12 research outputs found
The dynamics of innovations and citations
We present a model in which patent citations occur as new ideas are produced from combinations of existing ideas. An idea's usability in this process is represented as an interval in a variety space of ideas, whose length determines the likelihood of citation. This process endogenously derives exponential aging of patents, which is consistent with empirical observations. The endogeneity of aging sets our process apart from the standard preferential attachment literature
Homophily and Long-Run Integration in Social Networks
We model network formation when heterogeneous nodes enter sequentially and
form connections through both random meetings and network-based search, but
with type-dependent biases. We show that there is "long-run integration,"
whereby the composition of types in sufficiently old nodes' neighborhoods
approaches the global type distribution, provided that the network-based search
is unbiased. However, younger nodes' connections still reflect the biased
meetings process. We derive the type-based degree distributions and group-level
homophily patterns when there are two types and location-based biases. Finally,
we illustrate aspects of the model with an empirical application to data on
citations in physics journals.Comment: 39 pages, 2 figure
Diversity and Popularity in Social Networks
Homophily, the tendency of linked agents to have similar characteristics, is an im- portant feature of social networks. We present a new model of network formation that allows the linking process to depend on individuals types and study the impact of such a bias on the network structure. Our main results fall into three categories: (i) we compare the distributions of intra- and inter-group links in terms of stochastic dominance, (ii) we show how, at the group level, homophily depends on the groups size and the details of the formation process, and (iii) we understand precisely the determinants of local homophily at the individual level. Especially, we ¯nd that popular individuals have more diverse networks. Our results are supported empirically in the AddHealth data looking at networks of social connections between boys and girls.social networks, homophily, AddHealth, diversity, degree distributions
Spatiotemporal use predicts social partitioning of bottlenose dolphins with strong home range overlap
© 2018 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.Ranging behaviour and temporal patterns of individuals are known to be fundamental sources of variation in social networks. Spatiotemporal dynamics can both provide and inhibit opportunities for individuals to associate, and should therefore be considered in social analysis. This study investigated the social structure of a Lahille's bottlenose dolphin (Tursiops truncatus gephyreus) population, which shows different spatiotemporal patterns of use and gregariousness between individuals. For this, we constructed an initial social network using association indices corrected for gregariousness and then uncovered affiliations from this social network using generalized affiliation indices. The association‐based social network strongly supported that this dolphin population consists of four social units highly correlated to spatiotemporal use patterns. Excluding the effects of gregariousness and spatiotemporal patterns, the affiliation‐based social network suggested an additional two social units. Although the affiliation‐based social units shared a large part of their core areas, space and/or time use by individuals of the different units were generally distinct. Four of the units were strongly associated with both estuarine and shallow coastal areas, while the other two units were restricted to shallow coastal waters to the south (SC) and north of the estuary (NC), respectively. Interactions between individuals of different social units also occurred, but dolphins from the NC were relatively more isolated and mainly connected to SC dolphins. From a conservation management perspective, it is recommended that information about the dolphin social units should be incorporated in modeling intrapopulation dynamics and viability, as well as for investigating patterns of gene flow among them
The Network Structure of International Trade
Motivated by empirical evidence I uncover on the dynamics of French firms exports, I offer a novel theory of trade frictions. Firms only export into markets where they have a contact. They directly search for new trading partners, but also use their exist- ing network of contacts to remotely search for new partners. I characterize the dynamic formation of an international network of exporters in this model. I structurally estimate this model on French data and confirm its predictions regarding (i) the cross- sectional distribution of the number of foreign markets accessed by exporters and (ii) the cross-sectional geographic distribution of exports
Learning and the structure of citation networks
The distribution of citations received by scientific publications can be approximated by a power law, a finding that has been explained by “cumulative advantage”. This paper argues that socially embedded learning is a plausible mechanism behind this cumulative advantage. A model assuming that scientists face a time trade-off between learning and writing papers, that they learn the papers known by their peers, and that they cite papers they know, generates a power law distribution of popularity, and a shifted power law for the distribution of citations received. The two distributions flatten if there is relatively more learning. The predicted exponent for the distribution of citations is independent of the average in-(or out-) degree, contrary to an untested prediction of the reference model (Price, 1976). Using publicly available citation networks, an estimate of the share of time devoted to learning (against producing) is given around two thirds
Econometric analysis of network formation models
This dissertation addresses topics in the econometrics of network formation models. Chapter 1 provides a review of the literature. Statistical models focus on the specification of the probability distribution of the network. Examples include models in which nodes are born sequentially and meet existing vertices according to random meetings and network-based meetings. Within this group of models, special attention is reserved to the milestone work by Jackson and Rogers (2007): after having discussed and replicated the main results of the paper, an extension of the original model is examined and fitted to a dataset of Google Plus users. Even if statistical models can reproduce relatively well the main characteristics of real networks, they usually lack of microfundation, essential for counterfactual analysis. The chapter hence moves to considering the econometrics of economic models of network formation, where agents form links in order to maximise a payoff function. Within this framework, Chapter 2 studies identification of the parameters governing agents’ preferences in a static game of network formation, where links represent asymmetric relations between players. After having shown existence of an equilibrium, partial identification arguments are provided without restrictions on equilibrium selection. The usual computational difficulties are attenuated by restricting the attention to some local games of the network formation game and giving up on sharpness. Chapter 3 applies the methodology developed in Chapter 2 to empirically investigate which preferences are behind firms’ decisions to appoint competitors’ directors as executives. Using data on Italian companies, it is found that a firm i prefers its executives sitting on the board of a rival j when executives of other competitors are hosted too, possibly because it enables i to engage with them in “cheap talk” communications, besides having the opportunity to learn about j’s decision making process