Measuring distance to the SDG targets – Lithuania

Based on 118 available indicators allowing a coverage of 94 of the 169 SDG targets, Lithuania has currently achieved 16 of the 2030 targets, and many of the remaining distances to targets are small (Figure 2.41). For example, Lithuania has a very low water stress (target 6.4), low CO2 intensity (target 9.4) and a high GDP growth rate (target 8.1). However, some challenges remain; Lithuania is still very far (i.e. more than 3 standardised distances away) from meeting some 8% of the targets. For instance, Lithuania has a high incidence of tuberculosis (target 3.3), a high rate of premature mortality from non-communicable diseases (target 3.4) and a significant share of dwellings without access to basic sanitation (target  11.1).

Figure 2.41. Lithuania’s distance from achieving 94 SDG targets
Figure 2.41. Lithuania’s distance from achieving 94 SDG targets

Note: The chart shows current level of achievement on each available target. The longer the bar, the shorter the distance still to be travelled to reach 2030 target (dotted circle). Targets are clustered by goal, and goals are clustered by the “5Ps” of the 2030 Agenda (outer circle).

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

 StatLink http://dx.doi.org/10.1787/888933963633

The Measuring Distance to the SDG Targets Study is intended as an analytical tool to assist countries in identifying strengths and weaknesses across the goals and targets of the 2030 Agenda, and as such differs in nature from Voluntary National Reviews (VNRs) or other reporting processes. To ensure international comparability, indicators used in the Study are based on the UN Global List of Indicators on SDGs and are sourced from the UN SDG Database and OECD databases. VNRs typically use national indicators that reflect national circumstances and can be more up-to-date.

Figure 2.42, Panel A shows that Lithuania is on average closest to reaching goals on Sustainable Production, Climate, Energy, Economy and Implementation (goals 12, 13, 7, 8 and 17). On the other hand, Lithuania is furthest from Poverty Eradication, Gender Equality and Cities (goal 1, 5 and 11). Relative to the OECD average, Lithuania outperforms on goals such as Climate, Institutions and Implementation (goals 13, 16 and 17), as well as on goals relating to Prosperity (in particular goals 7 on Energy, 8 on Economy and 10 on Reducing Inequality). Conversely, Lithuania is relatively further away on goals such as Poverty Eradication, Health, Education, Water and Cities (goals 1, 3, 4, 6 and 11). However, considerable effort by the international statistical community will be key to fill the data gaps and allow a more accurate assessment (see Figure 2.42, Panel B). For example, if missing data were available on Sustainable Production, Climate, Oceans and Cities (goals 12, 13, 14 and 11), Lithuania’s performance on Planet and Prosperity could change from current assessments.

Figure 2.42. Lithuania’s distance from targets and data coverage, by goal
Figure 2.42. Lithuania’s distance from targets and data coverage, by goal

Note: Panel A shows the average distance the country needs to travel to reach each SDG. Distances are measured in standardised units (see Chapter 3 for details) with 0 indicating that the level for 2030 has already been attained: and 3 is the distance most OECD countries have already travelled. Bars show the average country performance against all targets under the relevant Goal for which data are available, and diamonds show the OECD average. Whiskers show uncertainties due to missing data, ranging from assuming that missing indicators are all 3 standardised distances from the 2030 target level to assuming that they are already at the target level. Panel B shows the share of targets covered by at least one indicator out of the 169 targets of the 2030 Agenda, according to the 17 goals and 5Ps.

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

 StatLink http://dx.doi.org/10.1787/888933963652

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