Goals that make a difference
Tanzania’s Ngorongoro National Park: the mere size of a nature conservation area says little about the state of its biodiversity
The Millennium Development Goals are spelled out in quantitative terms. Success or failure will be obvious. The MDGs have thus become standards against which the performance of individual countries is assessed. Will a particular country halve the number of people living in absolute poverty (compared with 1990)? Is it on its way to reducing maternal mortality by 75 %? Will all its children of school age actually attend classes five years from now?
The MDGs’ dynamism has turned out to be surprisingly strong. The impact is much stronger than expected by the sceptics who, at first, complained that the MDGs were merely non-binding declarations of intent.
Indeed, the world’s heads of state and government agreed on the MDG agenda in 2000 without assigning any responsibilities to ensure that the goals would be met. Today, two thirds of the time before the 2015 deadline has passed. The interim results are not good. It is obvious that the world community will not fully achieve the MDGs, not least because of the global economic and financial crisis, which has led to setbacks in developing countries. Nonetheless, most experts agree that the MDGs were a useful innovation. The quantified goals have proved useful in many ways.
For example, they have contributed to greater policy ownership of developing countries. The MDGs relate to the Poverty Reduction Strategy Papers (PRSPs) that developing countries have to present if they apply for funds from the World Bank or the International Monetary Fund. As the MDGs are based on a universal UN agreement, they are not targets simply imposed by donors. What matters even more is that the MDG agenda is a good starting point for domestic policymaking in developing countries.
However, the embedding of MDGs in national policies also raises questions. Statistics offices in developing countries often cannot provide the necessary data. One example is employment and income data (MDG 1): in many developing countries, the informal sector plays a significant role in the economy, but official statisticians do not keep track. The same is true of subsistence agriculture, which provides livelihoods to many poor people.
It is a universal goal to reduce poverty. But what needs to be done depends on the local circumstances. Policies are unlikely to succeed unless they take account of poor people’s coping strategies. Accordingly, developing countries need statistics that correspond to the reality of their daily lives. Capacity building – as provided by InWEnt – helps agencies and public authorities collect and process data in a way that lives up to this ambition. This is an important precondition for statistics to serve as the basis for debate and decision making.
Even apparently unequivocal MDG data can be misleading. Take MDG 7, for example, environmental sustainability. Data that accurately reflects the state of biodiversity is very rare. Typically, governments report what land they have reserved for conservation area. Such raw data, however, does not give any indication on its actual condition and how resources are actually managed.
A subgoal of MDG 7 is to improve water infrastructure. The idea is to modernise water supply and sanitation facilities so that fewer people will fall ill. Typically, data on new water pipes and toilets is collected. But whether the target groups actually use this infrastructure is quite another question. Experience from many countries shows that, in the rainy season, people tend to resort to natural water resources because they are close by. This practice, however, is questionable in health terms.
High fever or malaria?
MDG 6 is to contain the spread of HIV/AIDS, tuberculosis and malaria. Reliable diagnosis systems are needed to gauge success. In the case of malaria deaths, however, official statistics in many countries only record the correct diagnoses for well-to-do urban people who can afford to resort to doctors. In the countryside, the cause of death of poorer people is frequently not recorded – or generically indicated as “high fever”.
Many countries have made great strides in respect to school attendance (MDG 2). Kenya’s government even reports more than 100 % primary school enrolment because, thanks to political efforts, older children who so far did not attend classes have started to go to school too (see Monitor, p. 229).
School enrolment, however, is not an end in itself. What really counts is that children learn things so they can gain control of their lives and find good jobs. But MDG 2 does not measure the quality of schools. Reliable and meaningful data on this aspect is desirable and needs to be generated at the national level, according to national criteria.
Awareness of the importance of official statistics is growing in developing countries. With InWEnt’s support, the Commission of ECOWAS (Economic Community of West African States) is working on a standardised monitoring system for the poverty reduction strategies of the member countries. The goal of this initiative is not just to collect reliable data but to obtain a realistic picture of what is going on.
It is no coincidence that interest is also growing in statistics that do not immediately relate to the MDGs. For example, experts are working on the definition of indicators that would make it possible to assess aspects of public governance (within agencies or governments). Elements such as public participation, officials’ corruption or the rule of law are of particular relevance in this context (see the essay by Emily Calaminus, p. 244).
Despite the obvious methodological difficulties, such indicators of progress have been integrated in the poverty-reduction strategies of some countries. An InWEnt capacity-building programme in Zambia provided support to the relevant national actors to design a governance-focused data collection system. The programme was institutionally embedded in a governance secretariat with representatives from important national stakeholders. Of course it is particularly interesting to have indicators that not only convey a representative image of the reality but go further and indicate the most meaningful starting points for political reforms.
At the global level, several interesting projects are breaking new ground. The World Bank, the UNDP and several donors are supporting Poverty and Social Impact Analysis studies. The goal is to create quantitative models of development processes so as to be able to perform ex ante analyses of reform outcomes – such as the introduction of a new tax in a country. At the same time, the methodology would allow for assessment of the effects of the financial crisis on specific people. Obviously, such number games will be worthless unless they are anchored in empirical data.
The cooperation project between InWEnt and the OECD’s Global Project on Measuring Progress of Societies goes yet another step further. The goal is to identify indicators of development that go beyond generic data such as per capita revenue. The project is in line with the work of an international commission led by Nobel laureate Joseph Stiglitz. The commission presented its final report last summer (http://www.stiglitz-sen-fitoussi.fr/en/ documents.htm). Aside from Stiglitz, many other renowned experts took part.
The commission pointed out that many different factors affect people’s quality of life, including, for instance,
– the environmental conditions of the places where they live and work,
– their options to participate in political and social life or even
– things as simple as holidays and leisure.
With its report, the commission laid a scientifically-sound basis for defining meaningful development goals in the future.