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Grounded in first principles, my research agenda is organized around three areas: macroeconomics, econometrics, and game theory. One line of my research develops time and frequency-domain approaches to dynamic equilibrium models of expectations formation. Another line develops Markov chain Monte Carlo methods for estimating large-scale structural models. These tools are applied to study monetary and fiscal policy, asset prices, and social networks. Recently, I like to train neural nets regularized by economic theory. My previous research studies the evolution of cooperative and altruistic human behavior.

As an educator, I teach economics, statistics, and computer science to both high school and college students. I also co-founded Business School 101, a rapidly growing YouTube channel dedicated to providing practical business education to a broad audience. Beyond the classroom, I am a thematic investor for space economy and have rich experience in derivative trading.

Check out my channels on YouTube, Discord, and X for more, and email me if you have any questions. Feel free to sponsor (preferably via Dogecoin) the open-source content of this homepage.

• Policy Rule Regressions with Survey Data [PDF], with Leifei Lyu and Zheliang Zhu, revision requested at Journal of Economic Dynamics and Control, 2025
• Forecasting the Forecasts of Others on Social Networks [PDF], with Leifei Lyu, manuscript, 2025
• Appetite for Treasuries, Debt Cycles, and Fiscal Inflation [PDF], revision requested at Macroeconomic Dynamics, 2024
• 🔥 Fall 2025 game theory 🔥
• 🔥 Fall 2025 neural network 🔥
• Rocket Lab Q2 earnings call [8/7/25]

• Profile: Curriculum Vitae, Research Papers, Blog, Google Scholar
• Courses: Microeconomics, Macroeconomics, Monetary Economics, International Macroeconomics, Bayesian Statistics, Neural Network, Game Theory
• Affiliations: Saint Louis University, Business School 101, Insightful Minds in International Macro, Center for Economic Behavior and Decision-making, Rocket Lab

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