Foreign Aid Allocation: A Neural Network Approach


Aid Distribution
Kohonen Maps
Machine Learning
Data Mining

How to Cite

Rende, S. . (2017). Foreign Aid Allocation: A Neural Network Approach. Journal of Business Strategies, 34(1), 33–56.


During the last twenty years, there have been strong supporters of foreign
aid, and equally strong critiques. The debate is based on an effort to establish a
causal relationship between foreign aid and economic growth, and it is still ongoing.
Rather than seeking to uncover the causal relationships, I examine foreign aid and
its relation to structural indicators in aid dependent countries using a special type
of artificial neural networks, known as Kohonen maps. The findings suggest that
aid allocation and coordination could be based on institutional and climate-based
similarities across recipient countries rather than the geographical proximity or the
cultural ties, or preferences, between the donor and recipient countries.

This article is distributed using a Creative Commons Attribution-NonCommercial 4.0 license. Copyright remains with the author(s).