A stochastic generative model of the World Trade Network
Javier García-Algarra1, Mary Luz Mouronte-López2, Javier Galeano3
1Department of Engineering, Centro Universitario de Tecnología y Arte Digital, Las Rozas, Spain. javier.algarra@u-tad.com.
Scientific Reports
|December 8, 2019
Summary
A new stochastic model accurately replicates the World Trade Network's (WTN) structure and statistical properties. This model, combining preferential attachment and multiplicative processes, closely mimics empirical data from 1962 to 2017.
Area of Science:
- Economics
- Network Science
- Data Science
Background:
- The World Trade Network (WTN) offers insights into global economic interactions.
- Understanding the structure and generative mechanisms of the WTN is crucial for economic analysis.
- Key network properties like degree and strength are essential for this understanding.
Purpose of the Study:
- To develop a stochastic model for generating synthetic World Trade Networks.
- To ensure the synthetic networks closely replicate the properties of annual empirical WTN data.
- To validate the model's performance against historical WTN data.
Main Methods:
- A stochastic model integrating preferential attachment and multiplicative processes was developed.
- The model generates synthetic networks mimicking key topological and statistical properties.
- Model performance was evaluated by comparing synthetic networks with empirical data from 1962 to 2017.
Main Results:
- The proposed stochastic model successfully generates synthetic networks that closely mimic empirical World Trade Network data.
- The model accurately replicates important network properties such as degree and strength.
- Validation against annual data from 1962 to 2017 confirmed the model's efficacy.
Conclusions:
- The developed stochastic model provides a robust tool for simulating the World Trade Network.
- This model enhances the study of global trade dynamics and network evolution.
- The findings support the use of this model for future research in international trade analysis.
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