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Single Market Scoreboard

Economic resilience

Investment, innovation, trade and dependencies – why does it matter?

The single market’s scale and policies help increase the economic resilience of the EU economy by strengthening incentives to investment and innovation, playing a large role in global trade and tackling strategic dependencies in key areas.

The indicators in this section measure the performance of the single market in terms of its ability to drive investment, research and development (R&D), innovation and skills. These are key factors contributing to the EU’s long-term competitiveness. This section also looks at the single market’s current performance in the global scene by looking at the importance of the EU economy in external trade, the impact of dependency on non-EU countries for certain goods, and trends in energy prices.


Public investment as share of gross domestic product (GDP)

This chart shows the trend in public investment (gross fixed capital formation) as a share of annual GDP for the EU, the UK and the USA. The 2023, 2024 and 2025 values are forecasts.

Public investment is a measure of how much money a country spends to increase the value of fixed assets (for example, road infrastructure, buildings, equipment and intangibles). This investment is necessary for providing various public services, such as public administration, schools, hospitals, police and the army. A higher level of public investment leads to more capacity to deliver public services, resulting in, for example, improved roads, better healthcare and increased public safety.

The share of public investment in GDP increased during 2020, the first year of the COVID-19 pandemic. This increase was the result of more investment in public health and a fall in GDP. In the EU, public investment is supported by the NextGenerationEU initiative. However, a challenge to both public and private investment is the tightening of monetary policy due to higher inflation rates in 2023, which could lead to more restrictive financing conditions.

Source: European Commission, annual macroeconomic (AMECO) database

Private investment as a share of GDP

This chart shows the trend in private investment (gross fixed capital formation) as a share of annual GDP for the EU, the UK and the USA. The 2023, 2024 and 2025 values are forecasts.

The data refer to the increase of the capital stock belonging to enterprises and individuals, including equipment, land, houses and other buildings, and intangibles like R&D.  It measures how the private sector improves its capacity to produce goods, deliver services and increase income in the future. 

Private investment in the EU has recovered from its fall during the COVID-19 pandemic. As a share of GDP, it is currently higher than the UK and the USA’s. Forecasts indicate further increases in 2023, 2024 and 2025, supported by NextGenerationEU, meaning that the EU economy should develop faster. However, a challenge to both public and private investment is the tightening of monetary policy due to higher inflation rates in 2023.


Source: AMECO

R&D expenditure as a percentage of GDP

The following chart shows the development of annual R&D expenditure as a percentage of GDP for the EU, China, Japan, the UK and the USA.

EU R&D intensity grew from 2.12% to 2.27% of GDP between 2015 and 2021. However, it remains below that of the USA (3.46% in 2021), Japan (3.34% in 2021) and China (2.40% in 2020). With a gap of 0.73 percentage points, the EU remains some distance from its ambition to raise R&D intensity to 3% by 2030.

Source: Eurostat, OECD Main Science and Technology Indicators

Innovation and skills

Share of EU small and medium-sized enterprises (SMEs) introducing product innovation

This indicator measures the share of SMEs that introduced at least one product innovation either new to the business or new to its market.

Product innovation is a key ingredient for innovation as it can create new markets and improve competitiveness. Higher shares of product innovators reflect a higher level of innovation activities.

SMEs include all businesses with 10 to 249 employees, i.e. excluding micro-enterprises.

Source: Eurostat, Community Innovation Survey, 2010-2020

Number of patent applications per million inhabitants

The chart shows:
a)    the number of patent applications to the European Patent Office (EPO) by EU applicants per million population
b)    the number of patents filed under the Patent Cooperation Treaty (PCT) per million population by applicants’ country of residence. 

A patent application to the EPO can provide protection in up to 44 countries, including all EU countries, whereas a PCT patent application can provide protection in the 157 contracting states to the PCT. The number of EPO patent applications and PCT patent applications should not be directly compared because each system provides differing geographical scopes of protection.

Patent applications to the EPO by EU applicants grew on average by 1% every year between 2015 and 2022, reaching 151 per million inhabitants in 2022.

The number of PCT patent applications filed by EU applicants remained stable between 2015 and 2020, slightly decreasing between 2020 and 2021 to around 100 per million inhabitants. This figure is significantly lower than the number of PCT patent applications filed by applicants residing in Japan (358.87 per million inhabitants in 2021) and the USA (168.99) but higher than in China (39.03) and the UK (86.20).

Source: Eurostat (EPO patents), OECD (PCT patents), World Bank (population)

University rankings

These indicators show the number of universities in the global top 50 of two rankings: the Times Higher Education World University Rankings and the Shanghai Academic Ranking of World Universities.

Both sources show that the EU has far fewer universities in the top 50 than the USA and slightly fewer than the UK, even though the UK has a significantly smaller population. However, the EU comes in ahead of both China and Japan. The number of EU universities in the global top 50 has remained relatively stable over time.

Shanghai Academic Ranking of World Universities is based on research output (40%), the quality of faculty (40%), the quality of education (10%) and the per-capita academic performance (10%). Detailed information can be found at

The Times Higher Education World University Ranking is based on research output (30%), citations (30%), teaching (30%) and others (10%). Detailed information can be found at

World University Rankings
Academic Ranking of World Universities

Source: Times Higher Education, Shanghai Ranking Consultancy

Average test scores for 15-year-olds (PISA)

This chart shows the PISA scores of 15-year-olds in mathematics, reading and science in 2022, 2018 and 2015.

EU data are the average scores of the 27 Member States, weighted by the number of 15-year-olds enrolled in education. In 2022, Luxembourg did not participate so is not included in the EU average. Chinese data come from the following four Chinese provinces/municipalities that participated in PISA 2018: Beijing, Shanghai, Jiangsu, and Zhejiang. In 2022, China was unable to collect data because schools were closed during the intended collection period. In PISA 2015, Chinese data came from Beijing, Shanghai, Jiangsu, and Guangdong.

Overall, EU students underperform compared to their peers in the UK, the USA, Japan and China. Compared to 2018, EU students performed worse in 2022 in all three disciplines.

Source: OECD PISA database

Trade and strategic autonomy

Exports of goods and services as a share of the rest of world's imports

The chart shows the exports of goods and services of the EU, the UK, the USA, Japan, and China as shares of the rest of the world’s imports from 2015 to 2022. This helps evaluate the relative importance of exports from the EU and those four countries in the global market. A higher percentage indicates a more significant role in the global economy, and a lower percentage suggests a smaller presence.

The indicator is calculated using goods data from the Comtrade database and services data from the Word Bank’s World Development Indicators. Trade within the EU is not considered in the rest of the world’s imports or in the EU’s exports. The amount of trade in services within the EU and from the EU are estimated using ratios calculated with Eurostat data.

In 2022, EU exports in goods and services accounted for 16.2% and 33.1% of the rest of the world's imports, respectively. Among the countries featured in the chart, only China’s goods exports captured a larger share of its respective applicable market than the EU’s.

Source: Eurostat [bop_its6_det], UN Comtrade, World Bank

Global market share in medium- and high-technology manufacturing

This chart shows the global market share in medium- and high-technology manufacturing (gross value added) of the EU, China, Japan, the UK and the USA.

The data shows the gradual decline in the EU’s global market share in medium- and high-technology manufacturing value added. It also shows the somewhat faster fall in the US share. These decreases are the result of economic expansion in other countries, especially China (although there are only data for China’s market share from 2015, its contribution to global medium- and high-technology manufacturing value added has been estimated for previous years).

Source: UN Industrial Development Organization, Competitive Industrial Performance database; World Bank databases; Commission estimates

Global market share in high-technology exports

This chart shows the global market share in high-technology exports of the EU, China, Japan, the UK and the USA.

The chart shows that high-technology export market shares have been relatively stable over the past decade. Together, the EU and China account for half of total world-wide high- technology exports.


Source: World Bank

Strategic dependencies: overview

This chart shows the level of import dependencies in sensitive ecosystems1 in the EU, the UK, the USA, Japan and China, using two indicators: the number of dependent goods (left axis) and the share of dependent goods in the total import value (right axis). For each indicator, a higher value suggests higher import dependency.

The methodology used to identify dependencies is based on a modified version of the approach proposed by Arjona et al. (2023). All products imported by the EU from 2017 to 2020 are analysed as follows.

  • A product is considered to be foreign dependent in a given year if it fulfils two criteria:
    1. most imports come from fewer than three foreign countries
    2. imports are higher than exports.
  • Only the top 10% of the most dependent products that meet these criteria each year are considered.
  • Only the more persistent dependencies between 2017 and 2020 are retained, i.e. those identified in 2020 and/or at least 2 previous years. The final list is then limited to products belonging to sensitive ecosystems, which include (1) security and safety; (2) health; and (3) the green and digital transformations. Due to the definition of ecosystems being set at the NACE industry level, the alignment between HS6 products and sensitive ecosystems is rather approximate.

The EU has dependencies for 338 goods belonging to sensitive ecosystems. Among the countries in the chart, only Japan has fewer dependencies (279). China, the UK and the USA have a slightly higher number of dependencies. Furthermore, for the EU, dependent goods belonging to sensitive ecosystems account for only 11% of the total import value in the reference period. For all other countries, these account for more than 14%. Overall, the EU appears to have a lower overall degree of import dependencies in sensitive ecosystems compared with China, the UK and the USA. Despite similarities in these overall numbers, there are differences in the potential for further diversification of each area, as measured by global single points of failure2 (SPOF). The EU and the US face more SPOFs and thus a more limited potential for further diversification for a majority of the identified dependent products, while China faces SPOFs for less than 30% of its dependencies. 
Moreover, the EU appears more dependent on China than vice-versa. Over the period 2017 to 2020, the EU has been dependent on China on 147 products (out of the 338 outlined above), representing approximately 6.5% of total imports, while China has been dependent on the EU on 90 products (out of a total of 340 strategic dependencies), representing approximately 1.5% of total imports.

1 As defined in Commission Staff Working Document “Strategic dependencies and capacities” (2021).

2 As defined in An enhanced methodology to monitor the EU’s strategic dependencies and vulnerabilities - European Commission ( (2023). 

Source: European Commission

Strategic dependencies on raw materials

This chart shows the import concentration for a basket of critical raw materials in 2023 (data up to July) for the EU overall and each EU country. Import concentration measures how much a country relies on a limited number of sources for most of its imports. A value above 0.25 indicates a high degree of import concentration, a value between 0.15 and 0.25 indicates a moderate degree of import concentration, and a value below 0.15 indicates a low degree of import concentration. The lower the value, the better.

This indicator is calculated by taking a weighted average of the concentration of imports from outside the EU (in values) for each critical raw material at EU level. The weighted average corresponds to the respective proportion of each critical raw material in the entire basket imported by the EU and each EU country (in values).

The chart reveals a moderate level of import concentration for the EU overall, with a value of 0.22. Among EU countries, eight have import concentration levels higher than the EU average. In particular, three of them have a high level of import concentration, with values exceeding 0.25.

Source: European Commission

Electricity prices for non-household consumers

The chart shows non-household retail electricity prices in the EU, UK, USA and Japan. This indicator gives an idea of energy costs and cost-competitiveness, especially for those industries where electricity prices make up a significant proportion of total energy costs.

Non-household retail electricity prices in the EU are calculated using Eurostat data, broken down into two consumption bands. The data are from the first half of 2015 and are measured in euro per KWh, excluding VAT and other recoverable taxes.

  • The IC consumption band refers to medium-sized consumers with an annual consumption of between 500 MWh and 2 000 MWh, i.e the vast majority of small sized enterprises in services and manufacturing sectors, and gives an insight into  affordability.

  • The ID consumption band refers to large-sized consumers with an annual consumption of between 2 000 MWh and 20 000 MWh, such as in electricity intensive manufacturing sectors, and gives an insight into  international competitiveness.  Only this band is used for international comparisons.

Since 2021, average prices in the EU, the UK and Japan have been on a similar clear upward trend. The latest values are €0.16 per KWh for Japan (in the first half of 2022), €0.21 per KWh for the EU and €0.28 per KWh for the UK (both in the first half of 2023). However, prices in the USA (€0.07 per KWh) have remained significantly lower than in the EU, like in most other G20 countries, particularly those with emerging industrial economies.

Source: Eurostat 'Electricity prices for non-household consumers - bi-annual data (from 2007 onwards)' [NRG_PC_205]. International prices are reported for the USA, UK and Japan, using data from the US Energy Information Administration (EIA), the UK Department for Energy Security and Net Zero (DESNZ) and the International Energy Agency (IEA).

Electricity price volatility

This chart shows the relative difference in electricity prices in the EU, Japan, the UK and the USA. The coefficient of variation of electricity prices is used, which is the standard deviation of daily wholesale spot market electricity prices, divided by their annual mean.

The 2023 data covers prices up to early September. The EU values are calculated using the average prices of the following hubs: France, Germany, the Netherlands, Spain and Nordpool, weighted by traded volumes. The USA values are calculated using the arithmetic mean of the prices of the following hubs: PJM Western, NYISO Hudson Valley, MISO Indiana, ISONE Internal, ERCOT North and CAISO SP15 (the unweighted average is used because data on trading volumes are not available). For Japan, monthly prices from March 2023 are used (instead of daily prices), leading to an underestimation of price volatility for 2023.

Prices in 2023 have stabilised compared with the very volatile period between 2020 and 2022 but remain somewhat more volatile than between 2015 and 2019. Price volatility in the EU is comparable with that of Japan and the UK and is lower than in the USA.

Sources: S&P Global Platts (FR, DE, NL, ES, USA), Nord Pool (GB, Nord Pool markets - NO, DK, FI, SE, EE, LT, LV), Japan Electric Power Exchange

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