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# trade-communities | ||
Predicting international trade communities from world development indicators | ||
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## The problem | ||
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This project aimed to determine the predictive power of world | ||
development indicators for international trade communities, while inspecting changes and trends in | ||
these communities over time. It was hypothesized that world development indicators may contain the | ||
right balance of both sociologically and economically-driven information to predict international trade | ||
communities. | ||
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In order to test this hypothesis, a weighted, directed network was created using export FOB data | ||
from the International Monetary Fund’s (IMF) Direction of Trade (DOT) statistics. Communities were | ||
found in this network using the modularity maximization algorithm explained in [1]. These community | ||
classifications were then predicted from the World Bank’s World Development Indicators using a | ||
random forest classifier. | ||
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## References | ||
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1. Leicht EA, Newman ME. “Community structure in directed networks”. Phys Rev Lett. 2008 | ||
Mar 21; 100(11):118703. Epub 2008 Mar 21. |