Countries have traditionally placed tariffs on foreign products that enter their country for sale. The rationale behind this import tax is that it allows countries to protect their domestic industries and workers and is also a way for them to assert international dominance over rival countries and economic competitors. It’ s curious, then, given these shared rationales for the tax that tariff rates differ, so substantially between countries, across products, and over time. This project endeavors to apply machine learning and big data analysis methods to a dataset of more than10 billion tariff rate observations spanning 30 years, 130 countries, and 6,000 products for the purpose of detecting, measuring, and analyzing various economic and political determinants of tariff rates and trade volumes.

By engaging in this SuperUROP project, I hope to gain exposure to a longer-term, multidisciplinary research endeavor. I am majoring in Course 6-3 and minoring in economics. Having done internships in both fields, this project gives me a unique opportunity to apply machine learning techniques in the context of an economic phenomenon, a problem that requires an understanding of both artificial intelligence and global economic trends.