668. Synthetic networks generation and technology innovation
Invited abstract in session TA-9: Statistical methods for finance, stream OR in Finance and Insurance .
Tuesday, 8:30-10:00Room: Clarendon SR 2.01
Authors (first author is the speaker)
| 1. | Giulia Rotundo
|
| Statistical sciences, Sapienza University of Rome |
Abstract
This work elaborates on the role of assortative mixing in broadcasting technology diffusion. The role of assortativity intra-firm networks for
firms' innovation performance has been widely studied. The classic definition of assortativity through the Pearson correlation coefficient among the degrees of the nodes at the end of each edge captures the linear dependencies among the degrees of the connected nodes. This paper aims at pushing forward the concept of assortative mixing allowing for non linear dependencies. In order to achieve this task, the marginal distributions are fixed as the most detected from the empirical data sets and networks are generated for meeting an assigned joint distribution. The approach is different from the classic configuration model and its extensions which allow to build a network with a target level of correlation. The structure of the network impacts on the diffusion of technologies. Actually, the possibility to generate networks with specific properties allows to have a null model for investigating the role of topological structures in specific problems.
Keywords
- Graphs and Networks
- Financial Modelling
- Network Design
Status: accepted
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