SDG overview: the statistics

Citizens across the continent should demand more and better data to stimulate a healthy debate about the role of ‘good numbers’ in political accountability.

Actors in New York, September 2015, stage a tug-of-war between the rich and the poor to depict the world’s struggle against inequality. Photo: DON EMMERT / AFP

In June 2011, Shanta Devarajan, the World Bank’s Senior Director for Development Economics (DEC), published an article, Africa’s Statistical Tragedy. The piece detailed how the continent was suffering from faulty statistics, which informed wrong policy decisions. The author noted that the main problem with African statistics was the weak capacity of the continent’s countries in collecting, managing and disseminating data. National statistical bodies around the continent were inadequately funded and their responsibilities were often unclear. Moreover, statistical research in many African countries was “fundamentally political”, he argued, citing the case of poverty estimates. When statistical studies of this kind were conducted during an election year, for instance, they were likely to be kept under wraps. This problem is one reason why development partners such as the United Nations have in the recent past questioned whether African countries are capable of monitoring the progress of their policy commitments. In particular, questions have been posed on how Africa can monitor its progress in relation to the Sustainable Development Goals (SDGs), which include some 169 targets and 229 statistical indicators. Devarajan pointed out that many African countries on the continent had found it difficult to do the same for the Millennium Development Goals, which included 60 monitoring indicators. Devarajan called on African countries to make their data open, accessible and transparent, and to put in place standards whereby statistical activities are filtered through clearly articulated national sustainable development strategies. But the Director General of Rwanda’s statistics bureau, Yusuf Murangwa, observes that milestones in achieving better statistics are being reached, and are increasingly used to inform development.

This is related to growing interest in an evidence-based policy approach, coupled with ideas associated with the “management by results” paradigm. The Paris Declaration in 2005, which provides for a series of specific implementation measures and establishes a monitoring system to ensure that donors and recipients hold each other accountable for their commitments, and the Busan Declaration in 2011, which highlights a set of common principles for all development actors that are key to making development cooperation effective, have also motivated international agencies to put reliable statistical measurement at the heart of their monitoring and evaluation of development support. The National Institute of Statistics of Rwanda (NISR) has recently set out to improve its statistical methodologies, with the technical assistance of the World Bank, thereby providing sound guidance on strategies to tame poverty, Murangwa told Africa in Fact. He added that other African countries would need “consistent, regular and reliable statistics” to monitor and evaluate their SDGs performance, as well as contributing to measuring the progress of democracy and governance around the continent. Rwanda set out to clean up its statistical capacity after the World Bank detected inconsistencies between two measures of inflation in the 2010/11 and 2013/14 fiscal years, at a time when the country was coming up with plans to reduce poverty. Specifically, it turned out that the consumer price index (CPI) and the NISR price index – the so-called cost of living indicator – were not in harmony. Governments, and international financial institutions such as the World Bank, must allocate their development resources on the basis of reliable data, says Morten Jerven, an economic historian and professor in development studies at the Norwegian University of Life Sciences.

He argues that reliable statistics – including such basic elements to every economy as estimates of economic growth rates and per-capita income – are crucial to government operations in developing countries. His book Poor Numbers, which details how the world is misled by African development statistics, argues that developing countries have not been using statistics effectively to implement and monitor SDGs. “The paucity of accurate statistics is not merely a technical problem,” Jerven told Africa In Fact, “it is having a massive impact on the welfare of citizens.” African statistics “substantially misstate the actual state of affairs,” he added, with the result that inadequate resources are misapplied and development policy does not deliver the benefits expected. The problem is not so much a matter of sheer incapacity, Jerven argues. Rather, it involves the massaging of statistics by authorities, and therefore “misrepresentation of facts”. Yet without accurate statistics, African countries will be unable to evaluate and attain their transformational targets, the SDGs included. As an example he cites the recent rebasing of the Gross Domestic Product (GDP) of Kenya, Nigeria, Tanzania, Uganda, and Zambia, which resulted in supposedly higher GDP numbers for these countries. This might have had a feel-good effect, but it was otherwise of no significance to citizens. “The revised GDP numbers raise a lot of new questions,” he says. “What about the poverty statistics? If GDP is higher, how come poverty head counts are still higher than they were before?” Citizens should demand more and better data, says Jerven, to stimulate a healthy debate around Africa about the role of “good numbers” in political accountability. “Journalists and media should also engage African academics, African think tanks and African non-governmental organisations to facilitate a rich and diverse debate on the role of statistics and data in development.”

But the Sustainable Development Solutions Network (SDSN), a UN think tank that mobilises global scientific and technological expertise to stimulate practical solutions for sustainable development, says it can be burdensome for African countries to monitor SDGs. The body has estimated that tracking the SDGs would cost African countries about one billion dollars a year for the period running from 2015 to 2030. Half of this cost could be shouldered by development partners, but the remaining cost “greatly exceeds” the financial capacities of many African states, as well as the sums already allocated to respective national statistical offices from international aid, SDSN noted in a 2015 report on SDG monitoring and statistical capacity development. However, African countries could cover the budgetary load by using innovative approaches to data collection. This is especially the case with the emergence of big data and open data, which SDSN says should be integrated into official statistical production methods over time, reducing costs and fostering efficiencies. Other innovations would include using satellite imagery and mobile devices to track population movements. The latter approach, for instance, could be used to support the treatment of malaria. It is worth noting that open data is improving the availability of statistical numbers for development and, more specifically, for monitoring SDGs. According to the Open Data Institute, a United Kingdom based non-profit company, open data is helping countries across the globe in combating development challenges, both as a tool for measuring progress and in finding solutions. Open data can help in effectively targeting aid money, as well as in tracking development progress and preventing corruption, according to the organisation.

Open data has been used to support smarter city planning in Rio de Janeiro, streamline emergency responses in the Philippines, map the Ebola outbreak in West Africa and help parents to assess school performance in Tanzania. We live in an era when states’ de facto quasi-monopoly on statistical production is being challenged, says Dr Julius Kones, a statistics lecturer at the University of Nairobi. Public and private entities can, and must, work together to produce reliable indicators covering progress relating to the implementation of the SDGs. As an example of the devolution of statistics and how this can inform development in African countries, police officers in Burkina Faso are using geo-localised data on mobile phones to monitor road accidents, says Professor Emmanuel Bonnet of the Institute of Research for Development based in Marseille, France. This approach can also be used in other fields such as health care to monitor epidemics, or in governance to monitor political violence or natural disasters, he notes. Africa’s national statistical offices play an important role in the collection, coordination, reporting and validation of statistics relating to the SDGs, says Francis Atwoli, Secretary-General of Kenya’s Central Organisation of Trade Unions. Reliable, timely, consistent and comparable data represented the “spinal cord” of all efforts to measure and monitor progress towards sustainable development in Africa. As part of monitoring the continent’s progress towards implementing the SDGs, national statistical offices must provide international agencies such as the International Labour Organization with accurate data, which relies on the correct identification of appropriate data sources and methodologies, Atwoli added.

The national statistical offices of some countries in Africa have begun developing SDG reporting platforms. In Kenya, for instance, the reporting platforms include data submission portals that allow different providers to submit data that contributes to the indicator data bases, as well as dissemination portals that allow users to access tables, documents and publications. In Tanzania, the National Bureau of Statistics has started an ambitious plan, which seeks to domesticate SDG agendas. Among the prominent sectors where the domestication is being felt is health, where the statistics body has managed to rally the participation of local government authorities (LGAs) and stakeholders to define how national health targets can be aligned to SDGs. It has also lobbied for increased and innovative financing to support the agenda, targeting an increase in health sector spending in the national budget by 3%, increasing enrolment in the country’s health training institutions by 5,000 and improving recruitment, deployment and retention of health personnel, particularly in maternal and child health. Morris Aron, a Nairobi-based statistician and economist, says that African countries have begun to appreciate the role that verifiable and consistent numbers play in deepening their understanding of development. More accurate statistics are now providing evidence for the monitoring, follow-up and review of the SDGs and their related targets, as well as helping to inform countries’ development agendas, he argues. Improved data is already helping Kenya’s capacity to address its housing shortage, says Charles Hinga, the country’s housing and urban development principal secretary. “With reliable data, we have managed to map out areas that need urgent attention in terms of housing,” Hinga told Africa In Fact.

To support this, the Kenyan parliament has ratified a housing levy, which will come into effect in May 2019. The levy will see employees contributing 1.5% of their monthly salary to the new housing scheme, with employers paying the same amount, though the total monthly contribution of both sums together is capped at Ksh5,000 ($50). Kenyans have criticised the plan, saying that the funds will end up being stolen. Hinga says the aim is to ensure access to safe and affordable housing by upgrading slum settlements, as well as to free up congested urban spaces, thus making the country’s cities “safe and sustainable”. Some critics have questioned the data used in informing the housing project, with some bringing law suits against the government in relation to it. On 16 April this year, following a case filed by the Consumers Federation of Kenya and the Central Organisation of Trade Unions, the labour court issued orders temporarily stopping the government from implementing the 1% levy for the housing fund. In their application the two organisations claimed it was “unreasonable to compel citizens who will not secure a house to contribute towards house ownership by another person without corresponding benefits”. But Hinga says that the housing and urban development department is “working closely” with the Kenya Bureau of Statistics (KNBS) to improve housing statistics. The KNBS Director-General, Zachary Mwangi, says it is working to “increase substantially the availability of high-quality, timely and reliable data disaggregated by income, gender, age, race, ethnicity, migratory status, disability, geographical location, among other characteristics relevant in national contexts, by 2020.

”In March 2017, the Cape Town Global Action Plan on Sustainable Development Data, which proposes solid actions that will support countries in meeting the challenges of providing statistics for SDGs, was adopted by the UN Statistical Commission. Says Hinga, “The plan guides national statistics offices in providing data on global SDG indicators, to prop up the review and follow-up of progress towards SDGs.” In 2017, the UN Economic Commission for Europe developed a document known as the Road Map to support national statistical offices in contributing to the realisation of SDGs. It establishes mechanisms for international collaboration, assesses data gaps, develops national indicators and provides data on global SDG indicators, statistical capacity building and communication. Mwangi says national statistical offices have a key role to play in realising the SDG dream in African countries – measuring progress in relation to the SDGs. “Agenda 2030 says that the annual progress report on the SDGs prepared by the UN Secretary- General in partnership with the international statistical system will be based on global indicators and data produced by national statistical systems,” he says. Monitoring progress in relation to the SDGs and their respective associated targets will need close collaboration between statisticians and policymakers, Mwangi insists. To this end, statisticians need to be involved from the beginning in preparing national action plans and the selection of national indicators. In most East African countries the selection of national and sub-national objectives and measures is currently the responsibility of policymakers, with the support of statisticians. On the other hand, according to Mwangi, the selection of indicators and the determination of methodologies and data sources are the responsibility of statisticians in consultation with policymakers.

At the fifth International Conference on Big Data for official statistics held in Kigali, Rwanda between April 29 and May 3 this year, it was heard that big data could help in monitoring and appraising Africa’s development. Prominently featured in the conference was the fact that African countries could employ new data sources and new technologies to monitor SDGs. By embracing big data and modern technology, Jonathon W Ross of Geoscience Australia, the government’s technical adviser on geoscience, and custodian of the geographic and geological data and knowledge of the nation, said African countries would be able to tell how the planet was changing in terms of its land, atmosphere, cities, towns and villages. “Such an innovation has been used in Uganda, where early warning for crop failure has been used to enhance livelihoods and food security,” said Ross. To foster this two-way collaboration, national governments will need to designate a specific body to handle the SDG measurement system, he argues. This would help to improve information exchange, discussions about the implementation of accepted methodologies, and consistency in the work of all stakeholders. National coordinating bodies of this kind would also foster discussions between government agencies and international organisations on issues relating to data collection and analysis of SDG indicators, keep stakeholders abreast of statistical activities in the field of data collection and analysis, and boost coordination and joint advocacy activities around data collection with a specific focus on the SDGs.

 

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