Author: Mingxuan He (University of Chicago)
Website: mingxuanhe.xyz
Email: mingxuanh@uchicago.edu
Most cryptoeconomic policies today (e.g. inflation rate, burning rate) are either coded statically or rely on DAO governance for adjustments. This approach ensures decentralization, but the lack of real-time response mechanisms also make the tokenomics vulnerable to the impact of external shocks, such as a large price movements and hacks.
How do we design tokenomics that is robust against these shocks, while preserving decentralization? The bold yet rational answer is: let a bot run the economy.
In this research project, my aim is to build an autonomous algorithm that regulates a blockchain economy with two key parameters: staking rate and burning rate. In particular, I apply a modeling tool from modern macroeconomic theory called DSGE, which is the gold standard used by central banks worldwide to determine key economic parameters like interest rates. Cutting-edge data science tools such as machine learning and causal inference models will be applied in the calibration process. This research aims to provide guidance for the new generation of protocol tokenomics.
This is my ongoing M.A. thesis research which will go under the review of University of Chicago Kenneth C. Griffin Department of Economics.
This project is receiving community funding from Gitcoin Grants 18 - Token Engineering Commons round. The donation period is 08/15/2023 to 08/30/2023. [link to round] [link to project]
You can also donate to my ETH address at mingxuanh.eth or 0x4c1a316De360E08817eB88dD31A0E7305005fB65
Huge thanks to community members who contributed to these donations. These funds help me stay focused on conducting research as a public good.
- Token Engineering Commons (Twitter Space), August 2023
- UChicago Macroeconomics Workshop, May 2023 [slides]
Thanks to the group of UChicago scholars who kindly provides ongoing mentorship, discussion, and insights for my research, especially my advisor Prof. Gina Pieters. All errors are my own.