Chapter 1. How far are OECD countries from achieving the SDG targets?

1.2.1. The global framework for SDG follow-up and review

The main institutional structure for global SDG monitoring was set up prior to the adoption of the 2030 Agenda, with the creation of the Inter-Agency and Expert Group on SDG Indicators (IAEG-SDGs) in March 2015.2 The IAEG-SDGs’ task was to develop and implement a global indicator framework for the goals and targets of the 2030 Agenda (henceforth, the UN Global Indicator List). The framework, composed of 244 indicators,3 was finalised at the UN Statistical Commission session held in March 2017, and subsequently adopted by the UN General Assembly in the Fall of 2017. These indicators align with the 169 targets and 17 goals, but are not distributed evenly: goals have between 5 and 19 targets, and targets have between one (most targets) and five (target 3.3) indicators.

These 244 global indicators were classified into three tiers based on their methodological development and data availability, as follows:

• Tier I indicators are those that are conceptually clear, based on established methodology and standards, and regularly produced by at least 50% of countries accounting for at least 50% of the population of each region;

• Tier II indicators are those that are conceptually clear, based on established methodology and standards, but not regularly produced by countries; and

• Tier III indicators are those that still lack an established methodology or standards (IAEG-SDGs, 2019[7]).

The IAEG-SDGs is regularly revising indicators’ tier classifications as their methodology and data availability evolve. As of February 2019, 101 indicators were identified as Tier I, 84 as Tier II and 41 as Tier III. A further six indicators had multiple tiers (i.e. different components of the indicator are classified into different tiers). The average tier level of indicators varies across the goals, with some areas more advanced, such as goals relating to People, and other less, such as goals relating to Planet. This is reflected in the data available for this Study, as detailed in Section 1.3.1.

The IAEG-SDGs has recently presented a report outlining the methodological development of Tier III indicators, including the timeline for a comprehensive review of the UN Global Indicator List in 2020, also highlighting the work on data disaggregation (UN-ECOSOC, 2019[8]). Additionally, draft guidelines on data flows (IAEG-SDGs, 2018[9]) were agreed at the IAEG-SDGs November 2018 meeting, and discussed at the United Nations Statistical Commission meeting in March 2019. The guidelines state that global monitoring should primarily rely on country data produced by National Statistical Offices (NSOs). To support the development and compilation of these data, the IAEG-SDGs has identified custodian agencies for each indicator. These custodian agencies are responsible to help ensure international comparability, compute regional and global aggregates, and provide data for the UN Global SDG Indicators Database (UN Statistics Division, 2018[10]); henceforth, the UN Global Database.

The annual UN Secretary-General’s report (UN-DESA, 2018[5]) and UN-DESA’s Sustainable Development Goals Report (UN-ECOSOC, 2018[11]) are both based on the data available in the UN Global Database. This database provides access to data compiled by the UN system and other custodian agencies, and currently contains data for 153 individual indicators of the 232 unique indicators (244 including recurring indicators) in the UN Global Indicator List.4 However, these indicators vary widely in country coverage. For example, only half of them have comparable data available for at least 20 OECD countries, covering both EU and non-EU members, which is the minimum criterion regarding country coverage set for this Study. Many other studies have responded to the dearth of data on the UN Global Indicator List by limiting the targets covered, or by using other indicators (see Box 1.1).

1.2.2. The purpose and approach of this Study

This Study contributes to the OECD Action Plan on SDGs (OECD, 2016[22]), and in particular Action Area 2, which aims to “Leverage OECD data to help analyse progress in the implementation of the SDGs”. A central part of the OECD’s data effort aims to contribute to the global monitoring framework itself, and to the UN’s global reports on SDG progress. As a custodian agency, the OECD directly supplies data to the UN Global Database on official development assistance and other international flows, as well on gender-based legal discrimination through the Social Institutions and Gender Index (SIGI). It also contributes data to other custodian agencies across a range of topics including policy coherence, education, environment and migration (OECD, 2016[22]).

The Study deepens the OECD’s data-related support to member countries by offering a high-level picture of performance right across the goals and targets of the 2030 Agenda. It draws on data aligned with the UN Global Indicator List, and assesses where countries stand in relation to the targets that were agreed by Member States when setting the 2030 Agenda.5 It aims to help countries in both navigating and implementing the SDGs by:

• identifying available comparative indicators that members could use to set their strategic priorities within the SDG agenda, and to track progress towards them;

• assessing countries’ current position on each of the targets, and putting this into context through a comparison with the OECD average; and

• highlighting key data gaps where statistical development will be particularly important, either to track progress or to advance understanding of the policy drivers of SDG targets.

The Study’s methodology is described in detail in Chapter 3. To capture the effort needed to reach the different SDG targets, this Study applies a standardised method that measures the distance between OECD countries’ current performance and where they should be in 2030. Doing so requires identifying suitable data sources for indicators to track the targets and (where this is not specified in the 2030 Agenda itself) defining a desirable level to be achieved by 2030. This methodology distinguishes this Study from other approaches as detailed in Box 1.2.

1.2.3. Countries’ use of this Study so far

As part of their national SDGs implementation processes, several member countries have used evidence from the previous Study to:

• Communicate on SDGs: This includes initiatives to inform internal policy debates, to set priorities and goals for national strategies; to provide an overall picture of countries’ SDG performance as a starting point for a broader public debate; to present data coverage or data gaps in the UN Global Database; and to identify national strengths and weaknesses based on comparative results (e.g. Slovenia, Denmark).

• Develop national monitoring and reporting systems to select national indicators; to establish starting positions and nationally relevant target values, and to develop dynamic baselines (e.g. Czech Republic, Belgium).

• Identify policy-relevant areas of action, prioritising their alignment with SDGs (e.g. Slovak Republic, Poland).

Results of the 2016 and the 2017 editions were quoted in Voluntary National Reviews (VNRs) submitted to the UN-HLPF by Belgium, the Czech Republic, Poland, Slovenia, the Slovak Republic and Sweden. In 2018, Slovenia published an update of its 2017 VNR which used the 2017 version of the OECD Study to show progress made in SDGs implementation (United Nations[27]).

Statistics Netherlands issued two reports assessing the country’s performance on SDGs, which both used the OECD Study as one of the main resources for comparative data at country level (Statistics Netherlands, 2017[28]; 2018[29]). Denmark published a statistical report in 2017 aimed at providing an overall picture of the country’s starting point on SDGs to inform public debate (Statistics Denmark, 2017[30]), referencing the OECD Study among other international assessments of countries performance on SDGs. The Czech Republic used the Study results to identify policy gaps in its national implementation plan for the SDGs.

1.3.1. How many indicators of the UN Global Indicator List can be measured for OECD countries?

In total, this Study relies on data for 132 of the 244 UN Global Indicator List (or close proxies) that met the selection criteria outlined in the previous section. These indicators cover 105 of the 169 targets. However only 87 targets have at least one indicator with a clear normative direction, thereby allowing measuring distance to targets. Indicator coverage is uneven across the 17 goals, with the goals on Health (3), Infrastructure (9) and Education (4) having the largest share of targets covered by at least one indicator, and Oceans (14) and Sustainable Production (12) the lowest (Figure 1.2).

Figure 1.2. Share of the 2030 Agenda’s targets covered in this Study by at least one indicator, by goal

Percentage, all OECD countries

Note: Share of targets covered by at least one indicator in the present study, out of the 169 targets of the 2030 Agenda. Coverage is shown according to the 17 goals and 5Ps.

Source: OECD calculations.

 StatLink https://doi.org/10.1787/888933962702

1.3.2. What distance will OECD countries have to travel to achieve the SDGs?

Figure 1.3 shows distances from the 2030 targets for the OECD as a whole by goal and target, with the outer boundary indicating targets that are already achieved today. Distances differ significantly even when considering a specific goal, which suggests that, when seeking to identify strategic priorities for implementing the SDGs, countries should look at performance against targets rather than focusing on average results by goal. For instance, for the goal on Food (2), targets relating to soil quality and breed protection are fairly close to being met, but performance on obesity rates is far from the target level. Similarly, on the Institutions goal (16), most OECD countries perform well on registration of births, but poorly on confidence in national government.

Figure 1.3. OECD countries’ average distance from achieving SDG targets

Note: The chart shows how far OECD countries (on average) are from achieving each target for which data are available. The longer the bars, the shorter the distance to be travelled by 2030; target levels are represented by the outer dotted circle. The inner circle (the starting point for the bars) represents a score of 3 or more standardised distances away from target, which most OECD countries have achieved on most targets. Targets are shown by goal, and goals are clustered by the “5Ps” of the 2030 Agenda.

Source: See Annex 1.A for summary metadata, and www.oecd.org/sdd/OECD-Measuring-Distance-to-SDGs-Targets-Metadata.pdf for detailed metadata.

 StatLink https://doi.org/10.1787/888933962721

Table 1.1 further highlights these uneven performances. OECD countries are closest to reaching the 2030 targets (Panel A) in several fields that, conversely, remain critically important for less developed countries. For example, all OECD countries have already achieved maternal, infant and neonatal mortality rates far below those required by the 2030 Agenda (indicators 3.1.1, 3.1.2 and 3.2.2); most schools in OECD countries provide access to internet for pedagogical purposes (4.a.1); and almost all OECD citizens have access to electricity and mobile networks (7.1.1 and 9.c.1). On the other hand, Panel B shows where performance in OECD countries lags furthest behind the 2030 targets. This spans a wide range of fields, such as inequalities, education, biodiversity, healthy behaviours, violence and feelings of safety, and human rights. Distances are especially wide for indicators of relative poverty (1.2.1 and 10.2.1), learning disparities among students (4.5.1 and 4.6.1), gender inequality (5.2.1 and 5.5.1), obesity (2.2.2) and tobacco consumption (3.a.1). Overall, Table 1.1 shows that OECD countries’ average strengths and weaknesses are both spread across a wide range of goals and targets.

Despite variations within goals, it is also interesting to look at results at the goal level (Figure 1.4). OECD countries are, on average, closest to reaching targets for the goals on Cities (11), Climate (13) and Energy (7), while also showing relatively strong performances for the goals on Oceans (14), Sustainable Production (12), Biodiversity (15), Means of Implementation (17), Infrastructure (9) and Water (6). Conversely, while the Agenda’s overarching aim is to “leave no one behind”, OECD countries (on average) appear to be furthest from their 2030 targets on Gender Equality (5), Food (2) and Reducing Inequality (10). Targets pertaining to goals on Education (4) and Eradicating Poverty (1) and Economy (8) are also relatively far from being met.

When evaluating countries’ performances at the goal and 5P levels, attention should be paid to uncertainties arising from missing data – while also being mindful of the constraints imposed by the need to adhere closely to the UN Global Indicator List. Figure 1.4 indicates the potential impact of missing data on the distances measured at goal-level by showing (as whiskers) the full range of possible uncertainties (under the two assumptions that the indicators that are currently missing could either have attained their targets level or, conversely, be far away from those levels). The range of uncertainty is largest for most Planet goals, as well as for goals on Cities (11) and Reducing Inequality (10). Conversely, data are available for all UN Global Indicators in goals on Health (3) and Infrastructure (9) for OECD countries. This analysis shows that if data were available to fill these measurement gaps, the ranking of the goals by distance to target could change dramatically.

Figure 1.4. OECD countries’ average distance to targets by SDG goal

Note: This figure shows the average distance OECD countries need to travel to reach each SDG. Distances are measured in standardised units (see ‎Chapter 3 for details), from 0 indicating that the 2030 level has already been attained, to 3 as most OECD countries have already reached this distance. Bars show OECD countries’ average performance against all targets under the relevant Goal for which data are available. Whiskers show uncertainties due to missing data, based on the alternative assumptions that either missing indicators are 3 standardised distances away from the 2030 target or that they are all already at the target level.

Source: See www.oecd.org/sdd/OECD-Measuring-Distance-to-SDGs-Targets-Metadata.pdf for detailed metadata.

 StatLink https://doi.org/10.1787/888933962740

Distances from targets also vary significantly across countries (Figure 1.5). Especially on the goals relating to Reducing Inequality (10), Oceans (14), Gender Equality (5), and Eradicating Poverty (1), some countries are much closer to the 2030 targets than others. On the other hand, performance is more uniform across countries, and generally quite good, for goals relating to Institutions (16), Economy (8), Implementation (17) and Energy (7).

Figure 1.5. Distribution of OECD countries’ distances to targets around the median, by SDG goals

Note: The charts shows the distribution of OECD countries’ distances to targets on the 17 goals; distances are expressed in standardised units. Central diamonds refer to the OECD median distance. Box boundaries indicate the first and third quartiles of the country distribution. Whiskers indicate the 10th and 90th percentiles of the country distribution.

Source: See www.oecd.org/sdd/OECD-Measuring-Distance-to-SDGs-Targets-Metadata.pdf for detailed metadata.

 StatLink https://doi.org/10.1787/888933962759

1.3.3. Trends: Are OECD countries heading in the right direction?

Previous editions of this Study have focused on countries’ current position vis-à-vis the SDG targets, rather than on the direction or pace of improvement. Yet, even when a country is already at (or near) its 2030 target, it may slip behind without continued effort. Conversely, a country that is still far from its 2030 target might still reach it by maintaining the rapid progress that it achieved in the recent past. Examining OECD countries’ recent historical performance may therefore help to assess the likelihood of reaching the targets by 2030.

Among the indicators used in this Study, time-series are available for 76 indicators to assess changes since 2005; these 76 indicators cover 63 targets (the methodology is detailed in Chapter 3). Table 1.3 shows for each indicator, the number of countries which had been moving towards target, away from target, or for which no trend is visible (either because their historical performance has been broadly stable, or because the time-series is too volatile, or too short to identify a trend data).

Patterns differ across both OECD countries and the indicators and targets considered. One-third or more of OECD countries have been moving towards the targets for 33 indicators, while for 57 indicators at least one third of OECD countries display no visible trend. Finally, for 7 indicators, more than one third of OECD countries have been moving in recent years away from their 2030 targets. These negative developments characterise the targets pertaining to Food (2.2.2 on obesity), Heath (3.b.1 on vaccination coverage), Economy (8.1.1 on GDP growth, 8.2.1 on productivity growth, and 8.5.2 on unemployment), Cities (11.6.1 on material recycling rate) and Biodiversity (15.5.1 on the conservation status of major species groups and extinction risk over time).

These results should, however, be interpreted carefully. Progress towards the target says nothing about whether the pace recently achieved by a country would be sufficient to meet the target level by 2030. The evidence in Table 1.3 should therefore be considered as only a first step towards a more extensive analysis that would allow target-by-target projections of the future trajectories for each country. Such analysis could focus on those indicators that, while not having yet reached their target levels, are moving towards them, and on those that indicators that, while having already reached the targets, have been slipping back in recent years; it could also move beyond “business as usual” scenarios, to consider the effect of policies or other drivers on these trajectories.8

Figure 1.6 summarises the evidence shown in Table 1.3 at the goal level. The overall pattern is one of moderately positive overall changes. In particular, more than one third of OECD countries have been progressing toward the targets for the goals on Health (3), Gender Equality (5), Energy (7), Infrastructure (9), Means of Implementation (17), as well as for all five goals relating to Planet. Conversely, more than half of OECD countries achieved no significant changes for the goals on Eradicating Poverty (1), Food (2), Education (4), Energy (7), Reducing Inequality (10) and Institutions (16). For the Economy goal (8), one third of OECD countries have been moving away from the SDG targets.

Figure 1.6. Average number of OECD countries by types of trends, by goals

Note: Trends are assessed through the Spearman correlation coefficient between the indicator values in different years and time. The trend is described as “movement away from the SDG target” if the correlation coefficient (corrected for the normative direction of each indicator) is significant and negative; as “progress toward SDG targets” if the correlation coefficient is significant and positive; as “no trend identified or not enough data” when the coefficient is close to 0 or not significant or there are no dataseries available. The figure shows the average number of countries for each type of trend, grouped by goals, as detailed in Table 1.3.

Source: See www.oecd.org/sdd/OECD-Measuring-Distance-to-SDGs-Targets-Metadata.pdf for detailed metadata.

 StatLink https://doi.org/10.1787/888933962778

1.3.4. Monitoring the transboundary aspects of the 2030 Agenda

Actions taken in one OECD country can have an important impact on other countries’ ability to meet the SDGs, as well as on global public goods embedded in the 2030 Agenda. It is therefore important to assess the transboundary aspects of the Agenda, i.e. the effect a country achieving the targets may have outside its borders.

Measuring transboundary impacts is a task that can imply different levels of ambition. At one extreme, measuring these effects in a comprehensive way could require a full model describing how every country has an impact on every other country and on global public goods. This is an ambitious undertaking, but also one that goes well beyond what is feasible at the present state of knowledge. The narrower approach adopted here considers the transboundary aspects of the 2030 Agenda by assessing whether achieving each SDG target by one country could have a direct impact on another country or a global public good, as illustrated in Figure 1.7. These impacts include targeted policy actions (such as ODA spending, see Box 1.3), but also countries’ contributions to global public goods (such as the environmental assets covered by several Planet goals), and unintended spill-overs (such as pollution of shared bodies of water). The methodology and specific criteria used by this Study to identify transboundary indicators are discussed in Chapter 3 and in more detail in forthcoming working paper (Shinwell, fortcoming).

Figure 1.7. How “transboundary effects” are identified in this Study

Note: The diagram describes how transboundary effects are defined for the purpose of this Study. SDG targets are identified as having a transboundary aspect if Country A’s actions to achieve the target could impact on another single country (B); other countries in general; and/or global public goods.

The analysis is based on two distinct steps. The first involves identifying SDG targets whose wording (in the 2030 Agenda) explicitly implies actions taken by a country that would have an impact “elsewhere”. The analysis finds that 97 targets can be described as having transboundary elements (57% of all 169 targets); 50 of these are “means of implementation” targets, most of which relate to financing and supporting developing countries in achieving the SDGs. Transboundary targets are heavily concentrated in the Planet goals, where they account for 76% of the total, and in the Implementation goal (95%).

The second step requires identifying, among the indicators included in the UN Global Indicator List for which data are available, those that pertain to these “transboundary targets”. Only 31 of the 97 transboundary targets are covered by 34 indicators used in this Study. However, 13 of these indicators refer to official development aid targeting specific sectors, for which no target (end value) can be established; one additional indicator cannot be assigned a normative direction (17.3.2, i.e. share of remittances of GDP), so that only for 20 indicators “distances to travel” can be assessed. Data gaps in measuring OECD countries’ performance for these transboundary targets are largest for the goals on Sustainable Production (12), Institutions (16) and Means of Implementation (17).

Figure 1.8 provides a mapping of targets between domestic and transboundary and, for the latter (97), a breakdown between targets measured by ODA indicators (14), targets measured by non-ODA indicators (17) and the large majority (66) for which no indicators are currently available.

Figure 1.8. Domestic and transboundary targets and data gaps, OECD total

Note: “Transboundary non-ODA” are targets identified as transboundary which are not related to ODA funding, “Transboundary ODA” are targets identified as transboundary which are related to ODA funding, “Transboundary data gaps” are targets identified as transboundary for which there are no available data in this study, and “Domestic targets” are targets which are not identified as transboundary.

Source: Shinwell, forthcoming.

 StatLink https://doi.org/10.1787/888933962816

Figure 1.9 shows the distance to target for the 20 indicators for which targets levels to be achieved by 2030 could be defined; these refer to targets relating to Food (2), Energy (7), Infrastructure (9), Cities (11), Means of Implementation (17) and all goals relating to Planet. Figure 1.9 suggests that OECD countries have, on average, already achieved targets for the indicators relating to protected marine areas (14.5.1), forest as a proportion of total land area (15.1.1) and the intensity of forest use (15.2.1). Distances remain significant for the indicators on sustainable fishing (14.4.1), coverage of genetic information for animal breeds (2.5.1) and, to a lesser extent, CO₂ emissions (9.4.1). These results should however be considered in the light of the data gaps described above, and of the level of ambition implicit in the target levels.

Figure 1.9. OECD countries’ average distance from target for transboundary targets

Note: This figure shows the average distance that OECD countries need to travel to reach transboundary targets at the indicator level, limited to those indicators (20) for which target levels to be achieved by 2030 could be set. Distances are measured in standardised distances (see Chapter 3 for details): 0 indicates that the 2030 level has already been attained; 3 is the largest distance (i.e. the one that most OECD countries have already travelled). Indicators are grouped by goals.

Source: See www.oecd.org/sdd/OECD-Measuring-Distance-to-SDGs-Targets-Metadata.pdf for detailed metadata.

 StatLink https://doi.org/10.1787/888933962835

Box 1.3. Measuring progress in Official Development Assistance

The 2030 Agenda recognises the critical role of official development assistance (ODA) in supporting less developed countries to achieve the ambitions of the SDGs. At a global level, the achievement of the SDGs requires greater mobilisation of both public and private resources, from both domestic and international sources, as recognised by countries in the Addis Ababa Action Agenda (United Nations, 2015[32]). The goal on Means of Implementation (17) thus includes an explicit target (17.2) on the total value of ODA that donor countries should provide as a share of their gross national income (0.7% of GNI). OECD countries can hence be assessed in terms of how far away from this ODA target level they currently are.

In addition, however, the UN Global Indicator List also includes 13 measures of ODA in specific domains, spread over 11 goals. For example, under the Health goal, one target (3b) is about supporting research and development of vaccines and medicines in developing countries, monitored through an indicator (3.b.2) referring to total net ODA to medical research and basic health sectors. In these cases, no target level (end value) is specified in the 2030 Agenda, since this would require agreeing on what the desirable distribution of ODA across these sectors should be. Indeed, how ODA is distributed across sectors will generally vary from one donor country to another, as well as across recipient countries. In the absence of a fixed target level (end value), the measuring distance methodology of this Study could not be applied to these indicators, even if they are a core aspect of SDGs monitoring.

Figure 1.10 shows, in panel A, that ODA from countries that are members of the OECD Development Assistance Committee (DAC) – the leading international forum for bilateral providers of development co-operation – has hovered at around 0.3% of GNI over the past three decades, compared with a target of 0.7% first agreed in a UN resolution in 1970 (United Nations, 1970[33]). Panel B shows that, according to the UN Global Indicator List, most ODA goes to less developed countries and to small island developing states; measured under goal 10, and, when looking at distribution across sectors, to goals relating to Climate (goal 13, USD 31 billion), and Trade (goal 8, USD 28 billion). The UN Global Indicator List does not include ODA indicators relating to goals on Eradicating Poverty (1), Gender Equality (5), Cities (11), Sustainable Production (12), Oceans (14) and Institutions (16).

Figure 1.10. Official Development Assistance from DAC countries

Note: Panel A shows (net) ODA as a share of donor countries’ GNI from 1980 to 2017. Panel B shows ODA by sectors in SDG goals.

Source: (OECD, 2017[34]), “Creditor Reporting System: Aid activities”, OECD International Development Statistics (database), https://doi.org/10.1787/data-00061-en.

 StatLink https://doi.org/10.1787/888933962854