Measuring distance to the SDG targets – Slovenia
Slovenia has already achieved 24 of the 135 SDG targets for which comparable data are available and, based on recent trends, is expected to meet 4 additional targets by 2030 (Figure 1). As virtually all OECD countries, Slovenia has already met (or is close to meeting) most targets related to securing basic needs and implementing the policy tools and frameworks mentioned by the 2030 Agenda (see details in Table 1). It also displays some strengths on targets relating to income inequality and poverty (Goals 1 and 10) as well as in the Planet category (with the exception of Goal 14 on life below water). Yet, challenges remain. As in many OECD countries, behavioural risk factors are a challenge to people’s health and women's representation in the leadership positions need to be increased. In addition, there is scope to improve the accountability and diversity of public institutions.
This country profile provides a high-level overview of some of Slovenia’s strengths and challenges in performance across the SDG targets. As such, it differs in nature from Voluntary National Reviews (VNRs) or other reporting processes. To ensure international comparability, this assessment draws on the global indicator framework and relies on data sourced from the SDG Global Database and OECD databases. VNRs typically use national indicators that reflect national circumstances and are more up-to-date (see section How to read this country profile that provides some methodological details on country profiles).
Source: All data is taken and adapted from (UNDESA, 2021[1]), SDG Global Database, https://unstats.un.org/sdgs/unsdg and (OECD, 2021[2]), OECD.Stat, https://stats.oecd.org/ (accessed on 29 October 2021).
Income inequality and poverty in Slovenia are among the lowest in the OECD area. Slovenia has one of the lowest poverty rates in the OECD, with a relative income poverty rate of 8% in 2018 and a multidimensional poverty rate of 14%, well below the OECD average (Targets 1.2 and 10.2). Such low levels of poverty are partly explained by the breadth of redistribution through taxes and transfers, which reduce the Gini coefficient by 36% (Target 10.4), almost 50% more than for the OECD average. The low poverty rate is also explained by the dynamism of some economic sectors such as manufacturing (Target 9.2) as well as favourable developments in the labour market. The unemployment rate has been continuously declining over the past decade after a peak in 2013 and is now at 5% (Target 8.5), while the share of youth not in employment, education or training is at 9% (Target 8.6). Still, earnings remain below the OECD average (Target 8.5) and convergence of income levels towards the OECD average has stalled, reflecting weak labour productivity growth (Target 8.2).
Slovenia is pursuing an ambitious environmental policy. It is a leader on waste management, topping the OECD league on recycling (Targets 11.6 and 12.5) while per capita consumption of materials decreased despite economic growth (Targets 8.4 and 12.2). Slovenia is also well below the OECD average on food waste (Target 12.3) and enjoys an extraordinarily rich biodiversity and landscapes due to its location at the junction of several ecological systems. Slovenia’s natural endowment are enhanced by a tradition of close-to-natural forest management (Target 15.2). Further, protected areas cover 40% of the terrestrial area, well beyond the 2020 Aichi Biodiversity Targets of 17%. Yet, around 20% of freshwater, terrestrial and mountain areas that are considered as key for biodiversity are not protected (Targets 15.1 and 15.4) and life below water remains much less protected. Less than 4% of Slovenia’s (very limited) exclusive economic zones are protected and around 40% of the key biodiversity areas remain unprotected. As many other OECD countries, Slovenia has implemented some of the policy instruments listed under the Planet category, including on Targets 14.6 on harmful subsidies to fisheries and 15.8 on invasive alien species.
As in many OECD countries, behavioural risk factors are a challenge to people’s health. The Slovenian health system provides near universal coverage and a broad benefit package. Voluntary health insurance plays a large role in providing co-payments for health services and in lowering out-of-pocket payments (Target 3.8). As in many OECD countries, a large share of all deaths in Slovenia can be attributed to behavioural risk factors, including tobacco smoking, poor diet, alcohol consumption and low physical activity (Target 3.4), while air pollution also contributes to a sizeable number of deaths (Target 3.9). Around one fifth of Slovenian people are obese (Target 2.2) while alcohol intake ranks above the OECD average, contributing to alcohol use disorder that are much more prevalent than in other OECD countries (Target 3.5). Smoking prevalence has decreased for both adults and adolescents over the last decade, but over one in six adults are still daily smokers (Target 3.a).
Women's representation in the leadership positions could increase. While the share of women in managerial positions is around 40%, women held only 27% of the seats in the Slovenian Parliament (Target 5.5). In the private sphere, Slovenian women spend longer time in unpaid care and domestic work than men (Target 5.4) – with a gap of two hours, in line with the OECD average. There is also scope to foster inclusion beyond gender. One-fourth of adults do not achieve a minimal level of proficiency in numeracy and literacy (Target 4.6). Also, Slovenia only partially meets the requirements to facilitate orderly, safe, regular and responsible migration (Target 10.7).
There is scope to improve the accountability and diversity of public institutions. While global data to monitor the accountability and transparency of public institutions are not yet available, proxy measures show that only 42% of citizens reported having confidence in their country's judicial system and courts (Target 16.6). On diversity, youths and women are not well represented in the parliament, and Slovenia reports a low score on diversity of central government workforce (Targets 5.5 and 16.7) and below OECD average scores on the World Justice Project's index of civil justice (Target 16.3).
Like in many other OECD countries, data availability remains a challenge when measuring distances to targets (see the Overview chapter for details). For Slovenia, available data on the level of the different indicators allow covering 135 of the 169 targets. As shown in Figure 2 below, indicator coverage is uneven across the 17 goals. While eleven goals (within the People, Planet and Prosperity categories) have most of their targets covered (the indicator coverage exceeds 80%), coverage is lower for Goals 11 on cities and 14 on life below water, with 60% of their targets covered. Data gaps become starker when focusing on performance indicators, excluding those providing contextual information. In this case, coverage exceeds 80% for only Goals 3 on health and 4 on education. Moreover, for seven goals, mostly within the Planet category (Goals 12, 13, 14 and 15) but also Goals 5 on gender equality, 11 on cities and 17 on partnerships, data are lacking to monitor changes over time for more than two in three targets.
Note: The figure represents Slovenia's share of targets covered by at least one indicator for each SDG. Numbers from 1 to 17 stand for the goals: 1 No poverty, 2 Zero hunger, 3 Good health and well-being, 4 Quality education, 5 Gender equality, 6 Clean water and sanitation, 7 Affordable and clean energy, 8 Decent work and economic growth, 9 Industry, innovation and infrastructure, 10 Reduced inequalities, 11 Sustainable cities and communities, 12 Responsible consumption and production, 13 Climate action, 14 Life below water, 15 Life on land, 16 Peace, justice and strong institutions and 17 Partnerships for the goals. These goals are grouped under five broad themes (the “5Ps”): People, Planet, Prosperity, Peace and Partnership. Beyond data availability, other statistical gaps such as timeliness or granularity also need to be considered. For instance, given the lag in available data, the effects of the pandemic on current distance and trajectories may not be reflected in the estimates.
Source: All data is taken and adapted from (UNDESA, 2021[1]), SDG Global Database, https://unstats.un.org/sdgs/unsdg and (OECD, 2021[2]), OECD.Stat, https://stats.oecd.org/ (accessed on 29 October 2021).
While some SDG Targets are, on average, close to being met, performance is very uneven across the 17 Goals of the 2030 Agenda for Sustainable Development. Table 1 presents an overview of Slovenia’s progress towards targets based on available data for each of the 17 Goals. It shows that distances to Targets and trends over time differ significantly even when considering a specific goal.
The OECD report The Short and Winding Road to 2030: Measuring Distance to the SDG Targets evaluates the distance that OECD countries need to travel to meet SDG targets for which data are currently available. It also looks at whether countries have been moving towards or away from these targets, and how likely they are to meet their commitments by 2030, based on an analysis of recent trends and the observed volatility in the different indicators.
As most authors and international organisations, this report adopts a rather simple geometric growth model for assessing the direction and pace of recent changes in the context of the SDGs. Yet, instead of making direct estimates of the value of the indicator by 2030, it models the likelihood of achieving a specific level using Monte Carlo simulations.
While the report provides an overview of where OECD countries, taken as a whole, currently stand, country profiles provide details of the performance and data availability of individual OECD countries.
How to read the OECD SDG Wheel?
Progress on SDGs requires a granular understanding of countries’ strengths and weaknesses based on the consideration of the 169 targets of the 2030 Agenda. Figure 1 shows both current achievements (in the inner circle; the longer the bar, the smaller the distance remaining to be travelled) as well as whether OECD countries are on track (or are at least making progress) to meet their commitments by 2030 (in the outer circle).
The length of each bar shows current level of achievement on each target. As detailed in the Methodological Annex, countries’ distance to target is measured as the “standardised difference” between a country’s current position and the target end-value. For each indicator, the standardised measurement unit (s.u.) is the standard deviation observed among OECD countries in the reference year (i.e. the year closest to 2015). Therefore, the longer the bar, the shorter the distance still to be travelled to reach the target by 2030. The colours of the bars applied to the various targets refer to the goals they pertain to.
The outer ring shows how OECD countries are performing over time and how likely they are to meet the different targets by 2030 based on the observed trends of the various indicators. It uses stoplight colours to classify the progress towards the target:
green is used to indicate those countries that (based on the change in the different indicators over a recent period) should meet the target in 2030 just by maintaining their current pace of progress (i.e. more than 75% of (randomised) projections meet the target);
yellow for those countries whose current pace of progress is insufficient to meet the target by 2030 (i.e. less than 75% of randomised projections meet the target, while the correlation coefficient between the indicator and the year is high and statistically significant, implying that a significant trend could be detected); and
red for those countries whose recent changes have been stagnating or moving them further away from the target (i.e. less than 75% of randomised projections meet the target and the correlation coefficient between the indicator and the year is low or statistically insignificant, implying that no statistical trend could be identified).
How to read the Strength and Challenges sections?
With the aim of helping its member countries in navigating the 2030 Agenda and in setting their own priorities for action, this report relies on a unique methodology for measuring the distance that OECD countries have to travel to achieve SDG targets. The identification of the main strengths and challenges proposed in this report relies on current performances only:
A target is considered to be a strength when the distance to the target end-value is lower than 0.5 s.u. (i.e. the distance is deemed to be small) or when the country is closer to the target than the OECD average. For instance, while Korea's distance to Target 2.2 on malnutrition is 1.4 s.u. (i.e. classified as medium distance), the average OECD distance is 2.5 s.u. Therefore, Target 2.2 is categorised as being a strength for Korea.
A target is considered to be a challenge when the distance to target is greater than 1.5 s.u. (i.e. distance is deemed to be long) or when the country is further away from the target than the OECD average. For instance, Estonia's distance to Target 4.2 on pre-primary education is 1.1 s.u. (i.e. medium distance), which is higher than the 0.24 s.u. distance for the OECD average. Target 4.2 is therefore classified as a weakness for Estonia.
While the lack of consistent time series often prevents an exhaustive assessment of trends, they are discussed when available and relevant in nuancing the assessment of current performance.
How to read the Statistical Gaps section?
In total, this report relies on 537 data series supporting 183 of the 247 indicators listed in the global indicator framework (or for close proxies of these indicators). These indicators cover 134 of the 169 SDG targets. Yet, target coverage is uneven across the 17 goals and among OECD member countries.
Figure 2 summarises data availability:
darker blue bars indicate the share of targets for which at least one indicator (including indicators providing context information) is available
lighter blue bars indicate the share of targets for which the available indicator(s) include those having a clear normative direction (i.e. allowing to distinguish between good and bad performance), which are the only ones used to measure distances to target levels.
medium blue bars indicate the share of targets for which progress over time can be gauged (i.e. at least three observations are available over a five-year period).
All methods and concepts are further detailed in the Methodological Annex.