Combating COVID-19: Data everywhere but not the kind we need

By Julia Schmidt, Policy Analyst, Archita Misra, Policy Analyst and Johannes Jütting, Executive Head, Partnership in Development for the 21st Century (PARIS21)


This blog is part of a series on tackling COVID-19 in developing countries. Visit the OECD dedicated page to access the OECD’s data, analysis and recommendations on the health, economic, financial and societal impacts of COVID-19 worldwide.



statistics-covid-19-shutterstoc-1688596069Earlier this year at the Munich Security Conference, World Health Organisation Director-General Tedros Adhanom Ghebreyesus said, “We’re not just fighting an epidemic; we’re fighting an infodemic”. He was referring to the excessive amount of information surrounding the COVID-19 pandemic. Data dashboards, aggregators and charts of all types have formed the basis of much of what we know about the pandemic, lending a veneer of legitimacy to often contradictory or competing claims. While it is true that on some levels we have never had so much data, it may not be the data we need for sustained policy response and recovery. This is especially true among least-developed countries, where looming data gaps, even in foundational statistics, persist and may seriously undermine the ability of governments to develop effective COVID-19 response and recovery measures. Continue reading

Counting the invisible: Three priorities for strengthening statistical capacities in the SDG era

By Johannes Jütting, Executive Head PARIS21, Rolando Avendano, Economist, Asian Development Bank and Manuel Kuhm, Research Support Officer (PARIS21)

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Better policies need better data. High-quality data and official statistics are vital for governments, civil society, the private sector and the public to make informed decisions, create effective polices, and establish good governance. Under the 2030 Agenda for Sustainable Development, data-driven policy making takes on even greater significance. For if we are to “leave no one behind”, we must first ensure that everyone is counted.

Yet today, more than 110 low and middle-income countries lack functional civil registration and vital statistics systems and under-record or omit vital events of specific populations. Those living in poverty are most likely to be excluded—the poorest 20% of the global population account for 55% of unregistered births. Only 37 countries have statistical legislation that complies with the United Nations (UN) Fundamental Principles of Official Statistics.

If we don’t even know who the poorest are, how can we ensure that they aren’t left behind?

At the same time, while a global Sustainable Development Goal (SDG) indicator framework is an essential part of Agenda 2030, it is putting pressure on national statistical systems. In addition to the demand of compiling 232 national-level indicators, the Agenda requires that data are disaggregated by income, sex and gender, geography, age and disability, far beyond current capacity in many developing countries. Continue reading

SDG data discussion: what next?

By Johannes Jütting, PARIS21 Secretariat Manager

After months of intense discussions, representatives from more than 190 national statistical offices agreed on a global monitoring framework for the 2030 Agenda and the Sustainable Development Goals (SDGs). The 17 goals and 169 targets of the framework will be complemented by 230 indicators. This is a huge achievement given the complex political and technical challenges that had to be solved to reach a consensus. Now, the United Nations Economic and Social Council and the United Nations General Assembly formally will endorse the framework.

Avoiding a stalemate with this finish line in sight and addressing the framework’s remaining blind spots require urgent attention. The two main points that still need to be addressed are: i) integrating the SDGs into national priorities and strengthening national statistical capacities for that process and ii) improving the indicator set.

Integrating SDGs into national priorities

The following table captures different reporting levels, organizations in the lead and the purpose of the reporting exercises:

SDG monitoring – roles and responsibilities

Global Regional and thematic National
Responsibility for SDG reporting UN Statistics Division based mainly on national data collected by international agencies Regional organizations, UN and other agencies harmonising SDG methodology for regional reporting National statistical systems and third-party providers supplying national and subnational data
Original data sources Country-level Country-level Country-level
Purpose Global monitoring focusing on world progress overall Regional and thematic monitoring focusing on relevant progress National monitoring focusing on national and subnational priorities

The relationship between UN technical agencies, such as WHO, UNICEF and FAO, and national governments in the production of statistics is complex. Much of the data we have currently on poverty, health, education or nutrition comes from large-scale international household surveys run by these agencies in countries. This is done in close collaboration with national statistical offices and often includes a capacity-building component that is very useful. However, involving agencies in the production of data can be problematic too as they have their own thematic agenda that might not align with national priorities or could even contradict those priorities. With the heavy SDG agenda, this risk increases substantially and could lead to a crowding out of national capacities.

Another equally important issue is the measurement exercise’s purpose. Do we focus all our attention on how best to do global monitoring? Or do we also focus urgently on producing national SDG data roadmaps that identify country-specific baselines, data needs and data filling plans for effective country-level actions? We should not forget that the data are supposed to help policy makers make evidence-based decisions and achieve impact. This happens primarily at national and subnational levels.

Improving the indicators

Even with general agreement on the indicator set, the real work remains. The consensus is clear that the indicators will need to be defined further over the coming months and years. Many indicators are yet to be supported by the required data or methodology. National statistical systems will face trouble with certain indicators or simply will lack the incentives to measure them at all. A good example is indicator 10.5.1 that measures the “financial soundness” of national policies: no government will be motivated to report on this aspect if the country is not doing well, especially given the possible impact on foreign direct investment decisions. Or take indicator 16.4.1 that asks for a country’s total value of inward and outward illicit financial flows. Illicit flows by their very nature are clandestine, making only vague estimates possible at best. Another blind spot is the current indicator on corruption: bribery is measured in the public sector whereas the private sector is not considered. Moreover, the indicator set ignores some important problems entirely. Obesity, for example, is not included but is a growing health problem in many middle-income countries, straining public services.

More technical work clearly is needed. But more importantly, the international community needs to provide the financial means to enable national statistical systems to do the job they are asked to do without undermining national priorities and taking into account their current capacity.

Where to go from here

The agenda needs to move now from the global to the national and finally to the local levels. Building partnerships among public institutions – agencies of the national statistical system – citizens and the private sector at the local level is critical. This hopefully will lead to better planning of conventional statistical operations and to building new models that involve citizens, businesses and nongovernmental organisations.

The conclusion is that achieving the SDGs will depend largely on strengthening national and local capacities in a creative synergy of data producers and users. Only then can we hope that policies will be able to reach those who live on the fringes of society. This is how we can leverage data effectively to fulfil the 2030 Agenda’s promise to “leave no one behind.’’

This blog also appeared on The Huffington Post. Click here to read it anew.


This article should not be reported as representing the official views of the OECD, the OECD Development Centre or of their member countries. The opinions expressed and arguments employed are those of the author.