Twenty-first session of the Governing Council and Associated Events
The Council, in the session, will consider several issues, including the Director’s report on the Institute’s achievements in 2025 and the proposed work plan for 2026. The Management Seminar, organized by SIAP, aims to strengthen the leadership and management capabilities of the heads of NSOs by providing a forum to discuss, exchange views and share experiences. This year’s theme is related to User Engagement. The seminar will draw on the experience of participants in the areas of engagement with users of data and related stakeholders. The SBJ-SIAP Collaboration Seminar is about ‘Improvement of Data Collection and Dissemination’ adopted by NSOs. This aims to contribute towards user engagement of official statistics in Asia and the Pacific region by sharing the experience and challenge for improving of data collection and dissemination. Further information is available on the SBJ website: https://www.stat.go.jp/english/info/meetings/sbjseminar2025/index.html. The World Statistics Day Forum 2025 aims to deepen understanding of the challenges and roles of statistics, based on international trends in the use of statistics and data. Through keynote speeches by the United Nations Statistics Division and presentations of case studies from Japan, the forum will promote the importance of utilizing statistics both domestically and internationally. Further information, including schedules and venue, will be communicated in due course. Twenty-first session of the Governing Council of the Statistical Institute for Asia and the Pacific (SIAP), 1 and 2 December 2025, ChibaManagement Seminar SeriesTwentieth Management Seminar for the Heads of National Statistical Offices (NSOs) in Asia and the Pacific, 2 and 3 December 2025, Chiba and TokyoCollaboration Seminar of Statistics Bureau of Japan (SBJ) and SIAP, 4 December 2025 (morning), TokyoWorld Statistics Day Forum 2025, organized by the Ministry of Internal Affairs and Communications, Government of Japan, 4 December 2025 (afternoon), Tokyo
The National Strategies for the Development of Statistics (NSDSs) provide a comprehensive framework through which countries can identify, prioritise, and enhance targeted capabilities at individual, organisational, and system levels for effective, efficient, and inclusive production of official statistics. 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 NSSs, NSO leaders, and national planning senior managers to improve strategic planning for data and statistics development, as well as to adopt innovative tools and methods. This course will provide an overview of the NSDS Guidelines and the need for countries to design effective NSDSs. In addition, the course will feature special topics on Voluntary National Reviews, climate change data, Transformation and Modernisation (T&M) Enablers, with a hint on NSO Artificial Intelligence (AI) Readiness, as well as communications around NSDSs.
Disasters continue to have an ever-increasing impact on life, well-being and sustainable development. Given these impacts, there is high demand at the local, national and international levels for quality, integrated statistics to inform all phases of the disaster risk management cycle. 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. For instance, national disaster management agencies need disaggregated and georeferenced information on population, including vulnerable groups, as well as critical infrastructure. Similarly, ministries of finance need information on climate related risks to better prepare for potential shocks to the economy.
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 the proportions of people in informal employment ranges from close to two thirds in emerging economies to nearly 90% in low-income 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 with the objectives of:1) Assessing progress in the production of statistics on informal employment and employment in the informal sector in Asia and the Pacific Region, and major hindrances in data production;2) Providing technical information and illustrations of good practices on collecting and tabulating data on informal employment and employment in the informal sector aligned to the latest development in labour market standards, and categories of informal workers as well as related data needed for the preparation of SDG indicators;3) Promoting the collection of data and improvement of statistics on informal employment and employment in the informal sector as an integral part of national labour force statistics; and4) Providing guidance and illustrations of good practices on how to conduct diagnoses of informality and how to contextualize indicators to decide on priorities and inform policy development and monitoring.
Closing gender data gaps is essential for achieving the Sustainable Development Goals (SDGs). Gender statistics are critical for understanding the distinct realities of women and men, girls and boys, and for informing policies aimed at addressing inequalities, but data and information gaps are often impediments to achieving this. While efforts to enhance gender data production have advanced, significant gaps still remain. The intersection of big data, data science, and gender statistics holds immense potential to address persistent gender data gaps by leveraging advancements in technology. With the rise of digital data sources such as social media, satellite imagery, and mobile devices, coupled with increased computing power and sophisticated analytical tools, big data enables more granular, timely, and cost-effective insights than ever before. These advancements offer transformative possibilities for measuring and addressing gender inequalities in ways that traditional methods cannot.
The population and housing census is the most comprehensive source of data on the counts and characteristics of a country's population, forming the foundation of national statistical systems. Censuses provide essential social, economic, and demographic information, serving as baseline evidence for planning, developing, implementing, and monitoring policies across various sectors and diverse user needs, including research. They are also a critical source of population data for numerous Sustainable Development Goal (SDG) indicators, aiding in the monitoring of national progress towards achieving related targets.
ESCAP-SD, SIAP, SPC, UNFPA, UNSD
Fiji
Regional Workshop on Data Visualization for the Countries of Central Asia
This e-Learning course introduces concepts and methods for the valuation of ecosystem services and ecosystem assets as described in the System of Environmental- Economic Accounting -- Ecosystem Accounting (SEEA EA). The SEEA EA provides an integrated statistical framework for organizing 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 monitoring framework of the Kunming-Montreal Global Biodiversity Framework (GBF). The course is being organized by the United Nations Statistics Division (UNSD) and the United Nations Statistical Institute for Asia and the Pacific (SIAP), under the overall guidance of the United Nations Committee of Experts on Environmental- Economic Accounting (UNCEEA).
The Food and Agriculture Organization is the custodian agency responsible for developing and updating international methodologies and standards related to food and agriculture statistics. This includes: the World Programme for the Census of Agriculture (WCA); the 22 Sustainable Development Goal (SDG) indicators under FAO custodianship; guidelines related to agriculture surveys, fisheries statistics, food consumption; the food component of the Consumer Price Index (CPI); and the components of international classifications that are related to food and agriculture, including in the Central Product Classification (CPC), Harmonized System (HS) used for trade statistics and the International Standard Industrial Classification (ISIC) of all economic activities.These international methodologies, guidelines, and classifications are critical to enable the linkage of data across multiple sources. They are updated periodically to reflect economic, social and technological changes, though in a manner and with sufficient lag as to allow time trends to reflect actual phenomena rather than methodological changes. They are developed in consultations with experts from various subject matter areas and institutions, including national governments, international and regional organizations such as UN agencies, academia, non-governmental organizations and, where relevant, the private sector. They are presented to the UN Statistics Commission, representing over 180 UN member states, for final review and approval.FAO contributes to development of international methodologies and guidelines and classifications, and leads this work with respect to agriculture and food statistics, to leverage its expertise and meet its constitutional mandate, which requires the organization to: “collect, analyze, interpret, and disseminate information relating to nutrition, food and agriculture’, “promote and … recommend national and international action with respect to scientific, technological, social and economic research relating to nutrition, food and agriculture”; and “furnish such technical assistance as governments may request1.”
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 ecosystems. 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 initiative on sustainable development goals (SDGs) and the Global Biodiversity Framework (GBF).In the Asia-Pacific region, there is an increased demand for the compilation of ecosystem accounts in support of national policies aimed at the management of ecosystems, and compilation of indicators for national and international reporting. National statistical offices and ministries of environment of countries in the region have expressed strong interest in compiling various SEEA accounts, including taking steps towards compiling ecosystem extent, condition and services accounts which are among the most relevant accounts for informing biodiversity. Furthermore, with the recent adoption of the Kunming-Montreal Global Biodiversity Framework (GBF), demand by users for ecosystem accounts will increase as the SEEA EA is the methodological base for several headline indicators of the GBF. There is a need to strengthen the capacities of national statistical systems to produce and disseminate SEEA ecosystem accounts to better meet the needs of users for high quality integrated data on ecosystems in general and biodiversity in particular. The workshop, organized by the United Nations Statistics Division (UNSD) and the UN Statistical Institute for Asia and the Pacific (SIAP), 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 BPS Statistics Indonesia, aims to further build capacities in the Asia and the Pacific for the compilation of SEEA EA in support of SDG and GBF reporting.
This e-learning course introduces crime statistics from a gender perspective to produce reliable indicators to monitor the relevant Sustainable Development Goals (SDGs). The course offers participants an opportunity to explore 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 course is the third of its kind and builds on the content covered in the two previous e-learning courses from 2020 and 2022. This iteration of the course includes updated versions of the four modules from previous courses to reflect recent developments in crime and gender statistics. Additionally, it introduces two new modules: "Gender-related killing of women and girls (femicide/feminicide)" and "Technology-facilitated Violence against Women." Participants who completed earlier versions of this course will have the opportunity to refresh their knowledge and explore recent developments in crime statistics. The content of this e-learning course has been jointly developed by the United Nations Office on Drugs and Crime (UNODC), the UNODC-KOSTAT Centre of Excellence for Statistics on Crime and Criminal Justice in Asia and the Pacific (UNODC-KOSTAT CoE), the United Nations Statistical Institute of Asia and the Pacific (SIAP) and the United Nations Entity for Gender Equality and the Empowerment of Women (UN Women) Knowledge and Partnerships Centre in the Republic of Korea.
This course introduces machine learning as a tool for using either traditional (surveys, micro data,…) or non-traditional data sources (Big Data) to produce high quality predictions for Official Statistics or Sustainable Development Goals (SDGs) indicators.The course provides an opportunity for participants to explore and comprehend the techniques of machine learning and their links with traditional statistical methods. It aims 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 course has been developed as an interactive training composed of 6 + 1 modules. Each module is composed of several mandatory pedagogical activities, following a logical structure. Activities include videos, interactive videos, interactive web-based apps, chats, live lectures and webinars, document reading, exercises, polls and quizzes. A preliminary module, M0, serves as a reminder and proposes a summary of statistical notions, terminology and basic concepts used by data analysts. These notions will be used throughout the course. The course is hosted on the SIAP’s e-learning platform (LMS) which contains a forum for general questions and interactions with the SIAP’s lecturers and e-learning platform administrators. Mandatory weekly webinars, in the form of presentations or Q&A sessions will be proposed using the Microsoft Teams platform. The participants are expected to interact during live sessions and through forums embedded in each module.
Sustainable consumption and production (SCP) and increased resource efficiency are priorities for many countries. These linked priorities are also reflected in the 2030 Agenda and the Sustainable Development Goals (SDGs) which call for sustainable management and efficient use of natural resources. Data on economy-wide material flow accounts (EW-MFA) are necessary to inform policies not only for the management of natural resources and waste, but also policies related to circular economy, resource use and ecosystems. This course focuses on economy-wide material flow accounts which are part of the System for Environmental-Economic Accounting-Central Framework (SEEA-CF).
Gender equality is a fundamental principle embedded within the framework of the Sustainable Development Goals (SDGs). It is not only a standalone goal (SDG 5: Achieve gender equality and empower all women and girls) but also a crosscutting topic that influences the achievement of the goals of the 2030 development agenda.High quality, timely, comparable, and disaggregated gender data provide the evidence needed to measure progress towards achieving the gender-related SDG goals and targets. Such data are also indispensable in identifying gaps, informing policy decisions and implementing effective interventions. Some countries in Asia and the Pacific have made substantial progress to set up enabling environments for gender data and producing related statistics. However, challenges remain regarding the uptake of gender data either linked to gender data accessibility (openness, dissemination and NSO engagement with partners and stakeholders across the government and beyond) or to data literacy and documentary evidence of data use. According to the UN Women and Paris21 Gender Data Outlook (GDO) Index, multiple countries in Asia could improve in this regard. In the Pacific, GDO data are not available for most countries.
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 are organizing a Regional Training Workshop on SEEA Asset Accounts for Sustainable Development. The workshop will be held in Chiba, Japan from 16-19 June. The workshop will be conducted in English. The regional workshop is an opportunity for participants to increase their technical knowledge of the System of Environmental-Economic Accounting (SEEA) through lectures, exercises, and sharing country examples. Participants will learn about the SEEA framework and in particular the conceptual and compilation aspects for the SEEA asset accounts in physical and monetary terms. They will also learn about the relevance of the SEEA for evidence-based decision making and in monitoring national policies and international agreements including the Sustainable Development Goals. Institutional mechanisms, data governance, data sources and dissemination approaches will also be introduced. Furthermore, participants will have an opportunity to learn about the update process of the SEEA Central Framework. For additional information on the workshop, please see the concept note and provisional agenda attached.
The 2025 System of National Accounts (2025 SNA) was adopted by the United Nations Statistical Commission during the 56th session in March 2025. The 2025 SNA is integrated with the 7th edition of the Integrated Balance of Payments and International Investment Position Manual (BPM). Varying capacities and experiences of national statistical offices in implementing the 2008 SNA will have an impact on the smooth transition to the updated framework. The implementation challenges are accentuated especially in small island developing states and most developing countries where data collection is not frequent nor granular for the new standard breakdown and/or supplementary tables/accounts, due to an array of factors such as resource constraints amongst others.Past SNA outreach activities presented the key concepts, definitions, and recommendations of the SNA manual and guidance notes. During the introductory webinar co-organized by the Economic and Social Commission for Asia and the Pacific (ESCAP) Statistics Division, Statistical Institute for Asia and the Pacific, and the Pacific Community (SPC) in March 2025, participants raised the need to share country priorities and practices in implementing the SNA. Country-specific technical concerns and issues, however, would require in-depth training and technical assistance to ensure effective skills transfer. It is also imperative that national strategies for statistical development include the 2025 SNA.
The three-day crash course aims to equip participants with essential skills in R and RStudio, focusing on practical applications for data analysis for Official Statistics and SDG indicators. It is designed on an interactive platform to enhance a quick start in R, providing participants with practical skills to use a programming language for managing and analyzing data. Through guided exercises, interactive handouts with R and real-world-like applications, participants will gain confidence in using R for managing survey analysis data, for exploring and filtering data sets and for computing simple SDG indicators. This e-course is not a replication of the many online R tutorials that already exist, nor a substitute to these courses that should be used to complement the skills learned in this crash course. It aims at building capacity in national statistical systems for the use of the open source software R for Official Statistic, following the UN's commitment to leveraging open source solutions.
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. 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 selfengagement, 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.
Climate change is one of the most pressing issues in the Asia-Pacific region. Yet emissions from fuel combustion in the region (and globally) continue to trend upwards due to increased demand for energy. In addition, households and businesses are faced with frequent price shocks in many energy commodities. High quality, consistent data on energy is critically needed to inform effective pathways for addressing issues around energy use and availability, climate change mitigation and just energy transitions.National statistical offices (NSOs) and ministries of energy of countries in the region have responded to these needs by compiling basic energy statistics, energy balances and energy accounts. However, there continues to be a need to strengthen the capacities of NSOs and ministries of energy to produce and disseminate energy information to better meet the needs of users for high quality integrated data on energy and its relationship to the broader economy and climate change.The workshop, organized by the United Nations Statistics Division (UNSD) and the United Nations Statistical Institute for Asia and the Pacific (SIAP), with the support of the Office of the Director-General for Policy Planning on Statistical Policy of the Ministry of Internal Affairs and Communications of the Government of Japan, aims to further build capacities in the region for the compilation of energy information in support of energy and climate change policies.
The overall objective of the week-long training is to help participants better understand the use and benefits of Big Data in the production of gender statistics. To that end, the training program will present recent development in the compilation of gender statistics as well as new methods, case studies and processes that can facilitate the integration of Big Data in this process. The training will also emphasize the limitations, constraints and privacy issues inherent to the use of Big, non-traditional or administrative data. Please refer to the attached concept note, which provides a more detailed description of objectives, scope and requirements for the training.
It is well established that healthy ecosystems and biodiversity are fundamental to supporting and sustaining our wellbeing, our communities and our economies. Protecting and properly managing ecosystems is key to ensuring the continuous provision of ecosystem services such as pollination, carbon sequestration, flood protection, etc. Understanding the contribution of nature to our well-being and the impacts of our activities on the state of ecosystems are key for sustainable development.This e-Learning course introduces the System of Environmental-Economic Accounting--Ecosystem Accounting (SEEA EA), the agreed statistical framework for collecting and organizing 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 (SIAP), under the overall guidance of the UN Committee of Experts on Environmental Economic Accounting (UNCEEA).
SIAP, UNSD
e-Learning
Online
Webinar on the 2025 System of National Accounts
The 2025 SNA framework will serve as the internationally recognized standard for compiling economic activity measures. It aims to enhance the understanding of well-being and sustainability while providing adaptable methods to integrate environmental and social dimensions into economic statistics. Critical conceptual and measurement issues, such as in advancements of digital products, the complex interplay between economic, social, and environmental factors, and the intricacies of global trade, have been harmonized and incorporated into the updated framework to a great extent.As national statistical systems prepare to implement these updates, the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP) Statistics Division, the Statistical Institute for Asia and the Pacific (SIAP), and the Pacific Community (SPC) will jointly organize a webinar, in collaboration with the Intersecretariat Working Group on National Accounts (ISWGNA) and Project Management Team, to inform participants about the objectives of the SNA update, its implementation strategy, and the key changes introduced in the 2025 framework. This webinar will also provide an overview of the consolidated recommendations for updating the 2008 SNA, ensuring that national statistical offices can transition smoothly to the revised framework. While the 2025 SNA update emphasizes international comparability, the implementation strategy acknowledges country-specific circumstances, including national priorities, data availability, and resource constraints. The discussion will highlight recommendations on how these updates can be implemented effectively, particularly in the Asia-Pacific region, where some economies face significant resource limitations.
ISWGNA, ESCAP-SDD, SIAP
Webinar
Online
Webinar on the 2025 System of National Accounts
The 2025 SNA framework will serve as the internationally recognized standard for compiling economic activity measures. It aims to enhance the understanding of well-being and sustainability while providing adaptable methods to integrate environmental and social dimensions into economic statistics. Critical conceptual and measurement issues, such as in advancements of digital products, the complex interplay between economic, social, and environmental factors, and the intricacies of global trade, have been harmonized and incorporated into the updated framework to a great extent.As national statistical systems prepare to implement these updates, the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP) Statistics Division, the Statistical Institute for Asia and the Pacific (SIAP), and the Pacific Community (SPC) will jointly organize a webinar, in collaboration with the Intersecretariat Working Group on National Accounts (ISWGNA) and Project Management Team, to inform participants about the objectives of the SNA update, its implementation strategy, and the key changes introduced in the 2025 framework. This webinar will also provide an overview of the consolidated recommendations for updating the 2008 SNA, ensuring that national statistical offices can transition smoothly to the revised framework. While the 2025 SNA update emphasizes international comparability, the implementation strategy acknowledges country-specific circumstances, including national priorities, data availability, and resource constraints. The discussion will highlight recommendations on how these updates can be implemented effectively, particularly in the Asia-Pacific region, where some economies face significant resource limitations.
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).The DRSF aims to improve countries capacities to produce high quality, integrated statistics on disasters; and it is the basis for this course. During the course participants will learn about the importance of harmonized data and its relevance to policy making at the national and global level. Other topics covered include statistics on disaster risk, disaster occurrence and impacts, and economic losses. Further details on course content follow below. Please note that a course on disaster related statistics was last held in 2023; this is an updated course and those who participated in the 2023 course are welcomed to join.
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 underpin 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 Progress on the Sustainable Development Goals – The Gender Snapshot 2024 produced by the United Nations Entity for Gender Equality and the Empowerment of Women (UN Women) and the Department of Economic and Social Affairs (DESA) shows that while there are notable advancements, including reductions in poverty, narrowing gender gaps in education, and progress toward legal reforms, there remains progress to be achieved across all indicators, with only five years left to reach the 2030 Sustainable Development Goal deadline.
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.
National statistical systems are increasingly using administrative data to compile official statistics. Such data can be utilized to better meet the increasing demands for new statistics and indicators that are highly disaggregated. Administrative data is not collected for the primary purpose of compiling official statistics, and statisticians need to ensure that the data meets certain criteria before using it to produce official statistics. This course provides an overview of administrative data, a discussion of data quality issues and institutional mechanisms to ensure that administrative data can be used in the production of official statistics. The course builds upon content developed for in-person training courses conducted by UNSD and to which members of the Collaborative on Administrative Data have provided valuable input.
CPIs 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 banks for 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.
