Kevin M. Nguyễn

Machine Learning Project

Code Repository
Data Prep/EDA
Clustering
ARM
Decision Trees
Naive Bayes
SVM
Regression
Neural Networks
Conclusions

Introduction

Description:

Foreign aid allocation and its effects on international development

Since the end of World War II, one of the primary goals of the global community has been international development. International development is “a benevolent flow of resources and expertise from ‘developed nations’ to ‘developing nations.’” (African Studies Center, Boston University). In this context, developed nations, or the global north, include wealthy countries such as the United States, France, Japan, Germany, and the United Kingdom. Developing nations, or the global south, constitute poorer countries in Latin America, sub-Saharan Africa, Southeast Asia, and the Middle East. In simple terms, international development seeks to bridge the gap in wealth between the global north and the global south. According to the World Bank, the wealth disparity between countries has decreased since 1990. However, problems at the micro level continue to be severe. The UN found that the average income in North America is 16 times higher than the mean income in sub-Saharan Africa. Despite macro-level improvements over the past 25 years, international development is an ongoing issue. Developed countries are continually searching for methods to alleviate wealth disparity between nations.

“Poverty is not only about income levels, but for lack of freedom that comes from physical insecurity” 

Jacqueline Novogratz, The Blue Sweater: Bridging the Gap Between Rich and Poor in an Interconnected World

In the post-war era, the global community prioritized two methods of international development: foreign direct investment (FDI) and foreign aid. FDI is foreign investment in local economies by private actors. Corporate involvement in developing countries can stimulate economic growth and bring jobs to underemployed areas. While FDI allows businesses to participate in international development, contemporary research debates whether the net effect of FDI is positive or negative for developing countries. Some see globalization as a means to exploit developing countries while cutting costs and subverting high wages/labor laws in the global north. A much less controversial tool for international development is foreign aid. Money is sent from wealthy governments and individuals to developing countries and non-governmental/inter-governmental organizations for humanitarian and economic aid and development in the Global South. Ali and Isse (2006) found that GDP, trade, private credit, and government consumption were among the significant determinates of foreign aid allocation. This line of research can assist developing countries in prioritizing improvement in specific areas such as education and health care to stimulate foreign aid donations.

International development involves not only financial aid but also human and social development. Aid donors aim to empower individuals and governments in the global south to create sustainable and equitable societies. International development programs often include education, healthcare, infrastructure, social services, and economic aid. Although international development has brought significant benefits to many countries, it has faced criticism. Some argue modern international development practices promote Westernization and cultural imperialism and only reinforce global inequality rather than bolster equity. Others criticize the effectiveness and accountability of development programs and the unequal power dynamics between donor and recipient countries. The future of international development requires innovative and collaborative approaches that address the root causes of poverty and inequality while respecting local cultures and values. International development also requires addressing pressing issues such as climate change and environmental sustainability. Sustainable development practices need to be integrated into development programs to mitigate the impact of climate change on vulnerable communities. Additionally, international development should emphasize empowering women and promoting gender equality.

The success of international development relies on collaboration. Cooperation between governments, non-governmental organizations (NGOs), and local communities can generate productive development efforts. Developing countries often lack the resources or expertise to address complex economic issues. This deficit underlines the necessity of collaboration for sustainable development practices. International cooperation can also help facilitate knowledge sharing between developed and developing nations. Knowledge sharing enables local communities to take agency in their development. Collaboration is an essential component in the creation of long-term, sustainable development.

Machine learning implementation in international development can revolutionize development outcomes by improving the efficiency and effectiveness of aid programs. Through machine learning algorithms, aid organizations can analyze vast amounts of data to identify and address the most significant factors affecting poverty and inequality in the developing world. Moreover, machine learning can ease the monitoring and evaluation of aid programs, allowing organizations and watchdogs to assess program impact and make data-driven decisions about resource allocation. Although machine learning cannot ease all the complex challenges of international development, it can be a powerful tool for advancing the goal of creating more fair and sustainable societies globally.

Project Duration:

4 Months (Ongoing)

Date:

Spring 2023

Q&A

  1. Can Machine Learning predict how donor countries allocate foreign aid?
    • Yes! ML algorithms can help researchers discover patterns in aid allocation.
  2. How do wealthy nations decide to allocate aid?
    • Donor countries rely on a combination of political and socioeconomic factors to determine how to allocate aid.
  3. What are the factors that most influence where aid is sent?
    • GDP, refugee population, total population, and free speech were among the most important factors that influence how the US allocated foreign aid.
  4. How can developing countries use machine learning to stimulate aid donations?
    • Machine learning can aid developing countries by highlighting the factors that donor countries uses when determining aid allocation. Developing nations can then target those factors to stimulate more aid donations.
  5. How can developed countries use machine learning to determine how to allocate aid?
    • Developed nations can use machine learning to better assess potential aid recipients and how those countries fit in the the donor’s political and economic goals.
  6. What sources can provide good data that can be used in machine learning for aid allocation?
    • The World Bank maintains a large collection of both economic and social indicator data that can be used in this type of analysis.Additionally, organizations like Freedom House score countries based on political rights and civil liberties while Our World in Data scores countries based on political institutions.
  7. Which machine learning methods are the most useful for this line of research?
    • ARM, decision trees, naive Bayes, and linear regression can uncover specific factors that attribute to foreign aid allocation. Classification algorithms, like SVMs and neural networks, achieved high prediction accuracy when classifying countries based on aid level.
  8. How have economists used machine learning to research this field?
    • Economists have primarily relied on regression analysis for research in this field. This project demonstrates the additional benefits other ML algorithms can provide for researchers.
  9. Do political factors significantly alter how countries donate aid?
    • This project found that political institutions of recipient nations do affect how much aid is allocated.
  10. Do donors care about healthcare, education, and income inequality in aid receiving countries, or are political motivations what drive aid allocation?
    • The machine learning models that performed best in this project utilized data that included both political and socioeconomic indicators. This implies that donor countries consider both development status and political motivations when allocating foreign aid.