Modibo K. Camara is a microeconomic theorist who does work at the intersection of economics and computer science. He is an Assistant Professor of Economics at the Stanford Graduate School of Business.
Website: https://mkcamara.github.io/
Paper: https://mkcamara.github.io/ctc.pdf
Abstract: This dissertation leverages
methodologies from computer science to understand sources of complexity in
economic theory. Chapter 1 considers time complexity: how much time is needed
to make a decision. Chapters 2 and 3 consider informational complexity: how
much and what kind of data is needed to make a decision. I argue that this line
of work is critical for our understanding of economic behavior. The fact that
economic models often assume agents are capable of very complex behaviors can
lead to predictions and policy recommendations that are themselves quite
complex. Through applications in decision theory and mechanism design, this
work aims to help distinguish predictions and recommendations that are
unrealistically complex from those that are at least plausible.
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