POVERTY POVERTY AND EQUITY EQUITABLE GROWTH, FINANCE & INSTITUTIONS INSIGHT The Next Generation of Statistical Capacity Building THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 1 The Next Generation of Statistical Capacity Building This note was developed by a Task Force on Statistical Modernization under the StatCap Community of Practice. The work was overseen by Thomas Danielewitz and Utz Pape with helpful contributions from Professor Paul Cheung. © 2023 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. 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Any queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; fax: 202- 522-2625; e-mail: pubrights@worldbank.org. >>> Contents The 2021 World Development Report (WDR) Makes a Powerful Call for Data as a Pathway to Development 1 Data and Development: Lessons Learned from 20 Years of Experience in Statistical Capacity Building 2 Emerging Trends and Key Pivots in World Bank Support for Statistics and National Data Agendas 8 Adapting the World Bank to Deliver Innovative and Integrated Programs of Support to Clients 16 Notes 19 Appendix A: Strategic Agendas for Countries at Different Levels of Development 20 Figures Figure 1: International Action Plans on Statistics with Key Focus Areas 3 Figure 2: World Bank Financing for Statistical Development, 1999–2021 4 Figure 3: Average Statistical Performance Indicator Scores by Region, 2016–19 5 Figure 4: Shifting the Focus from NSO to NSS and INDS 12 Figure 5: Schematic Representation of an Integrated Data System for National Statistics 13 Tables Table 1: Statistical Capacity Building Achievements and Challenges for the World Bank and Countries 7 Table 2: Strengths, Weaknesses, Opportunities, and Threats for Official Statistics Producers 11 Boxes Box 1: Opportunity Insights: Track the Recovery 8 Box 2: Application of New Technologies to Collect and Analyze Critical Data for Policy Making 9 >>> The 2021 World Development Report (WDR) Makes a Powerful Call for Data as a Pathway to Development The WDR explores the tremendous potential of data to earned the NSO a central role in national economic planning. improve lives. For the vision to be achieved, a new compact The decennial population and housing census and well- on data is necessary. designed national survey programs are still the main source of socioeconomic information in many countries. NSOs, as a The data revolution holds the promise of better decision-making, result, have enjoyed a special position within government and improved service delivery, and increased accountability and in society as the main source of trusted information. The head transparency in the public sector. However, restrictions to data of an NSO, widely known as the chief statistician, is in most access, sometimes compounded by a reluctance to share, and countries the head of a professional service often called upon a growing awareness of the risks that come with data access to explain statistical trends to the public. and sharing, mean economies and societies are not harnessing the full potential of data. The highly curated and standardized data sets produced by the national statistical system (NSS), the professional ethos The national statistical system as producer and custodian shared by the cadre of statisticians, and the accumulated data of data sets of national importance is an integral part of the insights are still of national importance today and will remain national data ecosystem and instrumental to the success so in the future. However, the data revolution has created both of the data agenda. challenges and opportunities for the NSS, which requires a rethink of the production processes, the services offered, and For decades, national statistical offices (NSOs) have played a the institutional environment for statistical systems to remain central role in national information ecosystems. The compilation relevant in the future. of macroeconomic indexes and business statistics have THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 1 >>> Data and Development: Lessons Learned from 20 Years of Experience in Statistical Capacity Building The World Bank has supported NSSs to meet development Action Plan for Sustainable Development Data (CTGAP), objectives for almost two decades. was adopted by the United Nations Statistical Commission in 2017. The main objective has been to strengthen the capacity The World Bank’s support for statistical developments spans of developing countries to report to international monitoring two decades. Several successive action plans and initiatives at frameworks such as the Millenium Dvelopment Goals (MDGs) the international level have guided coordinated action among and subsequently the Sustainable Development Goals multiple stakeholders, including the World Bank, to achieve (SDGs). Earlier action plans focused mostly on building the a series of strategic objectives (see figure 1). These action basic capacities for statistical production, whereas subsequent plans have been accompained by coordination and funding action plans increasingly focused on dissemination and use of mechanisms, operational instruments, and technical guidance data for domestic policy purposes, modernization of production and tools. The current action plan, the Cape Town Global processes, and leadership and coordination of the NSSs. THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 2 > > > F I G U R E 1 - International Action Plans on Statistics with Key Focus Areas 2004 2011 2017 Cape Town Marrakech Busan Global Action Plan Action Plan Action Plan for Sustainable for Statistics for Statistics Development Data • Strategic planning • Data documentation • Leadership & coordination • Increased investments & public access • Innovation & modernization • 2010 Census round • Knowledge and skills • Core statistical programs • International household in using statistics • Dissemination & use survey network • Monitoring of international • National & international • Millennium commitments partnerships Development Goals • Robust financing and • Mobilize resources • International statistics funding mechanisms More than $1 billion in financing has been provided to more in 2004 as a “horizontal” adaptable program loan (APL). To than 125 countries since 2000. qualify for STATCAP financing, countries had to prepare a National Strategy for the Development of Statistics (NSDS), The World Bank provided more than $1 billion in grants and show national commitment and leadership to strengthen the loans to support statistical development during the period NSS, be willing to comply with good statistical practice, and 1999–2021. Of this, about $100 million came from the Trust participate in global monitoring activities. Most STATCAP Fund for Statistical Capacity Building (TFSCB), which provided projects have followed a similar design, with activities aimed 431 small grants (average grant size: $238,000). Another trust at strengthening statistical policy and institutional frameworks, fund, the Statistics for Results Facility Catalytic Fund (SRF- mechanisms for efficient management and coordination, CF), financed 9 projects totaling $79.2 million (average grant statistical infrastructure, statistical operations and procedures, size: $8.8 million) between 2009 and 2019. The ECASTAT Trust human resource development, and physical infrastructure Fund has provided $15 million to statistical development in the and equipment. countries of the Commonwealth of Independent States (CIS). Twenty-nine loan-financed STATCAP projects for total Larger system-wide improvements have mainly been financed commitments of about $917 million have been approved since by the International Development Association (IDA) and the 2004 or were in the pipeline as of 2021 (figure 2). Four of the International Bank for Reconstruction and Development projects are large regional projects that cover 23 countries, (IBRD) in accordance with the Statistical Capacity Building accounting for 70 percent of total IBRD/IDA commitments over (STATCAP) Program. The STATCAP Program was first this time (about $437 million). approved by the World Bank’s Board of Executive Directors THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 3 > > > F I G U R E 2 - World Bank Financing for Statistical Development, 1999–2021 917 431 79.2 103 15 8 9 29 ECASTAT SRF-CF TFSCB StatCap (IBRD/IDA) US$,millions # of projects Note: Regional projects covering more than one country are counted as one project. SRF-CF: Statistics for Results Facility Catalytic Fund; STATCAP: Statistical Capacity Building Program; TFSCB: Trust Fund for Statistical Capacity Building. More recently, as part of the 19th Replenishment of IDA (IDA19), had been made in NSDS implementation. The review further a global coalition of development partners agreed to a specific found that World Bank projects were not sufficiently including policy commitment for IDA resources to be targeted at closing the users of statistics in the design and implementation of core data gaps in the poorest countries.1 The policy commitment programs and that more attention should be given to training on Data for Policy (D4P) commits the World Bank to supporting and quality of statistics.3 With regard to funding and operational at least 30 IDA countries in improving the availability, timeliness, arrangements, the IEG recommended that the World Bank quality, and relevance of a core set of data for evidence-based increase financial commitments to statistics and strengthen decision-making.2 In IDA20, this commitment was updated in operational arrangements to ensure statistical capacity line with the 2021 WDR recommendations regarding the need building is embedded in Country Partnership Frameworks and to strengthen the institutional capacity of NSSs, as well as build operational portfolios. resilience to shocks such as the COVID-19 pandemic. More remains to be done to nurture the demand side of The World Bank has been effective in supporting strategic statistics and encourage openness and data sharing. planning, forging partnerships, and providing funding for statistical capacity building. The second major IEG evaluation in 2018 found that the World Bank had been effective at the country level in supporting data The first evaluation of the World Bank’s support for statistical production, promoting open data, and building the capacity of capacity building was done in 2011. The Independent NSOs in countries where it adopted a system-wide approach. Evaluation Group (IEG) reviewed three interlinked initiatives: However, the World Bank had been less effective in adapting the Marrakech Action Plan for Statistics (MAPS), the to the changed global partnership landscape, and even less Partnership in Statistics for Development in the 21st Century effective in fully using its leverage to encourage data sharing (PARIS21), and the TFSCB. The review found that significant by client countries that had been reluctant to do so. World Bank progress had been made in encouraging and supporting projects also had difficulties in bridging the vital link between developing countries to design NSDSs, but less progress statistical production and government decision-making. THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 4 Subnational data capacity, use of administrative data systems, received the lowest scores (figure 3). The notion that developing and big data were also highlighted as areas of weakness in countries would catch up through leapfrogging has so far failed World Bank engagements.4 to be realized. Instead, multitiered NSSs have evolved that differ vastly in governance arrangements and openness and in the Despite overall progress, the statistical performance gap way that technology, skills, and resources are used to produce between low-income countries and the rest of the world is and disseminate statistics. widening, especially with regard to data openness. Since 2016, Open Data Watch has released an annual report The Statistical Performance Indicator (SPI), launched in 2020, providing an assessment of the coverage and openness of shows a widening gap between statistical systems in low- official statistics in 187 countries using a mix of indicators. income countries and those in the rest of the world. From 2016 The overall Open Data Inventory (ODIN) score is an indicator to 2019, the statistical performance as measured by the SPI of how complete and open the data offerings of an NSO are. of low-income countries (LICs) rose 4.7 percent compared All countries have made progress on openness as measured with 7.7 percent for lower-middle-income countries (LMICs), by ODIN, but again, low-income countries lag behind. The 10.1 percent for upper-middle-income countries (UMICs), and openness score for all low-income countries has improved 26 6.5 percent for high-income countries (HICs).5 There is also percent since 2016, compared with 35 percent and 29 percent a significant gap across regions: Europe and Central Asia for LMICs and UMICs, respectively. HICs increased 13 percent, received the highest SPI score (71.9) and the Middle East but from an already high base.6 and North Africa (48.2) and West and Central Africa (49.6) > > > F I G U R E 3 - Average Statistical Performance Indicator Scores by Region, 2016–19 Europe and Central Asia 71.9 Latin America and Caribbean 61.1 South Asia 58.7 East Asia and Pacific 54.1 South and East Asia 52.7 West and Central Africa 49.6 Middle East and North Africa 48.2 0 20 40 60 80 2016 2019 Source: World Bank, World Development Report 2021: Data for Better Lives (Washington, DC, 2021); Statistical Performance Indicators (database), World Bank, Washington, DC (accessed January 2021), http://worldbank.org/en/programs/statistical-performance-indicators. THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 5 NSSs in fragile and conflict-afflicted situations (FCS) face of the situation. The task team leaders particularly highlighted special challenges. the need for support for COVID-19–specific surveys, household surveys (HIES, LSMS), and price data collection and labor force A 2019 evaluation of the SRF-CF found that the failures of surveys. They expressed interest in multi-modal solutions as two World Bank projects in Afghanistan and the Democratic something the World Bank should focus on going forward Republic of Congo were due to the weakness of the respective and mentioned a need to invest more in business continuity, NSOs to support a strategic, system-wide approach to including capability for remote work. statistical development, which had been the preferred modality for statistical capacity building until then. This was further World Bank–supported phone surveys of the impact of corroborated by the South Sudan STATCAP project, which COVID-19 show that advancements in data capture failed to meet its objectives because civil conflict broke out in technology and frequency of reporting is possible even in the country in 2014. This points to a need to address the special low-income countries. circumstances and needs of FCS and low-income countries. This could mean more narrowly targeted interventions that are During the pandemic, the World Bank supported 213 rapid tailored to the country context and realities on the ground. household surveys in 64 countries as well as business pulse surveys in 50 countries. These surveys produced crucial COVID-19 has revealed serious vulnerabilities in NSSs and information about the impact of the pandemic on livelihoods, a widening of preexisting disparities. jobs, and businesses. Due to the suspension of face-to- face interviews, the surveys were largely conducted through When the COVID-19 pandemic broke out in spring 2020, computer-assisted telephonic interviews (CATIs). This serves many NSOs suspended face-to-face interviews and staff were as an important “proof-of-concept” that new data capture asked to work from home—in many cases, without adequate technologies are possible. Despite challenges of limited technology for remote work. This left many NSSs under severe representativeness and often lower female response rates, strain at a time when policy makers urgently needed data on the CATI surveys have shown to vastly increase the efficiency evolving pandemic and its impact on public health, education, and speed by which data for key socioeconomic indicators are livelihoods, and the economy. According to a joint World collected, processed, and disseminated. Bank–United Nations survey of NSOs in 2020, 90 percent of NSOs in LICs and LMICs were struggling to meet international Despite considerable progress, serious challenges remain reporting requirements because of COVID-19.7 Sixty percent for the next generation of statistics projects. reported that they had to postpone the decennial population and housing census. Countries reported an urgent need for financial Much has been achieved since the STATCAP Program was resources, technical assistance, and facilities for remote work approved by the World Bank’s Board of Executive Directors and remote data capture. A Poverty and Equity Global Practice in 2004. The program has provided a useful framework for survey of task team leaders in July 2020 confirmed the severity strengthening NSSs through a comprehensive approach THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 6 and streamlined processing procedures. The framework practice. The program has also increased developing country has encouraged effective coordination, the participation of participation in global development and monitoring activities. international and bilateral donors, and the participation of This approach has served statistical systems well. But the national stakeholders. The main criteria for STATCAP projects working environment for statistics has changed, and so must have enticed countries to prepare NSDSs, demonstrate the focus for next-generation statistics projects. Table 1 national commitment and leadership to strengthen the national summarizes key achievements and challenges for the World statistical system, and be willing to comply with good statistical Bank and countries, respectively. > > > T A B L E 1 - Statistical Capacity Building Achievements and Challenges for the World Bank and Countries World Bank achievements World Bank challenges • The World Bank has effectively provided financing and • Support is needed for higher value-added processes technical assistance for basic statistical production such as analysis, dissemination, evaluation, and use of to meet development objectives and international data for policy reporting requirements • Digital transformation and evolving user preferences • The World Bank has developed an extensive set of tools are changing the operating environment for national and guidance for data production and dissemination, statistical offices (NSOs), requiring a repositioning of which is being offered to countries as global public goods the World Bank’s offerings • The World Bank’s rapid COVID survey program • NSO demand for support for resilience and crisis shows that technological advancement and rapid data management capacity of statistical systems in collection is possible in low-income countries IDA countries • Medium Income Countries (MICs) are reluctant to seek World Bank financing for statistical capacity building • The lack of a dedicated trust fund for data work is making it difficult to offer countries targeted, just-in-time technical assistance and advice Country achievements Country challenges • Most developing countries have now implemented their • Stark disparities exist between statistical systems in first National Strategy for the Development of Statistics, countries at different levels of development. Low-income with many on the second or third generation countries are evolving but not catching up • Fundamental statistical systems are in place and • COVID-19 has further exacerbated these disparities and operating in most countries, producing basic social, revealed significant vulnerabilities economic, and environmental data as well as Sustainable Development Goal indicators • FCS countries face a special set of challenges requiring tailored solutions and support • Developing countries are connected to international forums and international expertise, and have access to • The digital transformation has changed the operating support for statistical development environment for statistics, particularly for lower-middle- income countries and MICs, posing both opportunities and challenges THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 7 >>> Emerging Trends and Key Pivots in World Bank Support for Statistics and National Data Agendas The digital revolution has changed the operating However, the vast new technical possibilities have been environment for statistics and has increased competition accompanied by intense competition in the information space. in the information space. NSOs that were once the main, or in some cases the only, providers of socioeconomic information, are being challenged The operating environment for NSOs has changed significantly by new, nimbler, and more data savvy players who are not bound in the past decades. Computing power once prohibitively by the rigid definitions and standards of official statistics. The expensive has become affordable even for low-income and COVID-19 pandemic amplified this trend, with a proliferation of lower-middle-income countries. Data that had to be collected data sites providing near to real-time data on the impact of the manually are now ubiquitous because of digitalization and pandemic on public health, livelihoods, labor markets, and the e-government initiatives, which have also created a constant economy. Some were developed in public-private partnerships, flow of data from citizens and businesses to government such as Opportunity Insights: Track the Recovery (box 1), which agencies. The rollout of national ID programs, unique business uses a variety of high-frequency data sources to provide quick entity identifiers, and national address registers have created insights on pertinent issues. the potential for integrating data from disparate databases. B OX 1 : O P P O RT U N I T Y I N S I G H T S : T R AC K T H E R EC OV E RY Opportunity Insights was launched in 2018 as a research partnership between leading economists from Harvard University and Brown University. The institute uses big data and local partnerships to document issues of economic mobility and opportunity. Since its inception, Opportunity Insights has launched two major initiatives: (1) the Opportunity Atlas, a comprehensive census tract-level data set of children’s outcomes in adulthood using data covering nearly the entire US population, and (2) the widely cited Track the Recovery database, which uses data from private companies to track economic activity at a granular level in real time. Daily statistics on consumer spending, business revenues, employment rates, and other key indicators disaggregated by ZIP code, industry, income group, and business size are updated daily giving a current picture of the effect of COVID-19 on the economy and livelihoods across the United States. THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 8 Others are fully private or nonprofits offering subscriptions Innovations in data collection and fieldwork monitoring are services, such as the Centre for Monitoring Indian Economy rapidly becoming more available and more cost-effective. (CMIE). CMIE has filled an information gap caused by the For example, while agricultural censuses typically require a inertia of official statistics producers in India by building the significant investment, new technologies present a low-cost country’s largest database on the financial performance opportunity for regular updates and real-time monitoring of of individual companies. It conducts large-scale surveys conditions on the ground based on information from weather to estimate household incomes, patterns of spending, and stations, satellite imagery, and drone-based data collection. savings, and it has created the largest integrated database of Innovation can also be helpful in making data more meaningful the Indian economy. by integrating often fragmented data systems, as well as synthesizing the information in a way that is useful for policy The digital revolution has also promoted technical makers in decision-making. Some recent promising applications innovations to improve the frequency and timeliness of use satellite-based remote-sensing, telecommunication data for policy making. technologies, and social media to model and measure socioeconomic indicators (box 2). B O X 2 : A P P L I C A T I O N O F N E W T E C H N O L O G I E S T O C O L L E C T A N D A N A LY Z E C R I T I C A L D ATA F O R P O L I C Y M A K I N G Technical innovations have useful applications to capture environmental sustainability data, which are critical to measure natural disasters and climate change. These include the use of rain sensors and temperature to collect information on droughts and floods, or drones and satellite information for sampling framing of agricultural censuses and surveys. For example, satellite and weekly community survey data are being used to track the impact of climate change on pastoral conditions in the Sahel (Burkina Faso, Mali, Niger), a region prone to droughts. There are also recent remarkable applications for measuring economic activity with increasing granularity and scope. Night lights (satellite images of luminosity at night) could be used to estimate economic activity at the country level. Other recent approaches to measure economic activity rely on proprietary commercial data sets such as call detail records (CDRs). New sources of data also open the door for the construction of modern consumer price indexes (CPI), which can complement traditional data collection. Scraping online prices and other automatic price collection procedures to estimate CPIs are already being piloted and implemented in many developed countries and some developing countries. The e-bread index, a partnership between UN Global Pulse, PriceStats, and the Billion Prices Project at MIT, aims to analyze how scraping online prices can provide real-time insights on price dynamics, focusing on the case of bread in six Latin American countries. THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 9 User expectations have evolved. Governments are increasingly aware that the wealth of data available from public and private sources, in both structured Reliability and methodological soundness have always been the and unstructured formats, is invaluable to public policy making. hallmarks of national statistics. However, in recent years speed Many governments have evolved an active program to harness and mode of delivery have taken center stage. Users today such data with initiatives ranging from the deployment of data expect data to be delivered digitally across multiple devices scientists to establishing an agency to manage data resources. and platforms and in a format that enables quick analysis and Within this context, NSOs and NSSs—the producers and digital publishing. The economics profession is a good example custodians of official statistics—are increasingly at risk of of this transformation. Economists have always been major becoming marginalized. Official statistics, while still trusted consumers of official statistics. But the profession has changed as the cornerstone of the public data system, are no longer in recent years in a process coined “third-wave economics” by perceived as relevant for solving fast-evolving public issues. The Economist magazine.8 This involves three major changes. An independent review of the United Kingdom’s economic First, economists draw on data that are abundant and directly statistics in 2016, the so-called Bean Report,9 characterized relevant to real-world problems. Second, economists aim to official economic statistics as “showing their age,” having been use data to influence public policy. This requires them to do designed more than 50 years ago when the economy was more “quick-and-dirty” research in response to new policies. dominated by production of goods. In response, the UK NSS X, formerly known as Twitter, and other social media platforms underwent a major upgrade that included the establishment of have become popular venues to engage in debate and public the UK Data Science Campus in 2017 to boost capabilities, discourse. Third, this new type of economics involves little innovation, and responsiveness to users. theory. The data points used to build an argument or express a point of view are increasingly not official statistics, which are International development assistance must be adapted to often characterized by long time lags and at times not able to help NSOs meet these challenges. capture the modern economy comprehensively. Instead, real- time information on container ships waiting to unload, restaurant The international statistical community has acknowledged bookings, credit card spending, air passengers going through that the operating environment has changed and that NSOs security, Google search terms, and social media posts are and NSSs must reposition themselves to meet current and important new data sources. future challenges. In contrast to the MAPS and Busan Action Plan for Statistics (BAPS), which focused mostly on resource Users are also looking for context and insights. While data mobilization and building core statistical capabilities, the CTGAP from an individual survey—for instance, a labor force survey— emphasizes leadership, coordination, modernization, and might provide useful new data points, a thematic publication innovation. Member countries of the UN Economic Commission on the labor market combining data from household surveys, for Europe have launched a modernization program, sharing firm surveys, and administrative data is likely to add more experience and knowledge on the transformation process. informational value. This requires a systematic user-centered European countries have shown interesting examples of how approach about the best way of serving varying user needs the statistical system can remain relevant. Canada, a member of effectively, which is why most advanced NSOs have established the UN Economic Commission for Europe, is another excellent dedicated data dissemination units that employ diverse talents example of successful repositioning through a variety of and skills within data journalism and data science. strategies. Less-developed countries face far more formidable challenges, including reforms to legal mandates and institutional Official statistics producers are at risk of losing their arrangements, raising internal technical capabilities, and more coveted position as the primary sources of trusted importantly, meeting emerging demands for data (table 2). information. THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 10 > > > T A B L E 2 - Strengths, Weaknesses, Opportunities, and Threats for Official Statistics Producers NSS strengths NSS weaknesses* Experienced in data management, governance, Rigid processes and methods and generation of information Inflexible aging technology Strong focus on statistical standards and definitions Low productivity of traditional data collection Custodian of key official data sets such as surveys, censuses, system of national accounts Inability to respond quickly to emerging information needs Central position as key adviser to government on Slow to harness alternative sources of data socioeconomic and environmental information Difficulty attracting and retaining talent in highly competitive Legal act providing statutory access to private market for skills and public data Vulnerable to shocks, e.g., COVID-19 Well-known brand name NSS opportunities NSS threats New technological opportunities Proliferation of alternative “facts,” misinformation or “fake news” spreading rapidly through digital means Rapidly growing public and private digital data assets Declining trust in official sources of information Need for data stewardship and role of integrator of government data sets Declining survey response rates Demand for rapid data on topical issues, Competition from more agile, data savvy e.g., COVID-19, climate change, inequality, forced and better branded data providers displacement, digital economy, changing nature of work Note: *Weaknesses inspired by High-Level Group on Modernization of Official Statistics (HLG-MOS) – OECD/UNECE. A modern, adaptive, and integrated statistical system is think strategically and address both the enabling environment fundamental to the success of a data-driven public sector. for data use—for example, institutions and legislation, human resources (HR) and information technology (IT), data policies— A central idea in the 2021 WDR is that governments can extract as well as developing the data systems in key sectors such more value from their data assets by developing an environment as social protection, health, education, urban development, and infrastructure that enables the safe use and reuse of data disaster risk management, business regulation, taxation, for multiple purposes. The report puts forward several “pivots” and statistics. for the World Bank to steer away from “one-off data collection activities” toward supporting the development of integrated Integrating the NSS into the INDS national data systems (INDSs) that can help realize greater returns on data investments. Integration of the NSS as a key pillar of the INDS implies putting in place an effective governance architecture that facilitates the A whole-of-government approach will be needed to achieve this use of common standards and methods and ensures coherence vision. To fully realize the potential of data, governments must and consistency in the statistical measurements used across THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 11 different levels of government (figure 4). The abundance of data does not mean that the data are used effectively. Data must be curated and organized and delivered in a format that is meaningful to its users. Agencies in the NSS led by the NSO must acquire the skills and expertise to organize and integrate data into usable frameworks. > > > F I G U R E 4 - Shifting the Focus from NSO to NSS and INDS Integrated National Data System National Statistical System Developing the Setting up National Statistical Office environment and mechanisms to infrastructure to coordinate the use and reuse data ensemble of Building core capabilities to play an active through system official statistics role in shaping the national data system, integration producers and and lead the national statistical system in other stakeholders producing high-quality socioeconomic and in the NSS environmental statistics For modern statistical organizations, data integration within the 3. Integrating the perspectives and needs of data users, larger data system means going beyond production of basic both government and nongovernment, into statistical indicators. Statistics producers must, for example, integrate programming the user perspective into the statistical planning process to ensure that produced data are fit for purpose. At the technical 4. Integrating data from multiple sources for greater efficiency level, integration means the development of common platforms and value addition to statistical outputs and standards for data sharing and exchange. In the context of statistics production, it means combining data from one or Pursuing an integrated approach to statistical production more sources to create new and enhanced information and requires the NSO to upgrade its IT and HR capabilities and to knowledge products. Important aspects of integration include implement modern management models such as the Generic the following: Activity Model for Statistical Organizations (GAMSO) and the Generic Statistical Business Process Model (GSBPM). 1. Integrating the entities of the NSS through stronger governance and coordination mechanisms that enable use Some countries have successfully introduced register-based and reuse of administrative data for statistical purposes statistical models and mixed-mode methods that enable merging traditional surveys with administrative data to produce 2. Shifting the statistical production process in the NSO from a powerful new insights at higher frequency, increased granularity, siloed “stovepipe” model to a horizontally integrated platform and reduced cost. with specialized business units applying strict quality control procedures for each step of the production process THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 12 Starting in the 1970s, the Nordic countries were the first to build countries have moved in the same direction over the years, for a complete statistical system based primarily on an integrated example, Armenia, Ghana, New Zealand, and Uruguay. system of administrative and statistical registers (figure 5). More > > > F I G U R E 5 - Schematic Representation of an Integrated Data System for National Statistics “WHERE?” Built environment Geospatial data Environmental ENVIRONMENT Earth statistics observations Places “WHO?” “WHAT?” Geo ing renc refe refe renc Gov Services Gov Revenue Geo DATA ing Civil registration INTEGRATION Sales National ID Purchases Income Investment Consumption Payroll Saving & Investment Industry statistics Census People Businesses Transactions Demography Economic statistics Social statistics SOCIETY ECONOMY Note: Visualization inspired by the Committee of Experts on UN Global Geospatial Information Management (UN GGIM). THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 13 A modernization agenda for NSOs and NSSs. and must build a good foundation for an INDS. Hence, a modernization strategy should consider the current and future The most visionary and dynamic statistical offices have operating environment for statistics in a country based on a already begun to position themselves not just to benefit maturity model of statistical modernization. from the data revolution but to become champions of digital transformation in government. Others, unfortunately, have a Below are four proposed key pivots in the modernization agenda long way to go. Those that do not manage this transition well for NSOs and NSSs. run the risk of being sidelined by new, more agile players in the information ecosystem. 1. Governance: Effective management of the national statistical system to meet emerging data needs NSOs are aware of the need to modernize. A recent joint World Bank-UN-PARIS21 survey of NSOs revealed that NSOs see The institutional environment where the NSO and six top priority areas for investments in the coming years (% NSS operate and their governance structure must be of NSOs selecting):10 (1) administrative data and statistical strengthened for effective functioning. The institutional registers (89 percent), (2) coordination among NSS members environment is dictated by the political economy of the (84 percent), (3) data exchange and dissemination (83 percent), country, and for the World Bank to be effective, it must gain (4) data quality assurance (79 percent), (5) data processing a better understanding of this aspect of the governance and analysis (77 percent), and (6) integration of geospatial architecture before engaging. This notwithstanding, legal information systems (70 percent). mandates for the NSO and NSS need to be reviewed and upgraded. Outdated legal mandates may restrict the NSO The same survey also revealed a glaring shortfall in IT and and NSS from moving to new platforms and activities. New, financial resources, especially in LICs and LMICs. This resulted competing institutions contributing to the data agenda within in significant difficulties during the COVID-19 pandemic as the government risk causing friction and confusion in data statistical operations moved online. Around half of the NSOs production and coordination. A data agency may impose reported that staff did not have adequate internet access to work data standards that are at odds with the national statistical from home, and that the NSOs lacked secure remote access to standards established by the NSS. Political commitment data and cloud computing services. will be essential for official statistics along with appropriate policy reforms that provide the enabling environment for As the World Bank moves to broaden the engagement official statistics to grow. The mandate for the NSS to play from focusing specifically on statistics to the broader data an instrumental role within the data ecosystem must be ecosystem, it must not leave official statistics behind. Official recognized and strengthened. As statistical organizations statistics remain the foundation of the INDS. The modernization begin to use non-survey data such as administrative data of the NSO and NSS is an important prerequisite for building a records or big data, they will need to comply with national strong INDS. data protection policies and protocols, which may require updating statistical legislation. The key difference between STATCAP projects of the past 20 years and the modernization agenda proposed in this note is 2. Operations: Strengthen the institutional environment the area of strategic focus. Where first-generation STATCAP for quality statistics projects were aimed at establishing the building blocks of the NSS, particularly the NSO, a modernization agenda must focus Effective management of the NSS to meet emerging on how to build a stronger and more effective foundation for data needs is critical. The NSS is a system of complex the INDS. organizations. Modern management strategies should be put in place, including an organizational structure that This requires renewed attention to the enabling environment allows flexibility in deploying resources. An NSO with a rigid for statistics, the business processes by which statistics are organizational structure may face difficulties meeting new produced and disseminated, and how information flows through data demands that require collaboration across different the system and to the end user. professional workstreams. As the NSS increases its output to meet new demands, quality assurance mechanisms A modernization agenda is not exclusively for countries at are required to ensure the highest quality possible. Quality the upper end of the income spectrum. NSOs in low-income helps build trust in outputs. Additional organizational countries and FCS also have opportunities to modernize measures to improve quality and responsiveness could THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 14 include an appropriate data revision policy, a metadata NSOs managed to adjust and adapt, while others failed. policy, and an effective data dissemination platform. Adding value also implies strengthening the capacity of data users to use data in planning and decision-making. 3. Technology: Modernize statistical processes with This could be done by scaling up the World Bank’s data new capabilities and infrastructure literacy programs. Significant productivity gains can only be achieved with There is a need for a new national data modernization modern statistical production processes utilizing new strategy. capabilities and infrastructure. Innovative data capture methodologies have been implemented in many statistical The NSDS has been the main instrument for developing offices. The use of such methodologies will need to be countries to organize and present their vision to national and broadened. Data analytic technology, including geospatial international stakeholders. The NSDS has been a successful applications, is also gaining momentum. Taking advantage mechanism for mobilizing support for development activities. of IT advancements in data capture and analytics implies With the radically changing operating environment for official significant investments in IT infrastructure capabilities, statistics producers in recent years, it is time to update the NSDS from deploying such techniques to training staff to toward a new national data modernization strategy. The next use them. generation of statistical strategies must focus on addressing the challenges and implementing the strategic directions proposed 4. Information: Improving quality and range of statistical in this note. The overall theme of “modernization through outputs integration” should take center stage in these new national data modernization strategies. Improving the quality and range of statistical outputs must be the aim of any modernization program. For an NSO A graduated approach for NSOs/NSSs at different stages and NSS to remain relevant, their outputs must evolve of maturity will be needed. to meet the changing needs of their users. They must respond to the changing data needs of the country. The The operating environment differs widely between countries at NSO and NSS produce important benchmark series on different levels of development. The opportunities and demands the basic socioeconomic conditions of the country, such described above do not apply equally to all countries. This is as CPI and GDP. These benchmark series are important especially true for low-income countries and FCS. Therefore, a and must be continued. However, the NSO and NSS must graduated approach might be needed where interventions are also move forward and address issues of major concerns. tailored to the context and development stage of the country. Some countries have initiated “Pathfinder” projects to Appendix A illustrates what each of these strategic agendas produce data on emerging issues. Diverging responses could imply for countries at different levels of development. to the COVID pandemic is a good example of how some THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 15 >>> Adapting the World Bank to Deliver Innovative and Integrated Programs of Support to Clients Integrate evidence-based policy making and statistics into The World Bank’s country engagements start upstream the World Bank’s support for national data agendas. with a systematic country diagnostic (SCD), which informs the medium-term Country Partnership Framework (CPF). To successfully support modernization of statistics, the World The SCD includes a brief diagnostic of data gaps in key Bank will need to adapt its traditional approaches to statistical areas necessary for the country to adopt evidence-based capacity building. Seven recommendations are proposed development policies and monitor its development goals. under four headings: (1) Country Engagement Models, (2) The diagnostic pays particular attention to data that are Knowledge and Advisory Agenda, (3) Instruments and Funding relevant for monitoring of development goals related to Mechanisms, and (4) World Bank Collaboration. These the World Bank Group’s twin goals and the Sustainable recommendations are aimed at enabling the World Bank to Development Goals (SDGs). The data gap assessment effectively support countries in pursuit of a digital modernization derived from the SCD could be complemented by an agenda for statistics under the four strategic pivots described in assessment of the capabilities of the NSO and NSS to the previous section. produce high-quality statistical products. This capacity assessment could in turn form the basis for future 1. Country Engagement Model: New data chapters in statistical support engagements under the CPF. SCDs and CPFs Recommendation 1: Expand the SCD data gap assessment to include assessment of data system governance architecture, quality, and capabilities using frameworks such as SPI, ODIN, or UN NQAF (if available). THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 16 2. Knowledge and Advisory Agenda INDS. Particular attention is needed on issues related to data access, privacy and protection, and updating and The World Bank has a wealth of experience in key aspects alignment of statistical legislation with new data protection of the national statistical system, especially in areas such regulation in countries. as household surveys, welfare monitoring, computer- assisted interview technologies, digital data repositories, The World Bank is already engaged in international dissemination platforms, and data literacy. In recent years, dialogue in forums such as the UN World Data Forum, the World Bank has also built capabilities related to data the High-Level Group for Partnership, Coordination integration and geospatial techniques. The World Bank and Capacity-Building for Statistics (HLG-PCCB), the also has expertise in public sector reforms and digital High-Level Group for the Modernization of Official transformation. However, the knowledge base needs Statistics (HLG-MOS), and the Conference of European to be expanded around the intersection of public sector Statisticians (CES) as well as in UN initiatives such as reform, digitalization, and the data agenda, and especially the Collaborative on Administrative Data. To be effective, modernization of statistical systems, to enable the World this knowledge must be applied to operations; therefore, Bank to effectively advise clients on how to modernize the alignment between the international work and the in- and reform the NSS and integrate it into the broader country dialogue should be strengthened. Recommendation 2 : Strengthen the World Bank’s knowledge base with successful examples of modernization of NSSs. Recommendation 3 : Strengthen alignment between international work on statistical reform and modernization as agreed under CTGAP and country engagements. Recommendation 4 : Support countries in designing national data modernization strategies (next-generation NSDS). 3. Instruments: From standalone Investment Project Financing (IPFs) to programmatic approaches (P4Rs, DPF) The most used instrument for World Bank STATCAP projects has been Investment Project Financing (IPF), though Program-for- Results operations (P4R) have also been tried with success, for instance in Kenya (P149718). In rare instances, Development Policy Financing (DPF) has been used; for example, the 2010 Statistical Strengthening Loan to India supported institutional and policy-based reform by the government to strengthen state statistical systems within a national policy framework. In other instances, DPFs have included specific prior actions related to data access and data dissemination, as in the 2015 Enhancing Fiscal Capacity Development Policy Loan for Colombia. The modernization agenda requires countries to undertake significant reforms. In many cases, the statistical acts should be updated to provide better access to administrative data sources and registers, and to update and align statistical confidentiality rules with new data protection legislation. Countries also need new policies and institutional arrangements to improve coordination across government departments, ministries, and agencies. These types of reforms can be most effectively supported through development policy operations. THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 17 Recommendation 5 : Attract funding from donors and expand use of instruments appropriate for programmatic engagements and encourage the use of statistics. Recommendation 6 : Build a set of policy actions that are necessary for statistical modernization into DPF. Bank Collaboration: Complementing STATCAP projects These initiatives have been instrumental in bringing much with cross–Global Practice collaboration on programs to needed advice and financing to support clients in building the support data ecosystem development enabling environment for digital government, particularly in areas such as digital infrastructure, digital ID, digital government National data agendas are by nature multisectoral, involving services, and core systems such as integrated financial many ministries, departments, and agencies. To effectively management information systems, public procurement, and support clients, the World Bank must bring a diverse and flexible taxation. However, more needs to be done to integrate the package of knowledge and financing options. Several cross– public data agenda, and in particular official statistics, into digital Global Practice initiatives have been launched in recent years transformation initiatives. Integration with the INDS is critical to support countries in their digital transformation journeys for the continued relevance of the NSS, and in the same vein under banners such as GovTech, Identification for Development the World Bank must integrate support for statistical systems (ID4D), and Digital Development Partnership (DDP), and and policy making into the financing and advisory on digital several regional digital economy initiatives. transformation offered to clients Recommendation 7 : Build statistical modernization into public sector reform and government digital transformation programs where possible. THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 18 >>> Notes 1. IDA, “IDA19: Special Theme: Governance and Institutions” (Washington, DC: World Bank, 2019), https://documents1. worldbank.org/curated/en/696731563778743629/pdf/IDA19-Second-Replenishment-Meeting-Special-Theme-Governance- and-Institutions.pdf. 2. Working at national and regional levels, the D4P package includes the production of a core set of economic, social, and sustainability statistics essential for monitoring and evaluating public policies and programs. The D4P package covers eight core statistical operations plus two complementary data systems: (1) household surveys, (2) labor force surveys, (3) population census, (4) firm-level surveys, (5) establishment census, (6) agricultural data, (7) price data, and (8) administrative data. The complementary data systems are (9) the system of national accounts and (10) big data. 3. Independent Evaluation Group, Marrakech Action Plan for Statistics, Partnership in Statistics for Development in the 21st Century, and Trust Fund for Statistical Capacity Building, Global Program Review, Volume 5, Issue 3 (Washington, DC: World Bank, 2011). 4. Independent Evaluation Group, Data for Development: An Evaluation of World Bank Support for Data and Statistical Capacity (Washington, DC: World Bank, 2018). 5. Statistical Performance Indicators (database), World Bank, Washington, DC (accessed January 2021), https://www.worldbank. org/en/programs/statistical-performance-indicators. 6. Open Data Watch, ODIN: Open Data Inventory 2020/21 Annual Report, https://odin.opendatawatch.com/Report/ annualReport2020#sec4. 7. United Nations and World Bank, “Monitoring the State of Statistical Operations under the COVID-19 Pandemic” (June 2020). 8. “Enter Third-Wave Economics,” The Economist, October 23, 2021, https://www.economist.com/briefing/2021/10/23/enter- third-wave-economics. 9. Charles Bean, Independent Review of UK Economic Statistics (UK Government, 2016), https://www.gov.uk/government/ publications/independent-review-of-uk-economic-statistics-final-report. 10. United Nations, PARIS21, and World Bank, “Cape Town Global Action Plan Implementation Review: Survey of NSOs,” preliminary results (October 2021). THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 19 Simone D. McCourtie / World Bank >>> Appendix A: Strategic Agendas for Countries at Different Levels of Development Illustrative strategic directions for NSO/NSS at different levels of development Modernization pivots Basic Medium Advanced Strengthen the Generate demand. The Respond to growing need Reposition the NSO for governance architecture national statistical office for statistical information. real-time monitoring and to support national (NSO) should engage with Ensure official statistics knowledge generation. statistical system (NSS) key ministries such as the respond to broader national The NSO deepens and and integrated national finance ministry and central policy discussions, research, broadens collaboration with data system (INDS) bank to ensure statistical and public discourse as well government stakeholders, integration production responds to key as private sector needs. academia, media, policy needs. and associations. Include policies and Expand legal mandate. programs to strengthen the Establish legal mandate. As the NSS expands Expand legal authority coordination of the NSS The NSO must ensure and new opportunities to access and use and manage relations with data collection is for statistical production data (including “big all stakeholders. backed by an adequate become available, the legal data”) maintained by legal mandate, which mandate should be updated private corporations safeguards confidentiality to strengthen coordination and nongovernmental of respondents. and enable access to organizations, including for administrative data for testing and experimentation. Strengthen NSS statistical purposes. coordination. The NSO Data stewardship. should identify key statistics NSO to assume new Establish the NSO as producers at central role in INDS. As the data government “data steward,” government level and ecosystem evolves, the leading and advising other establish a coordination NSO must assume a new government agencies mechanism that holds role in the national data on data generation statistics producers to infrastructure as producer and dissemination. common national statistical of key data sets, custodian standards, identifies of statistical standards, and Assume leadership role stakeholder needs, and user of government data in international statistical can be used to mobilize for statistical production. community. Contribute THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 21 Table continued Illustrative strategic directions for NSO/NSS at different levels of development Modernization pivots Basic Medium Advanced government and donor funds The NSO should actively to development of news for statistics. participate in national statistical standards and consultations on data- measurements and International engagement. related policies and engage in technical The NSO begins legislation, including data assistance projects. engagement with the protection legislation. international statistical community on standards, Contribute to international methods, and reporting statistical agenda. requirements and The NSO can begin to explores opportunities for contribute to international development assistance. discussions on standards and methods and emerging Strategic planning and statistical domains. funding. The NSO should identify a set of strategic Increase domestic funding medium-term objectives for statistics. Ensure and develop a work plan regular allocation of fiscal that includes financing from resources to produce government and donor most official statistics. sources as well as technical If international assistance assistance requirements. is received, donors’ funds and domestic resources must be integrated through a common expenditure framework. Introduce effective Quality commitment. Establish quality Continuous quality management principles to Ensure professional assurance framework improvement. Regular improve data quality independence of the across the NSS. Establish quality monitoring and head of statistics and a quality assurance body follow-up to improve A modern institutional announce a clear (e.g., Statistics Council) statistical products and environment conducive to government commitment with overall oversight of processes. Institute planning the production of quality to quality statistics. the quality of the national and management principles statistics must ensure the statistical system. aimed at the optimal use professional independence, Apply quality principles. of available resources and impartiality and objectivity, The NSO develops and Institutionalize quality conduct periodic external transparency, confidentiality, implements institutional management. Establish a reviews of statistical quality commitment, and mechanisms to ensure body responsible for quality products and processes. adequacy of resources for quality in the statistical management in the NSO statistics producers. production process, such as that regularly monitors and NSO transition to a pre-announced program of publishes indicators of matrix organization with statistical publications, data statistical quality, including specialized departments for revision policy, etc. punctuality of release, each step of the statistical frequency of revisions and production process. Build capabilities for corrections, etc. The NSO quality statistics. Recruit comments publicly on THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 22 Table continued Illustrative strategic directions for NSO/NSS at different levels of development Modernization pivots Basic Medium Advanced professional statisticians statistical issues, misuse based on credentials and of statistics. offer attractive career path. Develop and implement Deepen organizational a code of conduct for capabilities. The NSO government statistician. establishes specialized divisions for standards and methods, fieldwork, etc., and initiates processes mapping to build an inventory of processes (using, e.g., the Generic Statistical Business Process Model). Expand skills and capabilities. Staff contingent should shift toward more IT and domain experts and expanding geospatial capabilities. Deepen cooperation with scientific community. Expand capabilities and Apply scientific principles. Transition to multimode Integrate and automate modernize technology The NSO establishes methods and integrated production systems. platforms and applications and regularly updates survey platform. When Data collection fully digital. sampling frames. data availability allows, the Respondents offered Modern statistical NSO should initiate the multimode response options processes must comply with Document methods production of statistical base (web, phone, mail, etc.). international standards, and standards. Develop registers on businesses Production processes guidelines, and good a basic compendium and people to enable the and quality checks fully practices. Statistical of standards and integration of administrative automated. Data warehouse agencies should constantly definitions and document data in the statistical is in place for all data strive for innovation and production processes and production process. storage, processing, optimization of the statistical quality assessments. and dissemination. production process. Implement database Invest in technology. technology. The NSO Institutionalize Invest in IT capacity for data should invest in a central experimental statistics. storage and processing data warehouse based on Expansion of data science and introduce computer- common sets of standards, capabilities to measure new assisted data collection classifications, and phenomena faster and more where possible. metadata that can serve as reliably, such as the digital a central repository for key economy, natural capital time-series data sets as well accounting, high-frequency as microdata. indicators, etc. THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 23 Table continued Illustrative strategic directions for NSO/NSS at different levels of development Modernization pivots Basic Medium Advanced Launch innovation lab. Launch innovation laboratory to experiment with new data sources. Improve quality and range Develop and implement Expand range of statistical Focus on knowledge of statistical outputs core statistical program. products in consultation generation. The NSO The NSO should develop a with users. Increased should launch “Pathfinder” Modern statistics must core program of household frequency and granularity of projects. serve the needs of not only and establishment- statistical products. Solicit national governments but based survey designed in regular user feedback for Advanced dissemination. also research institutions, consultation with key users continuous improvements Tailored dissemination to key businesses, the public, (e.g., the World Bank’s D4P to products and services constituencies. Multiplatform and the international Program). Key data sets offered. dissemination. Extensive community. Output quality such as price statistics and metadata repositories. is measured by the extent basic sector and industry Enhance digital data to which the statistics are accounts in the system of dissemination platform. Fully comply with relevant, accurate and national accounts should Add more functionality, open international reporting reliable, timely and punctual, be produced with regular data principles and access to requirements. Subscription readily accessible by and revision and rebasing. metadata repository. to SDDS+. clear to users, and coherent and comparable across Devise dissemination Expand international geographical regions policy and strategy to reporting. Close SDG and over time. inform users about terms data gaps, and domain and conditions for data specific frameworks. access. Basic metadata Graduate to Specialized should accompany Data Dissemination every release. Standards (SDDS). Build dissemination platforms. Web-based dissemination of statistical publications, microdata, and time-series indicators, e.g., Sustainable Development Goal (SDG) indicator database. Invest in data literacy. Roll out data literacy campaigns to equip key user constituencies such as policy makers, parliamentarians, associations, and media with the tools and skills to use data. THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 24 Table continued Illustrative strategic directions for NSO/NSS at different levels of development Modernization pivots Basic Medium Advanced Initiate international reporting. Begin reporting on SDGs, participation in International Comparison Program, and subscription to international data dissemination standards such as the General Data Dissemination Standards (GDDS). THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 25 THE NEXT GENERATION OF STATISTICAL CAPACITY BUILDING <<< 26