On metrics and financing for the Sustainable Development Goals

The world has experienced unprecedented growth in average per capita incomes over the last 50 years, but many countries continue to face deep economic, social, and/or environmental challenges. These include persistent extreme poverty, poor outcomes in human health and education, widespread malnutrition, high inequality measured by income or other characteristics, poor access to infrastructure, growing water stress, the degradation of terrestrial and marine ecosystems, pollution, and climate change. Under business-as-usual trajectories the environmental challenges in particular are expected to worsen significantly. Enhanced international policy coordination and cooperation around shared goals is required to reverse these trends, and many developing countries require more external financial assistance. In response governments have adopted international development goals, including the Millennium Development Goals (MDGs) and their successors, the Sustainable Development Goals (SDGs), which are to be achieved by 2030. These goals complement earlier tools for international policy coordination, notably the environmental conventions, such as the United Nations Framework Convention on Climate Change and the Convention on Biological Diversity. This thesis contributes to the need to understand how progress towards the SDGs can be monitored, how investment needs for climate-resilient development and the SDGs can be estimated, and what lessons can be drawn for international financing mechanisms in support of the SDGs from the experience of the health sector under the MDGs. These issues represent important contemporary questions in the scientific and policy literature, as evidenced by the rapidly growing scientific literature on the SDGs to which this thesis contributes. Chapter 2 introduces a novel SDG Index and Dashboards that combines official and science-based metrics to establish an SDG baseline for the 149 countries for which sufficient data are currently available. The SDG Index and Dashboards measure countries’ distance from achieving the goals, assess overall performance, and identify implementation priorities for each country. We find that many countries’ development models are imbalanced in favor of economic development and at the expense of social inclusion and environmental sustainability. We demonstrate the SDG Index’ usefulness as an explanatory variable in studying policy objectives, such as subjective well-being and in identifying policy priorities. Moreover, the chapter identifies major data gaps for monitoring the SDGs and suggests ways in which these can be closed in coming years. In Chapter 3 we consider the combined investment needs of development objectives in low-income country settings, as exemplified by the MDGs, and measures to adapt to a changing climate. Drawing on consensus investment needs for the MDGs in Africa, as established by the MDG Africa Steering Group, and the literature on investment needs for climate change adaptation, we propose and apply a methodology for integrating these assessments. The chapter reviews major line items in financing the MDGs and considers the nature and extent of additional measures to adapt to climate change, as well as associated financing needs. We find that climate change adaptation may increase total investment needs by some 40 percent. The analysis shows that development and adaptation measures need to be integrated along sectoral lines in order to facilitate implementation by governments. Chapter 4 extends this analysis to propose an analytical framework for SDG needs assessments that translates the 17 SDGs into eight investment areas and introduces a preliminary score to assess the quality and suitability of needs assessment studies. Using this framework, published sector needs assessments are analyzed, harmonized, and consolidated to arrive at a first assessment of private and public investment needs for the SDGs in low- and lower-middle-income countries. Incremental spending needs in these countries are estimated at $1.3-1.4 trillion per year. Approximately half of these incremental investments can be privately financed. Domestic resource mobilization can increase significantly, leaving an external financing gap of perhaps $152-163 billion per year (equivalent to 0.22-0.26% of high-income countries’ GDP) that must be met through international public finance, including Official Development Assistance. Globally, an incremental 1.5-2.5% of world GDP needs to be invested each year by the public and private sectors to achieve the SDGs in every country. Turning to the financing of the SDGs, Chapter 5 investigates the experience of the Global Fund to Fight HIV/AIDS, Tuberculosis and Malaria in financing the rapid scaling up of proven health interventions observed since 2002. The chapter identifies 8 key design principles of the Global Fund that set the institution apart from other multilateral financing mechanisms. It then considers to what extent these design principles have enabled rapid progress in combating the three infectious diseases in a broad range of operating environments, including fragile countries and countries with poor governance. The chapter concludes that the Global Fund has performed better than expected at inception, and that the key design principles explain this success. Adopting these principles may help multilateral grant financing mechanisms focusing on other SDG priorities – such as education; access to energy, water, and sanitation; nutrition; and smallholder agriculture – improve the effectiveness of resource use and accelerate progress towards the goals. In the Chapter 6, we investigate the Global Fund’s Technical Review Panel (TRP) to determine whether it had succeeded in reconciling the competing needs of country ownership of development programs and the need to ensure effective use of scarce resources. We also investigate whether the demand-based application process generated funding allocations that were in line with the Global Fund’s objective to direct funds towards the countries most in need. To answer these questions, we construct a novel dataset and conduct four sets of regression analysis using ordinary least squares and ordered logistic regression models. The chapter finds that the TRP operated in line with the Global Funds’ objectives and allocated funding to countries most in need, though we find evidence that countries with large populations suppressed the volume of financing requested from the Global Fund. The evidence suggests that the TRP promoted learning on how to scale up disease control programs and that the Global Fund operated equally well across different country environments, including fragile and poorly governed countries. The chapter closes by considering the policy implications for financing the SDGs in health and other areas. The concluding chapter summarizes the research findings and critically discusses the methodologies and data used in this thesis. It outlines suggestions for further research and summarizes policy implications for monitoring, implementing, and financing the SDGs.