Complex Network Analysis in Econometrics
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Multidisciplinary Applications".
Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 35227
Special Issue Editors
Interests: economic complexity system; complex networks; time series; econometrics; economic net-works
Interests: complex network; complex systems; social networks; cascading failure; high-dimensional system
Special Issue Information
Dear Colleagues,
With the in-depth study of information theory, econometric theory and data science, we have deepened our understanding of the causes and consequences of complex relationships, self-organizing behaviors, and systemic phenomena. Furthermore, to study the deeper formation mechanism of the real-world system, it is necessary to establish a more accurate model.
Real-world systems are usually complex; it is difficult to simulate the evolution process through modeling accurately, and it is difficult to observe individual behavior trajectories. Although scholars have gradually realized that real-world systems continue to self-organize and emerge nonlinear spontaneous orders, at the same time, there are self-similar characteristics between individuals, local structures, and overall structures, and they continue to deform, develop or decline with the self-adaptive behavior of individuals. In the real-world system, complex network methods can effectively study the self-organization and interaction mechanisms between individuals. Although complex networks have experienced vigorous development for decades, there is still a big gap between the evolutionary results of complex network models and real-world systems. It is challenging to describe the individual interaction mechanisms in the real-world system.
Econometric models are widely used to quantify interaction mechanisms among variables. However, in the era of big data, new data forms and complex relationships in the real-world system evoke unprecedented challenges to econometrics. In this research context, some interdisciplinary approaches have emerged, such as complex network analysis methods. We can build realistic models from real-world data. Researchers have begun to combine complex network, econometric methods and information entropy theory to reveal the interactions among variables of network data, such as econometric relations, transmission relations, and causal relations. The combination of complex network, econometrics methods and information entropy theory provide a new perspective for studying real-world systems with many nodes and complicated interactions.
Therefore, this Special Issue will accept unpublished original papers and comprehensive reviews focused on, but not restricted to, the following research areas:
- Network perception and reconstruction based on econometrics methods and information entropy theory;
- Integration of complex networks, econometrics and information entropy theory;
- Causal inference based on econometrics methods and information entropy theory;
- Economic and financial risk transmission network modeling and analysis;
- Cascade and catastrophe in economic and financial networks;
- Robustness in economic and financial networks;
- Predictive econometrics network modeling;
- Time series econometric network modeling and dynamic analysis;
- Nonlinear dynamics in econometrics networks;
- High-dimensional econometrics network modeling;
- Heterogeneity econometrics network modeling.
Prof. Dr. Xiangyun Gao
Dr. Feng An
Dr. Qingru Sun
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- complex network
- econometrics
- information entropy theory
- nonlinear time series
- causality inference
- economic system
- financial market
