News[2023]

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 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.

Disasters continue to have an ever-increasing impact on life, well-being and sustainable development. Given these impacts, there is a high demand at the local, national and international levels for high quality, integrated statistics to inform all phases of the disaster risk management cycle. Furthermore, disaster related statistics are not only relevant to those working to prepare and respond to disasters but also to the public at large, research institutions and policy analysts at the local and national levels. In response to the increased demands for disaster related statistics, the disaster management and official statistics communities in Asia-Pacific have developed the Disaster-related Statistics Framework (DRSF).

This course will focus on climate change indicators that can be compiled from environmental economic accounts. After a brief overview of climate change and, relevant polices and multilateral agreements, participants will learn how to compile various indicators that inform climate change. The focus of the course is on better understanding the relationship between climate change and economic activity. And the statistical framework that provides the concepts, definitions, and methodology for measuring this relationship is the System of Environmental Economic Accounting. In particular, participants will learn about physical supply and use tables for energy and air emissions, and indicators that can be compiled from these accounts. Other topics to be discussed include transaction accounts which can be used to derived expenditure type indicators such those on taxes on energy and pollution. Further details on course content follow below.

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.

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.

Disasters continue to have an ever-increasing impact on life, well-being and sustainable development. Given these impacts, there is a high demand at the local, national and international levels for high quality, integrated statistics to inform all phases of the disaster risk management cycle. Furthermore, disaster related statistics are not only relevant to those working to prepare and respond to disasters but also to the public at large, research institutions and policy analysts at the local and national levels. In response to the increased demands for disaster related statistics, the disaster management and official statistics communities in Asia-Pacific have developed the Disaster-related Statistics Framework (DRSF).

Historically business statistics have focused very much in measuring the economic performance and competitiveness of businesses. However, businesses play a very important role toward sustainability and wellbeing. Task team on well-being and sustainability under the UN Committee of Experts on Business and Trade Statistics (UN CEBTS) identified a set of 17 reference indicators related to the measurement of the business sector’s impact on well-being and sustainability. These indicators were based on the review of the indicators of the Sustainable Development Goal indicators of the 2030 Agenda for Sustainable Development and the core indicators for entity reporting on contribution towards implementation of the Sustainable Development Goals in order to provide a bridge between the information available at business level with business statistics and ultimately with relevant SDG indicators. This webinar series will focus on the set of indicators related to wellbeing and sustainability and is organized to (1) provide an overview of the importance of measuring impact of businesses on wellbeing and sustainability; (2) review data sources including, for example non-financial reporting; and (3) share country experiences on challenges and opportunities in the compilation of these indicators.

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Environment is one of the three pillars of the 2030 Agenda and the Sustainable Development Goals (SDGs). Compiling the environment related indicators is key to informing policies and measuring progress towards achieving the SDGs. This course focuses on the 25 SDG indicators that are under the custodianship of UNEP. In the 10 modules of the course, participants will learn about the importance of monitoring the environmental dimension of development, the linkages of indicators with existing statistical frameworks, and how to use environment statistics in decision making. They will also learn about indicators informing specific topics including sustainable consumption and production, waste and oceans. Target participants are officials in national statistical offices, line ministries (especially ministries of environment) and other institutions who are working on the SDGs and environment related issues. The course can also be useful to a wider audience who is interested in learning more about environmental SDG indicators.

This course in Thai language aims to build national capacities for the compilation of disaster related statistics for enhancing disaster management and promote the risk-informed sustainable development in Thailand. The course also aims to facilitate national monitoring and reporting on the Sendai Framework for Disaster Risk Reduction and the 2030 Agenda for Sustainable Development. It introduces concepts relevant to compiling disaster related statistics. The course consists of online modules and online discussion forums. The online modules provide an overview of several topics including measuring disaster risk, measuring economic losses and disaster-risk reduction expenditures. Online discussion forums will provide a venue allow participants to interact with each other and ask questions. For further details on the course, please refer to the attached guidelines for participants.

This course is an advanced course in data visualization, conceived as an extension to SIAP’s facilitated course “Data Visualization for Official Statistics and SDG Indicators” conducted in 2021 and 2022 or, alternatively, to the self-paced course “Principles of Data Visualization for Official Statistics and SDG Indicators” available on SIAP’s e-learning platform. This new course focuses on methods to produce high-quality graphics for monitoring and publishing official statistics and the Sustainable Development Goals (SDGs) indicators. It also highlights advanced topics such as network visualization, high dimension data visualization, visualizing uncertainty and address some important issues when communicating with graphics. In particular, storytelling and the construction of visual narratives for any type of audience, or inclusive data visualization, is emphasized and discussed.

The achievement of the Sustainable Development Goals (SDGs) requires the availability of high quality, timely and reliable data to produce the relevant SDG indicators and other statistics, disaggregated as relevant. In order to meet this need, official statistics must modernize and incorporate new data sources, including Big Data. At its 53rd session in 2022, the Statistical Commission underscored the importance of mainstreaming the use of big data and data science into the work programmes of national statistical offices and the necessity to include training in big data and data science into the training curricula of national statistical offices. This course is a first response to this injunction by sharing experience, and providing the pedagogical activities required for understanding the process leading to the production and dissemination of official statistics with new data sources.

Water is essential to achieve sustainable development. At a fundamental level, the availability of clean water in and of itself is necessary for our health and overall well-being. Water is also an important input to many economic activities, from the production of food and energy to the manufacturing of computers and cars. High quality and timely statistics on water are need in order to manage our water assets and track water supply and use. This course will focus on water statistics and accounts, as well as some important water aggregates and indicators (including SDGs). The water accounts are based on the System for Environmental-Economic Accounting-Water (SEEA-Water) and the International Recommendations for Water Statistics (IRWS). These two documents support analysis of the role of water within the economy, understanding of the hydrological cycle and valuation of water assets. They are consistent with the SEEA Central Framework and follow a similar accounting structure to the System of National Accounts (SNA).

With the increased and evolving demand for data from national development plans, Agenda 2030 for sustainable development goals, the current and post crisis affecting the World, including COVID-19 and climate change; National statistical offices (NSOs) continue to be at the forefront of developing and coordinating national statistical systems (NSS) as well as engaging with the larger data ecosystem. National statistical systems (NSS) in low and middle-income countries need to innovate and adapt quickly not only in terms of data production, but also in more effectively re-using, analysing, disseminating and communicating other existing sources of development data. The development of strong leadership and management skills at both senior- and mid - levels is key to ensure NSOs are positioned to drive change and operate in modern and dynamic data ecosystems. In this context, enhancing leadership skills of leaders of NSO through targeted trainings is an important strategy to position the NSO/NSS to respond to emerging data needs, strengthen institutional reputation, and build trust among citizens.

The System of Environmental Economic Accounting (SEEA) provides the agreed upon statistical framework for measuring the relationship between the environment and the economy. It is comprised of two complimentary international statistical standards: the SEEA Central Framework (SEEA CF) and the SEEA Ecosystem Accounting (SEEA EA). Adopted in 2021, the SEEA EA constitutes an integrated and comprehensive statistical framework for organizing data about habitats and landscapes, measuring the ecosystem services, tracking changes in ecosystem assets, and linking this information to economic and other human activity.

Within the framework of the Sustainable Development Goals (SDGs), gender equality is not only a standalone goal but also one of the crosscutting universal values that underpins the SDGs, and a necessary precondition for achieving the goals of the 2030 development agenda. Good quality, timely, comparable, and disaggregated gender data provide the evidence needed to measure progress towards achieving the gender-related SDG goals and targets. The 2022 Sustainable Development Goals Progress Report produced by the United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP) shows that while there has been notable improvements in overall data vailability in Asia and the Pacific since the first benchmark report in 2017, there are still significant data gaps. Notably, at the subregional level, the report highlights a lack of sufficient data for Goal 5 (Achieve gender equality and empower all women and girls) and thus presents an incomplete picture of anticipated progress towards this goal for the Pacific. Strengthening capacities to produce and use gender statistics is central to closing the gender data gap.

Inclusive and sustainable industrial development (ISID) is a primary source of income generation, allows for rapid and sustained increases in living standards of people, and provides technological solutions for an environmentally sound development. ISID is an integral part of the SDGs, particularly SDG 9, which focuses on industry, innovation and infrastructure. Promoting inclusive and sustainable industries and continuing to invest in physical infrastructure, innovation and research are vital to long-term economic development. Furthermore, industrialization not only contributes to economic growth and infrastructure upgrading, but can also directly and indirectly support the achievement of the SDGs’ socio-economic and environmental objectives through the creation of jobs, improvements in working conditions, innovation, and the development of new and greener production technologies. In addition to SDG 9, all other SDGs incorporate some industry-related aspects and targets.

The United Nations Statistical Institute for Asia and Pacific (UNSIAP), together with United Nations Children’s Fund (UNICEF) and Statistics Korea(KOSTAT) will organize a regional training on education data capacity building from 15 to 19 May 2023, in Daejeon, Republic of Korea. The program will focus on understanding education indicators based on household survey data, as well as administrative sources with a focus on SDG4 and other relevant SDG targets related to education such as child labour. Most of the indicators, however, will come from MICS 6 data, which should be available for all participating countries. In addition to the training, the capacity building activity will also serve as an opportunity for participating countries to share their experiences in terms of data use, including both Education Management Information Systems (EMIS) and household data.

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.

The numbers of refugees and internally displaced persons (IDPs) have increased rapidly in recent years, with UNHCR estimating over 100 million forcibly displaced persons in 2022. With displacement’s growing prominence, there is increasing interest at national, regional and international levels in statistics on refugees and IDPs including complete, accurate, timely and internationally comparable estimates of the numbers of people displaced, their well-being and vulnerabilities. Good-quality statistics are a requirement for developing, implementing and monitoring national, regional and international policies and agreements concerning refugees and IDPs. This course introduces the “International Recommendations on Refugee Statistics” (IRRS) and the “International Recommendations on IDP Statistics” (IRIS). These sets of recommendations were endorsed by the United Nations Statistical Commission in 2018 (IRRS) and 2020 (IRIS).

The System of Environmental Economic Accounting (SEEA) provides the agreed upon statistical framework for measuring the relationship between the environment and the economy. It is comprised of two complimentary international statistical standards: the SEEA Central Framework (SEEA CF) and the SEEA Ecosystem Accounting (SEEA EA). The SEEA CF takes a resource-based approach to measuring the supply and use of environmental resources and availability of environmental assets. The SEEA EA takes a more holistic, approach in providing a spatially explicit approach to compiling accounts on cosystems. The SEEA can be flexibly implemented by countries prioritizing accounts based on availability of information and policy priorities. The accounts are designed to respond to data needs for multiple policy initiatives including global initiatives on sustainable development and on mitigating and adapting to climate schange.

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.

The numbers of refugees and internally displaced persons (IDPs) have increased rapidly in recent years, with UNHCR estimating over 100 million forcibly displaced persons in 2022. With displacement’s growing prominence, there is increasing interest at national, regional and international levels in statistics on refugees and IDPs including complete, accurate, timely and internationally comparable estimates of the numbers of people displaced, their well-being and vulnerabilities. Good-quality statistics are a requirement for developing, implementing and monitoring national, regional and international policies and agreements concerning refugees and IDPs. This course introduces the “International Recommendations on Refugee Statistics” (IRRS) and the “International Recommendations on IDP Statistics” (IRIS). These sets of recommendations were endorsed by the United Nations Statistical Commission in 2018 (IRRS) and 2020 (IRIS).

The 2008 SNA is an update of the earlier version 1993 SNA; does not recommend fundamental or comprehensive changes; it is meant to be implemented in a flexible manner. These webinar series will focus on the current status of the implementation, challenges affecting the implementation, country practices to these challenges and also discuss how SNA 2025 would address these challenges.

This course introduces concepts relevant to compiling indicators that inform climate change. The topics covered include among others: climate change policies and indicators; energy and air emission accounts; and data sources. Weekly webinars will also be held as part of the course to provide an overview of the topics and allow participants to ask questions. Following the completion of the course and depending on resource availability, in-kind support will be provided to countries interested in the compilation of climate change indicators that will be introduced and discussed during the course.

The course is designed for personnel working in the field of statistics, whose main responsibilities include data analysis of SDG indicators and related statistics with a specific target on data scientists from NSOs with an experience in both statistical modelling (regression analysis, prediction, classification, ...) and with programming or algorithmic skills. Although no programming will be required to follow and succeed in the course, the pedagogical materials include R code, in the form of reproducible markdown notebooks, as well as some Python resources and code.