Measuring distance to the SDG targets – Switzerland

Switzerland has already achieved 31 of the 121 SDG targets for which comparable data are available and, based on most recent trends, is expected to meet 5 additional targets by 2030 (Figure 1). As virtually all OECD countries, Switzerland has already met (or is close to meeting) most targets related to securing basic needs and implementing the policy tools and frameworks mentioned in the 2030 Agenda (see details in Table 1). Switzerland is a prosperous economy and financial centre and despite high standard of living, the environmental performance is relatively good. Yet, challenges remain. For instance, as an Alpine country, the impact of climate change may be stronger than in other countries.

This country profile provides a high-level overview of some of Switzerland’s strengths and weakness in performance across the SDG Targets. As such, it differs from Voluntary National Reviews (VNRs) or other reporting processes. To ensure international comparability, this assessment builds 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).

Switzerland is a prosperous economy and financial centre. Before the pandemic hit, it was characterised by an economic growth well above that of the OECD area (Target 8.1) and an attractive labour market. Average hourly earnings are the highest in the OECD (USD PPP 29 per hour in 2018), and the unemployment rate is low – at 5% in 2020 (Target 8.5). In 2020, the share of youth not in education, employment or training was only 7%, half the OECD average (Target 8.6). These outcomes support, and are supported by, good health outcomes (Goal 3) and by a well performing education system (Goal 4). On industry and innovation, Switzerland is also among the best performing countries: it has a strong research density, research and development expenditure account for a significant share of GDP (Target 9.5) and the relative size of manufacturing value added per capita is well above the OECD average (Target 9.2).

Despite high standard of living – and correspondingly high consumption and resource use –environmental performance is relatively good. Switzerland's greenhouse gas intensities and is the lowest in the OECD (Targets 9.4 and 13.2). This reflects low energy intensity (Target 7.3) and high share of renewables in the electricity generation (Target 7.2, 60% in 2020). Switzerland is also one of the top OECD performers in terms domestic material consumption (Targets 8.4 and 12.2). Nevertheless, environmental pressures remains significant, due to the high standard of living and correspondingly high consumption and resource use. The mean population exposure to PM2.5 in cities is slightly above the target level but is improving (Targets 12.5 and 11.6). In addition, while Switzerland has one of the highest material recovery rate of municipal waste, per capita waste is among the highest in the OECD and is higher than 15 years ago (Target 11.6).

Resilience to natural disasters need to be improved. As an Alpine country, Switzerland is impacted by climate change more strongly than other countries. According to the Federal Council, annual mean temperatures have risen by about 2°C since monitoring started in 1864, twice as much as the global mean. Yet, Switzerland has not reached the maximum score on adoption and implementation of national Disaster Risk Reduction (DRR) strategies in line with the Sendai Framework and only half of local governments have adopted and implemented local DRR strategies (Targets 1.5, 11.b and 13.1). Natural disasters cost lives and disrupt socio-economic activities and livelihoods, causing important economic costs each time they occur. While cross-country comparison need to be done carefully, the human impact of disasters (for the latest year available) is well above the OECD average, with disasters directly affecting almost 4 000 per 100 000 population and causing 9 deaths (and missing persons) per 100 000 population.

Non-medical determinants of health may undermine future prospects. Switzerland’s population enjoys good access to health care through a mandatory private health insurance that ensures universal health care coverage. While health insurance providers set standard insurance premiums per person irrespective of income, and the government relies on public subsidies aim to mitigate the regressive effects of non-income related premiums, some households face significant out-of-pocket payments (Target 3.8). In addition, as in virtually all OECD countries, behavioural risk factors – especially poor nutrition, smoking, physical inactivity and alcohol consumption – are major drivers of morbidity and mortality. In Switzerland, both alcohol and tobacco consumption (as well as alcohol use disorders), although declining, are above the OECD average (Targets 3.5 and 3.a). Conversely, obesity remains below the OECD average but is on the rise (Target 2.2). Still, mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease remains well below the OECD average, reflecting the effectiveness of prevention policies (Target 3.4).

Tackling unequal opportunities requires further efforts. There is scope to improve the legal framework that aims at fostering gender equality (Targets 5.1 and 5.3) and women are underrepresented in both the public and economic spheres (Targets 5.5 and 16.7) – around a third of senior and middle management positions are held by women. Women in Switzerland still spend more time on unpaid domestic chores and care work than men, although the gap is half an hour lower than the OECD average (Target 5.4). Beyond gender inequality, socio-economic background appears to be more closely linked to success at school than it is in many other OECD countries (Target 4.5). Income redistribution through tax and transfers is limited but the high employment rates and short spells of unemployment allow Switzerland to enjoy an income poverty rate that is below the OECD average. When considering effects beyond national borders, while the Official Development Assistance from Switzerland remains below the 0.7% of GNI target, it is above the OECD average (Target 17.2). As in many OECD countries, the high cost of sending migrants’ remittances abroad limits their full potential on recipient countries (Target 10.c).

Like in many other OECD countries, data availability remains a challenge when measuring distances to targets (see the Overview chapter for details). For Switzerland, available data on the level of the different indicators allow covering 121 of the 169 targets. As shown in Figure 2 below, indicator coverage is uneven across the 17 goals. While six 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 13 on climate action, with only 60% of their targets covered, and for Goal 14 on life below water – Switzerland is a landlocked country and some Goal 14 targets may not apply. Data gaps become starker when focusing on performance indicators, excluding those providing contextual information. In this case, coverage exceeds 80% for only two goals, i.e. Goals 3 on health and 10 on inequalities. Moreover, for seven goals, mostly within the Planet category (Goals 12, 13, 14 and 15) but also in 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.

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 Switzerland’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.

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).

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.

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.

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