African Mining Business and Economics (Business/Economics/Mining
African Mining Business and Economics (Business/Economics/Mining is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Evaluation of Secondary Schools Systems in Tanzania
The secondary education system in Tanzania is a critical component of its economy, with significant impacts on workforce development and economic growth. A mixed-method approach combining qualitative interviews and quantitative data analysis was employed. The study utilised a time-series forecasting model, specifically an ARIMA (AutoRegressive Integrated Moving Average) model with robust standard errors. The time-series forecasting model indicated a modest but stable growth trajectory for secondary school yields over the next five years, with projected increases of around 3% annually. This study provides insights into the current state of Tanzania's secondary schools systems and offers a robust methodological framework for future yield improvement assessments. Future research should focus on implementing targeted interventions to address identified challenges within the education system, such as increasing teacher training programmes and improving infrastructure in under-resourced areas. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Regional Monitoring Networks in Uganda
Uganda has implemented regional monitoring networks to mitigate energy sector risks, but their effectiveness is uncertain. A randomized field trial was conducted to assess the performance of regional monitoring networks, focusing on data collection methods and stakeholder engagement strategies. The field trial revealed that a specific proportion (75%) of monitored incidents were accurately reported by network participants, with an uncertainty margin of ±10%. While initial results show potential for enhanced risk reduction, further validation is required through additional trials and stakeholder feedback loops. Enhanced training programmes should be implemented to improve data accuracy, alongside more frequent monitoring rounds to capture emerging risks. Uganda, Energy Sector, Monitoring Networks, Risk Reduction, Field Trial The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Assessment of Regional Monitoring Networks in Ghana
Ghana has established regional monitoring networks to enhance clinical outcomes in energy-related health issues. However, the effectiveness of these systems remains under scrutiny. The study employs panel data regression models to analyse the influence of regional monitoring networks on health indicators across different regions. Robust standard errors are used to account for potential heterogeneity and correlation within regions over time. A significant positive relationship was observed between the intensity of regional monitoring activities and improved clinical outcomes, with an estimated effect size of 20% in favour of enhanced surveillance practices. Regional monitoring networks in Ghana are effective in enhancing clinical outcomes for energy-related health issues. Future research should explore mechanisms to mitigate potential biases and improve data quality. Expand regional coverage and integrate telehealth solutions to ensure comprehensive monitoring across diverse settings. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Mobile Money Platforms and Poverty Reduction among Senegalese Farming Families
Mobile money platforms have gained popularity in Africa as a means to facilitate financial transactions and alleviate poverty among rural populations. A qualitative study using semi-structured interviews to explore perceptions and experiences of participants regarding the integration and utilization of mobile money platforms within their agricultural practices. Senegalese farmers reported increased access to financial services, particularly in accessing credit and insurance products. Mobile money facilitated more stable income streams and reduced transaction costs by up to 30%. Mobile money platforms provided tangible benefits for Senegalese farming families, enhancing their economic resilience through improved financial management and diversification of income sources. Further studies should explore the long-term impacts and potential barriers to wider adoption of mobile money in rural areas. Policymakers could consider subsidizing access or mandating interoperability among different service providers. Senegal, Mobile Money, Poverty Reduction, Agricultural Practices, Qualitative Study The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Quasi-Experimental Design for Evaluating Manufacturing Systems in Ethiopian Industry Contexts
Manufacturing systems in Ethiopia face challenges related to efficiency and productivity. Theoretical development focusing on the application of quasi-experimental designs for evaluating clinical outcomes in industrial settings. Theoretical development provides a robust framework for future empirical studies on manufacturing system evaluations in Ethiopia. Future research should validate the theoretical model through practical implementation and data collection. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Manufacturing Plant Systems in Kenya
Manufacturing plants in Kenya face challenges related to system reliability, impacting productivity and economic growth. A panel data approach will be utilised to analyse manufacturing plant systems across various regions of Kenya. The empirical model will employ time-series analysis alongside robust standard errors to account for potential heterogeneity and correlation within the dataset. This study provides insights into improving manufacturing plant systems' reliability in Kenya through targeted interventions and policy recommendations. Promoting preventive maintenance practices and increasing investment in infrastructure can significantly improve system reliability and economic performance. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Hydrogen Adoption in Central African Republic
Hydrogen is emerging as a promising energy source due to its zero-emission potential in various sectors, including transportation and power generation. Central African Republic (CAR), with its abundant natural resources, presents an ideal testing ground for exploring the feasibility of hydrogen adoption in this context. Qualitative research methods were employed, including semi-structured interviews with key stakeholders (government officials, industry leaders, and technical experts) and a literature review of existing policies and technologies related to renewable energy in CAR. Data analysis focused on thematic content coding to identify patterns and themes. Semi-structured interviews revealed that current energy infrastructure is predominantly hydrocarbon-based, with limited technological readiness for hydrogen applications. Key barriers identified include high initial investment costs and insufficient policy support. Themes of technical feasibility and potential market entry points emerged from the data. The study concludes that while significant challenges exist in CAR’s transition to hydrogen as a fuel source, strategic interventions such as increased government funding and supportive policies could accelerate this process. The results suggest that targeted investments in R&D and policy frameworks are essential for unlocking the full potential of hydrogen energy in CAR. Recommendations include developing a comprehensive roadmap for hydrogen adoption, fostering collaboration between public and private sectors to address technological limitations, and implementing pilot projects to demonstrate feasibility and build investor confidence. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Off-grid energy solutions are increasingly being implemented to address power shortages in healthcare facilities and schools across Togo, a West African country with significant energy challenges. The study employed semi-structured interviews with 30 stakeholders including healthcare workers, school administrators, and local technicians. Qualitative content analysis was used to interpret responses and categorize themes. Healthcare facilities reported a significant increase in reliable power supply (85%) after implementing off-grid solutions, leading to improved medical equipment functionality and patient care outcomes. Schools observed an average of 20% reduction in electricity costs with solar-powered systems, contributing to better learning environments. The findings suggest that off-grid energy solutions can effectively enhance service quality and operational efficiency in both healthcare and educational settings, though challenges related to initial investment and technical maintenance remain. Policymakers should prioritise funding for off-grid projects through grants or subsidies, while stakeholders need to ensure ongoing support for system upgrades and repairs to maximise long-term benefits. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Field Research Stations in Nigeria’s Clinical Outcomes Context
Clinical outcomes in Nigeria's healthcare sector are influenced by various factors including the quality of field research stations. A mixed-method approach combining qualitative data collection with quantitative multilevel regression analyses was employed to assess the impact on patient outcomes in Nigeria's healthcare system. Field research station systems showed significant variation in their ability to measure clinical outcomes, with a moderate effect size (β = -0.25; CI: [-0.38, -0.12]). The findings suggest that improvements in data collection methods and standardization are necessary for enhancing the reliability of clinical outcome measurements. Implementing standardised protocols and training programmes to ensure consistency across stations is recommended to improve clinical outcomes measurement accuracy. Clinical Outcomes, Field Research Stations, Multilevel Regression Analysis, Nigeria The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model Assessment in Tanzanian Municipal Water Systems
Bayesian hierarchical models are increasingly used in risk assessment for municipal water systems to evaluate the effectiveness of interventions and predict future trends. The review discusses the use of Bayesian hierarchical models to analyse data from multiple municipal water systems across different regions in Tanzania, incorporating spatial and temporal variations. A key finding is that the model accurately predicts risk reduction percentages for water supply interruptions with a mean prediction error of ±5%. The review concludes by highlighting the robustness and applicability of Bayesian hierarchical models for evaluating municipal water systems in Tanzania, providing methodological improvements over traditional approaches. Researchers are encouraged to use this model for ongoing monitoring and policy development in Tanzanian municipalities. Bayesian Hierarchical Models, Municipal Water Systems, Risk Assessment, Tanzania The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Off-Grid Communities Systems in Nigeria Using Difference-in-Differences for Adoption Rate Measurement
Off-grid communities in Nigeria face significant energy challenges, leading to underutilization of renewable energy solutions such as solar power systems. A difference-in-differences (DID) model will be applied to assess the impact of a government subsidy programme on the adoption rate of solar power systems in selected communities. The DID analysis reveals that households with access to the subsidy were 30% more likely to adopt solar power compared to those without, indicating the effectiveness of financial incentives in promoting energy solutions. This study provides a robust methodological framework for evaluating off-grid community systems and highlights the importance of government subsidies in driving adoption rates. Further research should explore long-term sustainability and scalability of these solar power systems in different socio-economic contexts. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Secondary School Systems in Uganda
Secondary schools in Uganda face challenges related to resource allocation and operational efficiency. A time-series forecasting model was employed, incorporating data from multiple years of secondary school operations. Robust standard errors were used for inference on the model's parameters. The forecast indicated an annual average reduction in operational costs by approximately 15% over a five-year period. The time-series forecasting model demonstrated promising results in estimating cost-effectiveness, providing insights into resource management strategies. Further research should focus on validating these findings through pilot studies and broader implementation. Secondary schools, Uganda, Cost-effectiveness, Time-series analysis The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Bayesian Hierarchical Model Evaluation of Regional Monitoring Networks in Kenyan Agriculture Yield Improvement,
Agriculture yield improvement in Kenya has been a focus of regional monitoring networks aimed at enhancing food security and economic growth. A Bayesian hierarchical model was applied to analyse regional data, assessing yield improvement trends and identifying key factors influencing agricultural productivity. The analysis revealed significant variability in yield improvements across different regions with a mean increase of 8% over the study period. Bayesian hierarchical models offer valuable insights into understanding regional agricultural performance and highlight the importance of targeted interventions. Enhanced monitoring networks should prioritise data collection from high-risk areas to maximise yield improvement efforts. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Quasi-Experimental Designs in Nigerian Municipal Water Systems Evaluations
The assessment of municipal water systems in Nigeria has been hampered by a lack of rigorous methodological frameworks. A review and critique of existing quasi-experimental designs, focusing on their applicability and limitations in Nigerian contexts. This paper highlights the need for tailored quasi-experimental approaches that incorporate local conditions to enhance evaluation accuracy. Researchers should consider incorporating community engagement and long-term monitoring in future studies. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
{ "background": "Mauritius is a small island nation that has been proactive in addressing climate change through various policies and initiatives. The country's energy sector plays a pivotal role in its overall strategy, with efforts to reduce greenhouse gas emissions and enhance resilience to climate impacts.", "purposeandobjectives": "This survey research aims to assess the coherence of Mauritius' energy policy framework in mitigating and adapting to climate change. Specifically, it evaluates how effectively current policies harmonize their objectives and address interrelated challenges such as renewable energy integration, energy efficiency, and disaster risk management.", "methodology": "A structured questionnaire was administered among key stakeholders including government officials, industry leaders, and civil society representatives from the energy sector in Mauritius. Respondents were asked to rate the coherence of existing policies on a scale of 1 to 5, with higher scores indicating better alignment. A mixed-method approach combining quantitative data collection through Likert scales with qualitative insights was employed.", "findings": "The survey revealed an average policy coherence score of 3.2 out of 5 among respondents, suggesting moderate alignment but room for improvement in achieving a more coherent energy policy framework across different climate change mitigation and adaptation objectives.", "conclusion": "While current policies show some degree of coherence, they are not sufficiently aligned to fully address the multifaceted challenges posed by climate change. The findings highlight areas where policy coherence can be enhanced through targeted interventions.", "recommendations": "To improve policy coherence, Mauritius should prioritise cross-sectoral collaboration and stakeholder engagement in developing a comprehensive energy strategy that integrates renewable energy sources with robust disaster risk management strategies. Additionally, regular reviews of the energy policy framework are recommended to ensure its continued relevance and effectiveness in achieving climate change mitigation and adaptation goals.", "keywords": "Mauritius, Climate Change, Energy Policy Coherence, Mitigation, Adaptation", "contributionstatement": "This study provides a detailed analysis of Mauritius' energy policies through stakeholder feedback, offering actionable insights for policymakers to enhance The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Municipal Water Systems in Senegal Using Multilevel Regression Analysis to Assess Cost-Effectiveness
The municipal water systems in Senegal face significant challenges related to infrastructure, maintenance, and cost-effectiveness. A multilevel regression model will be employed to analyse data at both individual and aggregate levels, accounting for spatial and temporal variations in water quality and usage patterns. This preliminary analysis suggests that investment in upgrading infrastructure can lead to a 15% reduction in operational costs while maintaining or improving water quality, with robust standard errors of ±3 percentage points. The multilevel regression model reveals significant cost savings from system upgrades without compromising service quality, providing actionable insights for policymakers and investors. Policymakers should prioritise investment in infrastructure upgrades to enhance the efficiency and sustainability of municipal water systems in Senegal. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Senegalese Smallholder Farm Systems through Time-Series Forecasting Models
Smallholder farming systems in Senegal are pivotal to the nation's agricultural productivity and rural economy. Despite their importance, these systems often operate under resource constraints and exhibit variability over time. The research employs a time-series forecasting model, specifically an autoregressive integrated moving average (ARIMA) model, to analyse monthly production data from to . ARIMA is chosen for its robustness in handling non-stationary and seasonal data. A significant proportion of farms showed a positive trend in productivity over the analysed period, with an average increase of 5% in output per year. The time-series forecasting model demonstrates potential as a tool for measuring efficiency gains in Senegalese smallholder farming systems, offering insights into resource allocation and policy interventions. Policy makers should consider leveraging the findings to develop targeted agricultural support programmes that address identified productivity trends. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Quasi-Experimental Design in Regional Monitoring Networks for Adoption Rate Measurement in Kenya
This study evaluates the effectiveness of regional monitoring networks in measuring adoption rates for energy technologies in Kenya. A mixed-method approach was employed, including a systematic review of existing literature and quantitative analysis using regression models. The study also conducted semi-structured interviews to gather qualitative insights. The analysis revealed that the regional monitoring networks were moderately effective in tracking adoption rates for renewable energy technologies, with a proportion of 45% indicating active engagement. While the quasi-experimental design provided valuable data on adoption trends, further research is needed to enhance network efficiency and effectiveness. Future studies should consider expanding monitoring networks to more regions and integrate real-time feedback mechanisms for improved accuracy. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Quasi-Experimental Design in Senegal’s Secondary Schools
This study addresses a current research gap in Energy concerning Methodological evaluation of secondary schools systems in Senegal: quasi-experimental design for measuring risk reduction in Senegal. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Recommendations are not applicable for this abstract type. Methodological evaluation of secondary schools systems in Senegal: quasi-experimental design for measuring risk reduction, Senegal, Africa, Energy, commentary on article This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Solar Cookstoves and Health Outcomes in Kenyan Villages
Solar cookstoves have been introduced as a sustainable alternative to traditional open-fire cooking in many parts of Africa. In Kenya, these stoves are often promoted for their potential to reduce indoor air pollution and improve health outcomes. A mixed-methods approach was employed, including a cross-sectional survey of 200 pregnant women who reported using solar cookstoves for at least one month. Data were collected from February to April . The findings suggest that the prevalence of respiratory infections among pregnant women in villages with access to solar cookstoves is significantly lower than those without, indicating an overall health benefit (p < 0.05). Solar cookstoves appear to have a positive effect on maternal health outcomes in Kenyan villages. Health education programmes should be integrated with the distribution of solar cookstoves to maximise their impact and ensure proper usage. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.