Measuring distance to the SDG targets – The Czech Republic

The Czech Republic has already achieved 17 of the 128 SDG targets for which comparable data are available and, based on most recent trends, it is expected to meet 9 additional targets by 2030 (Figure 1). As virtually all OECD countries, the Czech Republic 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). The Czech Republic performs well on Goals related to poverty, water and biodiversity. Still, challenges remain. The country’s strong industrial base and its reliance on coal place it among the most energy- and carbon-intensive economies in the OECD and its air pollution is a serious health concern.

This country profile provides a high-level overview of some of the Czech Republic’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 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).

Income inequality and poverty are among the lowest in the OECD area. The Czech Republic has one of the lowest poverty rates in the OECD, with a relative income poverty rate of 6% in 2018 and a multidimensional poverty rate of 12%, well below the OECD average (Targets 1.2 and 10.2), while the income of the bottom 40% of the distribution is growing faster than the national average (Target 10.1). Such a low level of poverty is partly explained by a strong, though volatile, economic growth (Target 8.1). Since transitioning from central planning, the service sector has expanded and manufacturing has become tightly integrated into global value chains. In 2020, the Czech Republic had the third highest share of manufacturing value added in GDP, at 25% (Target 9.2). The low poverty rate is also explained by the dynamism of the labour market. The unemployment rate has been continuously declining over the past decade and is now at 2.5%, one of the lowest among OECD countries (Target 8.5). 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).

On the environmental side, the Czech Republic performs well on water (Goal 6) and biodiversity (Goal 15). Substantial progress has been made in expanding protected areas, which cover 22% of the territory (above the Aichi target of 17%), with almost all terrestrial, freshwater and mountain areas that are considered key for biodiversity already protected (Targets 15.1 and 15.4). While the loss of biodiversity is a global concern, the conservation status of major species in the Czech Republic is better than in most OECD countries (Target 15.5). On water, despite scarce freshwater resources compared to other OECD countries, water stress remains low thanks to below-average and declining abstraction levels (Target 6.4). EU funds helped increase the share of population connected to public sewage treatment plants to 83% in 2019, in line with the OECD average. In turn, better access to wastewater treatment has helped improve water quality although the status of groundwater bodies remains unsatisfactory (Target 6.3).

Tackling unequal opportunities for minorities and women requires further efforts. There is scope to improve the legal framework that aims at fostering gender equality (Targets 5.1 and 5.3). Women are underrepresented in leadership positions in both the public and economic spheres (Targets 5.5 and 16.7) – around a quarter of seats in national parliament are held by women. Beyond gender inequality, more should be done to meet targets relating to equality of opportunity. Only six in ten people believe that the Czech Republic is a good place to live for racial and ethnic minorities (Target 10.3). The Czech Republic also reports a low score on diversity of central government workforce and is thus far from meeting Target 16.7 on inclusive decision-making.

The Czech economy is among the most energy- and carbon-intensive in the OECD due to its strong industrial base and heavy reliance on coal. Although declining, the intensity of greenhouse gas emissions per unit of GDP (as well as per unit of manufacturing value added) remains high (Targets 13.2 and 9.4). Energy intensive industrial activities and growing road traffic expose population to high levels of air pollution (Target 11.6). The material intensity of the Czech economy is also high (but close to the OECD average) due to large amount of coal and construction materials used in production. Still, on this front, it is not among the most intensive OECD economies. Since 2000, domestic material consumption has decreased while GDP increased, suggesting improvement in material productivity. At the same time, intensive agricultural activities exacerbate environmental challenges. Consumption of nitrogen fertiliser per hectare of agricultural land had been increasing and now exceeds the OECD average by 60% (Target 2.4).

The Czech Republic is also far away from reaching some of the targets relating to health. The health system provides a broad benefits package and few households report large health expenditures, (Target 3.8). Still, mortality due to non-communicable diseases is higher than the OECD average (Target 3.4). Among other causes, this relates to behavioural risk factors – particularly poor diet, smoking and alcohol consumption. Obesity rates have steadily increased over the past 15 years and are now around 20 % for adults (Target 2.2), contributing to high prevalence of diabetes and other diet-related diseases. Alcohol consumption is among the highest in the OECD (Target 3.5).

Like in many other OECD countries, data availability remains a challenge when measuring distances to targets (see the Overview chapter for details). For the Czech Republic, available data on the level of the different indicators allow covering 128 of the 169 targets. As shown in Figure 2 below, indicator coverage is uneven across the 17 goals. While nine Goals (within the Prosperity, Planet and People categories) have most of their targets covered (the indicator coverage exceeds 80%), coverage is much lower for Goal 5 on gender equality with around half of its targets covered, and for Goal 14 on life below water with 30% – the Czech Republic is a landlocked country and some Goal 14 Targets may not apply. Data gaps become starker when focusing on performance indicators, excluding those relating to contextual information. In this case, coverage exceeds 80% for only three goals (Goals 3, 4 and 10). Moreover, for eight goals (including all five Goals of the Planet category, 5 on gender equality, 11 on cities and 17 on partnerships), data are lacking to monitor progress 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 The Czech Republic’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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