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.
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. The weekly webinars are planned on Wednesdays at 4 p.m. Japan time.
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.
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.
The Partnership in Statistics for Development in the 21st Century (PARIS21) in collaboration with the Statistical Institute for Asia and the Pacific (SIAP) developed a unique training course for NSS, NSO leaders and national planning senior managers to improve strategic planning for data and statisticsdevelopment, using innovative tools and methods. The course will give a thorough introduction to the NSDS design process and introduces the data gaps assessment and planning using ADAPT. In addition, this course will feature special topics on gender statistics, climate change data as well as fragility and resilience of NSS in crisis context.
The 2030 Agenda encourages member states to conduct regular and inclusive reviews of progress at the national and sub-national levels which are country-led and country-driven. This course focuses on building capacity in countries for reporting on the SDG indicators using national indicator frameworks. During the course participants will learn about key concepts around metadata, particularly related to the SDGs, learn how to fill the SDG metadata template and better understand the importance of metadata to help explain the data and potential differences between data. The target participants are officials in national statistical offices, line ministries and other institutions who are responsible for providing data and metadata for one or more national SDG indicators. The course can also be useful to a wider audience who is interested to learn more about metadata in the SDG context
The causes and consequences of informal employment and employment in informal sector and their impact on achieving sustainable development continues to gain attention in national development agendas. The evidence in developing and emerging economies shows that on average more than half of the employment in non-agricultural sectors are informal and this rate can reach as high as 80% in some countries. Therefore, every national policy targeting poverty, social protection, or decent work needs to recognise the role of the informal economy in national development. Yet, the lack of data and statistics on the informal economy hinders the capacity of countries to better inform decisions and development policies. This regional training course brings together statisticians and labour analysts from Asia-Pacific national statistical systems to discuss technical aspects and share experiences in the production and use of statistics on informality
This e-Learning course introduces the System of Environmental Economic Accounting -Ecosystem Accounting (SEEA EA), the agreed statistical framework for collecting such information on ecosystems and their relationship to human activity. The SEEA EA provides an integrated statistical framework for organizing biophysical information about ecosystems, measuring ecosystem services, tracking changes in ecosystem extent and condition, and linking this information to measures of economic and human activities. It supports the compilation of indicators for several global policy frameworks including the 2030 Agenda for Sustainable Development and the associated SDGs indicators as well as the Kunming-Montreal Global Biodiversity Framework. The course is being organized by the United Nations Statistics Division (UNSD) and the UN Statistical Institute for Asia and the Pacific (UNSIAP), under the overall guidance of the UN Committee of Experts on Environmental Economic Accounting (UNCEEA).
(SDG 3.8.2 and related indicators)
SDG 3.8.2 indicator is focused on relatively large Out-of-Pocket (OOP) health spending which might lead to cutting spending on other basic needs such as education, food, housing and utilities. But, recognizing that for poor and vulnerable people it is the absolute level of OOP health spending that is crucial – even if it represents less than 10% of a household’s total consumption or income (budget) – indicators of impoverishing health spending are also used to track the lack of financial protection in health and demonstrate the interdependency between SDG 1 “End poverty in all its form everywhere” and SDG target 3.8 on “Universal health coverage”. Specifically, these additional indictors include the proportion of the population impoverished or further impoverished by household expenditures on health using different poverty lines. The Subregional Training on Monitoring Financial Protection in Health will explain in detail the rationale to track SDG indicator 3.8.2, why additional indicators are needed and how the monitoring framework can be expanded to support relevant policy discussions. This training will also discuss the data requirements to monitor the lack of financial protection in health.