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EU Blue Economy Observatory



Structural Business Statistics (SBS) compiled by Eurostat. The SBS were complemented by the EU Data Collection Framework (DCF)[1] for the primary sectors (capture fisheries and aquaculture). Given the time lag in the release of SBS and DCF data, the latest available year is 2020, which is used as the reference year for the current report.

For Coastal tourism, an ad hoc extraction of data was performed by Eurostat, which was complemented with information from the Eurostat’s nights spent at tourist accommodation establishments.

For the calculation of the maritime proportions, some specific sources were used as explained in the specific below. Finally, GDP and its components as published by Eurostat as well as the employment from the Labour Force Survey (LFS) were used for the comparisons of the Blue Economy with the overall economy.

The tables extracted from the Eurostat (and from the DCF) to make the estimations of economic indicators for the established sectors of the EU Blue Economy are summarised in next Table 1.

Table 1: Main data sources for the Established Sectors of the EU Blue Economy






Fisheries and aquaculture economic statistics.



Annual detailed enterprise statistics for services (NACE Rev. 2 H-N and S95).



Annual detailed enterprise statistics for construction (NACE Rev. 2, F).



Annual detailed enterprise statistics for trade (NACE Rev. G).



Annual detailed enterprise statistics for industry (NACE Rev. 2 B-E).



Expenditure by inbound tourists (from other EU countries) in each Member States. Ad hoc extraction by Eurostat.



Nights spent at tourist accommodation establishments by coastal and non-coastal areas.



GDP and main components (output, expenditure and income).

Prodcom (DS-066341)


Sold production, exports and imports by PRODCOM list (NACE Rev. 2) - annual data.

[1] Council Regulation (EC) No 199/2008 of 25 February 2008 concerning the establishment of a Community framework for the collection, management and use of data in the fisheries sector and support for scientific advice regarding the Common Fisheries Policy.


SBS data are based on enterprise data grouped under the declared main activity of each enterprise, according to the statistical classification of economic activities in the European Community (NACE Rev.2). Out of the 615 classes of activities singled out through a four-digit NACE code, 46 classes have been identified that have a principal or significant maritime component. They have been classified into sectors and subsectors (Table 2).

Table 2: Established Blue economy sectors: classification

[Table 2 Established Blue Economy sectors: classification]

While certain economic activities can be clearly identified as fully marine (e.g. Shipping and Maritime transport), for other sectors, the NACE classification includes both land and maritime activities (e.g. cargo handling, warehousing and extraction of oil and gas). In this latter case, alternatives sources are used for the estimation of the maritime proportion (see next Section).


As indicated above, several approaches have been followed to estimate the maritime proportions for those activities that encompass a maritime with a non-maritime component.

For industrial activities (i.e. Equipment and machinery and some activities in Processing of fish products), the Eurostat statistics on the production of manufactured goods (PRODCOM) were used to estimate the maritime proportion in two steps: 1) specific maritime products were identified within each NACE class; 2) the production value share over the total production of the class was calculated. (Table 3).

Given the high level of disaggregation of PRODCOM data, public available tables contain many confidential data points (e.g. when only one or two companies produce a specific item in a given Member State, those values are not published). In order to avoid the biased generated for confidential data, the proportions were calculated internally by Eurostat and transmitted to DG MARE. In a limited number of cases, the proportions could not be transmitted by Eurostat and, therefore, they were imputed based on the average for the EU.

Table 3: PRODCOM items considered maritime within each NACE class

[Table 3 PRODCOM items considered maritime within each NACE class]

For Oil and gas, the production onshore and offshore according to Rystad Energy UCube[2] was used to estimate the maritime proportions. For Marine renewable energy, the share of offshore wind energy was obtained from Wind Europe, compared to the total energy production from Eurostat.

For Other minerals, the following sources were used. For marine Aggregates (B 08.12), the statistics on aggregate production published by the European Aggregates Association. For Extraction of salt (B 08.93), the proportion of solar salt obtained from the European Salt Producers’ Association. Finally, for Support activities for other mining and quarrying the maritime proportion was calculated as the share of maritime B 08.12 (Aggregates) and maritime B 08.93 (Extraction of salt) over the total of mining activities (B05, B07 and B08). The estimations for Coastal tourism were calculated following a specific treatment (See specific Section below).

[2] Source: Rystad Energy UCube, version 2018-12-10.


SBS statistics provide a series of variables usually derived from the financial statements of the companies. For the analysis of the established sectors, the following selection of variables and indicators was used: employment (number of persons employed), wages and salaries, turnover, gross value added, gross operating surplus (profit or loss), gross investments and net investments. In addition, the following derived indicators were calculated: average annual wage per persons employed, GVA to turnover, profit margin (gross operating surplus to turnover – gross profit margin), labour productivity (GVA per person employed) and net investment ratio (net investment to GVA). This report focuses on the main variables, further details and breakdowns are available on the online Blue Economy Indicators tool. More details about the indicators and variables are explained in the glossary.


While the SBS database is quite comprehensive, a few missing points were still detected. To obtain a balance panel, a series of assumptions were made by applying the following rules:

  • Imputations are based on other data from the same Member State (i.e. no estimations based on data for other Member States).
  • Interpolation or the closest value over the time series of a NACE class (4-digit code) was used to impute missing values.
  • When no data were available for a NACE class (4-digit code), the data for the parent NACE group (3-digit code) were evenly distributed among the classes in the group.


Coastal tourism, is not a single economic activity but rather a set of activities undertaken by a specific type of consumer (the tourist). Coastal tourism happens when a visitor takes a trip to a coastal municipality[3]. It is considered to be part of this category the expenditures in accommodation, transport and other expenditures by tourists (for instance, cultural and recreation good, goods in specialised stores and food and beverage services). To calculate the contribution of Coastal tourism to the Blue Economy, a specific methodology has been followed.

Expenditure by inbound tourism

The data for Coastal tourism are based on the tourism statistics[4] compiled by Eurostat from the collection by national authorities and, in particular, on the data on the expenditure by visitors on trips. In principle, Member States compile data on outbound trips (e.g. the data for trips from Austria to France and Italy are compiled by the Austrian authorities). Once all Member States have transmitted the micro-data on their outbound trips, Eurostat can calculate the data for inbound trips (e.g. the data for trips to Greece from all Member States). The data refer to the expenditure of those trips with a breakdown for three categories: accommodation, transport and other expenditure as well as a breakdown for domestic trips and cross border trips (between EU Member States).

Variables: Turnover (expenditure), employment

The value of expenditure calculated as indicated above is assimilated to the turnover for the three subsectors in Coastal tourism (i.e. Accommodation, Transport, Other expenditure).

The rest of variables (employment, GVA, employee’s compensation) are estimated from the proportion of each one of them to turnover for the activities indicated in Table A.2.

Coastal vs. non-coastal

Finally, the indicator is further adjusted to take into account the maritime proportion. This is achieved by using data in tour_occ_ninatc to calculate the fraction of coastal tourism (Fcoast) as the number of nights spent in coastal areas (Ncoast) over total nights (Ntot):


Coastal areas, should be understood as the municipalities with a coastline or with at least 50% of their surface area within a distance of 10 km from the coastline. The classification of regions has been established by the TERCET Regulation: Regulation (EU) 2017/2391 of the European Parliament and of the Council of 12 December 2017 amending Regulation (EC) No 1059/2003 as regards the territorial typologies.

[3] Coastal municipalities are those Local Administrative Units (LAU) with a coastline or with 50 % of its territory within 10 km of the sea. The classification of regions has been established by the TERCET Regulation: Regulation (EU) 2017/2391 of the European Parliament and of the Council of 12 December 2017 amending Regulation (EC) No 1059/2003 as regards the territorial typologies. Some ad-hoc corrections on the request of the Member State exist, e.g. certain major cities are treated differently, e.g. Rome and Amsterdam.

[4] For further details, see: