{"type": "project", "title": "Dynamic Modeling for Optimal Cryptoeconomic Policies", "website": "https://github.com/mingxuan-he/dp-tokenomics", "bannerImg": "bafkreig73zx2pmlewd4tctq5qy7uook4sgk5ovwx3nob7ijdmxyjtbhiuu", "createdAt": 1690308159003, "userGithub": "mingxuan-he", "credentials": {}, "description": "About the project:\nMy name is Ming and I am a graduate student at UChicago studying computational economics.\n\nIn this thesis research project, my aim is to bridge techniques from macroeconomic/monetary theory (DSGE) with Web3 tokenomics to develop a model framework for the cryptoeconomy.\n\nThe model will show how staking and burning rules can be set dynamically and optimally to maximize the welfare of relevant actors in the ecosystem. It will guide the new generation of protocols with a staking and burning token model.\n\nImprovements on current approaches:\nThe idea of optimizing burning and staking using dynamic modeling tools has seen growing exploration recently (e.g. @urosnoetic's post about BME in the previous round of TE grants, and multiple papers from the economics/finance literature in 2022/2023). My novelty is to develop a fully testable, calibratable model that also addresses uncertainty and lack of information.\n\nCurrent state:\nI have formalize the baseline model (Biais et al, 2020) in the context of tokenomics, and I'm currently in the phase of building the full model. A pitch deck can be found under the \"presentations\" folder of the github repo. The slides summarizes the current state of the research project, include a detailed introduction for the project, literature review, some technical components, and next steps.\n\nExpected outcome:\nThe expected result is a complete master's thesis which will go under the review of a graduate research committee at University of Chicago Kenneth C. Griffin Department of Economics. I will open source the paper and any relevant code on Github.", "bannerImgData": {}, "projectTwitter": "MingXDynasty"}
Dynamic Modeling for Optimal Cryptoeconomic Policies
About the project:
My name is Ming and I am a graduate student at UChicago studying computational economics.

In this thesis research project, my aim is to bridge techniques from macroeconomic/monetary theory (DSGE) with Web3 tokenomics to develop a model framework for the cryptoeconomy.

The model will show how staking and burning rules can be set dynamically and optimally to maximize the welfare of relevant actors in the ecosystem. It will guide the new generation of protocols with a staking and burning token model.

Improvements on current approaches:
The idea of optimizing burning and staking using dynamic modeling tools has seen growing exploration recently (e.g. @urosnoetic's post about BME in the previous round of TE grants, and multiple papers from the economics/finance literature in 2022/2023). My novelty is to develop a fully testable, calibratable model that also addresses uncertainty and lack of information.

Current state:
I have formalize the baseline model (Biais et al, 2020) in the context of tokenomics, and I'm currently in the phase of building the full model. A pitch deck can be found under the "presentations" folder of the github repo. The slides summarizes the current state of the research project, include a detailed introduction for the project, literature review, some technical components, and next steps.

Expected outcome:
The expected result is a complete master's thesis which will go under the review of a graduate research committee at University of Chicago Kenneth C. Griffin Department of Economics. I will open source the paper and any relevant code on Github.
Dynamic Modeling for Optimal Cryptoeconomic Policies