Sara L.M. Davis

Now that members of the UN have adopted the ambitious Sustainable Development Goals (SDGs), the next question is: how to pay for it all? The answers raise questions about aid eligibility, transparency and accountability.

For SDG 3 on health, part of the cost will be covered by international and bilateral aid, including health financing mechanisms such as those in the World Bank, the Global Fund, DfID and PEPFAR. By redistributing the world’s taxes and wealth, these agencies enable developed countries to fulfill their obligations (under the Maastricht Principles) to support realization of economic and social rights in developing countries; and assist developing countries to realize their own human rights obligations.

But health aid falls far short of the need. With other crises looming, some donor countries are threatening to cut overseas health aid drastically. As a result, controversy has raged over how to equitably distribute diminishing funds. The tug of war is fiercest over health programs in middle-income countries, which are now home to 70% of people in poverty.

The problem is partly political: donors balk at funding states that appear able to pay their own way, while many middle-income countries balk at funding services for criminalized key populations vulnerable to HIV and TB (people who inject drugs, sex workers, men who have sex with men, transgender people, prisoners, migrants and refugees, among others). This tug of war has sometimes been disastrous: when Romania became ineligible for Global Fund support, the shortfall in funding for services to people who inject drugs created “a dramatic HIV/AIDS emergency.” Civil society groups that serve key populations in middle-income countries are demanding continuing eligibility for global health aid.

This raises the question of how countries are rated eligible in the first place: who decides, and based on what criteria?

Aid classification systems are one of many kinds of indicators proliferating as tools of global governance.1 Indicators like these increase the speed and ease of decision-making, which is attractive to fast-paced international agencies that must make difficult decisions quickly and then explain those decisions to diverse stakeholders. It is easier to communicate a simple, apparently objective indicator. But this apparent objectivity and rationality of indicators can mask weaknesses in data and the political pressures behind policy choices.2 The technical expertise needed to understand what makes up even a simple indicator can also make it difficult for the public to hold aid agencies accountable. The officials who develop and monitor the indicators have significant clout over countries they were not elected to govern.

Gross National Income (GNI) is a case in point. Most health aid donors use the World Bank’s GNI per capita (GNIpc) index to determine aid eligibility. However, critics have pointed out numerous weaknesses in GNI: arbitrary quantification measures, lack of commensurate categories, and weak data from underfunded statistics bureaus.3 Countries need to periodically update the “base year” against which growth is evaluated, creating bizarre, stark changes in income classification.4 Even the “per capita” is often unreliable: for example, in Nigeria, ethnic conflicts and lack of access to the Boko Haram-controlled north have meant that “no one knows for sure” how many Nigerians there are.Kerner and colleagues have found that some countries manipulate their GNI to stay aid-eligible.6 And GNIpc, a national measure, fails to capture internal inequality.

To address these concerns, the Global Fund and a group of health donors convened an Equitable Access Initiative (EAI) to explore alternatives. The EAI tested combinations of various health indicators with GNI to see if this created a more accurate income classification system. Unfortunately, though, health data are also not reliable; combining two kinds of weak data does not create a great index. Instead, when all was said and done, the Global Fund Board fell back on the old tools, and voted to use a three-year average of GNIpc.7

This failure to find a better indicator is frustrating, but the truth may be that indicators are the wrong answer when it comes to aid eligibility. For human rights advocates, a recommendation from one of the EAI analytical teams deserves consideration. The Institute for Health Metrics and Evaluation (IHME) recommended that aid agencies analyze countries’ budgets and expenditures to assess their “fiscal space”, or “the availability of budgetary room that allows a government to provide resources for a desired purpose.”8

IHME did not mention human rights in their analysis, but their recommendation is consistent with the International Covenant on Economic, Social and Cultural Rights, which requires states to use “maximum available resources” to fulfill economic and social rights. To assess whether they have done so, the Committee on Economic, Social and Cultural Rights recommends looking at similar countries for comparison, as well as at the past performance of the same country.

In many cases, this kind of review will find that countries are not spending what they could on health. If fiscal space review was done transparently and inclusively, it could spark more civil society and public advocacy for domestic health financing.

Thanks to poorly regulated global capitalism, income inequality is likely to increase. We can’t keep relying on old tools like GNI. To pay our way to fulfilling the SDGs, aid eligibility should be determined in ways that are transparent, inclusive and accountable to the public.  

Sara L. M. Davis, PhD,  is a visiting scholar at New York University’s Center for Human Rights and Global Justice, New York, USA, and was Senior Human Rights Advisor at the Global Fund to Fight AIDS, Tuberculosis and Malaria from January 2013 to May 2015. 

References

  1. Margaret L. Satterthwaite and Annjanette Rosga. “Trust in indicators: Measuring human rights.” Berkeley Journal of International Law 27/2 (2009): 253-315.
  2. Sally Engle Merry, Kevin E. Davis, and Benedict Kingsbury, The Quiet Power of Indicators: Measuring Governance, Corruption, and Rule of Law. Cambridge Studies in Law and Society: 2015.
  3. Morton Jerven, Poor numbers: How we are misled by African development statistics and what to do about it. Ithaca: Cornell University Press, 2013.
  4. Andrew Kerner, Morten Jerven and Alison Beatty. “Does it pay to be poor? Testing for systematically underreported GNI estimates.” The Review of International Organizations (2015): 1-38.
  5. Abraham Okolo, “The Nigerian census: Problems and prospects.” The American Statistician 53/4 (1999): 321-325.
  6. Ibid
  7. 35th Board meeting: The Global Fund Eligibility Policy. GF/B35/06 Revision 1, p. 3. Available at http://www.theglobalfund.org/en/board/meetings/35/ (accessed May 9, 2016).
  8. Peter S. Heller, “Understanding Fiscal Space.” https://www.imf.org/external/pubs/ft/pdp/2005/pdp04.pdf
 
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