International Journal of Economics & Management Sciences

Nigeria’s dependence on oil revenue has been a cause for concern, especially as oil is an internationally traded commodity whose price is subject to unpredictable changes. The volatility in price of oil has various implications for both oil importing and exporting countries alike. However, oil export revenue dependent nations are more prone to the consequences, especially during periods of negative volatility. Nigeria’s economy is highly dependent on crude oil export revenue, hence, fluctuations in oil prices affects Nigeria’s macroeconomics. This study empirically investigated the economic effects of oil price volatility on Nigeria’s economy using some macroeconomic indicators such as gross domestic product (GDP), exchange rate (EXR), interest rate (INR), Foreign Direct Investment (FDI), and balance of payment (BOP). Ordinary Least Square (OLS) estimation was used to assess the impact of oil price fluctuation (independent variable) on the macroeconomic indicators listed above (dependent variables). The result of the study shows that the macroeconomic variables respond to changes in the price of oil (volatility), although at varying extent/degrees. This result underscores the contribution of oil as the major foreign revenue earner for the country. Based on the result of the study, it is concluded that oil price volatility is linearly related to the macroeconomic variables investigated, and that price volatility has an effect on interest rate, balance of payment, gross domestic product and foreign direct investment. Consequently, it is recommended that Nigerian economy should be diversified to guarantee non-dependence on oil revenue as the major source of foreign income earner, and that investment in local production to encourage export, while discouraging over importation is imperative.

Vehicle Routing Problems (VRPs) have been one of the most complex planning tasks of logistics management in any supply chain. One of the real-life extensions of VRPs is incorporating the facility of cross-docking in it. Ensuring a smooth flow of goods across such a system is a crucial task for any logistics firm when there are many cross docks. The distribution center collects different inbound products from respective suppliers and delivers outbound products to various customers with the help of a state-of-the-art transportation and material handling system. The objective of this paper is to address the VRP, which minimizes the total cost of operations in view of a set of constraints under the scenario of multiple cross-docks. This has been solved using a variant of Genetic Algorithm with Best Cost Route Crossover and Swap Mutation. The algorithm has been applied on three test problems and the stability has been verified. The main contribution of this paper is that it highlights the issue of VRP in multiple cross-docks.

Background: Workers performance is the foundation for the development of an organization. Creating favorable working environment is fundamental to advance workers performance. Thus, the study was intended to measure level of work performance and to identify associated factors among workers in Amhara national regional state health bureau.
Methods: Across-sectional study design was employed among 357 employees. Data were collected using self-administrated structured questionnaires. It was entered in to Epi-info version 3.5.1 and analyzed using SPSS. Descriptive statistics was computed to summarize the result and represented by tables. Binary logistic regression was calculated to explore the relation between the predictors and outcome variable. Multivariate logistic regression model with 95% C.I. was also computed to determine the independent association of factors with work performance.
Results: The level of work performance was 76.64% (76.25-77.03). The majority of the employees' performance level found to be good. Salary [AOR=3.94 (1.41, 10.99)], years of working [AOR=3.07 (1.25, 7.49)], type of working department [AOR=6.77 (2.57, 17.79)] and type of work [AOR=0.32 (0.13, 0.77)] were independently predicting level of work performance.
Conclusion: The level of performance was comparable to other studies in similar settings. Encouraging employees with reasonable salary based on work experience and availing conducive work structure should be given due attention by the health bureau to have better organizational performance for development.

This research paper investigates the impact of agriculture on economic growth of Nigeria, considering the impact it will have to ensure the achievement of economic growth and recovery, from the devastating effects recession had on the economy from 2016 to the second quarter of 2017. Using Ordinary Least Squares (OLS) regression technique at 5% level of significance, it was discovered that exchange rate has positively and significantly impacted on agricultural output. Loans and advances, and total savings were also discovered to have significantly impacted agricultural output as a component of GDP. Based on the findings, the paper recommends that: moral suasion as a monetary policy be exercised, agricultural inputs be largely sourced locally and foreign exchange be made favorable, corruption that has eaten deep into the fabric of the society be effectively checked in the sector, government allocation to the sector be increased at the same time be monitored to ensure prudency in its usage, and finally government should encourage public private partnership in agriculture, for the achievement of stated goals.

The study attempted to analyse significances change in Indo-UAE trade since 2008. The concept of trade intensity and other statistical tests are used to examine changes between the two nations with the time horizon 2007 to 2016. Overall results show that the growth rate of India’s trade with UAE has comparatively higher in early period. Secondly the composition of India’s commodity basket reflects the dominance of manufacturing goods in exports and balance of trade is also favorable for India. Thus, there is a need to take some more steps to enhance in trade which is beneficial for both.

International students’ enrollment in higher education in the U.S has expanded considerably in the last decades. In 2015, the United States hosted more of the world’s 4.1 million international students than any other country (Institute for International Education, 2015). With the number of foreign students that come to study in the U.S, 14.5% of international students are African students with the majority of the population coming from Nigeria, Kenya and Ghana. The U.S. is often described as the land of opportunity abroad, but this research intends to explore that perception for international students, especially African students. Many consider African international students as the gateway to local business owners in the U.S seeking to expand a wider global horizon, especially in Africa. This research explored the different types of academic and social challenges faced by African international students in collegiate institutions in America through auto-ethnographic research, and to find possible solutions to those challenges faced by African students. This is a qualitative research approach that used the sequential autoethnographic experience of the author as the research tool in identifying and categorizing some of the challenges faced by African international students. It is the researcher’s intention that the findings in this research will be used as a guide for the next group of African international students aspiring to come to the U.S to study.

The objective of paper is to assess the efficiency of financial model to capture increasing volatilities across asset class markets of the three investment banks. For which data will be collect to forecast the credit risk, and to know how well our standard tools forecast volatility, particularly during the turmoil that extend throughout the globe. Volatility prediction is a critical task in asset valuation and risk management for investors and financial intermediaries. The paper will focus on Value-at-Risk (VaR) which is a standard model that has been forecasted using both nonparametric and parametric approaches and then Backtesting procedure had been applied to achieve the both outcome. One is to detect the underlying credit risk which is associated with the market as well as portfolio risk, and other is to perceive model which provide more accurate forecasting.