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A Two-Factor Model to Investigate the Effect of Time and Location to the Total Consumption Poverty Lines (TCPL) in Zimbabwe
Romeo Mawonike,
Blessing Chigunyeni
Issue:
Volume 5, Issue 2, March 2016
Pages:
39-48
Received:
27 January 2016
Accepted:
8 February 2016
Published:
1 March 2016
Abstract: Poverty is rampant throughout the entire country of Zimbabwe and is smelt everywhere as its wave penetrates every sector of the economy. Zimbabwe’s poverty is directly linked to its extremely high unemployment rate. Men, women, and youth are all affected by unemployment, including university graduates, as a number of industries and businesses have closed over the years, due to decline in tobacco exports, and the loss of revenue from the mining and farming sectors. Geographical location has a significant role in determining the income one has to spend to earn a living as there is some disparity in total consumption poverty lines with different provinces. Financial assistance or aids also varies in volume with the nature of province. In this paper, we seek to investigate whether Total consumption poverty line in Zimbabwe varies with time (type of month) and or with geographical location (the type of province into which one lives). We further seek to investigate which provinces share the same TCPL and which ones are most affected. We apply an ordinary Two–Factor Factorial Design to conclude our investigation.
Abstract: Poverty is rampant throughout the entire country of Zimbabwe and is smelt everywhere as its wave penetrates every sector of the economy. Zimbabwe’s poverty is directly linked to its extremely high unemployment rate. Men, women, and youth are all affected by unemployment, including university graduates, as a number of industries and businesses have ...
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Comparison of Logistic Regression and Linear Discriminant Analyses of the Determinants of Financial Sustainability of Rural Banks in Ghana
Godfred Kwame Abledu,
Akuffo Buckman,
Thomas Adade,
Samuel Kwofie
Issue:
Volume 5, Issue 2, March 2016
Pages:
49-57
Received:
8 February 2016
Accepted:
18 February 2016
Published:
4 March 2016
Abstract: Financial Sustainability is a primary issue for successful rural and community banks’ services. Establishing a system of sustained provision of modern financial services has, however, been challenging and most controversial. Several studies have been conducted on the determinants of sustainability of institutions in various countries. However, the levels of significance of the factors that influence financial sustainability of banks vary with studies. In addition, the results are mixed and empirical evidence regarding the determinants of rural and community banks’ sustainability is also missing. The objective of this study therefore was to develop a model which could be used to identify likely future rural and community banks that are non-sustainable. This study examined the determinants of financial sustainability of Rural and community banks using discriminant analysis (LDA) and logistic regression (LR) models.
Abstract: Financial Sustainability is a primary issue for successful rural and community banks’ services. Establishing a system of sustained provision of modern financial services has, however, been challenging and most controversial. Several studies have been conducted on the determinants of sustainability of institutions in various countries. However, the ...
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A Comparison of Artificial Neural Network and Time Series Models for Forecasting GDP in Palestine
Issue:
Volume 5, Issue 2, March 2016
Pages:
58-63
Received:
19 February 2016
Accepted:
28 February 2016
Published:
9 March 2016
Abstract: Time series of quarterly observations on Gross Domestic Product (GDP) is collected and used in this study. Forecasting results of ANNs are compared with those of the Autoregressive Integrated Moving Average (ARIMA) and regression as benchmark methods. Using Root Mean Square Error (RMSE), the empirical results show that ANN performs better than the traditional methods in forecasting GDP.
Abstract: Time series of quarterly observations on Gross Domestic Product (GDP) is collected and used in this study. Forecasting results of ANNs are compared with those of the Autoregressive Integrated Moving Average (ARIMA) and regression as benchmark methods. Using Root Mean Square Error (RMSE), the empirical results show that ANN performs better than the ...
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Comparison of Tests of Indirect Effect in Single Mediation Analysis
Chike Henry Nwankwo,
Amechi Henry Igweze
Issue:
Volume 5, Issue 2, March 2016
Pages:
64-69
Received:
16 January 2016
Accepted:
4 February 2016
Published:
18 March 2016
Abstract: This study compares various methods of mediations analysis. Firstly, it compares the two methods of calculating indirect effect which are product of coefficient and difference of coefficients respectively. Secondly, the study compares the three methods of testing the significance of indirect effect vis avis Sobel’s test, Aroian test and Goodman’s test. The differences in these three tests are due to variations in the methods of standard error computation. The findings are discussed. The results show that both methods of product of coefficients and difference of coefficients give approximately the same result. However the product of coefficient gave a slightly higher result. The comparison of test of indirect effect for mediator shows that the tests gave the same result for Sobel’s, Aroian and Goodman test. The study recommended further studies to seek methods of ascertaining the direction of relationship of indirect effect, other than those of the regression models, further studies may be carried out to determine the effect of multicolinearity on mediation results.
Abstract: This study compares various methods of mediations analysis. Firstly, it compares the two methods of calculating indirect effect which are product of coefficient and difference of coefficients respectively. Secondly, the study compares the three methods of testing the significance of indirect effect vis avis Sobel’s test, Aroian test and Goodman’s t...
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Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach
Ashenafi Senbeta Bedane,
Tejitu Kanko Tanto,
Tilahun Ferede Asena
Issue:
Volume 5, Issue 2, March 2016
Pages:
70-79
Received:
19 February 2016
Accepted:
29 February 2016
Published:
18 March 2016
Abstract: Malaria is one of the major mortality and morbidity incidences in the country. The main aim of the study is to determine the malaria distribution along months of year 2003 to 2012 at Kucha district. The risks of morbidity and mortality associated with malaria are characterized by its distribution in a period of time through month of year. The time series analysis of malaria prevalence in the Kucha district was tested through test of randomness using turning point approach. A time series analysis trend analysis and box-Jenkins models were employed to the data obtained from health centers of Kucha districts. Autocorrelation Function and Partial Autocorrelation Function were adopted to identify the appropriate box-Jenkins models. Autoregressive Integrated Moving Average models were adopted for final data analysis with differencing to attain stationary data. The quadratic trend was found best fit for malaria data and it shows a decreasing trend along a period of month of year 2010 to 2012. Based on the results of model diagnostic checking ARIMA model was found to be significantly fit the data for malaria prevalence forecast. As a result malaria distribution shows seasonal variation in the district especially in the month September to January and July to August. The highest malaria prevalence was observed in December months of each year while, low rate of malaria prevalence was observed in July months of each year.A study recommends that health professionals should pay special attention on December months of each year by suggesting precaution action for those people living in the district.
Abstract: Malaria is one of the major mortality and morbidity incidences in the country. The main aim of the study is to determine the malaria distribution along months of year 2003 to 2012 at Kucha district. The risks of morbidity and mortality associated with malaria are characterized by its distribution in a period of time through month of year. The time ...
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