About me:

Hey, welcome to my webpage! I'm a researcher in economics and I work on innovation & social networks. I've done my Ph.D in economics at GREThA, University of Bordeaux in France. 
My fields of interest are: economic geography, network dynamics, the determinants of innovation and the economics of science.
I am currently a postdoc at CREA, university of Luxembourg (http://wwwen.uni.lu/recherche/fdef/crea).
You can find my CV here.

Contact details:

CREA, Université du Luxembourg
Faculty of Law, Economics and Finance
162A, avenue de la Faïencerie
L-1511 Luxembourg
E-mail: laurent.berge@uni.lu
Tel: +352-46-66-44-6596



  • Bergé, L., T. Scherngell and I. Wanzenböck, forthcoming. “Bridging centrality as an indicator to measure the ‘bridging role’ of actors in networks: An application to the European Nanotechnology co-publication network.” · Journal of Informetrics 
    • Abstract In the recent past, we can observe growing interest in STI studies in the notion of positioning indicators, shifting emphasis to actors in the innovation process and their R&D inter-linkages with other actors. In relation to this, we suggest a new approach for assessing the positioning of actors relying on the notion of bridging centrality (BC). Based on the concept of bridging paths, i.e. a set of two links connecting three actors across three different aggregate nodes (e.g. organisations, or regions), we argue that triangulation in networks is a key issue for knowledge recombinations and the extension of an actor's knowledge base. As bridges are most often not empirically observable at the individual level of research teams, we propose an approximated BC measure that provides a flexible framework for dealing with the aggregation problem in positioning actors. Hereby, BC is viewed as a function of an aggregate node's (i) participation intensity in the network, (ii) its openness to other nodes (i.e. the relative outward orientation of network links), and iii) the diversification of links to other nodes. In addition, we propose a generalised version of the BC measure that accounts for different node categories. An illustrative example on the European Nanotechnology co-publication network observed at the level of organisations demonstrates the usefulness and complementary interpretation power in comparison to conventional centrality measures.

  • Bergé L., I. Wanzenböck and T. Scherngell, 2017.  "Centrality of regions in R&D networks: A new measurement approach using the concept of bridging paths". Regional Studies, 51(8) (linkPDF - most recent working paper)
    • Abstract This paper deals with the questions of how network proximity influences the structure of inter-regional collaborations and how it interacts with geography. I first introduce a new, theoretically grounded measure of inter-regional network proximity. Then, I use data on European scientific co-publications in the field of chemistry between 2001 and 2005 to assess those questions. The main findings reveal that inter-regional network proximity is important in determining future collaborations but its effect is mediated by geography. Most importantly, a clear substitution pattern is revealed showing that network proximity mainly benefits international collaborations.

  • Bergé, L., forthcoming. "Network proximity in the geography of research collaboration". Papers in Regional Science (linkPDF - most recent working paper)
    • Abstract This paper introduces a novel measure of regional centrality in the context of research and development (R&D) networks. It first demonstrates some substantial problems of social network analysis (SNA)-based centrality measures to cope with regional R&D networks in a meaningful way. It then introduces a new measurement approach of regional network centrality based on the concept of interregional bridging paths (indirect connections at the regional level). The paper shows that the formal definition of the regional bridging centrality measure can be expressed in terms of three simple components: the participation intensity of a region in interregional R&D collaborations; the relative outward orientation in terms of all established links; and the diversification of R&D collaborations among partner regions. The measure and its behaviour with respect to other conventional centrality measures are illustrated by use of the example of the European co-patent network at the NUTS-2 level.

  • Bergé, L., C. Bouveyron and S. Girard, 2012 "HDclassif: An R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data". Journal of Statistical Software, 46(6) (PDF)
    • Abstract This paper presents the R package HDclassif which is devoted to the clustering and the discriminant analysis of high-dimensional data. The classication methods proposed in the package result from a new parametrization of the Gaussian mixture model which combines the idea of dimension reduction and model constraints on the covariance matrices. The supervised classication method using this parametrization has been called high dimensional discriminant analysis (HDDA). In a similar manner, the associated clustering method has been called high dimensional data clustering (HDDC) and uses the expectation-maximization algorithm for inference. In order to correctly t the data, both methods estimate the specic subspace and the intrinsic dimension of the groups. Due to the constraints on the covariance matrices, the num- ber of parameters to estimate is signicantly lower than other model-based methods and this allows the methods to be stable and ecient in high-dimensional spaces. Experiments on articial and real datasets show that HDDC and HDDA perform better than existing classical methods on high-dimensional datasets, even with small datasets. HDclassif is a free software and distributed under the general public license, as part of the R software project.

Working papers:

  •  Bergé, L., N. Carayol and P. Roux, 2017. “How do inventors networks affect urban invention?” -- Job Market Paper -- (PDF)
    • Abstract Social networks are expected to matter for invention in cities, but empirical evidence is still puzzling. In this paper, we provide new results on urban patenting covering more than twenty years of European patents invented by nearly one hundred thousand inventors located in France. Elaborating on the recent economic literatures on peer effects and on games in social networks, we assume that the productivity of an inventor’s efforts is positively affected by the efforts of his or her partners and negatively by the number of these partners’ connections. In this framework, inventors’ equilibrium outcomes are proportional to the square of their network centrality, which encompasses, as special cases, several well-known forms of centrality (Degree, Katz-Bonacich, Page-Rank). Our empirical results show that urban inventors benefit from their collaboration network. Their production increases when they collaborate with more central agents and when they have more collaborations. Our estimations suggest that inventors’ productivity grows sublinearly with the efforts of direct partners, and that they incur no negative externality from them having many partners. Overall, we estimate that a one standard deviation increase in local inventors’ centrality raises future urban patenting by 13%.

  • Bergé, L., T. Doherr and K. Hussinger, 2017. “The Effects of Intellectual Property Rights on Publications of University Scientists.”  (PDF upon request)· 
    • Abstract We investigate the impact of the introduction of software patents on the publication volume and quality of university researchers in the US. A difference-in-difference approach that compares US scientists to a benchmark group of European peers reveals that the introduction of software patents in the US led to a smaller quantity of higher quality publications. Our estimates suggest that US publication counts of software scientists dropped by 17% albeit compensated by an increase in quality-weighted publications by 13%. Based on these results we can reject the concern that the introduction of patent rights had a negative impact on university science.

Work in progress:

  • "Linking geography to a new network-based typology of innovative firms using patent abstracts: A comparison of the US/EU biotech industry", with C. Bouveyron and P. Latouche
  • "FENmlm: An R package for the efficient estimation of maximum likelihood models with fixed effects."
  • “Is economic integration always good for innovation? A conceptual framework and empirical evidence for the US and the EU”, with I. Wanzenböck


  • HDclassif (R package): This package serves high dimensional data classification (supervised and unsupervised) based on the methods HDDA and HDDC. This package is available on CRAN: http://cran.r-project.org/package=HDclassif.
  • FENmlm (R package): This package is intended to efficiently estimate fixed-effects maximum likelihood models. Further, it allows for non-linear in parameters right hand sides with linear fixed-effects. The models currently available are: Poisson, Negative Binomial, Gaussian and Logit. This package is available on CRAN: https://cran.r-project.org/packages/FENmlm