ghanaopendata/ghanaian-research-english huggingface dataset:
Modelling aggregate domestic electricity demand in Ghana: An autoregressive distributed lag bounds cointegration approach

In spite of the varying supply boosting efforts made by various governments to deal with the existing demand-supply gap in the electricity sector, the incessant growth in aggregate domestic electricity demand has made these efforts futile. As an objective, this paper attempts to identify the factors responsible for the historical growth trends in aggregate domestic electricity demand quantifying their effects both in the short-run and long-run periods using the ARDL Bounds cointegration approach and the sample period 1975 to 2005. In the long-run, real per capita GDP, industry efficiency, structural changes in the economy, and degree of urbanisation are identified as the main driving force behind the historical growth trend in aggregate domestic electricity demand. However, in the short-run, real per capita GDP, industry efficiency, and degree of urbanisation are the main drivers of aggregate domestic electricity demand. Industry efficiency is the only factor that drives aggregate domestic electricity demand downwards. However, the negative efficiency effect is insufficient to have outweighed the positive income, output, and demographic effects, hence the continual growth in aggregate domestic electricity demand. As a policy option, we recommend that appropriate electricity efficiency standards be implemented at the industry level. © 2011 Elsevier Ltd.

Source: UG
Modelling an Efficient Gap Filler for DTT Network Using ADS Software

This paper proposes the modelling and simulation of a special gap filler intended to cover grey areas in the DTT network of Accra. This has become necessary due to the numerous areas of low signal coverage in the Accra DTT and the incapability of previous methods to efficiently address the problem. The ADS simulation consists of arrangements of components from the DBV-T library which consists of filters, amplifiers and a power source. This setup mimics a gap filler system with a better noise reduction implementation, several frequency values are being used for the simulation process. A significant increase in the output signal as in comparison to the input means the shaded areas will be properly covered. The results derived from the simulation of the ADS setup highly improved upon the output signal values, when compared to the ITU standard. Three (3) out of five (5) simulation results show values beyond the minimum signal level requirement. Also using MATLAB, the RF propagation toolbox which has the map tool feature was able to implement the gap fillers into the Accra area and gave a visual representation of the signal strength. Modelling a gap filler system which has better noise cancellation and which propagates better with a dipole antenna was achieved in this paper. The outcome of the paper shows that the gap filler modelling increase signals in grey areas.

Source: UG
Modelling and forecasting volatility of the Botswana and Namibia stock market returns: Evidence using GARCH models with different distribution densities

This paper estimates and compares alternative distribution density forecast methodology of three generalised autoregressive conditional heteroscedasticity (GARCH) models for Botswana and Namibia stock market returns. The symmetric GARCH and asymmetric Glosten Jagannathan and Runkle (GJR) version of GARCH (GJR-GARCH) and exponential GARCH methodology are employed to investigate the effect of stock return volatility in both stock markets using Gaussian, Student-T and generalised error distribution densities. The evidence reveals that the current shocks to the conditional variance will have less impact on future volatility in both markets. News impact is asymmetric in both stock markets leading to the existence of leverage effect in stock returns. Besides, both markets exhibit reverse volatility asymmetry, contradicting the widely accepted theory of volatility asymmetry. Regarding forecasting evaluation, the results reveal that the symmetric GARCH model coupled with fatter-Tail distributions present a better out-of-sample forecast for both stock markets.

Source: UG
Modelling catch per unit effort of the Black Volta near theBui dam in Ghana

The chlorophyll a concentration and water level of the Black Volta near the Bui dam were studied in relation to fish production as measured by catch per unit effort (CPUE) between February 2011 and December 2012. The primary objective was to develop a simple linear regression model for predicting CPUE levels. The mean estimated CPUE for 2011 and 2012 was lower (6.23 kg canoe−1 day−1) in the postwet season than in the dry season (10.86 kg canoe−1 day−1) with a mean of 7.95 kg canoe−1 day−1. Hence, the dry season was the most important season for fish catches in the study area. Predictor variables that significantly explained CPUE levels were chlorophyll a (positive correlation) and water level (negative correlation) (P = 0.0002). The model was validated with independent data from the same Black Volta in 2011 and 2012. This model, CPUE = (0.062 × chlorophyll a) − (0.456 × water level) + 3.363, explained 91% CPUE variability. Independent validation indicated that the model had the potential to predict CPUE (as a measure of fish production) in the Black Volta near the Bui dam. Hence, the model is also a valuable tool to predict future trends in the CPUE levels of the Black Volta. © 2016 John Wiley & Sons Ltd

Source: UG
Modelling Cloud Cover Climatology over Tropical Climates in Ghana

Clouds play a crucial role in Earth’s climate system by modulating radiation fluxes via reflection and scattering, and thus the slightest variation in their spatial coverage significantly alters the climate response. Until now, due to the sparse distribution of advanced observation stations, large uncertainties in cloud climatology remain for many regions. Therefore, this paper estimates total cloud cover (TCC) by using sunshine duration measured in different tropical climates in Ghana. We used regression tests for each climate zone, coupled with bias correction by cumulative distribution function (CDF) matching, to develop the estimated TCC dataset from nonlinear empirical equations. It was found that the estimated percentage TCC, 20.8–84.7 3.5%, compared well with stationobserved TCC, 21.9–84.4 3.5%, with root mean square errors of 1.08–9.13 1.8% and correlation coefficients of 0.87–0.99 0.03. Overall, spatiotemporal characteristics were preserved, establishing that denser clouds tended to prevail mostly over the southern half of the forest-type climate during the June–September period. Moreover, the model and the observations show a non-normality, indicating a prevalence of above-average TCC over the study area. The results are useful for weather prediction and application in meteorology.

Source: UG
Modelling electricity demand in Ghana revisited: The role of policy regime changes

As policy regime changes, demand elasticities are unlikely to be constant since individuals change how they form their expectations, and this will change the estimated decision rules. In this paper, the time-varying nature of electricity demand elasticities prior to and post the economic reform period in Ghana is analysed using the FM-OLS. Three different sample periods -pre-reform, post-reform, and full-period- was used in the analysis. The result from the full-sample period revealed that in the long-run electricity demand is significantly affected by industry efficiency, industry value added, and real per capita GDP. Urbanization rate, however, has no significant effect. The pre-reform estimate showed lower income, output, and urbanization elasticities but higher industry energy efficiency elasticity relative to the post-reform period. This suggests that technological change in the pre-reform period has been energy saving whilst technological change in the post reform period has been energy consuming. The result further showed evidence of changing structure of the economy from the more energy intensive sector to the less energy intensive sector after the reform. Government should renew her effort in promoting energy saving technologies in the industrial sector and adjust the industrial structure to encourage the expansion of low energy intensive industries or high technology efficient industries. © 2013.

Source: UG
Modelling geographical variations and determinants of use of modern family planning methods among women of reproductive age in Nigeria

Summary Understanding the level, trend, geographical variations and determinants of use of modern family planning (FP) plays a major role in designing effective interventions leading to increased usage. This study assessed these characteristics of FP use in Nigeria using data from the 2003, 2005 and 2007 National HIV/AIDS and Reproductive Health Survey, a national population-based household survey. A Bayesian geo-additive procedure was used, which provides flexible modelling of non-linear and spatial effects at a highly disaggregated level of states. The findings reveal considerable geographical variation in the use of modern FP in Nigeria, with a distinct north-south divide. Furthermore, a significant trend in the use of modern FP was evident, with an increase between 2003 and 2005 followed by a decline between 2005 and 2007. The effect of respondent's age was non-linear, and use of modern FP was found to differ significantly between never-married and currently/formerly married respondents. Awareness of FP methods and knowledge of where to get/buy FP services/methods were found to be significantly associated with usage. The findings provide policymakers with tools to prioritize the use of scarce resources for implementing FP and reproductive health interventions.

Source: UG
Modelling level, trend and geographical variations in stigma and discrimination against people living with HIV/AIDS in Nigeria

People living with HIV and AIDS (PLHA) often face stigma and discrimination. Stigma is a powerful tool for social control and PLHA are to varying degrees stigmatised against. Consequences of stigma and discrimination against PLHA may result in low turn-out for HIV counselling and testing, identity crises, isolation, loneliness, low self-esteem and lack of interest in containing the disease. To achieve the millennium development goal on HIV reduction, efforts should be targeted at measuring impact of HIV preventive interventions. In this paper, effort was made to explore geographical variations in addition to level and trend of accepting attitude towards PLHA using 2003 - 2007 population-based household survey data. Inferences are based on Markov Chain Monte Carlo techniques, while model selection was based on Deviance Information Criteria. Findings revealed significant positive trend and spatial variations on level of accepting attitude towards PLHA. Level of exposure to HIV prevention interventions and perceptions about social support received on HIV are significantly associated with accepting attitude towards PLHA. Findings provide policy makers with tools to discern states where prevention efforts on HIV-related stigma and discrimination should be intensified. This in turn, can enhance an effective utilization of scarce resources that is paramount in developing countries.

Source: UG
Modelling Long Memory in Volatility in sub-Saharan African Equity Markets

This study examines the long memory properties in the second moments of the return series in the equity markets of Ghana, Kenya, Nigeria and South Africa. Using 5219 daily observations of thin-trading adjusted total equity market return data, we find the presence of long-range dependency in the second moments of the return innovations in all the four countries’ equity markets in the full sample. To isolate spurious long memory, we perform structural breaks analysis to guide us in splitting the data for further examination. We find that all the four countries exhibited two structural breaks each during the sample period, and long memory identified in these two markets were not influenced by the structural breaks. This finding may have an influence on portfolio diversification and risk management. The long memory characteristics in the conditional volatility may also provide useful information to market participants in pricing long-term derivative contracts.

Source: UG
Modelling of fire count data: fire disaster risk in Ghana

Stochastic dynamics involved in ecological count data require distribution fitting procedures to model and make informed judgments. The study provides empirical research, focused on the provision of an early warning system and a spatial graph that can detect societal fire risks. It offers an opportunity for communities, organizations, risk managers, actuaries and governments to be aware of, and understand fire risks, so that they will increase the direct tackling of the threats posed by fire. Statistical distribution fitting method that best helps identify the stochastic dynamics of fire count data is used. The aim is to provide a fire-prediction model and fire spatial graph for observed fire count data. An empirical probability distribution model is fitted to the fire count data and compared to the theoretical probability distribution of the stochastic process of fire count data. The distribution fitted to the fire frequency count data helps identify the class of models that are exhibited by the fire and provides time leading decisions. The research suggests that fire frequency and loss (fire fatalities) count data in Ghana are best modelled with a Negative Binomial Distribution. The spatial map of observed fire frequency and fatality measured over 5 years (2007–2011) offers in this study a first regional assessment of fire frequency and fire fatality in Ghana.

Source: UG
: Modelling tempering behaviour of dark chocolates from varying particle size distribution and fat content using response surface methodology

Central Composite Rotatable Design (CCRD) for K=2 was used to study the combined effects of multi-stage heat exchangers for Stages 1 (14–30 °C) and 2 (12–28 °C) coolant temperatures at constant Stage 3 coolant and holding temperatures during tempering of dark chocolates using laboratory-scale mini-temperer. Quantitative data on chocolate temper index (slope) were obtained for products with varying particle size distribution (PSD) (D90 of 18, 25, 35 and 50 μm) and fat (30% and 35%) content. Regression models generated using stepwise regression analyses were used to plot response surface curves, to study the tempering behaviour of products. The results showed that both Stage 1 and Stage 2 coolant temperatures had significant linear and quadratic effects on the crystallization behaviour causing wide variations in chocolate temper index during tempering of products with variable PSD and fat content. Differences in fat content exerted the greatest variability in temperature settings of the different zones for attaining well-tempered products. At 35% fat content, changes in PSD caused only slight and insignificant effect on tempering behaviour. No unique set of conditions was found to achieve good temper in dark chocolate with a specified tempering unit. Thus, different combinations of temperatures could be employed between the multi-stage heat exchangers to induce nucleation and growth of stable fat crystal polymorphs during tempering. Variations in tempering outcomes of the dark chocolates were dependent more on the fat content than PSD.

Source: UG
Modelling the cost structure of small scale export oriented vegetable farms in the North and South Dayi Districts

Using the seemingly unrelated regression technique, we estimated the cost function, represented by the coefficients of cost share equations for fertilizer, fuel, agrochemicals and labour, is estimated for the vegetable export farms in the North and South Dayi Districts in the Volta Region of Ghana from cross-sectional time series data,. The elasticities of factor substitution and demand are estimated. There is a high and significant degree of substitution between agrochemicals and fertilizer (2.1576). The estimated cross price demand elasticities show that agrochemical and fertilizer are substitutes. One percent decrease (increase) in the price of fertilizer (agrochemical) will, significantly lead to 0,3232 (0.4268) percent decrease (increase) in the demand for agrochemical (fertilizer). These results mean that the effect of policy action on the price of one of these two inputs will also effect changes in the demand of the other input. The estimated elasticities of substitution and factor demand show that labour is a complementary, though insignificant, input for fertilizer, fuel and agrochemicals. Implication for managing fertilizer, fuel and agrochemicals and emerging farm businesses are discussed.

Source: UG
Modelling the distribution and transmission intensity of lymphatic filariasis in sub-Saharan Africa prior to scaling up interventions: integrated use of geostatistical and mathematical modelling

Abstract Background Lymphatic filariasis (LF) is one of the neglected tropical diseases targeted for global elimination. The ability to interrupt transmission is, partly, influenced by the underlying intensity of transmission and its geographical variation. This information can also help guide the design of targeted surveillance activities. The present study uses a combination of geostatistical and mathematical modelling to predict the prevalence and transmission intensity of LF prior to the implementation of large-scale control in sub-Saharan Africa. Methods A systematic search of the literature was undertaken to identify surveys on the prevalence of Wuchereria bancrofti microfilaraemia (mf), based on blood smears, and on the prevalence of antigenaemia, based on the use of an immuno-chromatographic card test (ICT). Using a suite of environmental and demographic data, spatiotemporal multivariate models were fitted separately for mf prevalence and ICT-based prevalence within a Bayesian framework and used to make predictions for non-sampled areas. Maps of the dominant vector species of LF were also developed. The maps of predicted prevalence and vector distribution were linked to mathematical models of the transmission dynamics of LF to infer the intensity of transmission, quantified by the basic reproductive number (R0). Results The literature search identified 1267 surveys that provide suitable data on the prevalence of mf and 2817 surveys that report the prevalence of antigenaemia. Distinct spatial predictions arose from the models for mf prevalence and ICT-based prevalence, with a wider geographical distribution when using ICT-based data. The vector distribution maps demonstrated the spatial variation of LF vector species. Mathematical modelling showed that the reproduction number (R0) estimates vary from 2.7 to 30, with large variations between and within regions. Conclusions LF transmission is highly heterogeneous, and the developed maps can help guide intervention, monitoring and surveillance strategies as countries progress towards LF elimination.

Source: UG
Modelling the distribution and transmission intensity of lymphatic filariasis in sub-Saharan Africa prior to scaling up interventions: integrated use of geostatistical and mathematical modelling

Background Lymphatic filariasis (LF) is one of the neglected tropical diseases targeted for global elimination. The ability to interrupt transmission is, partly, influenced by the underlying intensity of transmission and its geographical variation. This information can also help guide the design of targeted surveillance activities. The present study uses a combination of geostatistical and mathematical modelling to predict the prevalence and transmission intensity of LF prior to the implementation of large-scale control in sub-Saharan Africa. Methods A systematic search of the literature was undertaken to identify surveys on the prevalence of Wuchereria bancrofti microfilaraemia (mf), based on blood smears, and on the prevalence of antigenaemia, based on the use of an immuno-chromatographic card test (ICT). Using a suite of environmental and demographic data, spatiotemporal multivariate models were fitted separately for mf prevalence and ICT-based prevalence within a Bayesian framework and used to make predictions for non-sampled areas. Maps of the dominant vector species of LF were also developed. The maps of predicted prevalence and vector distribution were linked to mathematical models of the transmission dynamics of LF to infer the intensity of transmission, quantified by the basic reproductive number (R0). Results The literature search identified 1267 surveys that provide suitable data on the prevalence of mf and 2817 surveys that report the prevalence of antigenaemia. Distinct spatial predictions arose from the models for mf prevalence and ICT-based prevalence, with a wider geographical distribution when using ICT-based data. The vector distribution maps demonstrated the spatial variation of LF vector species. Mathematical modelling showed that the reproduction number (R0) estimates vary from 2.7 to 30, with large variations between and within regions. Conclusions LF transmission is highly heterogeneous, and the developed maps can help guide intervention, monitoring and surveillance strategies as countries progress towards LF elimination.

Source: UG
Modelling the drivers of land use and land cover change of the great Amanzule wetland ecosystem to inform the development policy of the southwestern oil-rich region of Ghana

This study focused on the current and future drivers of land-use change and its impact on the Amanzule wetland. It suggests policy implications for reviewing and strengthening existing policies for sustainable land use. This study employed remote sensing and GIS techniques, including participatory rural appraisal techniques. The administration of questionnaires and focus group discussions were conducted in the Ellembelle and Jomoro municipalities, where the Amanzule wetland provides economic and social services. The results showed increased land use over the last 32 years driven by various drivers, including food crop production, rubber plantations, oil and gas establishments, and infrastructure development. The study further revealed that these drivers could influence land-use change in 18 years (2018–2036). Urbanisation, cropland, rubber plantations, and shrubland will drive land-use change in the study area between 2036 and 2054. The Amanzule wetland area is expected to decrease from 272.34 ha in 2018 to 210.60 ha by 2036. The wetland area is expected to further decrease from 210.60 ha in 2036 to 174.33 ha by 2054. Other land use classes, such as mangrove and swamp forests, are also expected to decrease within the same period. The study recommends advocating for a wetland policy, enforcing the Land Use and Spatial Planning Act 925 and the Petroleum Exploration and Production Act 919 for sustainable development.

Source: UG