A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network

المؤلفون المشاركون

Liao, Hao
Vidmer, Alexandre

المصدر

Complexity

العدد

المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-12، 12ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2018-02-13

دولة النشر

مصر

عدد الصفحات

12

التخصصات الرئيسية

الفلسفة

الملخص EN

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?

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Liao, Hao& Vidmer, Alexandre. 2018. A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network. Complexity،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1133383

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Liao, Hao& Vidmer, Alexandre. A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network. Complexity No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1133383

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Liao, Hao& Vidmer, Alexandre. A Comparative Analysis of the Predictive Abilities of Economic Complexity Metrics Using International Trade Network. Complexity. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1133383

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1133383