It is now widely acknowledged that the world will not meet the Sustainable Development Goals (SDGs) by 2030. The UN’s own assessment finds that only a third of SDG targets are on track or making moderate progress, while nearly half are moving too slowly and a fifth are reversing.
This shortfall partly reflects the world’s slow pace of development since the SDGs were set, a trend exacerbated by global crises such as the COVID-19 pandemic, climate change, and geopolitical instability. But it is also a reflection of the SDG targets themselves, some of which were deliberately set as highly aspirational. Even with fast progress, they would have been nearly impossible to achieve by 2030. Goals like ending poverty or achieving universal access to clean water are nearly impossible to achieve in less than a generation because many countries are more than a hundred years away from these goals at a normal pace of development.
Ideal targets are feasible yet ambitious. They move the agenda forward by motivating policymakers, mobilizing resources, and inspiring innovation. There’s a fascinating parallel in sports: marathon runners often “bunch” their finishing times just below the hour or half-hour mark, suggesting that the target itself shapes performance. The same dynamic plays out at the country level. For example, when India set a national target to eliminate open defecation, the ambitious goal galvanized a massive public campaign, mobilized funding, and led to dramatic improvements in sanitation coverage.
With many SDG targets out of reach, countries face a critical question: how should they set development targets that are both relevant and aspirational? In a new paper, we propose a fresh approach to target-setting. Our method works by modeling the typical path of development for an indicator, calculating how long it usually takes to move between any two development stages based on past experiences around the world. An interactive visual explanation of the method is available here.
To see how it works in practice, suppose that Nepal wants to set a target for its under-five mortality rate in 2050.
This approach allows for target-setting across countries based on how fast a country is moving relative to the typical pace across countries, its own historical pace, or the pace of a benchmark country, such as the best performer in its region.
It also allows for the creation of global targets that are informed by country targets. One possible global target is the global projected value if all countries follow the historical pace of progress. Yet in many situations, historical development paths are unlikely to be appropriate; technological change may make expected future progress faster while climate change or geopolitical uncertainties may make it slower. If the typical historical path is not sufficiently ambitious, one could explore a global target that mimics the path of a historical best performer, such as the under-five mortality in India.
Ultimately, target-setting is a complex and multifaceted process. While this framework, like any framework, cannot deliver a universal solution, we hope it can equip users with the tools and information to establish both realistic and ambitious targets.
Care about another country or another development indicator? We have created a package in R, trackr, that allows you to create development targets at various levels of ambition using your data of interest. Reproducible code for the Nepalese example is available here.
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