Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/124122 
Year of Publication: 
2013
Series/Report no.: 
53rd Congress of the European Regional Science Association: "Regional Integration: Europe, the Mediterranean and the World Economy", 27-31 August 2013, Palermo, Italy
Publisher: 
European Regional Science Association (ERSA), Louvain-la-Neuve
Abstract: 
International regional competitiveness developed recently into smart, sustainable and inclusive growth objectives of the Europe 2020 policy programme, as envisioned for the cohesion policy reform after 2013 (EC, 2004). Currently, place-based development policies are proposed for future cohesion policy (Barca, 2009) and have taken the shape of smart specialisation strategies. These strategies are based on a systems way of thinking about innovation and growth (McCann and Ortega-Argilés, 2011) and they place a large emphasis on regional network data and analysis. However, crucial economic data on trade between regions are noticeably missing from European regional databases. This paper, therefore, proposes a new methodology to determine interregional trade and present a unique data set on trade between 256 European NUTS2 regions, for the year 2000. The methodology stays close to a parameter-free approach as proposed by Simini et al. (2012), and deviates therefore from earlier methods based on the gravity model that suffer from analytical inconsistencies. Unlike a gravity model estimation, our methodology stays as close as possible to observed data without imposing any geographical trade patterns. The resulting data can therefore be used as such in other research. We also perform an update of the dataset over the period 2000-2010. In our finding, most trade takes place within one and the same region, although there are large sectoral differences. The data shows that globalisation in trade is still limited with only a very small percentage of goods and services being traded with countries outside Europe. The European regional economy is therefore strongly interconnected, which is part of the explanation of the strong regional spillovers of the present economic crisis in Europe. Opposite to earlier findings (Combes and Overmand, 2004), we show that all eastern European regions catch-up to the rest of the European regions and not only the main economic eastern European centers. We do confirm a faster catch-up in these main economic centres. The banking crisis in 2008 showed a significant decline in trade of European regions with countries outside Europe with a strong recovery immediately afterwards. Trade of European regions with European regions from other countries stayed however permanently at a lower level showing the persistence of the crisis.
Subjects: 
regional trade data
parameter free estimation
non-survey estimation methods
Input-output modelling
Document Type: 
Conference Paper

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