News[2024]

The Sub-Group on Gender Statistics Training (SGGST) was established in 2018 to support national statistics offices in the Asia-Pacific region to develop statistical capacities to effectively produce and use gender statistics for gender policy decisions, advocacy, and tracking progress of the sustainable development goals. The SGGST comprises representatives from national statistics offices, national statistical training institutes, academia, the media, and civil society. 

Since its formation, the SGGST has been instrumental in providing guidance and leadership to several activities, most notably, the development of Gender Statistics Training Curriculum. The curriculum was launched in 2020 as a key resource to boost efforts at building and strengthening institutional capacity in the production and use of gender statistics in the Asia-Pacific region. The curriculum, which was designed in a modular structure, presents a structured approach for organizing and delivering training in gender statistics to diverse audiences in a systematic and effective manner. Since its release, the curriculum has been widely used for training (national, regional, and subregional) in Asia and the Pacific and by many other institutions (universities etc.) and agencies outside the region.

The collection, compilation and utilization of disaster and climate related statistics are priorities for many countries in Asia Pacific due to the significant impact of disasters on life, well-being and sustainable development. At national and sub-national levels, timely and accurate disaster related statistics are essential to support countries in all phases of the disaster risk management cycle from risk assessment to recovery and foresight. At the international level, the adoption of the Sendai Framework for Disaster Risk Reduction 2015-2030 has increased demands for monitoring disasters. 

To support countries in improving the availability and uptake of disaster related information, the UN Economic and Social Commission for Asia and the Pacific (ESCAP) has taken a multiprong approach to building capacity in the region. This includes developing methodologies for compiling disaster-related statistics and launching a portal targeted at policymakers to support decisionmaking around disaster risk mitigation and disaster response. 

Strengthening the collaboration between data producer in the national statistical system and users of this data in national disaster management agencies and other agencies involved in planning and responding to disasters is key to the uptake of official statistics in disaster related decision making. This webinar will highlight the challenges and opportunities in building statistical capacity in an increasingly digital and disaster-prone world, aiming to identify lessons and ways forward.

Consumer price indexes (CPI) measure changes over time in the general level of prices of goods and services that households acquire (use or pay for) for the purpose of consumption. In many countries, they were originally introduced to provide a measure of the changes in the living costs faced by workers, so that wage increases could be related to changing levels of prices. However, over the years, CPIs have widened their scope and now are widely used as a macroeconomic indicator of inflation, as a tool by governments and central banksfor monetary policy and for monitoring price stability, and as deflators in the national accounts. With the globalization of trade and production and the liberalization of the markets, national governments, central banks, and international organizations place great importance on the quality and accuracy of national CPIs, and their international comparability.
CPIs are official statistics that are usually produced by NSOs, Ministries of Finance and Labour, or central banks. They are published as quickly as possible, generally within four weeks after the reference period.This face-to-face course, developed jointly by SIAP, IMF, and SPC, aims to build capacity to improve the compilation of consumer price indexes (CPI) that reflect international standards and best practice as described in the 2020 CPI Manual. Course topics will include overview of index calculation methods, developing weights, selecting samples, price collection, data dissemination. The program will include interactive discussions to share country experiences, practical exercises to apply concepts and methods discussed, and limited lecture.

Quality data are vital for enabling governments, international organizations, civil society, private sector and the general public to make informed decisions and to ensure the accountability of representative bodies. Effective planning, follow-up and review of the implementation of the 2030 Agenda for Sustainable Development requires the collection, processing, analysis and dissemination of an unprecedented amount of data and statistics at local, national, regional and global levels and by multiple stakeholders. Achieving and maintaining public trust in official statistics requires that those statistics are produced in an objective, transparent and professionally independent manner. The statistical quality framework and quality review processes help promoting data quality. The United Nations Statistical Commission based on these considerations and other important principles established a set of Fundamental Principles of Official Statistics in 1994. These principles were adopted by the UN General Assembly in 2014. Many countries around the world have established a national code of practice or a national quality assurance framework for official statistics (NQAF) to capture those principles and best practices, and to safeguard public trust. In 2019, the United Nations Statistical Commission (UNSC) adopted the United Nations National Quality Assurance Frameworks Manual for Official Statistics (Manual) that has been developed by the Expert Group on National Quality Assurance Frameworks. 1 It supports countries in the development and implementation of a national quality assurance framework (NQAF) throughout their national statistical systems. It contains recommendations, an updated quality assurance framework and implementation guidance, including for the quality assurance of SDG indicator data and statistics and when different data sources are used. In addition, in 2023, the Commission endorsed a roadmap for the development and implementation of a national quality assurance framework.2 The 2030 Agenda explicitly calls for enhancing capacity building to support national plans to implement the sustainable development goals. The workshop will provide an opportunity to participants to learn basic concepts and frameworks on quality related to statistics, through handson sessions, with an overall aim to strengthen the capacity to produce a set of official statistics, including indicators, to track and monitor SDGs.

The United Nations Statistics Division (UNSD) and the United Nations Statistical Institute for Asia and the Pacific (UNSIAP), with the support of the Office of the Director-General for Policy Planning on Statistical Policy, the Ministry of Internal Affairs and Communications of the Government of Japan, and in collaboration with the National Statistical Committee of the Kyrgyz Republic are organizing the Regional Workshop on Accounting Approach to Climate Change and Biodiversity for Central Asia and the Caucasus. The workshop will be held in Bishkek, Kyrgyz Republic, from 9 to 12 September 2024. The workshop will be conducted in English, with Russian interpretation. 

The regional workshop is an opportunity for participants to increase their technical knowledge of the System of Environmental-Economic Accounting (SEEA) through exercises,  country examples and discussions focusing on accounts relevant to climate change and biodiversity including accounts on energy, air emission, carbon, ecosystem extent and ecosystem services. Participants will learn about the relevance of environmental economic accounts to climate change and biodiversity policies, and how SEEA can support measuring progress towards achieving the targets of national policies and international agreements including the Sustainable Development Goals, the Kunming-Montreal Global Biodiversity Framework and the Paris Agreement. Institutional mechanisms, data governance, data sources and dissemination approaches will also be introduced.

This regional training introduces crime statistics from a gender perspective to produce reliable indicators to monitor the relevant SDGs (SDGs 5 and 16). The training provides an opportunity for participants to learn about gender concepts and frameworks on SDG indicators relevant to crime and criminal justice statistics including gender-based SDG targets, with the overall aim of strengthening regional capacity in producing high-quality SDG indicator data and overall statistics, to inform policy decisions at national and international levels.

This training will provide NSO heads with leadership skills to improve their effectiveness through greater awareness of their strengths and weaknesses and the challenges they face both internally within their organization and externally within the larger environment they are engaging with. Often, NSO heads rarely have the opportunity to receive extensive feedback from staff and stakeholders outside. It is necessary to have to open opportunity and understanding to build a comprehensive plan for driving success within the NSO and the NSS, and by extension the data ecosystem. Each individual has his/her own leadership style. Nurturing and developing these styles and skills with keen understanding and awareness of the challenges surrounding them will significantly improve their positive self-engagement, collaboration, and contribution to the field they are engaged in. Leadership can be nurtured and developed if it is enabled to flourish in each individual using best practices built around: (1) assessment tools to help leaders look within and examine their identity, leadership skills and challenges and set developmental goals; (2) challenge-oriented, experiential, team-based activities that leverage their own experiences in cocreating solutions to enhance leadership skills; and (3) support through a peer learning and mentoring model that enable leaders to share their challenges, utilize innovation techniques and chart a course for greater effectiveness. Self-knowledge is an important key to effective leadership.

Identifying and responding to the needs of users for data and statistics is at the heart of the mission of National Statistical Offices (NSOs) and national statistical systems. NSOs already undertake many activities interacting with different users such as preparing press releases to aid journalists and communicate with the public at large and organizing launch events/workshops to disseminate important results from surveys and censuses. In general, the NSO interacts with users towards the tail end of the statistical production process when the data is disseminated. There is an opportunity for national statistical offices to further improve their collaboration with users by engaging more systematically throughout the statistical production process. User engagement is the process of conducting a dialogue with users of official statistics to understand their needs and improve the products, services and operation of a statistical organization accordingly.

Climate change is one of the most pressing issues in the Pacific region. Many countries are already experiencing intensifying threats such as rising sea levels, increasing ocean acidification, and escalating extreme weather events, profoundly impacting the region's economy, society, and environment. There is a need to address the well-being of people through good evidence-based policy. Reliable statistics and indicators on the impact of climate change are vital to enable evidence-based policy, decision-making, planning and investment. Importantly, these statistics and indicators must be able to speak to the range of economic, social and environmental impacts of climate change in a timely manner. This workshop aims to support capacity building and knowledge sharing across this topic in the region.

In the Pacific region, climate change is one of the most pressing policy issues given its wideranging impacts on well-being. At the Fifty-first Pacific Islands Forum in 2022, Pacific Island leaders emphasized climate change as an existential threat to the wellbeing, livelihoods, and security of the Pacific, resonating with the Boe Declaration (2018) and the Kainaki II Declaration (2019). Consequently, they declared a climate emergency. The region is already experiencing intensifying threats like rising sea levels, increasing ocean acidification, and escalating extreme weather events, profoundly impacting the region's economy, society, and environment. The urgency for scaled-up and cross-sectoral climate action is evident. To effectively address climate change, the Pacific Island Countries and Territories (PICTs) need to implement the 2050 Strategy for the Blue Pacific Continent and the Framework for Resilient Development in the Pacific and swiftly act on their national climate agendas in collaboration with regional entities such as agencies of the Council of Regional Organizations of the Pacific, including the Pacific Community (SPC), and the international development community. Reliable and actionable statistics and indicators on climate change impacts are vital to enable evidence-based policy, decision-making, planning and investment. Importantly, these statistics and indicators must be able to speak to the economic, social and environmental impacts of climate change.

This e-learning course aims to build capacity in national statistical systems for the development and implementation of Reproducible Analytical Pipelines (RAPs) for Official Statistics.

What is a Reproducible Analytical Pipeline?

Simply put, reproducible analytical pipelines (RAPs) are automated statistical processes (data processing and analysis) that codify to the greatest extent possible the production of official statistics. Common tools that are used to develop RAP include software such as R or Python, and version control management tools such as Git.

Reproducibility is at the heart of the approach. It implies that the outputs can be generated again with any new or revised input datasets using the RAP developed. This also implies drafting documents explaining the RAP that make it possible to build institutional knowledge and use the RAP in the future by new staff.  

Why are Reproducible Analytical Pipelines  important for Official Statistics?

All national statistical systems are engaged in the regular, high frequency production of many official statistics. For example, most countries compile monthly consumer price index (CPI). The input data for the compilation of CPI is generally the same from month to month. By developing and implementing an RAP for the compilation of CPI, countries can improve the timeliness and quality of the CPI since automation reduces the time required to clean and analyze the data; it also reduces the chance of errors that could occur when relying on non-automated processes. 

Furthermore, the Sustainable Development Goals (SDGs) require that countries use more diverse data sources in the compilation of indicators. The COVID-19 crisis has shown that automated tools can facilitate data analysis and reporting when these sources are updated. These tools, including software such as R and sharing platforms such as GitHub, allow statisticians  to streamline data cleaning, compilation, and analysis. 

Implementing these new approaches to data processing and analysis and utilizing these modern tools can aid in the timelier production of statistics and lower the time staff need to produce statistics. This approach is also more transparent, easier to review and to share among staff and thus less prone to errors in the data and/or statistical analysis. Furthermore, implementing good practices based on RAP can contribute to building institutional knowledge by ensuring that work programmes can be more seamlessly transferred among different staff and over time.

The Economic and Social Commission for Asia and the Pacific (ESCAP) is implementing a project supporting national statistical offices in Asia and the Pacific to leverage innovative data sources, tools and methods for the streamlined production and use of better, more timely data for official statistics: “The 2030 Data Decade – Strengthening the institutional capacity of national statistical offices in Asia and the Pacific to use innovative, new and big data sources for official statistics in support of the 2030 Agenda for Sustainable Development”, which is funded through the 2030 Agenda for Sustainable Development sub-fund of the UN Peace and Development Trust Fund (UNPDF).

Following a request received by the Vanuatu Bureau of Statistics (VBoS), as part of this project, ESCAP is providing technical support and guidance to Vanuatu for the integration of big data solutions into national development strategies for official statistics. Through initial engagement with VBoS, Land Accounts were identified as a key building block for addressing many identified needs relating to climate, the environment and agriculture. Producing land accounts will require land cover and, ideally, land use data, for two or more points in time. For Land cover data, it is proposed to build on the work that VBoS has done in partnership with Radiant Earth, subject to review of the sources, methods and code. This utilises the Forest Inventory as a ground truth dataset, which was made available to VBoS by the Department of Forestry. 

To support this work, further technical training is needed for VBoS staff and other Vanuatu government ministries. Training on Data Science and Machine Learning (ML) methods will be especially important to allow staff to utilise the concepts, methods and tools developed by Radiant Earth in this project.

The numbers of refugees and internally displaced persons (IDPs) have increased rapidly in recent years, with UNHCR estimating over 108.4 million forcibly displaced persons in 2022. Similarly, the issue of statelessness continues to persist in society, with 4.4 million people currently estimated to be stateless. This course introduces the “International Recommendations on Refugee Statistics” (IRRS), the “International Recommendations on IDP Statistics” (IRIS) and the “International Recommendations on Statelessness Statistics” (IROSS). These sets of recommendations were endorsed by the United Nations Statistical Commission in 2018 (IRRS), 2020 (IRIS) and 2023 (IROSS), respectively. The course is spread over six substantive modules and provides details on the statistical framework for compiling refugee, IDP and stateless persons statistics. It introduces concepts, definitions, classifications and methodologies relevant to collecting, compiling, analyzing and disseminating data and indicators on refugees, IDPs and stateless persons, 2 including Sustainable Development Goal (SDG) indicators. 

BPM7 and 2025 SNA webinars will be conducted  March 26 – 27  (Group 1-Asia) and April 3-4  (Group 2-Pacific).

Statistical Business Registers (SBRs) are often described as the backbone of economic statistics, as they provide the core infrastructure to support the collection of economic data and the production of economic statistics. They provide a coherent set of units and classifications to collect and compile data across all domains, and a consistent set of rules to maintain this set of units over time. SBRs are considered as the backbone for producing economic statistics that meet the increasing demand for better integrated, coherent and comparable statistics across countries and statistical domains. Inclusive and exhaustive SBRs are becoming an increasingly more important element of the statistical infrastructure for maintaining the relevance, responsiveness and quality of economic statistics in order to measure the structure and dynamics of economic activity.   

This webinar will provide the participants with a clear understanding of the importance of measuring digital trade, and the conceptual framework for measuring digital trade whilst focusing on the fundamental concepts and statistical definitions. A variety of examples and practical applications will be shared by country representatives. The webinar will also emphasize the importance of digital trade statistics in evidence-based policy making.

This course introduces the SEEA Central Framework, the international statistical standards for measuring the interactions between the environment and the economy. It is comprised of 5 modules. The first module introduces the SEEA. Modules 2 discusses accounting for physical flows while module 3 discusses accounting for environmental assets. The fourth module contains details on environmental activity accounts, combined presentations and indicators. The last module contains an overview of subsystems, applications and extensions.

Statistical Business Registers (SBRs) are often described as the backbone of economic statistics, as they provide the core infrastructure to support the collection of economic data and the production of economic statistics. They provide a coherent set of units and classifications to collect and compile data across all domains, and a consistent set of rules to maintain this set of units over time. SBRs are considered as the backbone for producing economic statistics that meet the increasing demand for better integrated, coherent and comparable statistics across countries and statistical domains. Inclusive and exhaustive SBRs are becoming an increasingly more important element of the statistical infrastructure for maintaining the relevance, responsiveness and quality of economic statistics in order to measure the structure and dynamics of economic activity. 

This webinar will provide the participants with a clear understanding of the importance of measuring digital trade, and the conceptual framework for measuring digital trade whilst focusing on the fundamental concepts and statistical definitions. A variety of examples and practical applications will be shared by country representatives. The webinar will also emphasize the importance of digital trade statistics in evidence-based policy making. 

more detail....

Pacific Community (SPC) has started an initiative to explore and identify the unmet needs for statistics in the Pacific region and undertook the region-wise comprehensive needs assessment. This needs assessment work will contribute to the development of the regional Capacity Development Framework, which is aimed to identify the needs and the appropriate capacity development modalities at three levels: system, institutional/organisational, and individual - more information can be found in a working paper aimed to highlight main features of the framework. The webinar is aimed at streamlining the statistical capacity development in the Pacific by making informed decisions and identifying systemic areas to focus on in the coming years. 

The Statistics Department (STA) of the International Monetary Fund (IMF), is implementing the “Environment and Climate Change Statistics Capacity Development Program”, supported by the State Economic Cooperation (SECO). The program is oriented towards assisting beneficiary countries in the development and dissemination of indicators most relevant to their policy needs. Accordingly, technical assistance will focus on developing one or two indicators that reflect the most urgent data needs of the targeted countries; and encompass the use of internationally agreed methodology or testing methodology underdevelopment. The program will build capacity in the project countries to compile select indicators through the organization of workshops, trainings, and targeted hands-on technical assistance.

Macroeconomic accounts provide comprehensive and detailed records of the complex economic activities taking place within an economy, and of the interactions between different economic agents, and groups of agents, in markets or elsewhere. As such, harmonization and consistency of the accounting framework allow economic data to be compiled and presented in a format that supports economic analysis, and policy decision making. This webinar series will provide the participants with a clear understanding of the importance of macroeconomic statistics and its components to an economy, whilst focusing on the fundamentals of the macroeconomic and financial statistics. This webinar will also enable the participants to have a comprehensive appreciation of the statistical linkages within the macroeconomic statistics framework.

This 8-week course developed by SIAP in partnership with the Asian Development Bank (ADB) introduces machine learning as a tool for using either traditional (surveys, micro data, …) or non-traditional (big data) data sources to produce high quality predictions for Official Statistics or Sustainable Development Goals (SDGs) indicators. It provides an opportunity for participants to explore and manipulate the techniques of Machine Learning and their links with traditional statistical methods. The 6 modules (+1 module with recalls/prerequisites) aim at providing an overview of the current methods and applications of Machine Learning, through simplified theoretical concepts, pedagogical case studies and interactive resources. The course is not based, nor does it require, a particular software. However, reproducible examples on either simulated or real data are provided using the R/RStudio environment. Some Python procedures and packages are also provided.