This is a chapter from **Tokenomics for Builders: The Practitioner’s Guide to Token Design.*
This document and all resources, threads, models, and materials linked to within are for informational purposes only. None of this document’s contents, nor the contents linked to within, should be construed as legal advice, financial advice, technical advice, investment advice, accounting advice, or representations in any way regarding legal, technical, financial, investment, or accounting matters by the author. The author is not a lawyer or financial advisor in any jurisdiction, and highly encourages readers to engage with registered professionals to ensure compliance with any and all relevant laws and regulations.*
We’ve reached the step many people think of when they think tokenomics - supply policy.
To complete this step, you’ll update the Tokenomics Modeling Spreadsheet featured in “Step 5: Supply Policy” of the Tokenomics Design Canvas to your specific design needs. The Tokenomics Modeling Spreadsheet is pre-populated with general industry best practices and standards, but each project is different. To help you update it to your needs, let’s discuss token supply from a data-driven lens.
A number of quantitative reports have analyzed how to optimize aspects like max supply, emissions rates, vesting, etc, including analysis of thousands of tokens and years of data conducted specifically to create this guide - we’ll look at all the data in this chapter.
Before getting carried away, it’s worth noting the relative importance of the topics in this chapter.
Builders think inflation matters, and of course, egregious hyperinflation does matter, but generally speaking the impact of inflation is largely overstated.
<aside> 💡 Separate analyses conducted by multiple parties using different data sets and methodologies have commonly found the same conclusion - that changes to token supply explain at most about 5% of price changes on a month-to-month or shorter time frame, even after controlling for overall market conditions.
In other words, 95% or more of token price performance is explained by factors other than emissions/inflation. These factors include incentive mechanisms, use cases, utility, value capture, value accrual, supply sinks, random events, narrative, etc.
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While emissions certainly can be optimized, builders should recognize the data suggests that the benefits of optimizing emissions are much smaller than typically believed.
This highlights how important it is to get other aspects of your token right first, and then optimize your emissions within the constraints the rest of your design creates.
Doing the design process in reverse - i.e. first optimizing emissions and then fitting the rest of the design to those emissions constraints - is illogical from a systems design point of view, and is not supported by the data either.
Fueled by an overblown fear of inflation - builders often only think about the risks of having too much token supply being in circulation.