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By the Numbers – How Donors Can Support a Demand-Led Post-2015 Data and Statistics Revolution

28-03-2014

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Do we need a ‘data revolution’ goal to create the right demand for a data and statistics revolution post-2015?

Recent calls for a ‘data revolution’ emphasise how in the dark we are on the social, economic and developmental status of developing countries, especially in Africa. Accurate, timely, relevant and available data and statistics in many cases simply don’t exist, particularly on households and individuals. With donors becoming increasingly concerned with measuring results, calls for more and better data are increasing.

But efforts to improve data are mostly donor-driven and given fluctuating aid levels, they’re rarely systematic, and relegated to technical discussions far-removed from what data should be for: good governance, transparency and accountability.

Devil in the Data

For most, this is a simple case of supply not meeting demand. The supply side being the low production, quality and availability of data, as a result of under-staffed and under-resourced statistics agencies mainly in Africa. The demand side is taken as read: national governments need statistics on all aspects of their societies in order to better design, implement and monitor the results of policies and programmes. Civil society organisations, academics, think tanks and donors clamour for more data for the same reason, and in order to advance their own work.

This is not a new problem, and the past five decades have seen significant efforts by donors in improving data and statistics across Africa. Global aid commitments to statistics reached US$ 2.3 bln in 2011-13 (approximately 1/5th of a per cent of total Official Development Assistance), and annual commitments to Africa fluctuate between US$ 100 and 200 mln for the past decade, mainly in grant funding.

With that aid, standards have been set, initiatives have been taken and manuals have been written. And yet, as debates since the publication of the UN High Level Panel report pick up, the demand for more and better data still mostly comes from the donor community.

Drive the Demand

Compared to Official Development Assistance (ODA) flows, governments in Africa continue to invest very few resources in national statistical offices, as Morten Jerven notes. They surely see the value of having more and better data and statistics. Still, in countries where resources are scarce, citizens want services and every investment boils down to a ‘chicken and egg’ parable, tough questions on financing better statistics have to be asked, such as:

  • Why invest in developing statistical capacity when consultants can dig up the relevant figures on an ad hoc basis using donor money? Or, indeed, why donors keep recruiting the continent’s best statisticians?
  • Why design your own methodologies for collecting comparable data in specific contexts when donors assess you on their quality standards?
  • Why produce timely, high-quality data when there is little money to be made from statistical products?
  • How can we be sure that better data will lead to better policy-making, and in what time frame?
  • Crucially, why put a figure on and make public the failings, faults and future fears of your government? Or, conversely, give donors a reason to reduce aid?

In the face of such pressures and questions, better statistics end up low on the list of public priorities for African countries. This is the real political economy of data demand and governance, which differs slightly from some donors’ description of the problem, and hopefully something the Data for African Development Working Group will unpack.

Admittedly, these questions are a bit cynical: many countries are implementing national strategies for improving their statistics systems under the PARIS21 initiative. Nevertheless, progress on implementing these strategies is slow, and the push is mainly coming from donors as a result of the Millennium Development Goals (MDGs).

There is a grey area between donors working to gather the data they need to show how effective they are, and supporting governments to make better policies and programmes. They toe a fine line between promoting policy-driven evidence-gathering and evidence-driven policy-making.

Made to Measure

From our perspective, discussions in preparation for post-2015 indicate the former. Calls for better data, greater transparency and increased use of technology should not only put pressure on developing country governments – donors have to find better ways to incentivise government demand for better data. Those hoping for a data revolution should remember that:

  1. The MDG agenda put a great strain on national statistics systems in Africa, and has achieved very uneven progress in directing resources to fill specific data gaps across the continent;
  2. Data to compare progress across countries is not the same data countries need to better design and manage policies and programmes;
  3. Developing fully capable and coordinated national statistical systems takes decades.

Amanda Glassman and Justin Sandefur at the Centre for Global Development argue that donors can incentivise African governments to invest in better data by tying increasing funding to metrics of quality data, prioritise core statistical products over incidental surveys and making sure statistics agencies don’t lose their best staff.

Funding for regional organisations can achieve economies of scale in the collection, harmonisation and storage of data, the provision of capacity building as well as the tracking of key data such as trade and migration for customs unions and common markets. The EU has over 50 years’ worth of experience to share in this area – as well as some funding.

Potential gains and savings will not be enough. To focus political commitment and create demand for the right reasons, let’s consider a global goal (with national targets) to improve the quality and availability of economic, demographic, environmental and social data alongside the goals in thematic areas. National targets would include a metric of the extent to which countries manage to make quality data available to its primary audiences (as defined by the countries themselves), and give this goal teeth for good governance, transparency and accountability.

Is such a goal a guarantee for governments committed to statistics and the development of a ‘culture of statistics’? Certainly not. Neither are targets under each of the ‘thematic’ goals, which further risk repeating mistakes of the past in concentrating efforts for better data in select areas. Does a goal guarantee that the issue won’t be a by-product of the outcome of the negotiations? Count on it.

The views expressed here are those of the author, and may not necessarily represent those of ECDPM.

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