The High-Level Panel has called for a data revolution to track progress towards international development targets. They were right to do so. But that’s not the only revolution that we need. If the international community is serious about ‘going to zero’ on poverty and other goals, we need to know what it will cost. Targets count for little if you can’t pay for them. And we also need to track the money to make sure it actually gets to where it is needed.
This is not just a matter of aid. As development assistance becomes less important it is the money the governments themselves commit that will make the difference. Unfortunately, it has taken thirteen years for anyone to start seriously tracking such spending on the MDGs. So all credit is due to Oxfam and Development Finance International (DFI) for comparing actual spending on MDGs to the MDG spending targets that governments have committed to.
There are four fundamental financial data problems that must solved if we are to make progress with post-2015 goals.
MDG spending targets don’t add up. The five MDG spending targets that Oxfam/DFI quantify represent up to 70% of all government revenues in a typical low-income country. If you add on African Union-agreed infrastructure targets then the total would rise to 110% of government resources. And this is before any allowance is made for spending on potential post-2015 goals on sustainable infrastructure, environment, security and justice. ODI country-focused research revealed the same story with development spending targets in three of the five countries ODI examined adding up to more than 100% of total resources available to government. The governments literally cannot afford to deliver all of the targets. The discrepancy is not just an unfortunate arithmetic error but a failure that removes any accountability. No government can be held accountable for failing to spend more than100% of its revenue. If the world is to sign up to post-2015 goals and if the world is prepared to be serious about ensuring there is the finance in place to make these goals a reality then there has to be a serious, considered and, above all, a coherent set of financial commitments.
MDG spending targets reflect planned allocations, not reality: the targets only refer to the budgeted amount. Yet, in many poor countries, the difference between what is announced in the budget and what is actually spent can easily be as much as 10-20%. In some years in Tanzania spending on capital projects was only half the budgeted amount. In Liberia, while the average difference was only 5% in some sectors, underspend has been more than 25%.
What are counted as MDG spending targets don’t target the poor (or the MDGs). The headline MDG spending targets relate to total health and total education budgets, but total spend in these sectors is a very inadequate measure of spending on the poor. In some countries a disproportionate part of the health budget goes on the hospital in the capital city that primarily serves the country’s elite: a tiny proportion of the population. Even in stable countries with well-functioning democracies the education budget can be very biased, with spending on each university student (often the children of the elite) a thousand times the amount spent on each primary-school pupil. Should we really account transfers to the richest sections of society as MDG spending? In many countries it is not how much is spent in aggregate that is critical, but how much is spent in the most needy parts of the country, and how much benefit reaches the most disadvantaged. Moreover, reaching the most isolated communities costs more than reaching those living in the capital. Getting child labourers into school and delivering health services to remote rural areas takes a bigger financial effort: the marginal costs of delivery are higher than the average costs associated with current spending. Yet, in many countries, budgets are the same regardless of where people live. And in some instances per-capita funding is actually less. For example, in Kenya, school budgets are set on the basis of the number of children enrolled. As a result the poorer districts have no resources with which to try and reach the many children that don’t yet attend school.
MDG spending may not reach the poor. Over twenty years ago the World Bank undertook the first ever Public Expenditure Tracking Survey in Uganda, which revealed that as much as two thirds of the spend on primary education did not reach primary schools, but was either redirected to other areas of spending or was stolen. Since then governments and donors have paid much more attention to safeguarding the flows of resources: subsequent surveys in Uganda and other countries showed that 80%–90% was reaching the intended beneficiaries. However, these surveys have been criticised for not tracking the final stage. Some exercises would track resources in greater detail, down to health clinics to check that the drugs financed by the centre had been signed for and received, but then fail to check whether the drugs actually reached the patient. There is a worryingly high level of anecdotal evidence of drugs going out of the back door of the clinic, with patients having to go and buy them from the local pharmacy store. In a context where spending is so poorly monitored, and financial regulations so weakly enforced, only the really naïve believe that a signed receipt was sufficient evidence that the drugs actually made it to the clinic let alone the patient.
The solution to these challenges is to extend the data revolution to budgets. We need to know what it would take to finance any goals that are adopted – and we need to know how governments spend their money, where the money goes, and who benefits. Achieving these goals will be tough. But it is not an impossible mission. As the Government of Uganda showed this month when it published online data for all its spending down to the level of each primary school, where there’s a political will, backed by a bit of external support, change is possible.
