Toward a new, collaborative global financing architecture for fragile, low, and middle-income countries’ data priorities
Abstract
The COVID-19 pandemic has occurred against a sobering global backdrop: national data collection programs and the production of core economic statistics have long been under-funded (by national government as well as the international development community), and data gaps are still significant. The pandemic has highlighted the importance of NSOs and the urgent need to strengthen and modernize core data collection programs as the backbone of national data systems. As the severity of this problem and its damaging implications are becoming more salient, members of the international development and national statistics communities have joined forces in an effort to address it. A collective, high-level effort is now being mobilized by senior leadership of the World Bank and the United Nations, in close collaboration with the Global Partnership for Sustainable Development Data, to join forces to increase global investments in fragile, low-and-middle-income countries’ data priorities and to better put data to work for green, resilient, inclusive development. Specifically, two new complementary funds have recently been launched by the World Bank and United Nations to support countries’ data systems, data capital, and risk analytics in a coordinated way: the World Bank-hosted Global Data Facility and the UN-hosted Complex Risk Analytics Fund (CRAF’d).
1.Introduction
This is a time of unprecedented crises – including the continuing COVID-19 pandemic, debt sustainability issues, climate change, demographic pressures, fragility, conflict, and refugee crises. High quality, timely, and comprehensive data are an essential building block to meet and overcome these crises, so that governments can formulate policy responses that are evidence-based and monitor overall progress towards the Sustainable Development Goals (SDGs). Country level data systems, however, are not adequately prepared to meet the challenges they face:
• Massive data gaps are preventing countries from monitoring progress on the SDGs. There are only 6 (of 17) SDGs for which more than two-thirds of countries have data to report on progress [1].
• A UN and World Bank survey suggests that in two thirds of low- and lower-middle-income countries, statistical agencies lack sufficient resources to meet the demands for data caused by the COVID-19 pandemic [2].
• Only one in six countries has sufficient data to report on SDG Goal 13: Climate Action, and the data that does exist is out of date – on average the latest data available is from 2015 [1].
• Two thirds of countries in Africa have been forced to postpone a planned census, further weakening data systems.
• Current investment levels for data and statistics are less than half of what is needed. Investments in data from external sources has remained static for nearly 10 years, and suffer from fragmentation and duplication of efforts. The funding gap for statistics per year is estimated to be 700 million USD – more than current available funding of 600 million USD [3].
• 274 million people require urgent international emergency support. Driven by climate change, conflict, and global crises, this number is at a record high. Yet only 51% of data for major emergencies is complete, and as a result humanitarian, development, and peace operations are less effective than they could be [4].
The pandemic has increased the need for more and smarter financing for data and statistics, by placing an increased burden for data on national statistical systems, while simultaneously squeezing domestic and foreign aid budgets alike and making data collection more difficult and expensive. A global consensus is emerging that more coordination and investment in data is needed. One in three Development Assistance Committee (DAC) members believe that investment in data is insufficient to make National Statistical Systems fit to meet Agenda 2030 [5], and four out of five DAC members believe that there is a need for more systematic co-ordination between donor and National Statistical Offices in partner countries [6]. In 2021, the UN World Data Forum adopted the Bern Data Compact for the Decade of Action on the Sustainable Development Goals, which calls for more and better investment in countries’ data systems, data capacity, and data capital to drive forward the implementation of the Cape Town Global Action Plan and the 2030 Agenda [6].
2.Supporting the realization of the data revolution
In the 2014 report of The United Nations Secretary-General’s Independent Expert Advisory Group (IEAG) on a Data Revolution for Sustainable Development, the IEAG elaborated on why humanity has crossed the threshold of the “Data Revolution” [7]. The report points to the rapid acceleration and improvement in human capacity to collect, manage, combine, analyze, and share a spectrum of data thanks to exponential improvements in technology and analytical power in recent years, and as a continuing phenomenon each day, coupled with a robust step-change across government, the private sector, and civil society in the recognition of the role of data for a range of social and economic benefits [7].
The clear implication is that as the world evolves, so too must the role of the national statistics office (NSO) and the way in which it undertakes statistical processes. Where sufficient capacity exists – together with requisite levels of political will, a permissive legal and regulatory enabling environment, and infrastructure permitting – NSOs are uniquely positioned to assume a central role to shepherd the data revolution. Specifically, while NSOs are joining an increasing plurality of data producers they nevertheless occupy a rarefied position in the data ecosystem; they can encourage and embrace innovations, modernization, and integration of new system-wide approaches to statistical processes. Despite the many disruptions caused by the pandemic, NSOs are increasingly taking up the mantle of responding to new data needs and demands. The UN-DESA/World Bank high-frequency phone surveys found that a majority of the NSOs polled are implementing surveys on COVID-19 and its impacts are working to establish national platforms to address the data needs of their government and citizens, and are increasingly relying on alternative data collection modes and data sources, including phone and online surveys, administrative data, remote sensing, and satellite imagery.
3.Data and statistics are subject to chronic underfinancing
The pandemic has occurred against a sobering global backdrop: national data collection programs and the production of core economic statistics have long been under-funded (by national government as well as the international development community), and data gaps are still significant [8]. The pandemic has highlighted the importance of NSOs and the urgent need to strengthen and modernize core data collection programs as the backbone of national data systems.
Overall donor financing for data collection and statistical capacity building in developing countries has long been insufficient to meet countries’ needs. The non-governmental Organization PARIS21 has found that the total share of Official Development Assistance (ODA) dedicated to data/statistics has stagnated at 0.3% (or approximately USD $600 million) per year, despite record ODA highs in recent years. The problem is that this amount is not enough to provide holistic support to national statistical systems low- and middle-income countries by a substantial margin. PARIS21 calculates the severity of this financing shortfall as follows:
• The cost estimate for holistic support for data/statistical systems is approximately USD $5.6 billion per year between 2019 to 2030 for 75 low and low-middle-Income and 69 upper middle-income countries, of which an estimated USD 4.3 billion (77%) of costs would be covered by domestic resources [3].
• Given current levels of ODA, this leaves a financing gap of USD 1.3 billion (23%) per year for other financing, such as external assistance from multilateral and bilaterals, as well other domestic sources [3].
As a result, during the 10-year period between 2002 and 2011, as many as 57 countries had zero or only one poverty estimate [9]. Population censuses, which should be conducted every ten years and are a critical source of disaggregated data for monitoring progress of development goals, are outdated in many LICs. In 2018 only 70% of them had conducted a population census since 2009 compared to more than 90% of MICs [1]. The COVID-19 pandemic has made this issue particularly acute, striking many countries in the middle of their 2020-round of census preparation activities. Delays, interruptions, and re-allocation of funds to other activities may compromise the quality or result in the cancellation of census projects. LICs are also lagging in the production of economic statistics. “Estimates of gross domestic product (GDP) and, more generally, the System of National Accounts, are important for many SDG indicators: about 10% require information on GDP, gross national income or sectoral value added – typically as the denominator. Yet less than half of all developing countries produce monthly data on industrial production, a key input into the estimation of GDP. And despite some progress, with many countries rebasing their GDP estimates after 2010, estimates in developing countries are often produced with outdated base years, a problem that is also more pronounced in low-income countries” [11].
More and better support for data and statistics systems can enable NSOs to evolve their role and functions, not just with respect to the types of data they collect, analyze, and share, but to include functions increasingly in demand from the growing multiplicity of stakeholders across the data production and use (supply-side and demand-side) continuum, including civil society, academic institutions, the private sector, government, media, and international organizations. New or additional roles and responsibilities for NSOs might run the gamut from broadening data collection approaches to include hitherto nontraditional sources of data, to raising the bar for quality control on a range of foundational and frontier data, to becoming “infomediaries” themselves by assuming a stronger coordination and dissemination role across an expanding constellation of data producers [12]. Innovative NSO models and functions in both the global north (for example, New Zealand) and south (for example, Mexico) may serve as a blueprint for this evolution, though support from NSO peers and expert development organizations, together with new modes of collaboration and partnership mechanisms, are needed to systematize such transformations in developing country contexts.
4.Financing the data revolution
This under-investment in statistical systems has caused significant gaps in high-quality data in low- and middle-income countries around the world. The gaps in development data threaten the effectiveness of the full spectrum of social and economic development initiatives, from human capital investments to digital economic reforms to the achievement of most of the Sustainable Development Goals (SDGs). Moreover, it is impossible to fathom the country-level policy failures, ineffective service delivery, allocative inefficiencies, and the extent to which poor and historically underserved populations have been further marginalized or driven deeper into poverty occasioned by these data gaps.
As the severity of this problem and its damaging implications are becoming more salient, members of the international development and national statistics communities have joined forces in an effort to address it. Their efforts have taken several forms in recent years and have generated calls for action, including the urgent need for data and statistics to support the achievement of the Sustainable Development Goals (SDGs). For example in the last few years, the UN’s High-level Group for Partnership, Coordination and Capacity-Building for statistics for the 2030 Agenda for Sustainable Development (which provides the strategic leadership for the UN Statistical Commission’s SDG implementation process with respect to statistical capacity building for the full implementation of the 2030 agenda) as well as chief statisticians of national statistical agencies and data experts from around the world launched the Cape Town Global Action Plan for Sustainable Development Data, which championed both a country-led investment blueprint for the development of statistics in 2016 [13] as well as a call for better global coordination of development financing – together with the potential development of a new financing model – for data to enable SDG implementation in 2018 [14]. Likewise in 2018, the UN-World Bank Group Strategic Partnership Framework for the 2030 Agenda launched a series of joint institutional commitments, including a core focus on “realizing the data revolution” through more concerted effort to fill pervasive data gaps across countries and transform this data and its use into transformational development support where it is most needed [15].
At the conclusion of the 2021 United Nations World Data Forum – hosted in Bern by the Government of Switzerland – country, bilateral and multilateral Forum participants adopted the Bern Data Compact for the Decade of Action on the Sustainable Development Goals, which calls for more and better investment in countries’ data systems, data capacity, and data capital to drive forward the implementation of the Cape Town Global Action Plan and the 2030 Agenda [6].
These and other similar calls for action have helped to catalyze significant global commitments for data and statistics, though despite increasing international and domestic investments, large gaps remain. Current investment levels for data and statistics are less than half of what is needed to deliver on the SDGs and investments in data from external sources has remained static for more than seven years [16], suffering from fragmentation and duplication of effort [17].
4.1Toward a coordinated global financing architecture for data and statistics
A coordinated global financing architecture is presently emerging to help unlock the potential of data for development and risk analysis at scale. New commitments featuring stronger international cooperation and leadership within low- and middle-income countries to support data and statistics are materializing, though additional key action is needed in the immediate term to maximize opportunities across regions to achieve the SDGs. Heartening progress is emerging where donor resources are intentionally pooled and used to leverage significant dedicated resources for sectoral development, such as World Bank IDA or IBRD resources, and which can collectively unlock an increase in (and sustained investment of) domestic resources for data and statistics.
A collective, high-level effort is now being mobilized by senior leadership of the World Bank and the United Nations, in close collaboration with country partners and in partnership with the Global Partnership for Sustainable Development Data [18], to join forces to increase global investments in fragile, low-and-middle-income countries’ data priorities and to better put data to work for green, resilient, inclusive development. Specifically, two new complementary funds have recently been launched by the World Bank and United Nations to support countries’ data systems, data capital, and risk analytics in a coordinated way: the World Bank-hosted Global Data Facility [19] and the UN-hosted Complex Risk Analytics Fund (CRAF’d).
4.2The Global Data Facility
The Global Data Facility is the new, World Bank-hosted fund to support data and statistics priorities at the global, regional, national, and community levels. It is designed to enable exponential improvements of and strengthened human capacity for data collection, data management, data governance, data analysis, data sharing, and data use and reuse for transformational social and economic development fragile, low- and middle-income countries.
The Global Data Facility has been designed to help enable the implementation of the Cape Town Global Action Plan. It will support investments in both the fundamentals and at the frontier of data and statistics. It is particularly designed to support the provision of expert advice and technical assistance to enable low- and middle-income countries to realize the benefits of – and safeguard against risks inherent to – strengthened data systems and data capital and related innovations. The sum total of these efforts is intended to support and enable the achievement of integrated national data systems, as described in detail in the 2021 World Development Report: Data for Better Lives [2]. This includes key support to modernize data systems and tap into a range of new data sources for better decision-making, improved efficiency, and strengthened information integrity at scale.
In launching the Global Data Facility, the World Bank was responding to a request to do so by the UN Statistical Commission’s High-Level Group for Partnership, Coordination and Capacity Building for Statistics for the 2030 Agenda for Sustainable Development (HLG-PCCB), to establish an innovative and responsive funding mechanism for data and statistical systems around the world. The Global Data Facility was thus designed to serve as a global coordination mechanism for a spectrum of partners, practitioners, and country clients to join forces in support of the global data revolution. Through the Global Data Facility, countries can work with development partners to invest in the data, data systems, and data capital which collectively underpin progress across all the SDGs, and which can increase the efficiency of investments in the full spectrum of social, economic, and sustainable development priorities.
The intention of the Global Data Facility is not to resolve all countries’ data systems and data capital constraints alone. Rather, it has been designed to catalyze and incentivize significant additional financing to tackle these realities, including under the $93 billion replenishment package of the International Development Association (IDA20), which will help the world’s 74 poorest countries respond to the COVID-19 crisis and build a greener, more resilient, and inclusive future [21]. The Global Data Facility will also seek to incentivize and enable long-term support for data priorities by catalyzing domestic investments in data and statistical systems, data infrastructure, data institutions, and technical capacity across data suppliers and data users. For example, the Facility can enable results-based financing and fund-matching with complementary resources from partners. Facility resources could also be used to pay down interest on a World Bank loan for data and data systems transformations (by increasing concessionality and softening IBRD/IDA terms). GDF resources could also support “first mile” collaborative landscape assessments, diagnostics, and reform or strengthen strategies which could also pave the way for a package of IBRD/IDA support for holistic, years-long collaborative implementation and country ownership. The Facility will additionally seek out opportunities for complementary financing and twinned technical assistance from partners and technical centers of excellence around the world to further coordinate, maximize efficiencies, and help scale priority data and statistics work across regions.
The Global Data Facility will thus ensure flexible and adaptive, country-led approaches which allow for a variety of entry points in countries and different levels of dialogue and engagement with country partners and practitioners supporting data and statistics priorities. The Facility will moreover build on and apply lessons from the World Bank’s decades of experience as a trusted fiduciary and in the management of global trust funds.
4.3Complex Risk Analytics Fund
The UN’s Complex Risk Analytics Fund (CRAF’d) [22] is designed to support more coherence and alignment of financing for data in fragile and crises settings, particularly for crisis anticipation, prevention, and response. CRAF’d is designed to help secure critical data and insights for faster, more targeted, and dignified support to lives and livelihoods in fragile contexts and in crisis situations. It will work to build datasets, close data gaps, develop analytical capacity, and connect silos to anticipate, prevent, and respond to humanitarian crises [23].
CRAF’d is the result of a multilateral partnership, which was inspired by the UN Secretary-General’s Data Strategy [24], and benefitted from collaborative design and input from across partners in Germany, the Netherlands, the United States, and the United Nations family, as well as other partners across the globe and thus stands as an effective example of multilateralism as envisioned in the UN’s Our Common Agenda report [25].
With sustainable and scalable financing, CRAF’d will seek to close gaps in real-time, high-resolution data on complex risks; support predictive models, as well as methods for the analysis of social media, geospatial, other data for crisis anticipation, prevention, and response; support for standard-setting for crisis data, including for responsible data use and interoperability at scale; and offer support for an open ecosystem to expand shared capabilities to access and use crisis data to prevent escalation and help facilitate rapid humanitarian response.
4.4The value proposition of this new World Bank-United Nations partnership on data financing
A key benefit of this new partnership between the World Bank and UN is to ensure complementarity in the design and functions of the Global Data Facility (GDF) and the Complex Risk Analytics Fund (CRAF’d). As a result, both financing mechanisms can leverage the respective comparative advantage of each institution to cover the entire landscape of data-driven country support and systems transformation – from crisis response and humanitarian interventions to scaling up social, economic, and sustainable development. This also enables synergy through new forms of value-creation for fragile, low-income, and middle-income countries.
Both funding mechanisms are being closely coordinated to ensure efficiencies, including in collaboration with the broader UN family, and they are working to align support as appropriate to enable economies of scale. The ambition of this new partnership is to open the door for more development partners to join this collective, collaborative effort, and to more efficiently and effectively align, allocate, and trigger greater levels of resources and technical support for countries’ data priorities.
Importantly, the two funds will be informed by, connected to, and build upon key work of partners. This includes initiatives such as the Global Partnership for Effective Development Cooperation and its Principles for Data and Statistics, the Bern Network Clearinghouse for Development Data, a new multi-stakeholder initiative supported by the Bern Network, designed to help increase transparency and efficiency of international financial support for data activities [26], and other efforts designed to help enable the achievement of SDG 17.18 (“enhance capacity-building support to developing countries … to increase significantly the availability of high-quality, timely and reliable data …”) [27].
4.5Next steps
This new data financing partnership between the World Bank and UN is working to raise at least $500 million over ten years to drive investments in a greener, better, and safer future with stronger data through the Global Data Facility and CRAF’d. It will also work to catalyze significant additional resources from multilateral and bilateral partners (including World Bank IDA/IBRD loans) and trigger more domestic financing and other investment to fill the world’s most critical data gaps.
Joining forces presents development partners with a unique opportunity to not only be at the forefront of a key initiative of global significance, but also improve allocative efficiency and scale the impact of existing resources for countries’ data priorities. For example, Global Data Facility resources can be allocated directly to country governments to deliver national or subnational priorities. They can be allocated via grants or rolling allocations to global centers of excellence to augment or support countries’ integrated national data systems transformations, and more. There is likewise potential, for example, to design Global Data Facility window allocations to address targeted regional or thematic priorities, to support global initiatives, and/or to enable experimentation or prototyping to achieve proof of concept and to seek to catalyze complementary resources to scale solutions.
The World Bank-United Nations partnership launched in April 2022 with a ministerial-level roundtable co-hosted by World Bank and United Nations leadership at the World Bank’s 2022 Spring Meetings, and is convening high-level events to collaborate with country partners, identify priorities, and enshrine new commitments for support, including at the UN General Assembly in September 2022. This new data financing architecture is designed to enable a step-change in collaborative support with and for low- and-middle-income countries, to help deliver on data systems and data capital needs and priorities.
As new opportunities and joint efforts continue to come into focus, all partners must recognize that country ownership and country leadership must remain at the center of these efforts and of financial support for data and statistics. This is because, in no uncertain terms, country ownership is the delta which will ultimately condition the effectiveness of these efforts [28]. To truly enable the achievement of sustainable results and establish a runway for long-term, effective financing for data and statistics priorities, the extent to which country leaders take up the mantle and accountability to support and implement the data revolution is the singular test of this collaborative enterprise. This includes, inter alia, bringing sufficient domestic spending to bear to sustain and expand on any progress achieved though Global Data Facility or CRAF’d support, such as harnessing this momentum toward the development of truly whole-of-government data systems and systemic support for data capital needs and broader data literacy and data use at the national and subnational levels. For these reasons and more, country ownership and country leadership will continue to serve as the lodestar for this effort and will help to ensure that the World Bank, United Nations, and the full range of participating development partners can continuously work to align and collaborate with low- and middle income country partners to deliver results on data and statistics priorities.
5.Conclusion
Countries around the world are seeing rapid advances in artificial intelligence, disruptive technologies, and digital economies, which are occurring alongside shocks and mega-trends like the COVID-19 pandemic, climate change, globalization, urbanization, and the rise of social media. People, objects, and connections are actively and passively producing data at previously unimaginable rates. The global increase in digital connectivity and exponential advances in data analytics capabilities across regions have coalesced to become a powerful engine for change. This combination of forces is rapidly transforming societies across the globe. In addition to the potential benefits of technological progress, there are also the specters of structural job loss, income inequality, atomizing of social consciousness, and loss of privacy – all factors with profound consequences for social and economic development across countries. Accompanying these trends is an increasing recognition of the need for new paradigmatic thinking about the relationships among governments, civil society, the private sector, and citizens, and the role of data, which underpins these relationships. Set against this backdrop, national data systems across low- and middle-income countries struggle to generate the data and analysis needed to inform and monitor development policies and programs, and to address crisis situations that require agility and responsiveness they often lack.
Strengthening data systems and data capital must remain priorities for the development community. But this cannot be a simple continuation of past efforts. The demand for data has evolved in its volume, scope, nature and origins. This evolution calls for a regular supply of more disaggregated, timelier, cost-effective, and more operationally relevant data. It further calls for the consistent and widespread, responsible and fair use of data for social, economic, and sustainable development in low- and middle-income countries, by enabling actors in the national and international data systems while establishing appropriate safeguards.
Achievement of these priorities requires fundamental, rapid modernization and innovation in the production, dissemination and use of data in and by the World Bank’s client countries, especially in fragile and conflict-affected countries. The growing volume of available and still largely under-exploited data, and the democratization of new analytical tools and methods, are the ingredients that make this rapid modernization possible. New investments in data and statistics systems, capital, infrastructure, and use are urgently needed. Without a renewed, concerted and coordinated effort by the international community, the data divide between fragile, low-and-middle-income countries and high-income countries will only continue to increase The new data financing partnership led by the World Bank and UN through the Global Data Facility and CRAF’d, is working to enable this much-needed concerted and coordinated effort to scale up support for countries’ data and statistics priorities, and invite all interested partners to join forces with this effort.
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