In the study "Economic potential of maritime regions" (as part of the Plan4Blue project) it was assessed how maritime economies contribute to national economies of Finland and Estonia and how productive and efficient blue economy sectors are in maritime regions. For the assessment the input-output methodology was used compiling first results which may be transferable to MSP processes.
Questions this practice may help answer
How contribute maritime economies to national economies of Finland and Estonia?
How productive and efficient are blue economy sectors in maritime regions?
The study on economic potential of maritime regions is part of the Plan4Blue project and aims to integrate socio-economic aspects into spatial planning.
Work Package 3 of Plan4Blue supports cross-border MSP by increasing the capacity of officials, planners and stakeholders to assess the interaction of socioeconomic marine activities and environmental values across space. Work Package 3 focuses on the effective visualization of current activities and planning options on maps, which requires optimal utilization of existing data. This aims to provide cost-efficient background information for decision-making and targeted production of new data.
The study is still ongoing but provides first results which are relevant for MSP processes as well.
Aspects / Objectives
The aim of the study was to find out whether the maritime sectors in Estonia and Finland are rather independent in their development within national economies. Previous literature from 2005 (“Korea study” and from 2016 (“Ireland study”) found stronger evidence of maritime sectors linkages with national economics. During research it turned out that there are descriptive inferences between blue industries as a part of blue region economy. The energy sector in Estonia involves, for example, the average largest fixed and current assets and highest number of employees, however, on average suffers losses (negative profit). In Finland average losses only occured in the marine construction sector.
The Input-output (I-O) methodology explores the linkage and production effects of the Estonian and Finnish maritime sectors on national economies and cross-border cooperation. There exist I-O tables for maritime sectors and products: in Estonia for fish and other fisheries products as well as for aquaculture products and water transport; in Finland for the fishing and water transport industries. For a more comprehensive picture, additionally two micro data was used:
Method 1: input-output tables showing how different sectors are interlinked with national economies. Data from OECD and national input and output tables have been used.
Method 2: AMADEUS (ET) and ORBIS (FI) micro data for descriptive statistics to answer the question how productive and efficient the blue sectors are in the two countries. For the AMADEUS data base, all companies are traced for up to 10 years. To minimize heterogeneity of estimates, data for the year 2015 for all Estonian and Finnish companies were extracted as the majority of them did not report back for this year.
Main Outputs / Results
The study provides preliminary information about the situation in both countries, which is quite similar.
The forward linkage effects of the maritime sectors /products are lower than those of other sectors / products. This means that booming economic activities, the maritime sectors are less stimulated by overall industrial growth than other sectors. The maritime sector is not so strongly influenced by businees fluctuations of national economies.
The backward linkage effects of maritime sectors are also lower than those of other sectors/products. Therefore, maritime sectors have smaller impacts in terms of investment expenditures on the national economy than other sectors.
First results are provided, for instance about the share of blue economy in regiona inputs (resources). For instance, for the county Ida-Viru in Estonia, the blue economy accounts for 65% of fixed assets although it constitutes only 8% of all companies in this region; 37% of employees are involved. A reason can be that out of 15 blue enterprises, 10 are from the energy sector, which is characterized by large stock of fixed assets and high labor demand.
The study provides information on availability and quality of statistical information and makes first proposals for the improvement of statistical data - also related to cross-border statistics which is an important topic in Eurostat. Another result is the mapping of economic activities in coastal regions and how productive and efficient blue sectors comparing to other sectors are. It therefore is an interesting method for benchmarking. Possibly, the I-O method is also fostering discussions between stakeholders and may be good for cross-country comparison.
A still open question is how to take dynamics of economy as well as dynamics of governance and legislation into account when applying the method.
Whether the method is useful for planners is also not fully clarified yet.
The applied methodology may be transferable to real MSP processes. However, it is not known yet. This is related to the statistical problem that the tables and methodology are weakly developed for analysing linkages between the sectors. Statistics have to be improved, especially with a view to cross-border cooperation. EUROSTAT is currently working on improving cross-border statistics.
Furthermore, the Input-Output analysis is informative but depends on availability of detailed tables. The AMADEUS database is a good source but expensive.
University of Tartu, Ülikooli 18, 50090 TARTU
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Fax: +372 737 5440
Costs / Funding Source
University of Tartu, School of Economics and Business Administration