ghanaopendata/ghanaian-research-english huggingface dataset:
Threshold quantities and Lyapunov functions for ordinary differential equations epidemic models with mass action and standard incidence functions

This paper presents a novel algebraic method for the construction of Lyapunov functions to study global stability of the disease-free equilibrium points of deterministic epidemic ordinary differential equation models with mass action and standard incidence functions. The method is named as Jacobian-Determinant method. In our method, a direct algebraic procedure that also relies only on determinant of the Jacobian matrix of the infected subsystem is developed to determine a threshold quantity, ′ 0 akin to the basic reproduction number, 0 of such class of models. The developed technique is applied on a wide variety of models to construct Lyapunov functions to study the global stability of the infection-free critical points. Further, implementation of our method reveals that the threshold quantity is the same as (or the square) of the basic reproduction numbers as obtained using the next-generation matrix method. It is further observed that even for models that do not use the standard or mass action incidence, the threshold quantity is still related to the basic reproduction numbers as obtained with the next-generation matrix method.

Source: KNUST
Time dependent variable in the Black-scholes: an application in life insurance contracts

Valuations of actuarial liabilities (benefits of insurance contracts) have been of major concern to managers and policy holders in the financial sector. These valuations are done through the standard BS-equation which assumes a constant rate of return. However literature has it that rate of return is time dependent and valuation under constant rate of return may impair the conclusions made on life insurance contracts. This study seeks to solve the modified Black-Scholes partial differential equation with the incorporation of time dependent rate of return in the valuation of life insurance contracts. Further, solutions to both the standard and modified model under two iterative techniques, Hopscotch and Crank-Nicolson, were investigated and compared. In line with these objectives, data was simulated and estimates for speed and level were computed for using Vasicek model. These estimates were now adopted in modeling the interest rate as a Cox-Ingersoll-Ross process. Solutions to both the standard and modified BS indicates that the Hopscotch converges faster than the Crank-Nicolson but the Crank-Nicolson gives consistent values than the Hopscotch. Further it was observed that value of life insurance contract from the modified model are much lower than that of the existing model.

Source: KNUST
Time overrun and cost effects of Tailings Storage Facility (TSF) Construction Projects in Ghana

Construction project time overrun is endemic and bears both direct and indirect cost implications to project budgets. This thesis seeks to, by questionnaire measure and through empirical method assess the percentage cost escalation of TSF projects that have overran their agreed upon completion dates. Data was obtained from 56 respondents comprising of contractors (51.8%), consultants (28.6%) and clients (19.6%). Of the total respondents, 23 were project managers, 20 were Civil Engineers, 8 were Quantity Surveyors, 5 belonged to other group of professionals. The study reveals that time overrun is frequent in TSF construction projects which is indicated by 86% of respondents who indicate time overrun was experienced by their projects. 57.1% of respondents asserted that their projects overrun cost by less than 5% of the project budget due to time overrun factor. 25% of surveyed respondents indicated their projects overran cost by 5% of their project budgets, 12.5% overran 10% of their TSF project budgets whiles 3.6% overrun cost at 15% of their project budget. Generating a predictive model for time overrun from the survey data revealed capacity, project duration and project budget as independent variables and time overrun as the dependent variable. The mean variation between time overrun and capacity of TSF, project duration and project budget in relation to construction projects in Ghana are equal hence the acceptance of the null hypothesis. Twenty-one (21) factors were identified by all respondents as cost factors that emanate as a result of poorly managed time overrun causes by industry practitioners. The highest ranked cost effect was identified to be Claims (ranked 8.21) with a standard deviation of 0546. Traditional contracting is ranked the most effective procurement system for time overrun mitigation partly. The use of effective procurement systems and the possible mitigation of time overrun causes be timeously made in order to curtail the effects of cost incurred due to time overrun in TSF construction projects.

Source: KNUST
Time Performance of public building projects in Ghana

This study investigates the time performance of public building projects in Ghana. The aim is to improve the time performance of public building projects in the country. The study adopted the quantitative research strategy and survey research method with the use of questionnaires and interview to seek Experts' Opinion on the projects duration estimation methods currently used in practice, the time performance of public building projects and relevant time-influencing factor within the Ghanaian construction environment. The result of the research revealed the mean Time Performance Index (TPI) of public building projects in Ghana within the range 1.9035 to 2.7143. This suggests that on the average, public building projects takes between 1.9035 to 2.7143 times the original project duration to complete, an indication of poor project time performance. The research identified this poor TPI to be due to over-dependent on experience for the determination of project duration and lack of proper project planning. Also public building projects durations were mostly given by the client who will normally not have any scientific basis for it. Thirty-five (35) significant construction time-influencing factors were established out of the 72 identified with the first six in the order of decreasing importance being Project Finance Method, Material (Prices/Availability/Supply/ Quality/Imports), Clients' Financial Ability, Completeness and Timeliness of Project Information, Variation Orders/ Additional Works (Magnitude, Timing, Interference Level) and Contractors' Financial Capability (Table 5.13). It was recommended that scientific approach and proper project planning be adopted for the estimation of project durations and time control to improve time performance.

Source: KNUST
Time Series Analysis of Malaria Cases in Ashanti Region, A Case Study of Out Patient Department of Komfo Anokye Teaching Hospital

Malaria still remains a public health problem in some regions of Ghana. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria cases in the Out Patient Department (OPD) of Komfo Anakye Teaching Hospital(KATH) using time series and ARIMA...

Source: KNUST
Time Series Analysis and Forecasting of Epack Mutual Fund Share Prices From 1999 to 2010.

Time series analysis and forecasting has become a major tool in different applications in the field of business Management, Economics and so on. Investment is an integral part of human life. This research work was carried out in Data Bank Asset Management Limited, Kumasi branch where data was collected on the EPACK Mutual Fund share prices which is one of their valuable products from January 1999 – 2010. A time series analysis was employed, where the trend of the share price exhibited a general upward moving quadratic trend with significant fall in the year 2009, but continued rising from January 2010 to December 2010. A mathematical model was developed to suit the share price where as a MatLab was used to code for the forecasted values.

Source: KNUST
Time series analysis of enrolment of pupils in public second cycle schools in Assin South District

Education plays an important role in a developing country like Ghana. Education is needed to improve productivity as a result of harnessing human resources effectively. After the basic education, the pupils are enrolled in the second cycle schools through the Basic Education Certificate Examination (BECE). The study analyses the mean number of pupils enrolled in the public second cycle schools in Assin South District in the Central Region of Ghana (from 1991 to 2012). It also uses the Box-Jenkins modeling to fit a model to the enrolment of pupils in the four (4) public second cycle schools, which can be used to predict future enrolment in the district. The secondary data obtained from the four (4) public second cycle schools in the district was made up of twenty-two (22) consecutive years of number of pupils enrolled from 1991 to 2012. The Box-Jenkins ARIMA modeling was used to model the data. The appropriate ARIMA models; ARIMA (2, 2, 1), ARIMA (2, 2, 2) and ARIMA (2, 2, 3) were chosen based on the autocorrelation and partial autocorrelation functions. The estimation of the model parameters was carried out using the maximum likelihood estimation method with the R statistical software package. The ARIMA (2, 2, 1) model was selected as the best model since its AIC and BIC values were far lower than the other competing models. The T-test revealed that the MA part of the ARIMA (2, 2, 1) was statistically not significant and the final ARIMA model for forecasting was ARIMA (2,2,0). It was observed that enrolment of pupils in the public second cycle schools in the district had been increasing and it may also increase in 2013, 2014 and 2015.

Source: KNUST
Time Series Analysis of Road Traffic Accidents in Ghana, A Case Study of Accra – Tema Motorway, Greater Accra Region

Road traffic accident in Ghana is increasing at an alarming rate and has raised major concerns. In this thesis, time series with Box – Jenkins method was applied to 31 years of annual road accident data from 1980 – 2010 to determine patterns of road traffic accident cases, injuries and deaths along the Accra – Tema motorway. Models were subsequently developed for accident cases, injuries and deaths. ARIMA (1,1,1) was tentatively used to model the injury and death data whilst ARIMA(0,1,2) was used to model the accident cases data. 10 years forecasts were made using the models developed and it showed that, road traffic accident cases, injuries and death would continue to increase.

Source: KNUST
Time Series Analysis of Microwave Transmission on the Yeji-Salaga Line-Of-Sight Telecommunication Link

Microwave links, which are used for communication, are mostly over land. The behaviour of the links over a water body depends on various factors such as atmospheric conditions, water body behaviour and the environment in which the link is operated. The Yeji-Salaga Line-of-Sight (LOS) microwave telecommunication link is along the Volta Lake. This study therefore aimed at investigating the microwave transmission on the Yeji-Salaga link using a time series Analysis. Sequence of observations of Received Signal Level (RSL) data were collected over five years between January, 2006 and December, 2010. The data was aggregated to obtain average monthly data. Seasonal Autoregressive Integrated Moving Average (SARIMA) models were developed on the RSL data collected. The most suitable model selected was SARIMA (1, 1, 1) x (0, 1, 2)12 based on the diagnostics of the residuals of each model and the minimum Information Criteria. Forecasting with the SARIMA (1, 1, 1) x (0, 1, 2)12 model for the period January, 2011 to July, 2011 agrees well with the observed data series collected over the same period. The results showed that SARIMA (1, 1, 1) x (0, 1, 2)12 model can be used to predict the performance of a microwave transmission link.

Source: KNUST
Time series analysis of malaria cases in the Berekum municipality

Health is a very essential aspect of human life. It is however imperative to know that one of the endemic diseases which deteriorates our health, Malaria poses a threat to 40% of the world’s population. In Ghana, it has become one of the leading causes of mortality and morbility particularly among pregnant women and children under five years. This research, therefore, sought to model the trend of Malaria cases from 2011 to 2015 and to forecast the incidence of Malaria cases for the years 2016 to 2018. The time series methods were used to explore the historical pattern of the variable of interest. The study adopted quantitative research approach and design. The pragmatic worldview as an interpretive framework which made use of quantitative methods in collecting data from the Berekum Municipal Hospital. Data collected during the study showed three trends from 2011 to 2017. From 2011-2013, a similar trend was seen where two peaks were recorded in a year (the middle and towards the end of the year) being the highest cases of malaria recorded. It further declined from 2014 to 2015 and continued for the predicted time series cases from 2016 to 2017. Therefore the community should expect a decline in malaria cases in subsequent years but there should be a system to monitor the trend in case there is any change. The trend of malaria cases should be modeled for different localities since climate factors may affect the prevalence and incidence of malaria.

Source: KNUST
Time Series Analysis of Value Added Tax Revenue Collection in Ghana

Economic growth is one of the major concerns of every government. In the quest to know how the Economy of Ghana is fairing through the various regimes of governance, increasing population and other factors that affects economic growth, this thesis has been purposed to study the behaviour pattern and trend in Ghana’s Domestic and Import Value Added Tax Revenue in Ghana and to choose the best model among various ARIMA models which pose’s high power of predictability for forecasting Ghana’s Real Domestic and Import VAT Revenue. Finally, the data of yearly Domestic and Import VAT revenue in Ghana from 1999 to 2009 was examined. The Box- Jenkins method of Time Series analysis was employed. The model; Y_t=〖2.0145Y_(t-1) –〖1.6275Y〗_(t-2 )+0.613Y_(t-3)+ 1.6053e〗_(t-1)-0.9999e_(t-2)+e_t+0.3402 An ARIMA (2, 1, 2) was deduced to be the best model to forecast Domestic VAT revenue in Ghana, Whilst the model; Y_t=〖0.1882Y_(t-1)+〖0.4917Y〗_(t-2 )+0.3201Y_(t-3)- 0.3196e〗_(t-1)+e_t+0.6093 An ARIMA (2, 1, 1) was deduced to be the best model to forecast Import VAT revenue in Ghana.

Source: KNUST
Time series analysis on membership enrolment of national health insurance scheme. a case study of Savelugu/Nanton District mutual health insurance scheme in Northern Region

The National Health Insurance Scheme (NHIS) is a social policy; a kind of social re-engineering that caters for the healthcare needs of the most vulnerable and all residents in Ghana. It allows everybody residents in Ghana to register with a nearby district mutual health insurance scheme for their healthcare needs. The research was undertaken to study the trend/pattern of membership registration at the Savelugu/Nanton District Mutual Health Insurance Scheme and also to select the best ARIMA model that will be use in predicting future enrollment values for the scheme. Secondary data was obtained from the office of the Savelugu/Nanton Mutual Health Insurance Scheme (SNDMHIS) from the inception of the Scheme in the year 2005 up to 2010. A mathematical concept, Time Series analysis was used to model the membership enrollment of the scheme and was used to make predictions of future enrollment into the scheme. The overall ARIMA model obtained was . The model was used to make prediction for 2011 and 2012. The predicted values recorded were decreasing from month to month. Findings from the study also indicate that enrollment of individuals to the scheme had experienced an increase and a decrease linear trend from the year 2005 to 2010. The highest enrollment (4,213) from the inception of the scheme was recorded in December 2008. Thereafter, enrollments have been declining gradually from year to year. However, most of other few high enrollment values were recorded from August to December over the period under study and same was seen from the predicted values of 2011 and 2012.

Source: KNUST
Time Series Analysis of Water Consumption in the Hohoe Municipality of the Volta Region of Ghana

Water is considered as lifeline of all living things especially humans, hence its availability is a critical component in the measurement of human wellbeing through the Human Development Index (HDI). Its production and distribution in Ghana particularly in the Hohoe Municipality of the Volta Region is a challenge. This study seeks to identify the best fit time series model to the water consumption data in the Hohoe Municipality and to forecast water consumption in the Municipality. This underpins the development of a time series model for forecasting water consumption levels of the residents, institutions and businesses in the municipality. Several time series models including AR, MA, ARMA, ARIMA and SARIMA were fitted to the data, and it emerged that the most adequate model for the data was ARIMA (2, 1, 2). There will be no astronomical increases in water consumption levels in the municipality over the next 4 years. It is recommended that the Ghana Water Company Limited should use the model and its forecasted figures in its operational and planning activities.

Source: KNUST
Time Series Analysis on Syphilis in Asikuma Ododen Brakwa District

Syphilis has re-emerged as a global public health issue. In lesser developed countries, millions of people are contracting the disease which can be fatal without access to proper treatment. This thesis has been aimed to study the behavior pattern and trend in syphilis cases in the Asikuma Odoben Brakwa district in the Central Region. The best model among various ARIMA models was chosen which possess high power of predictability for forecasting the syphilis prevalent rate between the female and males in Asikuma Odoben Brakwa district from 2007 to 2011. Finally the data for the positive cases for both male and female from 2007 – 2011 was examined. The Box–Jenkins method for analyzing Time Series was used in the research finding. The model was ARIMA(1,1,1)〖(0,1,1)〗_([12]) was selected to be the best model to forecast syphilis cases in the district.

Source: KNUST
Time series arima modelling of inflation in Ghana: (1990 – 2009)

Throughout the world, most central bank policy initiatives have been aimed at achieving and maintaining price stability and the Bank of Ghana is no exception to this rule. This study attempts to outline the practical steps which need to be undertaken in order to use the autoregressive integrated moving average (ARIMA) model for forecasting Ghana’s inflation. The main focus of the study is to model inflation and hence used to forecast the monthly inflation on short-term basis, for this purpose, different ARIMA models are used and the candid model is selected based on various diagnostic, evaluation and selection criteria. It can be concluded that the model has sufficient predictive powers and the findings are well in line with those of other studies. Again the study models inflation for the periods of 1990 to 2000 and 2001 to 2009 and it was realized that the inflation model for the period of 1990 to 2000 is ARIMA (1, 2,2) written as (y_t ) ̂=18.5770+0.455848t-3.57e^(-0.3) t^2+0.7807y_(t-1)-1.0813ε_(t-1)+0.1020ε_(t-2)+(ε_t ) ̂. Whilst that of 2001 to 2009 is modelled as ARIMA (2, 2, 1), written as (y_t ) ̂=34.3958-0.637228t+4.40e^(-0.3) t^2-1.3764y_(t-1)-0.4389y_(t-2)+0.9860ε_(t-1)+(ε_t ) ̂ It was concluded that inflation for the period of January 2001 to December 2009 was less than that of January 1990 to December 2000. The model is recommended for use by stakeholders because it has a lower error variance of ±1 which follows closely with the actual data. It is recommended further to be used as the basis for constructing deterministic models such as first and second order differential equations by future researchers

Source: KNUST
Time Series Analysis on Multiple Macro Economic Indicators in Ghana

The study sought to test the hypothesis that there is no relationship between real effective exchange rate and other macroeconomic variables.This study was done by developing an empirical model for Real Effective Exchange Rate with special focus on Foreign aid using the cointegration, vector and error correction (VEC) and vector auto regression (VAR) approach. Annual data covering the period 1980 to 2011 was collected (World Bank Development Indicators). The outcome of the study showed that foreign aid as well as government expenditure, Aid, Money supply, Terms of Trade and Openness of the economy have appreciating effect on Real Effective Exchange Rate. On the other hand Government Expenditure had depreciating pressure on Real Effective Exchange Rate. We also established from the variance decomposition and impulse response function that foreign aid is an important determinant to real effective Exchange Rate.

Source: KNUST
Time series modeling and forecasting of the demand of some petroleum products in Ghana

The study is an application of Box-Jenkins ARIMA modelling and forecasting to petroleum products demand in Ghana. Monthly data on demand levels from January, 1999 to December, 2010 of petroleum products namely; Gas Oil, Liquefied Petroleum Gas (LPG) and Premix Fuel were analysed and forecasts made 12 months ahead. Thus, after stationarity was established through differencing of the data, the sample ACF and the sample Partial Autocorrelation Function (PACF) of the differenced data were considered to generate possible models after which the AIC, AICc and BIC of the candidate models under the various data were examined and those candidate models with the smallest AIC, AICc and BIC were chosen as the best-fit models among the candidate models and used for forecasting. The best fit model for the National Gas Oil demand, National LPG demand and National Premix demand levels were found to be ARIMA(1,1,3), ARIMA(2,1,3) and SARIMA(3,1,0)(2,0,0)[12] respectively.

Source: KNUST
A Times Series Analysis into the Rainfall Patterns in Four Selected Regions of Ghana

In recent times there have been calls on the climatic changes that are happening and the need to put measures in place to forestall drastic changes in the climate. In this study therefore, we attempted to study the trend of rainfall patterns in Ghana for four regions: Northern, Western, Eastern, and the Greater Accra Region, using four models namely: Linear Trend with Seasonal Terms, Seasonal Exponential Smoothing, ARIMA, Simple Exponential Smoothing, and Linear (Holt) Exponential Smoothing. All the ARIMA models are one model family, and the Simple Exponential Smoothing and Linear (Holt) Exponential Smoothing which is one model family, since the Simple Exponential Smoothing is just basics of the Linear (Holt) Exponential Smoothing. We have been able to show that the best model for the prediction of rainfall in the regions under study was Linear Trend with Seasonal Terms; in choosing this model we used the Means Square Error (MSE) and the R-Square as a criterion for the selection of the best model for prediction. We also further were able to come to the conclusion that the levels of rain in this four regions are not going to fall but rather will rise at least for the year 2011.

Source: KNUST