Statistical Capacity Building Research Articles

Building Capacity for COVID-19 Surveillance: A Statistics Course for Health Officials in Seven Low- and Middle-Income Countries

During the COVID-19 pandemic, a group of health program implementors and research analysts across seven low- and middle-income countries (LMICs) alongside Boston-based collaborators convened to implement data-driven approaches for public health response. An intensive statistics and data science training short course was developed to ensure that in-country researchers could implement the necessary statistical methods for COVID-19 surveillance. The main goal of the course was to enable interpretation of findings from time series analyses and flag potential data issues. This manuscript summarizes our experience teaching this course, including a detailed course overview, participant feedback, and thoughts on how targeted, online courses can be used to support statistical capacity building in LMICs.

Sustainable Statistical Capacity-Building for Africa: The Biostatistics Case

Several major global challenges, including climate change and water scarcity, warrant a scientific approach to generating solutions. Developing high quality and robust capacity in (bio)statistics is key to ensuring sound scientific solutions to these challenges, so collaboration between academic and research institutes should be high on university agendas. To strengthen capacity in the developing world, South–North partnerships should be a priority. The ideas and examples of statistical capacity-building presented in this article are the result of several monthly online discussions between a mixedgroup of authors having international experience and formal links with Hasselt University in Belgium. The discussion focuses on statistical capacity-building through education (teaching), research, and societal impact. We have adopted an example-based approach, and in view of the background of the authors, the examples refer mainly to biostatistical capacity-building. Although many universities worldwide have already initiated university collaborations for development, we hope and believe that our ideas and concrete examples can serve as inspiration to further strengthen South–North partnerships on statistical capacity-building.

The highways and side roads of statistical capacity building

This paper proposes an approach to guide statistical capacity building in developing countries using an analysis based on components of the World Bank’s Statistical Performance Indicator on a sample of 215 countries. The approach demonstrates the importance of expanding traditional capacity-building activities to include programs to strengthen and better monitor the ability of National Statistical Systems (NSS) to respond to user data needs. Based on this analysis, the paper recommends a two-step strategy for building and enhancing the statistical capacity of national statistical systems in developing countries. The strategy creates a sustainable trajectory for developing NSSs that meets the growing demands of local and global data users. The paper emphasizes the importance of donor coordination and South-South learning initiatives for international capacity-building efforts.

Comments: Development of an early career academic supervisor in Statistics - a discussion on a guiding rubric

The authors are commended for highlighting a South African university system problem that has grown steadily over recent years. Much has been written about the dearth of academic statistical expertise in South Africa. In her Presidential address at the 2010 South African Statistical Association conference (see [1]), Ms Yoko Chhana, highlighted two reasons why statistical capacity building was severely restricted in South Africa. Retaining statisticians in academia was highlighted as a key concern, a point which lends support to the crux of this paper. The shortage of experienced staff to mentor and train the next generation of academic statisticians is a result of poor retention policies which therefore impacts on the development of early career supervision skills.

Individual capacities influencing uses of routine health data for decision making among health workersat Muhimbili National Hospital; Dar es Salaam – Tanzania: a quantitative study

Background: The availability of health workers with the capacity to read and understand statistical data and then use them for work-related decision-making, therefore, supporting their institutions or the existing health system at large in developing countries is important. However, in some countries, Tanzania inclusive, this has remained critical. This requires the capacity-building of potential users. The study aimed to assess individual capacities influencing use of routine health data for decision-making among Emergency Medicine health workers at Muhimbili National Hospital (MNH).
 Methods: The study design used was a descriptive cross-sectional using a quantitative approach. Stratified random sampling was used to sample Nurses, Medical officers, Residents, and Emergency medicine specialists. A semi-structured questionnaire was used to collect data. The study involved 76 health workers working in the Emergency Medicine Department (EMD) at MNH.
 Results: Results showed 61.6% use of routine health data for decision making. Working experience, job title, and education level had a statistically significant association with information used for decision-making. There was a statistically significant difference in routine data use between those who had poor and good knowledge to collect, analyze, interpret, and use data. Also, results showed that there was a statistically significant difference in routine data use between those who had poor and good skills to collect, analyze, interpret, and use data. Specialists had a good level of knowledge and skills on data use compared to other health workers.
 Conclusion: The study demonstrates partial use of routine health data for decision-making with an interplay of individual capacities. A framework for statistical capacity building in Tanzania needs to be built, by training a cadre of health workers with core competencies and skills in measuring progress in the health system that could generate sustainable demand for data use within the health systems of the country.

Capacity development in household surveys experience from the centre for development data training initiative

Household surveys remain the major source of official statistics for monitoring development policies particularly in developing countries. In the context of rapid developments in data needs, extensive methodological work, data processing and use at national and international levels and a remaining capacity gap despite efforts for statistical capacity building in last decade, it is critical for training centers to keep up to speed with international best practices. This paper show that the approach of the Centre for Development Data Training initiative (C4D2 Training Initiative) is highly effective and stand to have a long-term impact on household survey capacity in Africa region. It is made of several components all of which aim to bolster capacity development in the region. It harmonizes and improves the quality and sustainability of training on household surveys through increased local capacity and greater dissemination of best practices, creates a network among participants and trainers to facilitate knowledge exchange on best practices as well as survey harmonization across countries. Taking advantage of benefits, the initiative should endeavor other regions subject to their interest and embrace the use of virtual and web-based training.

The Highways and Side Roads of Statistical Capacity Building

The Highways and Side Roads of Statistical Capacity Building

Statistical capacity building for sustainable development: Developing the fundamental pillars necessary for modern national statistical systems1

Statistical capacity building for sustainable development: Developing the fundamental pillars necessary for modern national statistical systems1

Can Statistical Capacity Building Help Reduce Procyclical Fiscal Policy?

AbstractFew papers have attempted to assess the role of ‘capacity’, especially in the area of macroeconomic statistics. Consequently, we make an attempt to advance this literature through the construction of a ‘statistical capacity building index’ and then test its explanatory power on the cyclicality of government spending. Using panel data from 62 developing countries, we find evidence that improvements in this index are associated with less procyclicality of government spending over the period 1990–2012, with the significance of this relationship dependent upon the quality of administrative and technical capacity of budgetary institutions. Copyright © 2017 John Wiley & Sons, Ltd.

JOS Special Section on The Role of Official Statistics in Statistical Capacity Building – Editorial

JOS Special Section on The Role of Official Statistics in Statistical Capacity Building – Editorial

Invited Commentary Special Section: The Role of Official Statistics in Statistical Capacity Building

Invited Commentary Special Section: The Role of Official Statistics in Statistical Capacity Building

Statistical Capacity Building of Official Statisticians in Practice: Case of the Consumer Price Index

Abstract This article focuses on the issue of statistical capacity building of official statisticians using the case of the consumer price index (CPI) as an illustrative example. Although used for indexation of salaries, pensions, and social welfare benefits, but also as an approximation of the general inflation rate, there are several unresolved methodological issues associated with CPI’s calculation. Apart from the choice among two alternative concepts, the challenge of how to include owner-occupied housing (OOH) in CPI has also not been adequately resolved yet. Analysis in the article is based on Slovenian data. The results show that accuracy of the CPI significantly improves if it is calculated using one of the superlative and symmetric formulas, and that it makes sense to include OOH in CPI using the total acquisitions approach. The analysis further indicates that the choice of the index formula for calculating CPI has a much greater impact on the CPI value than inclusion of OOH. Academic research findings such as these should not remain unknown to the wide professional community of official statisticians. Formal channels for knowledge transfer from academia to official statistics providers should be established to facilitate continuous statistical capacity building of official statisticians.

Can Statistical Capacity Building Help Reduce Procyclical Fiscal Policy in Developing Countries?

Few papers have attempted to assess the role of “capacity,” especially in the area of macroeconomic statistics. Consequently, we make an attempt to advance this literature through the construction of a “statistical capacity building index,” and then test its explanatory power on the cyclicality of government spending. Using panel data from 62 developing countries, we find evidence that improvements in this index are associated with less procyclicality of government spending over the period 1990–2012; with the significance of this relationship dependent upon the quality of administrative and technical capacity of budgetary institutions.

Can Statistical Capacity Building Help Reduce Procyclical Fiscal Policy in Developing Countries?

Few papers have attempted to assess the role of 'capacity,' especially in the area of macroeconomic statistics. Consequently, we make an attempt to advance this literature through the construction of a 'statistical capacity building index,' and then test its explanatory power on the cyclicality of government spending. Using panel data from 62 developing countries, we find evidence that improvements in this index are associated with less procyclicality of government spending over the period 1990-2012; with the significance of this relationship dependent upon the quality of administrative and technical capacity of budgetary institutions.

Tracking Progress Towards Statistical Capacity Building Efforts: The African Statistical Development Index

Cet article présente l'Indice de développement statistique africain, un indice composite ayant pour objectif de supporter le suivi et l'évaluation de la mise en oeuvre du Cadre stratégique régional de référence pour le renforcement des capacités statistiques en Afrique. Cet indice permet, entre autres, d'identifier les forces et faiblesses du système statistique national de chaque pays africain en vue de favoriser des interventions ciblées de la part des intervenants. Pour ce faire, cet article présente la raison d'être et le contexte entourant le développement de l'indice. Par la suite, il s'attarde sur la méthodologie entourant son développement incluant la sélection des composantes et des variables, les pondérations et le processus d'agrégation ainsi que celui de validation. Il présente une application de la méthodologie sur un échantillon des pays africains et compare finalement l'indice à d'autres indices de développement statistique existants sans oublier les limitations relatives à son utilisation. This paper presents the development of the African Statistical Development Index, a composite index that aims at supporting the monitoring and evaluation of the implementation of the Reference Regional Strategic Framework for Statistical Capacity Building in Africa. It also helps to identify, for each African country, weaknesses and strengths of the National Statistical Systems so that support interventions can be developed. The paper first gives the rationale behind the development of the index as well as the context. It then elaborates on the methodology used to develop the index, including the selection of components and variables, the scaling of the variables, the weighting and aggregation schemes, and the validation process. The methodology is applied to a sample of African countries. Finally, the paper compares the proposed index to existing statistical capacity building indicators and highlights the related limitations.

On statistical capacity building in Nigeria: A necessary step towards achieving millennium development goals (MDGs)

On statistical capacity building in Nigeria: A necessary step towards achieving millennium development goals (MDGs)

Producing Knowledge for Development: Research at the World Bank

Research is one of the important activities of the World Bank and an essential input to lending. To meet the challenges of development and poverty reduction, the Bank must combine the power of ideas and with finance. Generating about the impact of policies in specific contexts is essential to accelerating growth and achieving the UN's Millennium Development Goals in developing countries. Creating involves data production, analytical studies, global monitoring and projections, statistical capacity building, policy review, and advice. The lending, learning, and knowledge cycle has both an internal and an external dimension. Research findings are an essential input to Bank operations and lending. They are used in the Bank's advisory services, which include policy dialogue with governments, analytical reports (known in Bank jargon as economic and sector work), and technical assistance. In addition to research, development practitioners and policymakers need access to good-quality country-level and comparative data. This must be combined with high-quality global monitoring and consistent projections to enable policymakers to adjust development strategies to a rapidly changing external environment. World Bank lending provides opportunities for learning about development. Key to such learning is the evaluation of programs in a rigorous way that isolates their effects from those of other factors. Ex post, research strengthens the lending-learning-knowledge cycle by drawing lessons from lending operations. Ex ante, it explores the likely outcomes of different policy options by applying historically derived to current development challenges. Externally, the Bank influences the global environment in which development efforts are undertaken by producing and disseminating research and data that contribute to global development knowledge. Bank staff is given the mandate and resources to do so by its governing body, which represents governments. Bank publications address the specific needs of clients, as well as issues and themes crucial to understanding the development process itself. These publications boost developing countries' access to information and analytical capacity and strengthen their ability to engage on the global stage. This article first describes the organization, staffing, resources, and research agenda at the World Bank. It then presents an assessment of the quality and relevance of this research, drawing on the findings of a recent independent evaluation. Organization of World Bank Research Research is done throughout the World Bank under the general direction of the senior vice-president and chief economist. Research is carried out by Bank staff, often in collaboration with external consultants. The bulk of research is conducted by the research group in the Development Economics Vice Presidency (DEC). Research is also produced by other staff from six regional vice presidencies (Africa, South Asia, etc.) and five networks: Environmentally and Socially Sustainable Development, Infrastructure, Finance and Private Sector Development, Human Development, and Poverty Reduction and Economic Management. Bank research is financed by the administrative budget (including a substantial amount financed by the Research Committee) and by external trust funds. The Research Committee, created in 1971 and chaired by the chief economist, has its own budget and allocates research grants competitively, following a formal review process. The Research Committee also supports capacity-building initiatives in developing countries, such as the African Economic Research Consortium (AERC), and provides financial support to economics education in underserved areas of the world. DEC is divided into five teams: Data Group, Prospects Group, Research Group, Development Policy, and World Development Report. The Research Group produces empirical and methodological research on development policy. …

Measuring Statistical Capacity Building: A Logical Framework Approach

This paper suggests a way forward in the effort to measure statistical capacity building by combining features of two tools – the Project Management System, a logical framework methodology that the IMF Statistics Department uses to plan, monitor, and evaluate technical assistance projects, and the Data Quality Assessment Framework, a methodology for assessing data quality that brings together best practices and internationally accepted concepts and definitions in statistics

Measuring Statistical Capacity Building: A Logical Framework Approach

This paper suggests a way forward in the effort to measure statistical capacity building by combining features of two tools - the Project Management System, a logical framework methodology that the IMF Statistics Department uses to plan, monitor, and evaluate technical assistance projects, and the Data Quality Assessment Framework, a methodology for assessing data quality that brings together best practices and internationally accepted concepts and definitions in statistics.