An article out this past week in IT Connect, Creating New Science with Amazon Web Services, focuses on PhD student Charlie Manzanares’ research in economics; specifically, looking at rich data sets to determine what “airline travel and pricing [would] look like today if major carriers had not been permitted to merge.” Earlier this year, the Department of Justice announced an investigation into whether or not there was collusion among U.S. airlines that resulted in illegally restricting carrier capacity and setting airline prices. Manzanares’ work may very well help determine if that did happen.

The research is the result of an early collaboration with the eScience Institute, along with encouragement from Amazon’s Pat Bajari, who leads that company’s Central Economics Team. Manzanares obtained an internship with Bajari’s team, and it was there that he was encouraged to look into UW’s machine learning classes. “Without machine learning and the eScience Institute,” says Manzanares in the article, “this work would not have been possible.”

“If things go well,” says Manzanares, “our model could be one of the first in the U.S. to provide antitrust authorities with the ability to estimate the impact of this type of collusion on consumer welfare, at scale, which might be useful to the DOJ as they develop their investigation.”

You can read the full article here:

Manzanares will be presenting his work into this subject at UW’s Cloud Day, November 12.