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Jesse G

- Research Program Mentor

PhD candidate at Université Panthéon-Sorbonne (Paris I)

Expertise

Economics (Micro/Macro), Finance, Statistical Analysis, Machine Learning, Economic Philosophy, History of Economic Thought

Bio

Centuries ago, Thomas Carlyle memorably called economics the "the dismal science" in reference to its relentless focus on the bottom line: productivity, output, money! But economics sits at the intersection between so many disciplines: philosophy, statistics, mathematics, finance, business, management. It is the science of human activity. Where we find people making decisions, we find economics. I was drawn to the field exactly for the wide variety of opportunities it provides. My current work fuses machine learning and traditional economic theory to use big data, web scraping, and language modeling to improve our understanding of trade, international relations, and future economic growth. These academic pursuits bleed over into my personal life. I enjoy programming and learning about AI, especially reinforcement learning. I like to learn about and program the state-of-the-art models that play video games. Obviously I like to play video games myself too, especially classic strategy and role playing games (nerd!). I also like exercising (jump rope, Brazilian jujitsu, yoga, and weight lifting), doing crossword puzzles, and learning new languages.

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Robots, Bubbles, and Efficient Markets

There's an old joke in economics that goes like this. A financial economist is walking with his student, and the student sees a $100 dollar bill on the ground. The student is excited, and goes to pick it up, but the professor stops him and says, "there couldn't be $100 on the ground. If there were, someone would have already picked it up!" The professor is expressing the "Efficient Markets Hypothesis", that claims all stock prices are correct, because if they weren't someone could buy and sell them to pick up $100. Of course, many economists don't believe this! There is a whole school called Behavioral Economics that studies how markets fail, why prices are wrong, and the human psychology that causes these inefficient markets to emerge. Typically, behavioral economists work with volunteers, who trade stocks or play games (not the fun kind). The economist try to create price bubbles or market frenzies, and show how irrational people are. But what about AIs? We could program AI to play in these game environments together, and see if the same bubbles and market frenzies occur. Do they eventually turn into the efficient professor after playing the game many times? Can they adapt when the rules of the game are changed? What can we learn about ourselves by studying how robots behave in similar situations?

What Makes a Country Rich?

You can probably name some rich countries and some poor countries, but what makes a rich country rich? Is it natural resources? Their system of government? Their "human capital" -- education and civic spirit? Or is it just a capricious accident of history we have no control over? Whatever you think, the chess grand master Ben Feingold once said (I'm paraphrasing), "unless you know why you gave you answer, your answer isn't right!" How would you go above proving your theory? You could look at case studies, for example, what did the USA do in the post-war years? What did China do under Deng Xiaoping, or Singapore under Lee Kuan Yew? But... how do we know if these methods can generalize? To go from the general to the particular, this is the role of statistics! Using econometric analysis -- a fancy way of saying statistics -- we can test theories about what causes economic growth, and try to uncover some ideas for leaders and politicians who want to create prosperity for their nations.

Coding skills

Python, MatLab, R,

Languages I know

French, Advanced; Chinese, Advanced

Teaching experience

I was an agricultural technician and trainer in Peace Corps Senegal from 2010-2012, and later a kindergarten teacher in Shanghai from 2014-2019.

Credentials

Work experience

Organization for Economic Cooperation and Development (OECD) (2021 - Current)
Consultant
Little Scholars Academy (2022 - Current)
Teacher

Education

Michigan State University
BS Bachelor of Science (2009)
Political Theory and Constitutional Democracy; Economics
Université Panthéon-Sorbonne (Paris I)
MA Master of Arts (2020)
Financial Economics
Université Panthéon-Sorbonne (Paris I)
PhD Doctor of Philosophy candidate
Financial Economics

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