A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network
The complex networks approach has proven to be an effective tool to understand and predict the evolution of a wide range of complex systems. In this work, we consider the network representing the exchange of goods between countries: the international trade network. According to the type of goods the...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/2825948 |
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| _version_ | 1832556467422494720 |
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| author | Hao Liao Alexandre Vidmer |
| author_facet | Hao Liao Alexandre Vidmer |
| author_sort | Hao Liao |
| collection | DOAJ |
| description | The complex networks approach has proven to be an effective tool to understand and predict the evolution of a wide range of complex systems. In this work, we consider the network representing the exchange of goods between countries: the international trade network. According to the type of goods they export, the complex networks approach allows inferring which countries will have a bigger growth compared to others. The aim of this work is to study three different methods characterizing the complex networks and study their behaviour on two main topics. Can the method predict the economic evolution of a country? What happens to those methods when we merge the economies? |
| format | Article |
| id | doaj-art-55bbc47fe04548f288b35a8fe5b808c0 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-55bbc47fe04548f288b35a8fe5b808c02025-02-03T05:45:24ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/28259482825948A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade NetworkHao Liao0Alexandre Vidmer1National Engineering Laboratory for Big Data System Computing Technology, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, ChinaNational Engineering Laboratory for Big Data System Computing Technology, Guangdong Province Key Laboratory of Popular High Performance Computers, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, ChinaThe complex networks approach has proven to be an effective tool to understand and predict the evolution of a wide range of complex systems. In this work, we consider the network representing the exchange of goods between countries: the international trade network. According to the type of goods they export, the complex networks approach allows inferring which countries will have a bigger growth compared to others. The aim of this work is to study three different methods characterizing the complex networks and study their behaviour on two main topics. Can the method predict the economic evolution of a country? What happens to those methods when we merge the economies?http://dx.doi.org/10.1155/2018/2825948 |
| spellingShingle | Hao Liao Alexandre Vidmer A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network Complexity |
| title | A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network |
| title_full | A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network |
| title_fullStr | A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network |
| title_full_unstemmed | A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network |
| title_short | A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network |
| title_sort | comparative analysis of the predictive abilities of economic complexity metrics using international trade network |
| url | http://dx.doi.org/10.1155/2018/2825948 |
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