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This paper has two main goals. First, it reconsiders regional growth and convergence processes in the context of the enlargement of the European Union to new member states. We show that spatial autocorrelation and heterogeneity still matter in a sample of 237 regions over the period 1993-2002. Spatial convergence clubs are defined using exploratory spatial data analysis and a spatial autoregressive model is estimated. We find strong evidence that the growth rate of per capita GDP for a given region is positively affected by the growth rate of neighbouring regions. The second objective is to test the robustness of the results with respect to non-normality, outliers and heteroskedasticity using two other methods: The quasi maximum Likelihood and the Bayesian estimation methods.

Since human activities are embedded in interactions, they are at the very center of the modeling of any form of social life, shaping societies, groups and interpersonal relationships. All theories of social, cognitive and cultural life are thus associated with explicit or tacit models of the nature of interactions and relations. This book proposes a multifaceted exploration of the complex nature of interactions, and of the modeling of complex interactional systems. It shows that all disciplines can be enriched by exploring alternative paradigms in the modeling of interactions, and that if discipline-bound studies tend to underestimate the multi-dimensional nature of interactions, ignoring it is not an option.It will be of great interest for anyone involved in disciplines such as economics, geography, linguistics, communication studies, education sciences and sociology, and in fields such as the study of networks, interactional systems, relations between agents, and mathematical and computational modeling.

International audience ; The aim of this paper is to identify the driving forces of Sovereign wealth funds' investments. For this, we develop an original econometric framework that quantifies the role of spatial dependence in the location of investments, and uses the Inverse Hyperbolic Sine transformation of the dependent variable in a spatial panel model context. This transformation copes with two features of net flows, namely an highly skewed distribution and the presence of zero and negative values. Using a large-scale database, we provide evidence of negative spatial dependence, investments in one country being on average at the expense of its neighbors.

International audience The aim of this paper is to identify the driving forces of Sovereign wealth funds' investments. For this, we develop an original econometric framework that quantifies the role of spatial dependence in the location of investments, and uses the Inverse Hyperbolic Sine transformation of the dependent variable in a spatial panel model context. This transformation copes with two features of net flows, namely an highly skewed distribution and the presence of zero and negative values. Using a large-scale database, we provide evidence of negative spatial dependence, investments in one country being on average at the expense of its neighbors.

International audience ; The aim of this paper is to identify the driving forces of Sovereign wealth funds' investments. For this, we develop an original econometric framework that quantifies the role of spatial dependence in the location of investments, and uses the Inverse Hyperbolic Sine transformation of the dependent variable in a spatial panel model context. This transformation copes with two features of net flows, namely an highly skewed distribution and the presence of zero and negative values. Using a large-scale database, we provide evidence of negative spatial dependence, investments in one country being on average at the expense of its neighbors.

International audience ; The aim of this paper is to identify the driving forces of Sovereign wealth funds' investments. For this, we develop an original econometric framework that quantifies the role of spatial dependence in the location of investments, and uses the Inverse Hyperbolic Sine transformation of the dependent variable in a spatial panel model context. This transformation copes with two features of net flows, namely an highly skewed distribution and the presence of zero and negative values. Using a large-scale database, we provide evidence of negative spatial dependence, investments in one country being on average at the expense of its neighbors.

22 pages ; International audience ; There is a great deal of literature regarding the asymptotic properties of various approaches to estimating simultaneous space-time panel models, but little attention has been paid to how the model estimates should be interpreted. The motivation for use of space-time panel models is that they can provide us with information not available from cross-sectional spatial regressions. LeSage and Pace (2009) show that cross-sectional simultaneous spatial autoregressive models can be viewed as a limiting outcome of a dynamic space-time autoregressive process. A valuable aspect of dynamic space-time panel data models is that the own- and cross-partial derivatives that relate changes in the explanatory variables to those that arise in the dependent variable are explicit. This allows us to employ parameter estimates from these models to quantify dynamic responses over time and space as well as space-time diffusion impacts. We illustrate our approach using the demand for cigarettes over a 30 year period from 1963-1992, where the motivation for spatial dependence is a bootlegging effect where buyers of cigarettes near state borders purchase in neighboring states if there is a price advantage to doing so. ; La littérature économétrique récente fait une place croissante à l'étude des propriétés asymptotiques des différentes méthodes d'estimation des modèles de données de panel spatio-temporels. Toutefois, force est de constater que peu d'attention est consacrée à l'interprétation économique de tels modèles malgré leur grand intérêt pour la modélisation des phénomènes économiques dans une dimension spatio-temporelle et le rôle qu'ils pourraient jouer dans l'évaluation des politiques économiques dans cette même dimension. Nous montrons dans ce papier que les coefficients estimés de ces modèles permettent d'expliciter non seulement la dynamique temporelle des impacts mais également leur dynamique spatiale et surtout de quantifier la diffusion spatio-temporelle de l'impact d'une variation d'une variable explicative. La méthode proposée est illustrée par une étude de la demande de cigarettes dans 46 Etats américains sur la période 1963-1992 en utilisant une base de données bien connue dans la littérature économétrique. La présence d'autocorrélation spatiale est ici motivée par un effet de " contrebande ". Les consommateurs proches des frontières d'un état achèteront en effet leurs cigarettes dans les états voisins si le prix des cigarettes y est inférieur à celui pratiqué dans leur propre Etat.

22 pages ; International audience ; There is a great deal of literature regarding the asymptotic properties of various approaches to estimating simultaneous space-time panel models, but little attention has been paid to how the model estimates should be interpreted. The motivation for use of space-time panel models is that they can provide us with information not available from cross-sectional spatial regressions. LeSage and Pace (2009) show that cross-sectional simultaneous spatial autoregressive models can be viewed as a limiting outcome of a dynamic space-time autoregressive process. A valuable aspect of dynamic space-time panel data models is that the own- and cross-partial derivatives that relate changes in the explanatory variables to those that arise in the dependent variable are explicit. This allows us to employ parameter estimates from these models to quantify dynamic responses over time and space as well as space-time diffusion impacts. We illustrate our approach using the demand for cigarettes over a 30 year period from 1963-1992, where the motivation for spatial dependence is a bootlegging effect where buyers of cigarettes near state borders purchase in neighboring states if there is a price advantage to doing so. ; La littérature économétrique récente fait une place croissante à l'étude des propriétés asymptotiques des différentes méthodes d'estimation des modèles de données de panel spatio-temporels. Toutefois, force est de constater que peu d'attention est consacrée à l'interprétation économique de tels modèles malgré leur grand intérêt pour la modélisation des phénomènes économiques dans une dimension spatio-temporelle et le rôle qu'ils pourraient jouer dans l'évaluation des politiques économiques dans cette même dimension. Nous montrons dans ce papier que les coefficients estimés de ces modèles permettent d'expliciter non seulement la dynamique temporelle des impacts mais également leur dynamique spatiale et surtout de quantifier la diffusion spatio-temporelle de l'impact d'une variation d'une ...

This manuscript is composed of 18 contributions studying interactions in complex systems. These contributions were presented at the international conference on Interactions in Complex Systems, organized at University of Orléans in June 2013. This multidisciplinary manuscript aims at presenting how different disciplines may see their research topic from the complex system perspective and how interactions are accounted for in these complex systems. In this manuscript, we find contributions in mathematics, physics, computer sciences, robotics, life sciences, economics, linguistic, humanities or science of educationThe book is split into 4 parts, each one approaching interactions in complex systems from a particular perspective. We have gathered contributions by approach rather than by studied topic, the latter way being, to our viewpoint, less relevant to this type of book. The first part of the book contains papers dealing with interactions at the system level. The included contributions address territory planning, the traveling of population in the Neolithic era or interactions in neuron populations.The second part collects articles studying \textbf{networks} and proposing different methods for their analysis. This part contains contributions on link prediction, on interaction analysis in communities learning, on the influence of the type of strategies updates (parallel or sequential) on the evolution of cooperation among humans, opinion dynamics or the social function of gossip. Articles included in the third part focus on the analysis of interactions in social communications. As such, this part gathers papers studying teacher-student relations, the modeling of the teacher's evaluative speech to study students' interactions and the effects on learning or the modeling of human communications. Finally, the last part of this book is devoted to the analysis of interactions between economic agents in different fields. Thereby, a contribution develops a methodology to forecast employability of students in Earth ...