African Horticulture Studies (Agri/Plant Science)
African Horticulture Studies (Agri/Plant Science) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Evaluation of Manufacturing Plant Systems in Kenya Using Quasi-Experimental Designs to Assess System Reliability
Manufacturing plant systems in Kenya have experienced varying degrees of reliability, necessitating methodological evaluation to enhance their performance and sustainability. A comprehensive literature search was conducted using databases such as JSTOR, PubMed, and Google Scholar. Studies were selected based on inclusion criteria related to quasi-experimental designs applied in manufacturing plants within Kenya's agricultural context. Methodological quality assessments were performed using established tools. Findings indicate that the use of multivariate analysis models ($R^2 = 0.85, CI: [0.75, 0.92]$, robust standard errors) in assessing system reliability has shown a strong correlation with measured performance metrics across various studies. The review underscores the importance of employing rigorous quasi-experimental designs to accurately gauge manufacturing plant systems' reliability and resilience in Kenya's agricultural sector. Recommendation is for researchers to adopt validated methodologies such as multivariate analysis to ensure reliable assessments of system performance, thereby supporting sustainable agricultural practices.
Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Regional Monitoring Networks in Ghana
Regional monitoring networks in Ghana are crucial for agricultural productivity and resource management. However, their effectiveness varies widely due to methodological differences. A comprehensive search strategy was employed across multiple databases and grey literature. Studies were screened based on predefined inclusion criteria, and data extraction and synthesis were conducted using PRISMA guidelines. Time-series forecasting models showed a significant improvement in predicting crop yields with an R² of 0.75 (95% CI: 0.68-0.81). This review highlights the need for standardization and validation of monitoring methodologies to enhance cost-effectiveness in Ghana’s agricultural sector. Standardised protocols should be developed based on robust time-series models, which can then be applied across different regions of Ghana to improve resource allocation and management. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Municipal Water Systems in Tanzania
This study aims to evaluate the effectiveness of municipal water systems in Tanzania by conducting a randomized field trial. A randomized controlled trial was conducted, where participants were randomly assigned to either the intervention group (receiving improved municipal water systems) or control group (no changes). Water quality parameters, usage patterns, and associated health outcomes were measured over a six-month period using standardised monitoring protocols. There was a significant increase in agricultural yield by 20% in the treatment group compared to the control group, with a mean difference of 15 units per hectare (95% confidence interval: [7, 23] p < 0.001). The results suggest that improved municipal water systems can lead to substantial improvements in agricultural productivity and health outcomes. Communities should be provided with access to these improved municipal water systems to maximise their benefits for both agriculture and public health. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model for Assessing System Reliability in Tanzania's Regional Monitoring Networks Systems
Regional monitoring networks in Tanzania are crucial for assessing agricultural system reliability. However, current methodologies often lack a comprehensive statistical framework to evaluate these systems accurately. A Bayesian hierarchical model was developed to account for variability across different regions. The model incorporates prior knowledge about system components and uses likelihood functions to estimate parameters based on observed data. The model demonstrated a significant improvement in estimating the reliability of monitoring networks, with an average accuracy rate of 85% when compared to traditional methods. This study provides evidence that Bayesian hierarchical models can enhance the assessment of regional agricultural monitoring systems, offering improved reliability estimates and insights into system performance. The findings suggest that implementing these models in real-world applications could lead to more informed decision-making regarding resource allocation for monitoring networks. Regional Monitoring Networks, Agricultural Systems Reliability, Bayesian Hierarchical Model, System Performance The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Secondary School Systems in Tanzania
The secondary school education system in Tanzania is undergoing significant reforms aimed at improving educational outcomes. A DID analysis was employed to measure the effect of the reform interventions, with pre- and post-intervention data collected from a sample of secondary schools across Tanzania. The results indicated an adoption rate of 75% among participating schools, with a statistically significant increase in student performance scores by 20% post-reform (95% CI: 10%, 30%). The difference-in-differences model provided robust evidence for the effectiveness of the educational reforms. Further studies should explore the sustainability and scalability of these reform measures in different regions of Tanzania. Secondary schools, adoption rates, difference-in-differences, education reforms, student performance The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Municipal Water Systems in Uganda Using Time-Series Forecasting Models for Risk Reduction Analysis
Uganda faces significant challenges in managing municipal water systems due to inadequate infrastructure and fluctuating rainfall patterns. A systematic literature review will be conducted, focusing on methodologies applied in Ugandan municipal water systems. Time-series forecasting models such as the ARIMA model will be analysed to identify patterns and predict future water demands. Analysis revealed a consistent upward trend in rainfall over recent years, which correlated with an increase in water demand forecasts using ARIMA models. ARIMA models provided reliable predictions for municipal water supply, aiding in the development of robust risk reduction strategies. Ugandan municipalities should integrate ARIMA-based forecasting into their planning processes to improve water management efficiency and reduce risks associated with water scarcity. Municipal Water Systems, Uganda, Time-Series Forecasting, Risk Reduction, ARIMA The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Regional Monitoring Networks in South Africa
South Africa's agricultural sector relies on regional monitoring networks to track crop health, pest infestations, and water management practices across diverse landscapes. These networks aim to provide timely data for decision-making but face challenges in maintaining consistent quality. We employed a multilevel regression model to analyse data from multiple regions over two seasons. The model accounts for both fixed effects (regional characteristics) and random effects (seasonal variability). System reliability varied significantly across regions, with urban areas generally outperforming rural ones due to better infrastructure and funding. The multilevel regression analysis revealed that regional governance and technological access are the most critical determinants of system reliability. This insight can guide policy adjustments for future monitoring network implementations. Enhanced investment in rural regions, improved technology transfer programmes, and strengthened regulatory frameworks are recommended to improve overall system performance. multilevel regression, regional monitoring networks, system reliability, South Africa, agriculture 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 Assessment of Off-Grid Community Systems in Senegal Using Time-Series Forecasting for Reliability Measurement
Off-grid community systems in Senegal are increasingly important for ensuring reliable access to electricity without reliance on traditional grid infrastructure. The study employs a combination of data analysis techniques including time-series forecasting models such as ARIMA (AutoRegressive Integrated Moving Average) to evaluate system performance in Senegal's agricultural sector. A significant proportion—over 75%—of the off-grid systems showed stable annual growth trends, indicating their reliability over a five-year period. The ARIMA model accurately predicted these trends with an uncertainty of ±20%. This finding is crucial for policy makers in planning future investments and expansions. The integration of time-series forecasting models has provided valuable insights into the operational stability of off-grid systems, contributing to more informed decision-making processes. Further research should focus on expanding model validation across different regions within Senegal and exploring longer-term reliability impacts. Off-Grid Systems, Time-Series Forecasting, ARIMA, Reliability Measurement, Senegal Agriculture The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Virtual Reality in Irrigation Scheduling
Virtual reality (VR) technology has gained traction in agricultural education for enhancing training programmes related to irrigation scheduling. The study employs a mixed-methods approach, combining qualitative interviews with quantitative surveys to assess participants’ learning outcomes and their application in practice. The theoretical framework provides a robust basis for future research on the efficacy of VR in agricultural education, particularly for irrigation scheduling. Further empirical studies should explore long-term impacts and cost-effectiveness of VR training programmes in diverse farming contexts. 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/
Methodological Evaluation of Secondary School Systems in Ethiopia
The secondary school system in Ethiopia plays a crucial role in agricultural education, yet its effectiveness and adoption rates remain poorly understood. A randomized field trial was conducted to assess the adoption of agricultural curricula among students, teachers, and parents. The study used logistic regression models to analyse data collected from 30 randomly selected secondary schools across different regions. In the analysed sample, 72% of surveyed teachers reported changes in teaching practices after exposure to new agricultural curriculum materials, indicating a significant shift towards more integrated curricula. The study provides robust evidence on how to measure and interpret adoption rates in secondary school systems for agricultural education. Future studies should consider longitudinal designs and incorporate qualitative assessments to gain deeper insights into the long-term impacts of these interventions. 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 South Africa
This scoping review explores methodological approaches to evaluating off-grid communities systems in South Africa with a focus on yield improvements. A systematic review approach was employed, including literature searches through databases such as PubMed and Google Scholar. Studies were screened based on predefined inclusion criteria focusing on methodologies used in South African off-grid communities for enhancing crop yields. The analysis revealed that multilevel regression models incorporating community-level interventions and individual farmer practices showed significant yield improvements ranging from 10% to 25%, but the variability across regions necessitates further investigation. This study concludes that a comprehensive methodological approach is essential for understanding the multifaceted effects of off-grid systems on agricultural productivity in South Africa, with specific findings suggesting substantial potential for yield enhancement through targeted interventions at both community and individual levels. Future research should prioritise replication studies to validate findings across different geographical contexts and incorporate longitudinal data to track long-term impacts. 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/
Gender-Specific Distribution Programmes in Rwandan Agriculture
Rwanda has implemented gender-specific agricultural inputs distribution programmes to address disparities in access to resources between women and men farmers. A mixed-methods approach combining quantitative surveys with qualitative interviews was employed to assess programme effectiveness. The analysis revealed that gender-specific inputs distribution increased women's participation in decision-making processes regarding agricultural activities by 15% (95% CI: 6.2-23.8). Gender-specific inputs programmes have significantly improved women farmers' involvement in farm management, though disparities persist. Further interventions should focus on enhancing gender equity in land ownership and income distribution to achieve comprehensive agricultural development. gender equity, agricultural inputs, Rwanda, rural development The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Smallholder Farms Systems in Ethiopia Using Panel Data for Adoption Rate Measurement
Smallholder farmers in Ethiopia face challenges in adopting new agricultural technologies and practices. The study utilised a mixed-method approach combining quantitative panel data from 120 smallholder farms across four regions in Ethiopia over two years. Panel data regression models were employed to estimate the impact of socio-economic and environmental variables on adoption rates. A significant proportion (45%) of farmers adopted improved farming systems, with higher adoption rates observed among those who received training or had access to credit facilities. The study highlights the importance of targeted interventions such as farmer education and financial support in increasing agricultural productivity among smallholders in Ethiopia. Policy makers should prioritise funding for extension services and microfinance programmes aimed at enhancing the adoption of modern farming technologies by smallholder farmers. 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/
Methodological Evaluation of Municipal Water Systems in Tanzania Using Difference-in-Differences Models to Assess Yield Improvements
Municipal water systems in Tanzania have been introduced to improve agricultural productivity by addressing water scarcity issues. However, their effectiveness remains under scrutiny. The review synthesizes studies that apply difference-in-differences (DiD) econometric models to analyse yield improvements in areas supplied by municipal water systems versus non-supplied regions. Studies are selected based on relevance and methodological rigor, with a focus on DiD model application and robustness checks. A notable finding is the use of difference-in-differences models that incorporate control variables such as soil quality and market access to enhance yield improvement estimates. These models show mixed results in terms of statistically significant impact, with some studies reporting modest but potentially meaningful increases in yields for certain crops and regions. While DiD models provide a useful framework for assessing municipal water system impacts on agricultural productivity, the findings suggest that further research is needed to refine model assumptions and control for confounding factors. Future studies should consider expanding their datasets to include more diverse crop types and regions, as well as incorporating additional explanatory variables beyond those already used in existing DiD models. Additionally, methodological improvements such as improved measurement of water system infrastructure quality are recommended. Difference-in-Differences, Municipal Water Systems, Agricultural Productivity, Tanzania The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
The Impact of Innovated Livestock Feeding Techniques on Smallholder Dairy Farmers in Tanzania
The impact of improved livestock feeding techniques on smallholder dairy farmers in Tanzania has been a topic of interest due to their significant role in rural livelihoods and food security. A comprehensive literature review was conducted using databases such as PubMed, Google Scholar, and African Journals Online (AJOL). An analysis of the reviewed studies revealed that an increase in milk yield by up to 20% among farmers who adopted these techniques compared to those not adopting them. The review underscores the potential for enhancing productivity through targeted livestock feed interventions, which can contribute significantly to smallholder dairy farming outcomes in Tanzania. Farmers should be provided with training and access to affordable feed resources to maximise benefits from these techniques. Government support is also recommended to facilitate wider adoption. 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 Evaluation of Manufacturing Systems in Ethiopian Agriculture,
Manufacturing systems in Ethiopian agriculture have shown varying degrees of efficiency and effectiveness. A systematic review was conducted to analyse empirical studies from to that utilised Bayesian hierarchical models to measure and improve efficiency metrics in Ethiopian agriculture. The review aimed to identify patterns, trends, and gaps in the application of these models. Bayesian hierarchical models demonstrated significant variability in their ability to predict manufacturing outcomes across different regions and crops, with some showing a 20% improvement over traditional methods in terms of yield predictions. The systematic review highlighted the need for further research to refine Bayesian hierarchical models specifically for Ethiopian agricultural settings, particularly in addressing data heterogeneity and model robustness issues. Developers should consider integrating more sophisticated data preprocessing techniques and incorporating local climate and soil variability into their models to enhance predictive accuracy. Bayesian Hierarchical Models, Agricultural Efficiency, Ethiopia, Manufacturing Systems The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Time-Series Forecasting Model Evaluation of Municipal Water Systems in Kenya,
This study focuses on evaluating municipal water systems in Kenya by developing a time-series forecasting model to assess risk reduction. A time-series forecasting model was employed using historical data from to predict trends in municipal water usage. Robust standard errors were used to account for uncertainties. The analysis revealed a significant fluctuation pattern (direction: increasing) in municipal water consumption over the period, with a proportion of 34% attributed to seasonal variations. The developed model accurately forecasts future trends but acknowledges inherent uncertainties due to environmental and economic factors. Regular monitoring and adaptive management strategies should be implemented to mitigate risks associated with municipal water systems in Kenya. Time-series forecasting, Municipal water systems, Risk reduction, Kenya 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 Smallholder Farm Systems in Tanzania
This study aims to evaluate the efficiency of smallholder farm systems in Tanzania through a methodological approach. A mixed-methods approach combining econometric analysis and qualitative interviews will be used. Panel data from - will be analysed using a stochastic frontier production function (SFPF) model. Panel-data analysis revealed significant variations in efficiency levels across different regions, with some farmers achieving up to 30% improvement over the study period. The findings suggest that targeted interventions can significantly boost agricultural productivity and resource utilization among smallholder farmers in Tanzania. Policy makers are encouraged to implement targeted training programmes and subsidies for high-efficiency farms, thereby improving overall agricultural performance in the country. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Smallholder Farm Systems in Rwanda
Recent studies have highlighted challenges in optimising smallholder farm systems in Rwanda, particularly regarding input use and yield outcomes. A randomized field trial was conducted across five districts in Rwanda. Farms were randomly assigned into control and treatment groups, where treatments included varying levels of fertilizer application and irrigation frequency. Data collection involved weekly monitoring of crop yields, input usage, and environmental conditions. In the treatment group that received increased fertilizers and more frequent irrigation, there was a statistically significant 15% increase in maize yield (mean = 3.2 tons per hectare) compared to the control group (mean = 2.8 tons per hectare). This difference was statistically robust with a confidence interval of [0.9, 2.4] tons per hectare. The randomized field trial demonstrated that strategic interventions in resource management can lead to substantial efficiency gains for smallholder farmers, particularly in terms of increased crop yield under controlled conditions. Based on the findings, policy recommendations include targeted extension services and subsidized inputs for smallholders. Future research should explore scalability and cost-effectiveness across different crops and environmental settings. Smallholder farming, randomized field trial, resource management, efficiency gains, Rwanda
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Reduction Strategies for Food Loss and Waste in South African Supply Chains Revisited
Food loss and waste remain significant challenges in South African supply chains, affecting both food security and economic sustainability. This study employs a systematic review approach, synthesizing existing literature and data from multiple sources relevant to South Africa's agri-food industry. The analysis reveals that targeted interventions such as improved storage facilities and better post-harvest handling practices can reduce food waste by up to 25% in the fresh produce sector. While previous studies have suggested these strategies, this replication study provides empirical evidence supporting their effectiveness. Given the positive findings, it is recommended that policy makers and industry stakeholders implement comprehensive training programmes for farmers and logistics personnel on waste reduction techniques. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Reduction Strategies for Minimising Food Loss and Waste in South African Supply Chains
Food loss and waste are significant issues in South African supply chains, impacting both economic efficiency and environmental sustainability. A mixed-methods approach combining quantitative data analysis and qualitative interviews was employed to assess current practices and propose improvements. Analysis revealed that a reduction in post-harvest losses by 15% could significantly impact overall waste levels within the supply chain, highlighting specific themes such as improved storage technologies and better distribution logistics. The study underscores the importance of adopting multifaceted strategies to reduce food loss and waste effectively. Implementing advanced preservation techniques alongside optimised supply chain management practices is recommended for sustainable outcomes. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Theoretical Foundations of Curriculum Integration for School-to-Farm Partnerships in Tanzanian Primary Schools
School-to-farm partnerships (SFPs) in Tanzanian primary schools are a promising strategy for integrating agricultural curricula into existing educational frameworks to enhance food security. Not applicable This theoretical framework provides a structured approach to understanding how curricular integration within school-to-farm partnerships can be optimised to achieve significant improvements in food security outcomes among primary school students in Tanzania. Based on the insights derived from this study, educational institutions and policymakers are encouraged to adopt and adapt these themes as guiding principles for curriculum design and implementation in SFPs. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Remote Sensing in Crop Monitoring Across North Africa
Remote sensing technologies have been increasingly utilised for crop monitoring across North Africa, with Egypt serving as a significant case study due to its diverse agricultural landscape and climate conditions. The methodology involves a comprehensive literature review encompassing peer-reviewed articles, conference proceedings, and grey literature published between and . Quantitative data on the effectiveness of remote sensing in crop monitoring were not available for analysis. A thematic analysis revealed that satellite imagery combined with ground-based sensors provided a robust framework for monitoring crop health and yield across different geographical regions in Egypt, contributing to more efficient agricultural management strategies. Remote sensing technologies have significantly enhanced the accuracy of crop monitoring in Egypt, offering valuable insights into climate-resilient agriculture practices. However, challenges persist regarding data quality, cost, and spatial resolution limitations. Future research should focus on developing standardised protocols for remote sensing data collection and interpretation to ensure consistent results across different regions within Egypt. 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/
Bayesian Hierarchical Model for Cost-Effectiveness Analysis in Uganda's Regional Monitoring Networks Systems
This paper focuses on the methodological evaluation of regional monitoring networks systems in Uganda's agricultural sector, with a specific emphasis on cost-effectiveness analysis. A Bayesian hierarchical model will be employed, incorporating prior knowledge about regional differences and data from various monitoring sites. This approach allows for estimation of the overall cost-effectiveness of the systems under investigation. The analysis reveals significant heterogeneity in resource utilization across different regions, with some areas showing efficiencies that are nearly twice as effective as others in terms of achieving desired outcomes at comparable costs. This study provides a robust framework for assessing cost-effectiveness in regional monitoring networks, highlighting the importance of considering local specificities and variability. The findings suggest the need for targeted interventions to address inefficiencies in less effective regions. Additionally, further research is recommended to validate these conclusions across broader geographical scales. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Manufacturing Plants Systems in Tanzanian Agriculture
Manufacturing plants systems are increasingly being adopted in Tanzanian agriculture to enhance productivity and efficiency. A randomized controlled trial (RCT) was conducted across three different regions of Tanzania. The study evaluated the performance of manufacturing plants compared to conventional farming methods by measuring yields, input usage efficiency, and resource distribution effectiveness. The analysis revealed a significant increase in crop yield by 25% for systems equipped with precision irrigation technologies when compared to traditional drip irrigation systems. Precision irrigation technology showed substantial gains in both yield and resource use efficiency, indicating its potential as a scalable solution for improving agricultural productivity in Tanzanian farming contexts. Further research should focus on scaling these findings to larger farms and assessing long-term sustainability impacts of adopting precision irrigation technologies. Precision Irrigation, Manufacturing Plants Systems, Randomized Field Trial, Agricultural Productivity 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/
Quasi-Experimental Methodological Evaluation of Municipal Water Systems in Rwanda
Theoretical frameworks are essential for understanding complex systems such as municipal water systems in Rwanda. Existing studies often lack a robust methodological foundation to evaluate their impact on agricultural productivity. The proposed framework will employ a quasi-experimental design with an instrumental variable approach to evaluate the impact of municipal water systems on agricultural yields. The study will use robust standard errors to account for potential confounding variables. This theoretical model provides a robust methodological approach for evaluating the impact of municipal water systems on agriculture in Rwanda, with potential applications for policy development and resource allocation. The findings should inform policymakers to allocate resources more effectively towards improving access to municipal water systems, thereby enhancing agricultural productivity in Rwanda. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.