Published statistics

Statistics on electric vehicle (EV) recharging stations are necessary due to the increasing importance of electro-mobility and the rising share of electric cars. Eurostat currently publishes regional statistics on the number of electric vehicles, at NUTS 2 level, through a voluntary regional data collection.

New data sources, such as proprietary data available to the European Alternative Fuels Observatory (EAFO), enable the calculation of statistical indicators to assess the density and distribution of recharging stations by energy capacity at NUTS 3 level with the aim to enrich the regional statistics without additional burden to national authorities.

Statistics under development on the distribution and density of recharging stations for electric vehicles are calculated using annual data available from EAFO which is then complemented by the open-sourced OpenStreetMap (OSM) data to enable routing calculations and by the NUTS classification to enable the aggregation and calculation of the indicators at NUTS 3 level.

Data are published via a dataset in the database.

Statistics on public transportation are crucial for effective planning and development, allowing city planners and transportation authorities to design systems that meet demand and optimize routes and schedules. Furthermore, statistics on the availability and efficiency of public transportation are considered valuable for promoting alternative modes of travel in support to the objectives of the EU sustainable and smart mobility strategy.

New data sources, such as the General Transit Feed System (GTFS) database on public transportation and the Open Street Map (OSM), enable the calculation of statistical indicators aiming to enrich regional statistics without additional burden to national authorities.

Statistics under development on the availability and efficiency of public transport are calculated using two open-sourced data, from the General Transit Feed System (GTFS) database and the Open Street Map (OSM). The two datasets are then complemented by the NUTS classification to enable the aggregation of the indicators at NUTS 3 level. The Eurostat 2021 Census population Grid data is also added to factor in the percentage of population covered by public transport compared to passenger cars.

Data are published via a dataset in the database.

The job vacancy rate by occupation and region offers detailed insights into labour demand in the EU. These statistics under development address critical data gaps in official job vacancy statistics by informing about employers’ recruitment needs at both occupational and regional levels. This information is partly derived from a novel data source on online job advertisements collected thanks to the web-scraping of hundreds of online job portals.

The corresponding dataset is published in Eurobase, the dissemination database of Eurostat.

The multi-country national accounting matrices based on the FIGARO tables (FIGARO-NAM) are a powerful tool to deepen the understanding of the EU’s economic dynamics.

The FIGARO-NAM data link the real sector economy with capital and financial accounts, highlighting resource allocation across institutional sectors and their interactions with industries and products. They provide a more comprehensive picture of the economic structures across the 27 EU countries and their main trading partners.

Data are published via Excel and CSV files.

Tourism satellite accounts (TSA) assess the macro-economic dimension of the tourism sector and give insights on its contribution to the European economies. TSA complement the existing tourism statistics that usually focus on physical tourism flows rather than monetary flows. Countries compile TSA guided by the international recommendations laid down in the TSA recommended methodological framework, albeit with different levels of implementation and comparability.

These statistics under development are based on a 3-yearly data collection by Eurostat, in which countries can share their available TSA indicators on a voluntary basis. This exercise produces tables comprising data for most EU countries as well as estimates of EU aggregates. The data include information on tourism consumption broken down by origin of the guest, type of visitor, or information on how much tourism contributes to the economy in terms of gross value added.

Data are published via a Statistics Explained article.

Timely statistics on port activity and maritime vessel traffic are important for monitoring fluctuations in economic activity. Information on port calls is currently published by Eurostat quarterly approximately one year after the end of each quarter.

New data sources, such as the automatic identification system (AIS) and administrative data available to the European Maritime Safety Agency (EMSA), enable early estimates of maritime vessel traffic within few weeks after the end of the reference period. Additionally, the use of new data sources does not create additional burden to respondents.

Statistics under development on early estimates of maritime vessel traffic are based on official Eurostat statistics of previous quarters, AIS and administrative data available to EMSA. The autoregressive integrated moving average model with exogenous variables (ARIMAX) is used to combine input data and to estimate port calls by vessel type at EU level shortly after the end of each quarter. The estimation method was tested for the period 2015-2019. Eurostat is planning to test further the developed method and update regularly the port call estimates for the most recent quarter.

Data are published via a dataset in the database.

Industry concentration is the degree to which production in an industry or in the whole economy is dominated by a few large firms. These statistics under development are the first effort to calculate the industry concentration in the EU for sections of the statistical classification of economic activities (NACE). This is done based on data available in the EuroGroups register (EGR) and from structural business statistics (SBS). The EGR is the central statistical business register used by Eurostat and the EU and EFTA countries' statistical authorities. SBS data contain the detailed structure, economic activity, and performance of businesses over time.

Data are published via a Statistics Explained article and an Excel file.

The European space economy thematic account aims to provide a harmonised framework for the production of reliable and comparable statistics on the space economy in Europe. It covers the main gross domestic product (GDP) indicators, such as output, gross value added, and employment in the space sector. This approach offers multiple possibilities for economic analyses and measurement of the space economy in Europe.

The first published results on the EU space economy concern data on exports and imports of spacecraft, including satellites, and spacecraft launch vehicles. The results cover the time series 2010 to 2021. In addition, the following publications have been released:

• the list of comparable statistical codes to measure the space economy at international, North American, and European levels
• the methodology to build the European space economy thematic account.

Data are published via an Excel file and 2 publications.

Statistics on labour market demand for ICT specialists in online job advertisements (OJAs) provide detailed and timely information on employers’ needs for digital professionals. These statistics under development are produced using OJAs collected from hundreds of online job portals. The job advertisements are obtained through web scraping. The information retrieved from these ads are processed to classify them according to variables, such as occupation or location.

Data are published via datasets in the database.

Multifactor productivity (MFP) is a measure of economic performance that compares the amount of goods and services produced (output) to the amount of combined inputs used to produce those goods and services.

In simple terms, a change in MFP can be described as the change in the volume of output (expressed in terms of real gross value added) that cannot be explained by changes in the quantity (and quality) of capital and labour inputs used to generate that output.

Data are published via an Excel file.

The flash estimates on income inequality and poverty indicators are an answer to the policy demand for providing timelier data in the social domain. They measure the yearly changes of main income distribution indicators, including the at-risk-of-poverty rate and the income quintile share ratio. Flash estimates should estimate to the extent possible the values captured in the EU-SILC survey. They are mainly based on microsimulation models which make use of EUROMOD, the tax benefit model at EU level developed by the institute for social and economic research (ISER) at the University of Essex.

Flash estimates have a release date appreciable earlier than the actual data. These can complement the EU-SILC data and feed preliminary discussion and analysis until the final EU-SILC data is released.

Data are published in a report.

Income and consumption aggregates drawn from national accounts (macro-level data) describe the situation of households as an institutional unit in the macroeconomic context. Income distribution (from the EU Statistics on Income and Living Conditions, EU-SILC) and consumption data (from the Household Budget Survey), on the other hand, are based on micro-level data and used to measure inequalities in the context of social policies.

Differing concepts and data collection practices mean that the messages from these different sources do not necessarily lead to the same conclusions as regards people’s prosperity. By comparing micro- and macro-level statistics on households, we can understand their complementarities and differences, and build robust links between the data sources.

Social surveys and national accounts are compared as regards household income and consumption by analysing methodological concepts as they apply to data sources and underlying data.

Data are published via Excel files.

QALI estimates the growth of hours worked (Labour Input) taking into account the quality of the workforce based on experience and skills.

To do so, QALI combines macrodata (from national accounts) and microdata (from surveys EU Labour Force Survey (LFS), EU Structure of Earnings Survey (SES), EU Statistics on Income and Living Conditions (EU-SILC)) and the information provided is more detailed in comparison to when only macrodata are used.

The QALI indicator should be considered as statistics under development for several reasons: some detailed results can't be published because of confidentiality and reliability of data sources, the definition of employment in LFS differs from that used in national accounts, SES as a four-year survey should be interpolated for the years in between, industry classification has changed in 2008. Moreover, the weighing of hours using earning shares is not an assumption used in core national accounts.

Nevertheless, the approach used to produce the QALI indicator gives a more detailed picture of the input of labour to the production process. QALI is a more suitable method to use in growth accounting analyses as it better explains GDP developments.

Data are published via Excel files.

Analysis of and aggregated data tables on the structure of multinational groups in the EU. The analysis is based on data from the EuroGroups Register (EGR) - the central statistical business register used by Eurostat and the EU and EFTA countries' statistical authorities. The EGR covers multinational enterprise groups operating in the EU and provides yearly data on them. EGR data are considered as statistics under development because they are incomplete and not fully accurate.

Data are published via a Statistics Explained article.

The joint distribution of income, consumption and wealth designates the links and interplay between the three economic dimensions. These data help at describing material well-being and households' economic vulnerability and contribute to explain the dynamics of wealth inequalities. These statistics under development were produced by Eurostat by merging information coming from different databases so as to obtain a fused dataset containing information on the three dimensions for each observation.

Data are published via a dataset in the database.

Labour market transition statistics show the movements of individuals between employment, unemployment and economic inactivity. These statistics present estimated breakdowns (by sex, age and duration of unemployment) that are important to understand the differences in transition probabilities between different groups.

Data are published via a dataset in the database.