In 2015, the world embarked on an ambitious journey with the adoption of the 17 Sustainable Development Goals (SDGs), a comprehensive agenda aimed at addressing global challenges by 2030. These goals, ranging from eradicating poverty to combating climate change, represent a unified vision for a better future for all nations. However, the path to achieving these goals is not just about setting targets; it’s fundamentally about measuring progress. Are we on track? Do we have the data to even know?
The SDGs dramatically expanded the scope of global development monitoring compared to their predecessor, the Millennium Development Goals (MDGs). While the MDGs had a relatively modest set of 60 indicators, the SDGs encompass a staggering 231 indicators across 169 targets. This exponential increase in data requirements poses a significant challenge for the statistical systems of countries around the globe. To put this into perspective, even by 2015, the target year for the MDGs, nations were only reporting data for an average of 68% of the MDG indicators.
Increased Data Requirements by SDGs
The complexity of the SDG indicators further exacerbates the data challenge. When the global indicator framework was established by the UN General Assembly in 2017, a substantial 36% of the 231 indicators lacked internationally agreed-upon methodologies or standards. It wasn’t until recently, thanks to dedicated efforts from the global statistics community and the Inter-Agency and Expert Group on SDG indicators, that methodologies were developed for all indicators, making it theoretically possible to track them.
However, the mere existence of methodologies does not automatically translate into data availability. A significant hurdle remains in the capacity of countries’ statistical systems to collect and report data on these indicators. Despite the rapid progress in methodological development, many nations are struggling to provide the necessary data to monitor their SDG progress. The international community must now shift its focus towards bridging these data gaps with the same urgency and commitment that was shown in establishing measurement standards.
The World Bank’s 2021 World Development Report: Data for Better Lives introduced the Statistical Performance Indicators (SPI) as a tool to assess the strengths and weaknesses of national statistical systems. The SPI evaluates performance across five key pillars: data use, data services, data products, data sources, and data infrastructure. Focusing on the data products pillar, which utilizes data from the UN SDG database and OECD data, we can analyze countries’ data reporting on SDG indicators.
Alarmingly, substantial data gaps exist in our ability to assess country-level progress towards the SDGs. On average, countries have reported data for only 55% of the SDG indicators for the period between 2015 and 2019. No country has reported data on more than 90% of the indicators, and a concerning 22 countries have reported on less than 25%. This reveals a significant lack of comprehensive data to accurately track global progress.
On a positive note, data reporting has improved for most SDGs in recent years. For 10 out of the 16 analyzed goals, data reporting was higher in 2019 than in 2015. Goals that previously suffered from low reporting rates have shown particularly strong improvements. For instance, reporting on industry, innovation, and infrastructure (Goal 9) increased from 40% to 53%. Even environmental SDGs, which already had relatively higher reporting rates, have seen further improvements.
Progress on SDG Data Reporting (2015-2019)
Despite these improvements, the current rate of progress in SDG data reporting is likely insufficient to achieve comprehensive monitoring by 2030. Linear trend analysis of data from 2015 to 2019 suggests that no SDG is on track to achieve full data reporting across all countries. Data on gender equality (Goal 5) remains particularly scarce. Furthermore, these projections do not account for the disruptive impact of the Covid-19 pandemic, which has significantly hampered data collection efforts, causing delays in censuses and surveys and potentially exacerbating data availability and quality issues in the years ahead.
Interestingly, country income level is not as strong a predictor of SDG data reporting as one might expect. According to the UN SDG database, high-income countries are, on average, trailing behind low- and middle-income countries in data reporting. This effect is partially influenced by small, high-income island states and, to a lesser extent, oil-producing countries in the Middle East. However, even when considering only countries with populations exceeding one million, high-income countries only perform on par with lower-middle-income countries.
Unlike the MDGs, which primarily focused on developing nations, the SDGs are universal and apply to all signatory countries, regardless of income level. While not every indicator is relevant to every nation, the SDGs address global challenges that necessitate universal participation and accountability. For instance, high-income countries reported a mere 25% of the indicators related to gender equality (Goal 5). Issues such as gender discrimination and violence, equal opportunities for women in leadership, and universal access to sexual and reproductive health are clearly not priorities solely for low-income countries.
SDG Data Reporting by Income Level (2019)
The observation that statistical capacity alone may not fully explain SDG data reporting is further supported by the analysis of the SPI. The correlation between the SPI pillar measuring SDG data reporting and other SPI pillars, such as data sources and data infrastructure, is weaker than the correlations among these other pillars themselves. This suggests that while a robust statistical system is important, political will and prioritization may also play a significant role in driving SDG data reporting. Countries may be collecting more data than they are currently reporting to the UN SDG database. It is worth noting that for OECD countries, data submitted to the OECD has been incorporated to supplement the UN SDG database for a more comprehensive picture.
The value of reporting SDG data extends beyond simply monitoring progress. Research indicates a positive correlation between countries’ performance in measuring MDG progress and their actual progress towards achieving the goals. This suggests that the principle of “what gets measured gets done” holds true in the context of international development. By utilizing tools like the SPI to track SDG data reporting, countries can gain valuable insights into their reporting gaps and identify areas where increased effort is needed to ensure that the global community can effectively track progress towards the ambitious SDGs by 2030.
The data and R code for the analysis reported in this blog post can be found here.
