Brendan Galvin: using data to model China’s construction, oil investments

Monday, May 18, 2020
by Sharon Adarlo

Brendan S. Galvin, 22, Class of 2020


Galvin is obtaining his bachelor’s degree from the Woodrow Wilson School of Public and International Affairs (WWS) with a concentration in international relations. He is set to complete requirements for the Certificate Program in Statistics and Machine Learning at the Center for Statistics and Machine Learning (CSML), the finance certificate from the Bendheim Center for Finance, and the certificate in history and the practice of diplomacy from WWS.



Galvin’s independent project for CSML analyzed the interplay between China’s oil investments and construction contracts the country enters into with oil-producing countries, with a particular emphasis on corruption as a factor for investment.

“As the second largest oil consumer in the world, China relies on imports for eighty percent of its total petroleum. The Chinese Communist Party accordingly treats China’s energy security as a high strategic priority,” said Galvin. This project sought to empirically contribute to the debate over whether Chinese construction efforts support the party’s strategic need for oil security and the role of corruption in this process.

Some analysts think that with China entering these huge construction contracts for building dams, roads and other projects, this may leave countries less likely to act against Chinese oil interests, which is to win greater access to oil, said Galvin.

For his project, Galvin created a network of all Chinese firms involved in construction or oil and utilized a mathematical formula used by economists to see how much construction from one firm would support oil investments by another firm. This was a way to see how different firms are interacting with each other, he said.

For information undergirding his project, Galvin utilized data sets from the World Bank, the American Enterprise Institute’s China Global Investment Tracker, and Transparency International’s Corruption Perception Index as a measure of country-year corruption among recipients of Chinese investment.

Galvin used machine learning and statistical techniques to see how this network of different firms was formed and how they interact with each other. His mathematical analysis supports the theory that large construction projects by Chinese state-owned enterprises align with oil investments in corrupt locations.

Galvin’s project melds many of his interests, such as international relations, economics and mathematics. He appreciated how his coursework in data science and statistics complemented the rest of his studies.

“I think statistics is an invaluable tool whatever you do,” he said. “There are a lot of insights in data that have not been explored in many fields yet. You can read some things on history, politics, or economics and then turn to data and explore these topics in a deeper way to answer some interesting questions.”

After graduation, Galvin wants to pursue a career in public service and earn an advanced degree in economics or politics.


Extracurricular activities:

Galvin was a catcher on Princeton’s varsity baseball team. He parlayed his playing skills to a spot on the Republic of Ireland’s national baseball team. (Galvin is a dual Irish citizen.) He played for the team for two summers while he was a student at Princeton.

“It was really cool,” he said. “It was great training in Dublin and getting to play in the European championships against other countries.”

Galvin was also an Outdoor Action (OA) leader and enjoyed mentoring students during his time in OA.


For fun:

Galvin enjoys hiking, being outdoors, working out, reading non-fiction such as history, and hanging out with his family.