Marine Socio-economic Indicators

the lead parter is the Northern & Western Regional Assembly    + 353 94 986 2970

The goal of this activity was to develop a suite of Marine Socio-economic Indicators for the European Atlantic Periphery.

In the development of the framework, a decision on what data to collect and the preferred data sources was agreed upon by the Marnet partners. Indicators should ideally be representative, quantifiable, comparable, reliable, adaptable and relevant. A stakeholder meeting was held in each partner region in order to develop a comprehensive list of indicators, applicable across sectors for valuation.

The agreed upon dataset is comprised of business indicators, physical indicators (also referred to as proxies) and population and social data. Business indicators include data on turnover, value added, employment, exports and number of enterprises. This data is available from national statistics institutes (NSI) for each industry by NACE code. The physical indicators can be used to give further information on a sector such as production tonnage for fish landings, or number of accommodation nights in relation to marine tourism. The physical indicators vary by sector. Where industries are only partly marine, proxies can provide a useful means to make estimates on the marine share of the industry. Where data is not readily available, or is not easily extracted or identifiable as marine, a proxy can be used as a representation. Proxy indicators can be both easier to collect and appropriate for characterizing the development of a given activity in a particular geographical area. These indicators are often available from Eurostat, NSIs and the relevant national government agencies or departments.

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To ensure the reliability and comparability of data, the preferred data sources were established databases within national statistics institutes (NSI) and Eurostat that were based on the NACE classification system. Where data was not available from these institutions, other public and private sources were utilized to gather data, such as state agencies, R&D institutes and industry associations.

For more information, please refer to Foley at al., 2015


Action Leader: University of Stirling, Scotland.

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