Measuring development goals

Towards a data revolution

Development efforts are often hampered by poor or non-existent data. While attempts are being made to address this, much more needs to be done to improve official data by developing countries themselves, particularly as new development goals are set for the post-2015 period.     

Does singer Bono from the group U2 sense a data revolution brewing? He recently became a self-declared “factivist”–an evidence-based activist, with poverty first and foremost in his sights. Bono claims that if the current downward trajectory continues, “we can get closer to the ‘zero zone’ where extreme poverty is virtually eliminated by 2028”. Could he be right? The problem is, we may never know, not unless we improve the quality and availability of the vast array of data for measuring progress now starting to flow. With the 2015 deadline for the Millennium Development Goals (MDGs) looming, the UN High-Level Panel on the Post-2015 Development Agenda recently called for a “data revolution”. The MDGs and corresponding national development goals have been bearing fruit with increased statistical production and use. More data are available, including big data, and there are more strategic approaches to developing statistical capacity. Financial support for statistics (most of it coming from the European Commission, the World Bank, the United Nations Population Fund (UNFPA) and the United Kingdom) has substantially increased: US$2.3 billion was committed to statistics over the period 2010-12, a 125% increase in global contributions since 2008. Along with this, more than 100 countries have adopted the National Strategy for the Development of Statistics (NSDS) approach, the international benchmark for developing statistical capacity.        

Why, then, the call for a “data revolution”? One of the weak points to address is official data at the national level. These are needed to measure progress and achieve sustainable results. The trouble is, there is a misalignment between the MDGs and the national capacity needed to measure and achieve them. This leads to discrepancies between nationally and internationally reported numbers.         

Take education in Mozambique, for example, where national estimates show that 90% of primary pupils who start grade one go on to finish primary school. That’s nearly double the corresponding UN estimate, creating an unreliable basis for policymakers to work from (see graph). To be sure, many similar data gaps have been reduced, in Nepal and Zambia for instance, but too many persist, to the detriment of development programmes.       

How can we get better, more reliable data? Resources are key: less than 1% of official development assistance (ODA) goes to developing statistical capacity in countries. Even were this proportion to increase, we would need a global strategy that identifies gaps in data production, increases the accessibility of existing statistics and galvanises international efforts to develop a baseline for gauging performance after 2015.     

Improving timeliness would be one goal of such work. Even in countries where methods have been optimised, policymakers get frustrated about not having the kind of data that they need soon enough, whether for tackling food shortages or building new schools. “Bring me the data” is how former Nigerian President Obasanjo voiced this dissatisfaction. He is right to make such a plea. Despite an explosion in data availability, official statistics in many developing countries are often of varying quality, out of date and reported far too infrequently.        

But while government leaders face a vast knowledge rift, more could be done with existing material. Data and surveys are out there–they just need to be made more accessible.      

The Accelerated Data Program (ADP) is improving this situation, providing support to 45 national statistical offices to maintain online survey catalogues. Users can search the data they need and access it freely. The Central Statistical Agency of Ethiopia has published more than 100 surveys in its catalogue with a clear microdata access policy. Rwanda, Tanzania and Nigeria also have an open dissemination policy and distribute microdata files to researchers.        

Still, more can be accomplished, particularly by using technological innovations. Bill Gates remarked that “innovations in measurement are critical to finding new, effective ways to deliver these tools and services to the clinics, family farms and classrooms that need them”. The rapid expansion in mobile and Internet connectivity and the rapidly declining costs of innovative technologies offer hope for statistical surveys of all kinds.         

Mobile phones are a good example. In Kenya, 93% of households have a mobile phone, and adoption is increasing fast. For statisticians, mobile phones offer the potential of modernising and bolstering traditional methods of collecting statistics through household surveys with the likes of phone surveys, text message surveys, the deployment of electronic forms on digital survey devices and more.          

The “data revolution” is for, about and by people. Little wonder that so many international organisations, including the OECD, are providing more open and accessible data, while civil society groups such as ONE, Oxfam and Development Initiatives actively campaign for more democratic, open and human data, based on, say, well-being rather than pure economic growth.        

Can development really benefit from this? As Shaida Badiee from the World Bank recently told a PARIS21 global partnership meeting, statistical capacity first has to become smarter. Demand for data is at an all-time high and the “data revolution” provides us with an historic opportunity to tap into open and big data sources. From long-standing goals, such as fighting poverty and disease, to more contemporary targets concerning gender and child literacy, the post-2015 development goals can be based on more robust and instantly measurable indicators than ever before.     

Source: PARIS21

Of course, better statistics are not enough to improve policymaking, nor indeed the human condition. As PARIS21 knows only too well, bad politics can stop even the best data from being applied. However, facts that are gathered widely and deeply with the involvement of people cannot be ignored for very long.        

That is why PARIS21 is actively helping countries develop their statistical capacity and get the evidence out. Let’s call it a kind of “factivism”, which we believe can give the “data revolution” some teeth and, as Bono hopes, help shake poverty for good.      

References    

Elliot, M. (2013), Bono: Fight poverty to reach the “Zero Zone”, www.CNN.com.        

Chen, Shuang, et al. (2013, forthcoming), “Towards a Post-2015 Framework that Counts: Aligning Global Monitoring Demand with National Statistical Capacity Development”, PARIS21 Discussion Paper Series, No 1.        

Prydz, Espen (2013, forthcoming) “‘Knowing in Time’: How technology innovations in statistical data collection can make a difference in development”, PARIS21, OECD, Paris.    

Visit www.paris21.org     

PARIS21

The Partnership in Statistics for Development in the 21st Century (PARIS21) is a global partnership of statistics users, producers, donors and technical partners, from both developed and developing countries. PARIS21 works on improving national statistical capacity and the use of statistics and reliable data in the decision making process. One of its key roles since its inception in 1999 has been to help countries develop National Strategies for the Development of Statistics (NSDS), providing vision and guidance to improve capacity. Many PARIS21 stakeholders are at the forefront of surveying techniques, taking part in the International Household Survey Network (IHSN, www.ihsn.org), which fosters co-ordination among international organisations and agencies. It is complemented by the Accelerated Data Program (ADP), which supports better quality survey data and access to survey data. IHSN and ADP are implemented by PARIS21 in close collaboration with the World Bank. 

© OECD Observer No 295 Q2 2013




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