Barriers to cross-region research and development collaborations in Europe: evidence from the fifth European Framework Programme

Abstract

The focus of this paper is on cross-region R&D collaboration funded by the 5th EU Framework Programme (FP5). The objective is to measure distance, institutional, language and technological barrier effects that may hamper collaborative activities between European regions. Particular emphasis is laid on measuring discrepancies between two types of collaborative R&D activities, those generating output in terms of scientific publications and those that do not. The study area is composed of 255 NUTS-2 regions that cover the pre-2007 member states of the European Union (excluding Malta and Cyprus) as well as Norway and Switzerland. We employ a negative binomial spatial interaction model specification to address the research question, along with an eigenvector spatial filtering technique suggested by Fischer and Griffith (2008) to account for the presence of network autocorrelation in the origin-destination cooperation data. The study provides evidence that the role of geographic distance as collaborative deterrent is significantly lower if collaborations generate scientific output. Institutional barriers do not play a significant role for collaborations with scientific output. Language and technological barriers are smaller but the estimates indicate no significant discrepancies between the two types of collaborative R&D activities that are in focus of this study.

Neighborhood impacts on household participation in payments for ecosystem services programs in a Chinese nature reserve: A methodological exploration

“…The ESF method has been used in recent years in studying migration (Clairfontaine et al, 2015;Griffith et al, 2017;Liu and Shen, 2017), real estate prices (Clairfontaine et al, 2015;Griffith et al, 2017;Liu and Shen, 2017), crime distribution and dynamics (Chun, 2014;Helbich and Arsanjani, 2015;Medina et al, 2018), and ecological and biogeographical issues (Michel and Knouft, 2014;Sternberg et al, 2014;Yang et al, 2014;Lara et al, 2016). As people residing in the same or close neighorhoods tend to be similar in a variety of dimensions, e.g., values, attitudes, incomes, physical environments, and policy contexts, this leads to spatial autocorrelation in those measures.…”

European R&D networks: a snapshot from the 7th EU Framework Programme

“…The table is organized in three columns. The first column displays the estimation results from a specification similar to other studies that have used previous FP data (Scherngell and Barber 2011;Scherngell and Lata 2013;de Clairfontaine et al 2015 to name a few). In line with these studies, we find a negative effect of geographical distance and institutional/language barriers.…”

European R&D networks: a snapshot from the 7th EU Framework Programme

“…A special issue of 'Science and Public Policy' focused on the evaluation of FP5 (see Arnold, Clark, and Muscio 2005;Guy, Amanatidou, and Psarra 2005;Polt and Streicher 2005). The economic geography literature has analysed FP5 data to investigate themes such as international cooperation, the relative strength of geographical versus technological proximity for knowledge transfer, and the potentially deterring role of distance, culture and other barriers (Maggioni, Nosvelli, and Uberti 2007;Scherngell andBarber 2009, 2011;de Clairfontaine et al 2015). Taking an alternative approach based on economic complexity or 'econophysics', Almendral et al (2007) contains an advanced statistical analysis of the network of cooperative projects using FP5 data (see also Barber et al, 2006, for advanced 'econophysics'-type statistical analysis on FP1-FP4 data).…”