distributed lag (ARDL) model to empirically analyze the model since the variables were stationary at levels I(0) and first difference I(1). The empirical results in the long-run indicated that gross domestic product per capita and female unemployment rate was found to have a negative significant effect on crime rate in Nigeria while urban and rural population, male and female unemployment rate were found to have a positive significant effect on crime rate in Nigeria. Also, the results of the short-run indicated that gross domestic product per capita and higher education was found to have a negative significant effect on crime rate in Nigeria while urban population, male unemployment rate and poverty rate were found to have a positive significant effect on crime rate in Nigeria in the short-run. Therefore, for a country like Nigeria to reduce criminal activities in the country, there must be an increase in the income of the people. Also, government should invest more in education because it makes the people more rational and more risk averse and so it reduces the propensity to commit crimes. Therefore, higher education attainment will be the cure for criminal activities in Nigeria. Government should also create more jobs because high unemployment rates will compel people to commit crimes and this will increase crime rate in Nigeria. Lastly, there should be high budgetary provision towards poverty alleviation programme because higher poverty may lead to higher crimes rate due to depression or mental illness associated with being poor and this will decreases the rate of return of legal activities and more likely to increase return of illegal activities.
Abstract: The study examined the determinants of crimes in Nigeria from economic and socioeconomic perspectives: A macro-level analysis using a time series data covering the period of 1990 to 2014. Both economic and socio-economic factors that determinant crime were included in the model. The economic factors include GDP per capita; male unemployment rate; f...
Show More
-
Magnitude and Factors Affecting Out-of-Pocket Medical Expenditure among Outpatients in ST.Paul Hospital Millennium College, Addis Ababa, Ethiopia
Amelewerk Alemu,
Mesfin Aklilu,
Wogayehu Tadele
Issue:
Volume 4, Issue 1, March 2019
Pages:
29-34
Received:
1 February 2019
Accepted:
18 March 2019
Published:
12 April 2019
Abstract: The Objectives of the study is to assess the magnitude and factor that affect out-of pocket medical expenditure among outpatients department in St Paul’s hospital Millennium College, Addis Ababa, Ethiopia. An Institution-based cross-sectional study in quantitative method was conducted among outpatient services. The required sample size is determined by single population and double population proportion formula. The final sample size was 422. A descriptive statistical analysis, binary and multivariable logistic regression model was used to describe the findings. Gender, marital status, educational status, occupation, family size, total income was statistically associated with TOOPME at Sig< 0.2. Statistically associated with TOOPME In multivariate analysis were marital status (B=.197; CI 95%190.2-585; sig .000), Occupation status (B=-.174; CI 95%-180—39.6; sig .002), family size (B=.229; CI 95%58-150; sig .000), and total income (B=.305; CI 95%10Table: 1 9-227; sig .000). The financing system of health care should be based on the principle of cost sharing so that there will be resource pooling among the poor and the rich. The financing mechanism should also move into prepayment schemes or insurance to protect the poor from unanticipated health care costs.
Abstract: The Objectives of the study is to assess the magnitude and factor that affect out-of pocket medical expenditure among outpatients department in St Paul’s hospital Millennium College, Addis Ababa, Ethiopia. An Institution-based cross-sectional study in quantitative method was conducted among outpatient services. The required sample size is determine...
Show More
