6 December 2018: A paper from the Friedrich Ebert Stiftung (FES) reviews the process involved with identifying the SDG indicators, noting that although the SDGs were negotiated and agreed by all UN Member States, the global statistical community has defined the SDG targets through the indicators. The paper emphasizes that the indicators will determine whether the 2030 Agenda for Sustainable Development is ultimately pronounced a “success, a failure or something in-between.”
The paper titled, ‘The 2030 Agenda: An Unprecedented Statistical Challenge,’ provides a critical examination of the SDG indicators from a statistical perspective and outlines some measurement challenges. Authored by Steve MacFeely (FES), the paper notes that SDG indicators are only performance metrics as they inform whether a target is being achieved or not. However, he writes that relatively little discussion has addressed the additional data required to inform and design integrated policies in order to implement actions to achieve the SDG targets.
The MDGs contained 60 indicators, but countries could only populate two-thirds of them by 2015.
Reflecting on the Millennium Development Goals (MDGs) – the predecessor framework of the SDGs – the paper notes that the MDGs’ requirements were modest, both in number and complexity, with eight goals, 21 targets and 60 indicators, compared with 17 goals, 169 targets and 232 indicators for the SDGs. Despite that, it says, at the end of the MDGs’ lifecycle in 2015, countries could only populate, on average, two-thirds (68%) of the MDG indicators.
Among other challenges, the author remarks that some Member States’ insistence on prioritizing official country data may be counterproductive in the longer term as it may place an “enormous burden” on some countries, and could result in many SDG indicators remaining unpopulated. He notes that the SDGs are likely to be the driving force for statistical advances in the coming years, in terms of statistical concepts, methodology, statistical organization and the use of new data sources. He warns, however, that these developments could open the door to the outsourcing or privatization of official statistics if the existing systems fail to deliver on expectations.
MacFeely discusses big data and administrative data, predicting that the latter will be “a must richer source of useable data,” but notes that attention to administrative data is lacking. He stresses the importance for national statistical offices (NSOs) and National Statistical Systems (NSSs) to secure legal access to administrative data, adding that the UN Economic Commission for Europe (UNECE) has recommended changes to statistical legislation to ensure that NSOs or NSSs have access to all the data sources necessary for statistics.
On the cost of measurement, MacFeely reports that resources required to support the poorest countries in implementing the SDG indicator framework range from US$1 billion to US$1.25 billion per annum, while implementing the SDGs could cost between US$3.5 and 5 trillion per year.
The author presented the paper at an event hosted by FES at UN Headquarters in New York, US, in November 2018. The event was moderated by Chantal Line Carpentier, UN Conference on Trade and Development (UNCTAD), and involved Ivo Havinga, UN Statistics Division, and Sally Engle Merry, New York University.
Also on the SDG indicators, the UN’s Inter-Agency and Expert Group on SDG Indicators (IAEG-SDGs) held its eighth meeting to discuss work plans for moving remaining indicators out of ‘Tier III’ (on which no agreed methodology for measurement are available), and to consider proxy indicators for Tier III indicators. The meeting took place at the Swedish International Development Cooperation Agency (SIDA) headquarters in Stockholm, Sweden from 5-8 November 2018. [Publication: The 2030 Agenda: An Unprecedented Statistical Challenge] [Landing Page]