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.
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.
SDMX stands for Statistical Data and Metadata eXchange. It is an ISO standard designed to describe statistical data and metadata, normalize their exchange, and improve their efficient sharing across statistical and similar organizations. SDMX provides an integrated approach to facilitating statistical data and metadata exchange, enabling interoperable implementations within and between systems concerned with the exchange, reporting and dissemination of statistical data and their related meta-information. This course has been developed by Asian Development Bank (ADB), United Nations Statistics Division (UNSD), Economic and Social Commission for Asia and the Pacific (ESCAP), and Statistical Institute for Asia and the Pacific (SIAP) with comments from the Bank of International Settlements (BIS) and the International Labour Organization (ILO).The course will be available in ADB eLearn, and is free-of-charge, self-paced, and open to anyone who is interested in learning more about SDMX.
The Council, in the session, will consider several issues, including the report of the Director on its achievements in 2023, the proposed work plan for 2024, and the formulation of the strategic plan for 2025-2029. Management Seminar will be organized by SIAP, in collaboration with Statistics Division of the United Nations Economic and Social Commission for Asia and the Pacific. The seminar aims to strengthen the leadership and management capabilities of the heads of NSOs by providing a forum to discuss, exchange views and share experiences. The theme of this year’s seminar is related to Fundamental Principles of Official Statistics (FPOS). The seminar will draw on the experience of participants in the areas of data stewardship and data governance.
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.