ghanaopendata/ghanaian-research-english huggingface dataset:
Modeling inflation rates and exchange rates in Ghana: application of multivariate GARCH models

This paper was aimed at investigating the volatility and conditional relationship among inflation rates, exchange rates and interest rates as well as to construct a model using multivariate GARCH DCC and BEKK models using Ghana data from January 1990 to December 2013. The study revealed that the cumulative depreciation of the cedi to the US dollar from 1990 to 2013 is 7,010.2% and the yearly weighted depreciation of the cedi to the US dollar for the period is 20.4%. There was evidence that, the fact that inflation rate was stable, does not mean that exchange rates and interest rates are expected to be stable. Rather, when the cedi performs well on the forex, inflation rates and interest rates react positively and become stable in the long run. The BEKK model is robust to modelling and forecasting volatility of inflation rates, exchange rates and interest rates. The DCC model is robust to model the conditional and unconditional correlation among inflation rates, exchange rates and interest rates. The BEKK model, which forecasted high exchange rate volatility for the year 2014, is very robust for modelling the exchange rates in Ghana. The mean equation of the DCC model is also robust to forecast inflation rates in Ghana. © 2015, Nortey et al.; licensee Springer.

Source: UG
Modeling Interest Rate Dynamics for the Bank of Ghana Rates using the Hull-White Model

Interest rates play an important role in the financial environment, affecting business transactions directly or indirectly. Fluctuations in interest rates caused largely by demand and supply of credit, regulated by the apex banks, impacts business transactions in the Economy. Understanding the dynamics of interest rates is therefore very important to Financial institutions, individual and corporate investors. In this work, the dynamics of Bank of Ghana’s, daily interest rates, ( Jan 2020 - July 2021) is modeled using the Hull-White model. London interbank offer rates, for the same period are included in the analysis. By estimating the parameters of the model, and using a computation algorithm for the solution of the SDE of the model; It is found that the mean reverting model captured the BOG and LIBOR rates well, largely maintaining the trend of the data structure. It also pointed to the presence of jumps in the data sets

Source: UG
Modeling nutrient and water productivity of sorghum in smallholder farming systems in a semi-arid region of Ghana

The CERES-sorghum module of the Decision Support System for Agro-Technological Transfer (DSSAT) model was calibrated for sorghum (Sorghum bicolor (L.) Moench) using data from sorghum grown with adequate water and nitrogen and evaluated with data from several N rates trials in Navrongo, Ghana with an overall modified internal efficiency of 0.63. The use of mineral N fertilizer was found to be profitable with economically optimal rates of 40 and 80 kg N ha−1 for more intensively managed homestead fields and less intensively managed bush fields respectively. Agronomic N use efficiency varied from 21 to 37 kg grain kg−1 N for the homestead fields and from 15 to 49 kg grain kg−1 N in the bush fields. Simulated grain yield for homestead fields at 40 kg N ha−1 application was equal to yield for bush fields at 80 kg N ha−1. Water use efficiency generally increased with increased mineral N rate and was greater for the homestead fields compared with the bush fields. Grain yield per unit of cumulative evapo-transpiration (simulated) was consistently higher compared with yield per unit of cumulative precipitation for the season, probably because of runoff and deep percolation. In the simulation experiment, grain yield variability was less with mineral N application and under higher soil fertility (organic matter) condition. Application of mineral N reduced variability in yield from a CV of 37 to 11% in the bush farm and from 17 to 7% in the homestead fields. The use of mineral fertilizer and encouraging practices that retain organic matter to the soil provide a more sustainable system for ensuring crop production and hence food security.

Source: UG
Modeling of rotavirus transmission dynamics and impact of vaccination in Ghana

The main research focus of the Electron Microscopy and Histopathology Department in the past 20 years has been in the areas of enteric diarrhoeas with special emphasis on rotavirus. Through its diarrhoea surveillance studies, the Department has helped to firmly establish rotaviruses as a major cause of diarrhoea in children, and document the circulation of unusual rotavirus genotypes in Ghana. The Department has also recently expanded its diagnostic repertoire to include the identification and characterization of noroviruses, astroviruses, and other enteric viruses.

Source: UG
Modeling soil and plant phosphorus within DSSAT

The crop models in the Decision Support System for Agrotechnology Transfer (DSSAT) have served worldwide as a research tool for improving predictions of relationships between soil and plant nitrogen (N) and crop yield. However, without a phosphorus (P) simulation option, the applicability of the DSSAT crop models in P-deficient environments is limited. In this study, a soil-plant P model integrated to DSSAT was described, and results showing the ability of the model to mimic wide differences in maize responses to P in Ghana are presented as preliminary attempts to testing the model on highly weathered soils. The model simulates P transformations between soil inorganic labile, active and stable pools and soil organic microbial and stable pools. Plant growth is limited by P between two concentration thresholds that are species-specific optimum and minimum concentrations of P defined at different stages of plant growth. Phosphorus stress factors are computed to reduce photosynthesis, dry matter accumulation and dry matter partitioning. Testing on two highly weathered soils from Ghana over a wide range of N and P fertilizer application rates indicated that the P model achieved good predictability skill at one site (Kpeve) with a final grain yield root mean squared error (RMSE) of 535kgha-1and a final biomass RMSE of 507kgha-1. At the other site (Wa), the RMSE was 474kgha-1 for final grain yield and 1675kgha-1 for final biomass. A local sensitivity analysis indicated that under P-limiting conditions and no P fertilizer application, crop biomass, grain yield, and P uptake could be increased by over 0.10% due to organic P mineralization resulting from a 1% increase in organic carbon. It was also shown that the modeling philosophy that makes P in a root-free zone unavailable to plants resulted in a better agreement of simulated crop biomass and grain yield with field measurements. Because the complex soil P chemistry makes the availability of P to plants extremely variable, testing under a wider range of agro-ecological conditions is needed to complement the initial evaluation presented here, and extend the use of the DSSAT-P model to other P-deficient environments. © 2010 Elsevier B.V.

Source: UG
Modeling the Amount of Waste Generated by Households in the Greater Accra Region Using Artificial Neural Networks

Waste can be defined as solids or liquids unwanted by members of the society and meant to be disposed. In developing countries such as Ghana, the management of waste is the responsibility of the metropolitan authorities. These authorities do not seem to have effective management of the waste situation, and therefore, it is not unusual to see waste clog the drains and litter the streets of the capital city, Accra. )e impact of waste on the environment, along with its associated health-related problems, cannot be overemphasized. )e Joint Monitoring Programme report in 2015 ranked Ghana as the seventh dirtiest country in the world. )e lack of effective waste management planning is evident in the large amount of waste dumped in open areas and gutters that remains uncollected. In planning for solid waste management, reliable data concerning waste generation, influencing factors on waste generation, and a reliable forecast of waste quantities are required. )is study used two algorithms, namely, Lev enberg–Marquardt and the Bayesian regularization, to estimate the parameters of an artificial neural network model fitted to predict the average monthly waste generated and critically assess the factors that influence solid waste generation in some selected districts of the Greater Accra region. )e study found Bayesian regularization algorithm to be suitable with the minimum mean square error of 104.78559 on training data and 217.12465 on test data and higher correlation coefficients (0.99801 on training data, 0.99570 on test data, and 0.99767 on the overall data) between the target variables (average monthly waste generated) and the predicted outputs. House size, districts, employment category, dominant religion, and house type with respective importance of 0.56, 0.172, 0.061, 0.027, and 0.026 were found to be the top five important input variables required for forecasting household waste. It is recommended that efforts of the government and its stakeholders to reduce the amount of waste generated by households be directed at providing bins, increasing the frequency of waste collection (especially in highly populated areas), and managing the economic activities in the top five selected districts (Ledzekuku Krowor, Tema West, Asheidu Keteke, Ashaiman, and Ayawaso West), amongst others.

Source: UG
Modeling the effect of seasonal climate variability on the efficiency of mineral fertilization on maize in the coastal savannah of Ghana

This study set out to (1) calibrate and evaluate the performance of APSIM in simulating maize response to N, P and residue management and (2) identify strategies to reduce instability in crop production, and increase the efficiency of mineral fertilizer use. The response of maize to inorganic nitrogen (N) and phosphorus (P) additions were determined in the coastal savannah agro-ecology in the main rainy and secondary rainy seasons, of 2008 and 2009. Field experiments were set-up in a randomized complete block design with different levels of N (0–120 kg N ha−1) and P (0–30 kg P2O5 ha−1) mineral fertilizer. The APSIM model adequately simulated agroecosystem dynamics, resulting in the following RMSE values: anthesis (1.2 days), maturity (2.0 days), maximum LAI (0.18 m2m−2) total-biomass (543 kg ha−1), grain yield (318 kg ha−1), N uptake (12.6 kg ha−1), P uptake (2.2 kg ha−1) and in-season soil water content (0.01 mm). A long-term simulation study (30 years) showed that probabilities of obtaining higher yields were higher in the main growing season than in the secondary growing season. The efficiency of mineral N fertilizer use was also higher in the main growing season. The use of 40 kg N ha−1 mineral N fertilizer in both seasons was more efficient than using 80 kg N ha−1. The variability in the efficiency of mineral fertilizer use was higher in the secondary growing (44–96 %) than in the main growing season (27–48 %). Retaining crop residues yielded higher stability in grain production and increased the minimum grain yield production significantly. Applying 40 kg N ha−1 and 30 kg P2O5 ha−1 mineral fertilizer with crop residue retention will reduce the uncertainty in maize production, particularly in the secondary growing seasons which are characterized by prolonged drought spells. This study suggests that resource-poor farmers will be better off prioritizing the main growing season for rainfed maize production and applying a moderate amount (40 kg N ha−1) of N fertilizer rather than the 90 kg N ha−1 currently recommended for the coastal savannah of Ghana in the secondary growing season because of the higher instability in yields associated with N fertilizer use in this season.

Source: UG
Modeling the environmental suitability of anthrax in Ghana and estimating populations at risk: Implications for vaccination and control

The overall goal of the department is to conduct research and provide solutions to nutritional problems in Ghana. In pursuance of this goal, the Nutrition Department since its inception has focused its research in the areas of maternal, infant and young child nutrition, food consumption and food security and micronutrient deficiency and interventions. These are priority food and nutrition problems in Ghana.

Source: UG
Modeling the impacts of contrasting nutrient and residue management practices on grain yield of sorghum (Sorghum bicolor (L.) Moench) in a semi-arid region of Ghana using APSIM

The cropping systems model APSIM (Agricultural Production Systems sIMulator) was applied to assess the response of sorghum grain yield to inorganic fertilizers applications and residue retention in diverse farmers’ management systems (homestead fields and bush farms). The model was parameterized using data collected from experiments under optimum growth conditions (limited water or nutrient stress). Independent data from field experiments with three levels of P and four levels of N fertilizers conducted at two different locations and soils were used to evaluate the model. Soil water and fertility parameters measured were used for simulations while same starting conditions were assumed for unmeasured parameters for all trials. APSIM predicted the grain yield response of sorghum to both N and P applications with an overall modified internal coefficient of efficiency of 0.64. Following model parameterization, a long-term simulation study was conducted using a stochastic weather data derived from historical weather data to assess the effects of crop residue management on grain production. A gradual decline in sorghum grain yield was simulated over the 30-year simulation period in both the homestead fields and the bush farms, with yields being much lower in the latter under farmers’ management practices. Half the amount of mineral N fertilizer used in the bush farms was needed in the homestead fields to produce the average grain yields produced on the bush farm with full fertilization, if crop residues were returned to the fields in the homestead. Year-to-year variability in grain yield was consistently higher with the removal of crop residues, irrespective of management systems. APSIM was responsive to both organic and inorganic fertilizer applications in the study area and also highlighted the essential role of crop residues and inorganic fertilizer in influencing the temporal sorghum grain production and hence the impact of farmers’ management practices on food security. This was evident in the rapid decline in soil organic carbon (SOC) accompanied by a decline in grain yield over the 30 years of cropping. The use of inorganic fertilizer and retention of crop residues (SOC) are critical for attaining food security in the study area.

Source: UG
Modeling the relationship between precipitation and malaria incidence in children from a holoendemic area in Ghana.

Climatic factors influence the incidence of vector-borne diseases such as malaria. They modify the abundance of mosquito populations, the length of the extrinsic parasite cycle in the mosquito, the malarial dynamics, and the emergence of epidemics in areas of low endemicity. The objective of this study was to investigate temporal associations between weekly malaria incidence in 1,993 children < 15 years of age and weekly rainfall. A time series analysis was conducted by using cross-correlation function and autoregressive modeling. The regression model showed that the level of rainfall predicted the malaria incidence after a time lag of 9 weeks (mean = 60 days) and after a time lag between one and two weeks. The analyses provide evidence that high-resolution precipitation data can directly predict malaria incidence in a highly endemic area. Such models might enable the development of early warning systems and support intervention measures.

Source: UG
Modeling the solar drying kinetics of gamma irradiation-pretreated oyster mushrooms (Pleurotus ostreatu

Oyster mushroom slices (Pleurotus ostreatus) were exposed to γ-radiation as a pretreatment and solar dried to investigate the influence of irradiation on drying kinetics. Processing conditions included exposure of mushrooms to 0 kGy (control), 0.5 kGy, 1.0 kGy, 1.5 kGy and 2.0 kGy of γ-radiation at a dose rate of 1.7 kGy/h and drying at a mean temperature of 53.2±6.4°C. Experimental drying data were fitted to 5 thin layer drying models by non-linear regression. Irradiation was observed to enhance the drying rate of mushroom slices, with higher doses causing faster moisture removal. Drying characteristics of slices exposed to lower dosages were best described by Page's model (R2=0.9878, 0.9967, 0.9925 correspondingly for "control" (0.0 kGy), 0.5 and 1.0 kGy while the Diffusion model best fit the data for those exposed to higher doses of radiation (R2=0.9938, 0.9890 for 1.5 and 2.0 kGy respectively). Deffranged from 1.88 to 2.44 x 10-08 and increase from "control", 0.5 kGy, 1.0 kGy, 1.5 kGy to 2.0 kGy. Irradiation of mushrooms as a pretreatment for drying increases moisture diffusivity and drying rate with higher doses having the most effect. © All Rights Reserved.

Source: UG
Modeling the spatial distribution of Global Solar Radiation (GSR) over Ghana using the ̊Angström-Prescott sunshine duration model

Solar radiation is an important geological and meteorological parameter. In most developing countries, data is readily unavailable owing to lack of instrumentation and skilled personnel. In this study, Global solar radiation (GSR) over Ghana has been quantified using the Angström–Prescott ˚ sunshine model with sunshine duration data from 22 synoptic stations distributed across the country’s ecological zones. The simulated data was gridded at 10 km by 10 km, establishing the spatial distribution of solar radiation over the country. Comparison with satellite data showed good results with root mean square error (RMSE) values of 1–5 MJm−2day−1 and correlation coefficient of 60 - 66%. Meanwhile, the esti mated total GSR over the country was found to be 412.82 MJm−2day−1. The savanna zone had the maximum estimated total monthly mean GSR for the year, with the highest value of 20.76 MJm−2day−1 in Navrongo. The forest zone had the minimum estimated total annual mean GSR, with the lowest radiation level in Oda (17.11 MJm−2day−1). A maximum and minimum mean clearness index of 0.59 and 0.48 respectively are estimated, implying that about 53% of solar radiation at the top of the atmosphere reaches the study area after attenuation. The satellite data has a total monthly mean horizontal Global Solar irradiance of 366.62 MJm−2day−1. The study shows that the region is a potential field to harness and optimize solar energy for the operation of photovoltaic systems and solar collectors for industrial and domestic applications

Source: UG
Modeling the spatial distribution of Global Solar Radiation (GSR) over Ghana using the ˚Angström-Prescott sunshine duration model

Solar radiation is an important geological and meteorological parameter. In most devel- oping countries, data is readily unavailable owing to lack of instrumentation and skilled personnel. In this study, Global solar radiation (GSR) over Ghana has been quantified us- ing the ˚Angström–Prescott sunshine model with sunshine duration data from 22 synoptic stations distributed across the country’s ecological zones. The simulated data was gridded at 10 km by 10 km, establishing the spatial distribution of solar radiation over the country. Comparison with satellite data showed good results with root mean square error (RMSE) values of 1–5 MJm −2 day −1 and correlation coefficient of 60 - 66%. Meanwhile, the esti- mated total GSR over the country was found to be 412.82 MJm −2 day −1 . The savanna zone had the maximum estimated total monthly mean GSR for the year, with the highest value of 20.76 MJm −2 day −1 in Navrongo. The forest zone had the minimum estimated total an- nual mean GSR, with the lowest radiation level in Oda (17.11 MJm −2 day −1 ). A maximum and minimum mean clearness index of 0.59 and 0.48 respectively are estimated, implying that about 53% of solar radiation at the top of the atmosphere reaches the study area after attenuation. The satellite data has a total monthly mean horizontal Global Solar irradiance of 366.62 MJm −2 day −1 . The study shows that the region is a potential field to harness and optimize solar energy for the operation of photovoltaic systems and solar collectors for industrial and domestic applications.

Source: UG
Modeling variations in the cedi/dollar exchange rate in Ghana: an autoregressive conditional heteroscedastic (ARCH) models

This research article aimed at modeling the variations in the dollar/cedi exchange rate. It examines the applicability of a range of ARCH/GARCH specifications for modeling volatility of the series. The variants considered include the ARMA, GARCH, IGARCH, EGARCH and M-GARCH specifications. The results show that the series was non station ary which resulted from the presence of a unit root in it. The ARMA (1, 1) was found to be the most suitable model for the conditional mean. From the Box–Ljung test statistics x-squared of 1476.338 with p value 0.00217 for squared returns and 16.918 with 0.0153 p values for squared residuals, the null hypothesis of no ARCH effect was rejected at 5% significance level indicating the presence of an ARCH effect in the series. ARMA (1, 1) + GARCH (1, 1) which has all parameters significant was found to be the most suitable model for the conditional mean with conditional variance, thus showing adequacy in describing the conditional mean with variance of the return series at 5% significant level. A 24 months forecast for the mean actual exchange rates and mean returns from January, 2013 to December, 2014 made also showed that the fitted model is appropriate for the data and a depreciating trend of the cedi against the dollar for forecasted period respectively.

Source: UG
Modeling variations in the cedi/dollar exchange rate in Ghana: an autoregressive conditional heteroscedastic (ARCH) models

This research article aimed at modeling the variations in the dollar/cedi exchange rate. It examines the applicability of a range of ARCH/GARCH specifications for modeling volatility of the series. The variants considered include the ARMA, GARCH, IGARCH, EGARCH and M-GARCH specifications. The results show that the series was non stationary which resulted from the presence of a unit root in it. The ARMA (1, 1) was found to be the most suitable model for the conditional mean. From the Box–Ljung test statistics x-squared of 1476.338 with p value 0.00217 for squared returns and 16.918 with 0.0153 p values for squared residuals, the null hypothesis of no ARCH effect was rejected at 5% significance level indicating the presence of an ARCH effect in the series. ARMA (1, 1) + GARCH (1, 1) which has all parameters significant was found to be the most suitable model for the conditional mean with conditional variance, thus showing adequacy in describing the conditional mean with variance of the return series at 5% significant level. A 24 months forecast for the mean actual exchange rates and mean returns from January, 2013 to December, 2014 made also showed that the fitted model is appropriate for the data and a depreciating trend of the cedi against the dollar for forecasted period respectively.

Source: UG