Understanding Token Economics — Part 1

Establishing a framework for understanding tokenomics for future application to the OATH Ecosystem

Justin Bebis
5 min readJul 10


With the launch of Oath Governance, it has become especially important for our community to develop a common understanding of tokenomics. To this end, I will be writing a few articles to explore the subject both generally and in the context of OATH. Let’s start this article with a brief overview of what exactly tokenomics are, how they work, and how we can think about them.

What are Tokenomics?

Tokenomics generally refer to an economic framework that protocols can use to manage supply and demand of their token and align incentives between stakeholders. As central banks can use inflation to modulate the behavior of citizens, token administrators use inflation to program behaviors in their ecosystem participants.

As a risk manager, I view tokenomics in those terms. Much like energy, risk cannot be created or destroyed. It can only be deferred (vesting), diffused (marketing), and better understood (auditing). Economic risks and rewards affect how protocols and their users behave, and understanding them better allows us to manage them effectively.

How can we Evaluate Tokenomics?

Expressing something as complex as tokenomics mathematically is like catching a greased pig. Think of the below equation as a simple mental model more than a formal tool for analysis.

With this in mind, let’s establish a simple differential equation to help our evaluation:


Tokenomics work by modifying different aspects of this equation. Performing buybacks, burning tokens, or getting users to stake assets increases the b variable and reduces the s variable, resulting in a fundamental shift in value as well as increasing the magnitude of that shift overall. This growth can increase the R variable as traders attempt to price in future growth based on each fundamental change.

As inflation decreases and more tokens are removed from the liquid supply, it’s easy to see how protocols can unlock exponential growth opportunities:

Integration of the above equation


So, in plain English, effective tokenomics will increase the value of a token by increasing the amount of tokens removed from the market (b), decreasing the amount of tokens added to the market (i), and surfacing the data and intelligence required for speculators to understand the value of these changes (R). Effective tokenomics will also ensure any tokens added to the market (i) are encouraging behaviors that will result in an increase in token burn (b) and speculative demand (R).

A keen observer will note that the opposite is also true. Aggressive tokenomics strategies that feature locking, options, and heavy inflation can be viewed as a means of creating leverage. As locks expire, options are exercised, and yields diminish, the economic effects of these mechanisms will have a similar yet opposite impact on an ecosystem’s value.

Why utilize tokenomics?

Tokenomics have a number of compelling use-cases, as exercising influence over the supply of a digital currency allows protocols to shift risk upstream, create leverage, and punch way above their weight class. If well-planned, these shifts can unlock massive opportunities for growth.

One of these use-cases is user onboarding, which is best accomplished through things like airdrops, referrals, and other one-off incentives. User retention and sybil resistance are the two strongest considerations, and can be achieved through nuanced reward weighting, good infosec practices, and vesting.

Another strong use-case for tokenomics is reducing concentration risk. Money managers rarely want to be providing a large share of a protocol’s liquidity, as it would put them on the hook for anything that goes wrong and increase the likelihood of insolvency.

Finally, tokenomics strategies can allow protocols to generate income to finance developments, diversify their treasury, or fund incentives. We see this being done through bonding, distribution of option tokens, and treasury management.

A beautiful marriage of each of the above use-cases is deepening liquidity, which inherently reduces concentration risk, allows a protocol to onboard larger customers, and scales protocol revenues up. If managed properly, increases in serviceable market associated with deepened liquidity can even help diffuse the risks associated with tokenomics strategies.

How can we utilize tokenomics?

Since the beginning of DeFi in 2020, countless mechanics have been created with varying degrees of efficacy. Below, find a non-exhaustive list of mechanics, and please comment any I missed.

Direct Token Incentive Types
Indirect Token Incentive Types
Disincentive Token Types

Additionally, incentivizing different types of tokens carries different types of benefits. Putting incentives toward 2-sided market liquidity, for example, won’t take as many native tokens off the market (b), but will allow for greater speculative demand (R).

Tokenomics in Practice

Ideally, tokenomics allow protocols to better serve users. In many cases, this means deepening liquidity to facilitate new stages of growth and creating new methods for ecosystem participants to generate income.

It’s always good to remember that any tokens taken off the market temporarily will find their way back, so scaling up yields, emitting deferred assets, and promoting lockups will create a pocket of risk that will eventually need to be diffused.

Additionally, this article is only half of the equation. Analyzing risks associated with tokenomics may start with math, but it ends with compliance. Different types of token incentive mechanisms carry different regulatory weight, with some of the above mechanisms being illegal in certain jurisdictions without adequate compliance measures.

In part two, we will explore the regulatory drawbacks and benefits of different tokenomics strategies, followed by a discussion thread on forum.oath.eco to start shaping the future of OATH in part three.



Justin Bebis

Smart Contract engineer focused on high-performance blockchain networks