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This paper aims to present an extension of the ICES model to capture the public sector. Departing from a demand system mainly derived from the GTAP model, ICES-XPS model disentangles the private and the public actors. The paper reviews the changes in both the database and the model equations following the existing literature and considering the availability of data as well. The model is then tested with a series of simple experiments to highlight its contribution to economic analysis in which the public sector may play an important role. Finally, we show the flexibility in the closure rule of the public sector that allows addressing different policy research questions.

The present research has been developed within the EU FP7 VECTORS project (http://www.marine-vectors.eu/). The main scope of the project (2011-2015) has been to evaluate, from a multilateral perspective, drivers, pressures and vectors of changes in marine life of three main European seas (Baltic, Western Mediterranean, North), the mechanisms by which they do so and the impacts that they have on ecosystem structures and functioning as well as on economic activities and wellbeing. This paper describes the methodology, data elaboration and main results of a modelling exercise aiming to assess the economic effect of future changes in the EU marine ecosystem in the medium term (2030). We focus on those changes potentially affecting the fishing and the tourism sectors in two different IPCC SRES scenarios, the A2 and B1, varying in the future trends of population, GDP, prices, as well as the overall impact on environment. Sector-specific economic impacts are channeled through increases in fishing effort, due to lower availability of commercial fish species, and decrease in tourism demand following deterioration of marine ecosystem quality. Impacts on EU coastal countries Gross Domestic Product are negative and larger when the tourism sector is affected. This is explained by the much higher contribution of tourism than fishery in the production of value added. Negative impacts are also larger in the A2 than in the B1 scenario. The largest GDP losses due to adverse impacts on fishery are experienced by Spain (-0.13%), those related to tourism by Italy (almost -1%). Percent changes in sectoral production are notably larger than GDP ones: the largest contraction in fish sector production occurs in France (-24.7%). Notable decrease in coastal tourism demand occurs in Spain and the Netherlands. In general the Western Mediterranean is the most adversely affected region, whereas the Baltic Sea denotes a particular vulnerability to losses in tourism value added compared to the BAU. North Sea countries experience smaller losses.