Department of Statistics

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On the Efficiency of Treatment Comparisons in a Randomised Block Design
(University of Ghana, 1976-05) Nkansah, P.T.; Odoom, S.I.K.; University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistics
The Application of Queuing Theory to Customer Service at Selected Branches of the Standard Chartered Bank Ghana Limited.
(2004-12) Thompson-Nunoofio, E.; Odoom, S. I. K.; University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistics
This thesis investigates the Application of Queuing theory to customer services at selected branches of the Standard Chartered Bank in Accra. The problem investigated was to determine among other things whether the customer service points of the bank functions well without bottlenecks or undue delays. That is this thesis intends to investigate, (a) If the bank current system of operation at the customer service points is satisfactory. (b) If not what changes are required to improve the mode of operation at the service points of the bank. The methodology employed was to collect data from the customers arriving at the service points of the bank. Customers arriving at the service points of the bank are given identification or trial numbers such as 1, 2, 3 etc in the order of their arrival. Their clock time of arrival, beginning of service and at the end of service are observed for each customer at a duration of at least three(3) hours for three days for the selected branches under study. The data was analyzed by preparing an elaborate worksheet using Microsoft Excel. This would depict the state changes for any arriving customer during the period of observation. A summarized relative frequency distribution was also depicted for the inter arrival and service times. This would enable the researcher to know the proportion of customers whose inter arrival and service times fall within a certain category for each day of observation. This would help determine in what ways the queues differ from day to day and, possibly from one branch to another. The results obtained indicate that a customer spends a minimum of thirty (30) minutes at the service points of the bank. Hence the conclusions that follow indicates that very few cash booths are opened to serve customers at the various hours of the day at the service points of the selected branches of the bank investigated. Consequently, excessive long queues are observed at the service points of the selected branches of the bank. This means that the current demand for service at the selected branches of the bank exceeds the current capacity to provide that service. Hence, cashiers at the cash booths of the selected branches of the Standard Bank, Ghana Limited spend most of their times serving customers at the service points of the bank. To improve the mode of operation, an additional teller window should be opened to serve customers at the service points of the bank at various hours of the day. This would reduce the burden on the cashiers and enhance efficient customer service delivery.
The Application of Queuing Theory to Customer Service at Selected Branches of the Standard Chartered Bank Ghana Limited.
(University of Ghana, 2004-12) Thompson-Nunoofio, E.; Odoom, S.I.K.; University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences Department of Statistics
This thesis investigates the Application of Queuing theory to customer services at selected branches of the Standard Chartered Bank in Accra. The problem investigated was to determine among other things whether the customer service points of the bank functions well without bottlenecks or undue delays. That is this thesis intends to investigate, (a) If the bank current system of operation at the customer service points is satisfactory. (b) If not what changes are required to improve the mode of operation at the service points of the bank. The methodology employed was to collect data from the customers arriving at the service points of the bank. Customers arriving at the service points of the bank are given identification or trial numbers such as 1, 2, 3 etc in the order of their arrival. Their clock time of arrival, beginning of service and at the end of service are observed for each customer at a duration of at least three(3) hours for three days for the selected branches under study. The data was analyzed by preparing an elaborate worksheet using Microsoft Excel. This would depict the state changes for any arriving customer during the period of observation. A summarized relative frequency distribution was also depicted for the inter arrival and service times. This would enable the researcher to know the proportion of customers whose inter arrival and service times fall within a certain category for each day of observation. This would help determine in what ways the queues differ from day to day and, possibly from one branch to another. The results obtained indicate that a customer spends a minimum of thirty (30) minutes at the service points of the bank. Hence the conclusions that follow indicates that very few cash booths are opened to serve customers at the various hours of the day at the service points of the selected branches of the bank investigated. Consequently, excessive long queues are observed at the service points of the selected branches of the bank. This means that the current demand for service at the selected branches of the bank exceeds the current capacity to provide that service. Hence, cashiers at the cash booths of the selected branches of the Standard Bank, Ghana Limited spend most of their times serving customers at the service points of the bank. To improve the mode of operation, an additional teller window should be opened to serve customers at the service points of the bank at various hours of the day. This would reduce the burden on the cashiers and enhance efficient customer service delivery.
Academic Performance in a University with Senior High School Entry Grades
(University of Ghana, 2012) Kobina, F.
The objectives of this study are to determine if Senior High School entry grades used for university admission could predict final performance in Methodist University College Ghana (MUCG) and to establish the relationship that exist between entry grades E, D7 or E8 and final performance of students who entered MUCG with these grades. The study population comprises of students who entered MUCG with Senior Secondary School Certificate Examination (SSSCE)/West African Senior School Certificate Examination (WASSCE) results. Out of this population, 888 students were selected from the academic years 2000/2001 to 2007/2008 for the study. Multiple regression, chi-square test of independence and correlation were used to analyze the data. The findings revealed that there is a weak correlation between entry grades E, D7 or E8 and final cumulative grade point average in MUCG. Based on the findings, it is recommended that a standardized entrance examination should be conducted for Senior High School students who are not able to meet the initial admission requirement, especially those with at most two subjects being grades E/D7/E8.
Application of Time Series in Predicting the Water Levels of the Akosombo Dam
(University of Ghana, 2013-05) Mensah, D.; Doku-Amponsah, K.
Energy from hydro-electricity is the cheapest form of power generation in this country. The Volta River Authority can however generate power optimally if water levels within the dam is between 240ft and 280ft. This is not always the case, since the only source of water for the dam is rainfall, which is also random and dependent on weather conditions. Knowledge of the water level within any month of the year will therefore be very useful in the production, distribution and management of power from the dam.The study looked at how use of time series analysis could be used in predicting the average monthly water levels of the Akosombo dam. The study took a step-by-step approach of the Box-Jenkins ARIMA process and arrived at a seasonal model (1,1, 0) × (0,1,1) 12 . This model turned to be a good forecast for the average monthly water levels. Per the findings in this research work, it was recommended that, if data points were in the excess of 70, then the Box-Jenkins ARIMA model can be used to predict prices of utilities such as water and electricity. Fellow statisticians were also encouraged to look at other forecasting tools such as artificial neural networks since it had very good features as the Box-Jenkins ARIMA model.
Modelling Rates of Inflation in Ghana. An Application of Autoregressive Conditional Heteroscedastic (ARCH) Type Models
(University of Ghana, 2013-06) Mbeah-Baiden, B.; Dasah, J.B.; Nortey. E.N.N.; University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistics
The research is based on financial time series modelling with special application to modelling inflation data for Ghana. In particular the theory of time series is explored and applied to the inflation data spanning from January 1965 to December 2012 which were obtained from the Ghana Statistical Service. Three Autoregressive Conditional Heteroscedastic (ARCH) family type models (traditional ARCH, Generalized ARCH (GARCH), and the Exponential GARCH (EGARCH)) models were fitted to the data. This was especially so because the data were characterized by changing mean and variance. The Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) were used to assess the performance of each of the fitted models such that the model with the minimum value of AIC and BIC was adjudged the best model. The results revealed that the ARCH – family type models, particularly, the EGARCH (2, 1) was superior in performance in forecasting Ghana’s monthly rates of inflation. The results also showed that the monthly rates on inflation were not weakly stationary and although there was the presence of asymmetric effects in the volatility in the monthly rates of inflation, there was an absence of leverage effects as positive shock increased the volatility in the monthly rate of inflation more than a negative shock of equal magnitude. The study recommends that policy makers and all interested in modelling and forecasting monthly rates of inflation in Ghana should consider using the Heteroscedastic models as it is able to properly capture the volatilities in the monthly rates of inflation. Analysis were done using MINITAB 16.0 and EVIEWS 5.0.
Comparative Analysis of Statistical models in Credit Assessment
(University of Ghana, 2013-06) Ansah, A.Y.; Nortey, E.N.N.; Baidoo, I.
With the emergence of the current financial crisis, important advances have been made in credit risk management. Inherent in this management process is the assessment of creditworthiness routine which subsequently leads to a credit granting decision. This study is aimed at developing a statistical model that can be used to ascertain credit assessment and to predict the probability of default of firms seeking credit from a Ghanaian commercial bank. Subsequently, an attempt was made to find financial ratios that can best be made used to successfully construct the model. To achieve these purposes, the study employed the Probit and logit models for comparative reasons in terms of their predictive abilities. Performance of the models was assessed using the percentage correctly classified (PCC) and the area under the receiver operating characteristics curved (AUC) where significant differences between the two models were observed. It was found that both the Probit and the logit classifiers yield very good performance rates but the logit model performed better for credit scoring. It was also found that ratios bordering on assets to liability ratios, account receivable to liability, Cash to Assets, current liability to total liabilities , Net current asset ,and total asset firm size are those that were significantly helpful in scoring credit applicant. Practically the model assist in reducing the time spent on evaluating credit applicant of each firm subject to the model and also serve as a difference between application serving and portfolio management . Indeed the multiplier effect will be a significant improvement in loan portfolio quality of the model user.
Modelling Ghana Stock Exchange Indicies and Exchange Rates with Stable Distributions
(University of Ghana, 2013-06) Kallah-Dagadu, G.; Nortey, E.N.N.; Doku-Amponsah, K.
Most of the concepts in theoretical and empirical finance that have been developed over the last 50 years rest upon the assumption that the return or price distribution for financial data follows a normal distribution. But this assumption is not justified by empirical data. Rather, the empirical observations (financial returns) exhibit excess kurtosis, more colloquially known as fat tails or heavy tails. This research first described the stable distribution family -   stable, Levy stable, Cauchy and Gaussian or Normal distributions. The study presented three methods of estimating parameters of   stable distributions, namely Maximum Likelihood estimation, Empirical Characteristic function and Sample Quantile methods, and goodness of fit tests- K-S and Chi-square, were used to quantitatively assess the quality performance of their respective estimates. A sample of weekly financial data (GSE All-Shares index, USD/GHC, GBP/GHC and EUR/GHC exchange rates) covering the period of 02/01/2000 − 31/12/2011 was analysed, and fitted to   stable, Cauchy and Normal distributions. Diagnostic tests such as P-P and Q-Q plots and goodness of fit tests (K-S, Chi-square, Anderson-Darling and Shapiro-Wilk) were graphically and quantitatively used to assess fitness to the returns of the data respectively. The study concludes that the weekly return distributions of Ghana financial data are heavy tailed and asymmetry and the maximum likelihood estimation method produce the most accurate and efficient estimates for the   stable fit to the data. The weekly financial data considered were modelled with   stable distribution and recommends that for efficient risk and assets returns management, analysts should explore and discover actual return distributions of financial data and not desist from speculative assumptions.
Some Approaches to Modelling Need-Based Financial Aid to Needy Students in the University of Ghana
(University of Ghana, 2013-06) Agbedor, P.M.; Nortey. E.N.N.; University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistics
It was asserted that University and university systems around the world are faced with rapid growing demand and decreasing or static government investment (Marcucci and Johnstone, 2010). In response to this assertion, many countries introduced cost-sharing in order to preserve the quality of higher education. In order not to deny academically talented young people from poor families from accessing higher education, governments and individual institutions started offering financial assistance to needy students. For this same cause the University of Ghana established a Student Financial Aid Office (SFAO) in 2005 which aims at awarding scholarships to needy but brilliant students. Little is known about how the SFAO awards its scholarship. Many countries have adopted the means testing method to enable them target the scarce funds to only needy students. Hence the aim of this study is to develop a statistical model (a means testing statistical model) for assessing the need of a student who applies for financial aid and awarding the scholarship accordingly. A random sample of 384 undergraduate regular University of Ghana students was selected to fill a questionnaire on a wide range of questions. Factor analysis was used to extract critical factors which were used to assess the need levels of the students and responses of each respondent were scored based on weights assigned to the variables. The scores were then used to compute the Relative Need Index for every respondent; furthermore, students were categorized into five need groups according to their need levels. It was found out that only 2.7% of students sampled fell in the most needy group and 15.6% were in the least needy group. On the other hand, majority of the students were in the middle level class which are the needy and the less needy groups, constituting 23.1% and 47.3% of the total sample respectively. It was concluded that information on income is difficult to come by in our part of the world, therefore the family income component was not included in the analysis. It was also established that, even though means testing has its challenges it is adopted by countries and institutions in order to allot financial assistance to students efficiently. The developed means testing formula was recommended to the University of Ghana for adoption.
Delinquency and Default Risk Modeling of Microfinance in Ghana
(University of Ghana, 2013-06) Arku, D.; Doku-Amponsah, K.; Baidoo, I.K.
The objective of this research was to identify the risk factors that influence loan default of customers in the microfinance sector and to develop model that links these factors to credit default for any customer in the sector. Data from a microfinance institution based in Accra was used. A binomial logistic regression analysis was fitted to a data of 472 customers who were granted credit from January 2011 to December 2012. Based on the Wald criterion, it was realized that among the variables that were considered only six out of the 16 predictor variables significantly influence the probability of loan default. One of the key findings of the study was the fact that the loan officer has a significant effect on loan default risk. Other factors include; Client‟s age, Assessment, Type of collateral, guarantor, and residential status. The findings suggest that, default rate is higher for trading and manufacturing sectors than for food vendors as well as those in the service sector. Clients in the service industry are relatively less risky. Clients with guarantors or security other than household items perform well in their obligations. The findings indicated that the responsibility of the loan officer have a tremendous impact on loan default. A test of the full model against a baseline model was statistically significant, indicating that the predictors, as a set, reliably distinguished defaulters and non- defaulters. The Receiver Operating Characteristics (ROC) that measures the sensitivity and specificity of the model was significant at 0.05 level. Using the hold out sample, the model is able to classify defaulters and non-defaulters with at least 80% accuracy. This means that for every four out of five clients, the model is able to predict correctly: default or otherwise. The model could serve as tool to manage and improve loan decision and ultimately enterprise profitability.
Investment Portfolio Optimization with Garch Models
(University of Ghana, 2014-06) Siaw, R. O.; Doku-Amponsah, K.; Mettle, F. O.; University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistics
Since the introduction of the Markowitz mean-variance optimization model, several extensions have been made to improve optimality. This study examines the application of two models - the ARMA-GARCH model and the ARMA- DCC GARCH model - for the Mean-VaR optimization of funds managed by HFC Investment Limited. Weekly prices of the above mentioned funds from 2009 to 2012 were examined. The funds analysed were the Equity Trust Fund, the Future Plan Fund and the Unit Trust Fund. The returns of the funds are modelled with the Autoregressive Moving Average (ARMA) whiles volatility was modelled with the univariate Generalised Autoregressive Conditional Heteroskedasticity (GARCH) as well as the multivariate Dynamic Conditional Correlation GARCH (DCC GARCH). This was based on the assumption of non-constant mean and volatility of fund returns. In this study the risk of a portfolio is measured using the value-at-risk. A single constrained Mean-VaR optimization problem was obtained based on the assumption that investors’ preference is solely based on risk and return. The optimization process was performed using the Lagrange Multiplier approach and the solution was obtained by the Kuhn-Tucker theorems. Conclusions which were drawn based on the results pointed to the fact that a more efficient portfolio is obtained when the value-at-risk (VaR) is modelled with a multivariate GARCH.
Modeling Mortality amongst Children under Five Years in Ghana: Comparism of Different Modeling Techniques
(University of Ghana, 2015-06) Nanga, S.; University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistics
Child mortality is regarded as one of the most revealing measures of society’s ability to meet the needs of its people.The Millennium Development Goal 4 (MDG 4) advocates a reduction of under-five mortality rate by two-thirds between 1990 and 2015. The main objective of this study was to develop a validated set of statistical models and select the most appropriate model to predict mortality among children under five and to compare the influence of selected risk factors on the probability of death before the age of 5 years among children in Ghana. The study revealed that the kth Nearest Neighbor was the most efficient in modeling Mortality in Children under five with a CCR of 83%.This is followed by Logistic Regression with a CCR of 81% and the least was Neural Network with a CCR of 80%. The highest educational level of mother, Age of mother at birth, Type of toilet facility used by family, alcohol consumption and the wealth index of family were discovered as the most important variables in predicting mortality amongst children under five in Ghana across all models. The study recommended that policy holders must ensure that every household has a place of convenience that is hygienic which has the tendency to prevent diseases like diarrhea which can result in the death of children under five. The government must also intensify public education on the dangers and effect of child mortality on society and also carry out measures to help reduce mortality significantly
On Parameter Estimation for International Market Cocoa Prices Modelling and Forecasting
(University of Ghana, 2015-06) Okyere, F.; Iddi, D.; Nortey, EN.N.; University of Ghana, Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistics
Time series analysis and forecasting has become a major tool in different applications in business phenomena, such as daily stock prices, weekly interest rates, quarterly sales, monthly supply figures, annual earnings, daily cocoa prices, etc.. It has two goals: perception or modeling random mechanism and prediction of future series quantities according to the past. In this thesis, ARIMA (Auto Regressive Integrated Moving Average) model has been used for monthly cocoa prices at the international market for years 2000 to 2014 from Bank of Ghana (BoG). Based on the inspection of the ACF, PACF autocorrelation plots, the most appropriate orders of the ARIMA models are determined and evaluated using the AIC, AICC and BIC criterion. For the monthly cocoa prices at the international market, ARIMA (0, 1, 1) or IMA (1, 1) or was appropriate for predicting future monthly prices. 1 2 1.1663 0.1663 t t t t Y e e e      In developing any time series model, parameter estimation is one of the crucial steps to consider. For this reason, this thesis focus on comparing the relative performance of model parameter estimations with Maximum Likelihood and Conditional Least Squares Estimations. A simulation exercise was carried out for the sample periods to see to which model parameter estimates could track the path of the actual estimates based on 500 simulation from ARIMA (0, 1, 1) or IMA (1, 1). This is basically to validate the method of parameter estimates of the model based on its predictive power. It was measured by Estimate, Standard Error, Bias estimate and mean square error (MSE). The simulation results suggested that with at least 50 sample size, maximum likelihood (ML) and Conditional least squares (CLS) are identical in parameter estimation. Hence, industry players and all those interested in modelling and forecasting future values can adopt any of this two method, Maximum Likelihood and Conditional Least Squares in estimation model parameter because both are identical in parameter estimation.
Statistical Analysis of the Effect of Inflation and Exchange Rate on Stock Market Returns in Ghana
(University of Ghana, 2015-06) Kwofie, C.; Mettle, F.O.; Doku-Amponsah, K.; University of Ghana, College of Basic and Applied Sciences School of Physical and Mathematical Sciences Department of Statistics
The study examined the effect of exchange rate and inflation on stock market returns in Ghana. Monthly inflation and exchange rate data obtained from the Bank of Ghana and monthly market returns computed from the GSE all-share index from January 2000 through to December 2013 was used. The Autoregressive Distributed Lag (ARDL) cointegration technique, the Error correction parametization of the ARDL model and Markov transition probabilities were used in unveiling this dynamics. The ARDL and its corresponding error correction model were used in establishing the long and short run relationship between the Ghana Stock Exchange (GSE) market returns, inflation and exchange rate. The study revealed that there exist a significant long run relationship between GSE market returns and inflation. However, there existed no significant short run relationship between them. The result also showed a significant long and short run relationship between GSE market returns and exchange rate. Furthermore, due to the existence of the long run relationships, Markov transition probabilities were used to determine the long run distributions of inflation and exchange rate. The study also revealed that in the long run there is a high probability that the cedi will depreciate against the dollar and also there is a high probability that inflation will lie between 10% and 20% inclusive in the long run.
Modeling Gdp Using Vector Autoregressive (Var) Models: An Empirical Evidence from Ghana.
(University of Ghana, 2015-06) Amoah, E.; Baidoo, I. K.; Lotsi, A.; University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistics
This study used the VAR models to model the Growth Domestics Products (GDP) of Ghana with other two selected macroeconomic such as inflation and real exchange rate for the period of 1980 to 2013. Data were taken from the World Bank’s World Development Indicators and Bank of Ghana. This study employed co-integration test and vector error correction models (VECM) to examine both long-run and short-run dynamic relationships between the GDP and the macroeconomic variables. The time series properties of the data were, first, analysed using the Augmented Dickey-Fuller (ADF) test. The empirical results derived indicate that all the variables were stationary after their first differencing; i.e. variables are integrated of order one, I(1). The study further established that there is cointegration between macroeconomic variables and GDP in Ghana indicating long run relationship. The VECM (3) model was appropriately identified using AIC information criteria with co-integration relation of exactly one .The above long term relation indicates that Real Exchange Rate have a negative effect on GDP whiles Inflation (CPI) showed a positive effect on GDP. The study further investigated the causal relationship using the Granger Causality analysis, which indicates a uni–directional causal relationship between GDP and Real Exchange rate and bi-directional causal relationship between GDP and Inflation rate at 5%. Hence the findings that inflation has a long-run relationship between GDP growth and influences it positively in Ghana, government should invest in local industries to boost domestic production of tradable which would maintain higher export volumes. This will help reduce Exchange rate and hence impact on inflation, thereby increasing GDP growth rate.
Determinants of the Promotion of University Of Ghana Lecturers: A Survival Analysis Approach
(University of Ghana, 2015-06) Letsa, C. B.; Doku-Amponsah, K.; Iddi, S.; University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistics
The desire to reach the peak of one’s chosen career makes us curious and hardworking enough to attain positions and ranks. This is no different in the academia where lecturers look forward for promotion. However, there are perceived and actual factors contributing to promotion among University of Ghana lecturers which is examined. The factors contributing to promotion of University of Ghana lecturer and how long it takes a lecturer to earn a first promotion, were the objectives of this study. The Kaplan-Meier (KM) method was used in descriptive analyses. Proportional Hazards (PH); Cox, Exponential, Weibull and Gompertz and Acceleration Failure Time (AFT); Exponential, Weibull, Log-logistic and Lognormal modelling were techniques employed in further analyses. According to the KM estimate, the average time a lecturer first promotion is 8.09 years. Based on AIC values of 518.20076 and 3459.829, the best-fitting PH and AFT models were the Gompertz and Weibull distributions respectively. Married lecturers have the same chance to earn a first promotion as compared to their single counterparts. Again, male lecturers and female lecturers in the University of Ghana do not have different time to first promotion
Statistical Analysis Of Retroviral (Hiv) Status And Other Maternal Risk Factors Associated With Low Birth Weight And Low Apgar Score Of Infants: Evidence From The Greater Accra Regional Hospital.
(University of Ghana, 2015-06) Mensah, E. Y. D.; Mettle, F. O.; Doku-Amponsah, K.; University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistics
Low birth weight and low Apgar score are major determinants of morbidity, mortality and disability in infancy and childhood. These are very important health indicators, but little is known about their causes among HIV-infected mothers in Ghana. They are also risk factors for long-term impact on health outcomes in adult life. Quantitatively, birth weight and Apgar score of an infant summarizes the morbidity conditions (LBW and LAS), with Apgar score measuring the extent of asphyxia. The study comprised data obtained through personal interviews from mothers in their postpartum at Ridge Hospital, and a secondary data generated from the mother’s antenatal book. The study sought to identify risk factors associated with LBW and LAS. The study encompassed 330 women who delivered at Ridge Hospital between February and March 2015. The prevalence of LBW and LAS at Ridge Hospital were 18.8% and 15.2% respectively. Using logistic regression, the significant risk factors associated with LBW were found to be Retroviral (HIV) status of the mother, Gestational Age, Daily Hours Rested, Frequency of Eating and Type of Cooking Fuel used. The factors that significantly influenced LAS were Retroviral (HIV) status of the mother, Gestational Age and Daily Expenditure. The results have shown that HIV-Positive Mothers are more likely to give birth to a newborn with LBW and LAS. There is also evidence that significant differences exist between the two levels of Retroviral (HIV) status with regards to birth weight and Apgar score using multivariate analysis of variance (MANOVA). Retroviral (HIV) status of the mother was found to be the most important determinant for both LBW and LAS. Therefore, it is recommended that mothers infected with HIV should be made aware so that this knowledge can facilitate early counseling and treatment to prevent LBW and LAS, and the transmission from mother-to-child. Also during pregnancy, antenatal clinic services should be encouraged especially on health education.
Estimating Value-At-Risk and Expected Shortfall on Emerging Markets: Evidence from Ghana Stock Exchange
(University Of Ghana, 2015-06) Kyei-Boadu, N.B.
An important component of Value-at-Risk (VaR) and Expected Shortfall (ES) estimation is using robust volatility models, thus the need to test the relative performance of a wide range of volatility forecasting models to ascertain the one that gives the most adequate VaR and ES forecast. Risk management has become very necessary for institutions in all sectors of an economy. Stock markets represent almost all sectors of an economy; the Ghanaian stock market being no exception. With listed companies from manufacturing, financial, agricultural, mining, oil and gas and services industry, the Ghana Stock Exchange (GSE) is a good place to test risk measures basically developed for advanced and liquid economies. This study tests the relative performance of a range of volatility models (RiskMetrics (EWMA), GARCH, EGARCH) in forecasting Value-at Risk (VaR) and Expected Shortfall (ES). Bi-weekly returns of Fan Milk Limited (FML) and GSE Composite Index (GSECI) spanning over a period of fourteen years (Jan 2000-Dec 2013) were used. Residuals of the GARCH and EGARCH models were assumed to follow a normal and student-t distribution. The first 215 observations were used to estimate model parameters while the last 150 observations used to verify and back-test the VaR forecasts. From the empirical results the ARMA-GARCH with normally distributed error terms was seen as the best volatility model for VaR and ES estimation for both FML stock and GSECI. Even though other models passed the Kupiec Unconditional coverage test, the number of VaR violations outnumbered that of the ARMA-GARCH model.
Statistical Analysis Of Socio-Economic Determinants On Child Labour And Schooling In Ghana
(University of Ghana, 2015-06) Oheneba, T.E.
The objective of this study was to find the socio-economic determinants of child labour and schooling in Ghana. To this end, the 2003 Ghana Child Labour Survey data was analysed. The main techniques used were the simple logistic regression and multilevel logistic regression analysis. Results of the analysis showed that gender of head of household, marital status of parents, father’s occupation, mother’s occupation, relationship to head of household, place of residence, literacy of head of household, sex of the child and highest educational level attained by parents are all significant determinants of child labour and schooling in Ghana. It was also found out that if a parent is an unpaid apprentice, it raises the probability that, his/her child will attend school and work. The children who are sons and daughters of the household head are not as likely to find themselves in school and work as opposed to other relations living in the household. In spite of the fact that 10-14 years of age is a typical school going age, in the case of the groups that were studied, it came out that, majority of this age group were found working. Children who combined school with work mainly come from parents who are single. These children lived in urban areas where job opportunities are available.
Recruitment and Retention of Public Sector Teachers in Ghana: A Discrete Choice Experiment
(University of Ghana, 2015-06) Gad, B. K.; Baidoo, I. K.; Iddi, S.; University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistic
The shortage of public sector teachers in rural areas is one of the main challenges facing policy makers in the education sector, in both developing and developed countries. This study sought to analyze the preferences of teachers, and how they would respond to alternative incentives associated with working in a rural location. Discrete Choice Experiment (DCE) which is rooted in Random Utility Theory (RUT) was used to capture the responses of 120 teacher trainees in Berekum College of Education. However, the full and the subgroup models were generated using the binary probit in STATA (Version 11.0). Marginal effect was also estimated. The magnitude of estimates from both the probit model and the marginal effects indicate that, for rural area posting, teachers in the public sector generally prefer and place higher priority on incentive packages such as granting of study leave with pay, provision of housing and promotion after three years of work. This was generally supported by the subgroup analysis. Also, the levels of salary will be traded off for non-financial incentive packages. It is recommended that in order to desist from force recruitment and the problem of mitigating geographical imbalances of public sector teachers, policy makers in the education sector should adopt a strategy by granting of study leave with pay, provision of housing and promotion after three years of teaching in rural areas

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