What Is Tokenomics

Tokenomics is not “the economics of a coin” and not a spreadsheet with allocation percentages. It is an analytical discipline that determines whether a project survives or not. Below is a formal definition, the sciences tokenomics draws from, how it differs from cryptoeconomics, and a numerical example that shows how parameter choices destroy or save a system.

Definition

Sustainability is a state of equilibrium in which the chosen supply and demand models appear beneficial to key stakeholders in both the short and long term.

Three key words: models, stakeholders, sustainability. If a project lacks even one of these elements, it is not tokenomics — it is a Google Sheets table.

Timeline

Tokenomics ≠ Cryptoeconomics

Cryptoeconomics studies economic mechanisms in blockchain systems broadly: consensus, validation, MEV. Tokenomics focuses on designing and analyzing tokens as economic instruments.

Whether tokenomics is a subset of cryptoeconomics or a standalone discipline remains debated. Kensuke Ito (2024) in Cryptoeconomics and Tokenomics as Economics: A Survey with Opinions (arXiv:2407.15715) proposes treating tokenomics as a separate field that overlaps with cryptoeconomics but is not contained within it — since tokenomics relies on microeconomics, behavioral economics, and game theory beyond the blockchain context.

In practice, the boundary runs along the object of analysis: studying PoW/PoS consensus, MEV strategies, and gas optimization — that is cryptoeconomics. Designing emission curves, airdrop strategies, staking rewards, and token utility — that is tokenomics. The fields overlap: staking rewards simultaneously affect network security (cryptoeconomics) and the token supply model (tokenomics).

Six Disciplines Behind Tokenomics

Tokenomics does not invent theory from scratch. It takes tools from six established disciplines and applies them to systems with a token:

What tokenomics is built on

Web2 vs Web3: What Changes for Economics

The comparison is easiest to see through a loyalty program.

Web2 Loyalty Program

The project fully controls user behavior. The flow is linear:

1. The user performs “useful actions” (purchases, surveys)
2. The project issues points at its own rate
3. Points are redeemed for benefits within the project ecosystem

The project controls everything: the earning rate, the rewards catalog, the redemption rules. The user is a passive participant.

Web3 Tokenization

The user owns the token and makes independent decisions:

1. The project issues tokens for useful actions
2. The user decides what to do: spend within the ecosystem, sell on the market, or hold
3. The ecosystem is independent of the project — other developers build utility
4. Token markets allow exchanging the token for BTC, ETH, or stablecoins

This is why the unit economics of a token project is radically more complex than traditional: CAC depends on the token price, the price depends on demand, demand depends on the number of users.

Numerical Example: Three NFT Economy Variants

Let’s walk through a concrete example. A game with NFT characters has 100 participants. Each can buy one of three NFT types:

Now let’s calculate the supply-demand balance over the full lifecycle. We assume participant daily expenses are token sinks (burns or protocol fees that leave circulation), so in Variants B and C they count as demand alongside the NFT purchase; in Variant A expenses are zero, so the sink term vanishes.

Variant A (Cheap NFT)

• Buyers: 100 × 90% = 90 people
• Token supply: 90 × 1 × 60 days = 5,400
• Token demand (NFT purchases): 90 × 20 = 1,800
• Result: supply 5,400, demand 1,800 → supply is 3x greater than demand

Variant B (Mid-range NFT)

• Buyers: 100 × 50% = 50 people
• Supply: 50 × 3 × 90 = 13,500
• Demand: NFT purchase (50 × 100 = 5,000) + expenses (50 × 1 × 90 = 4,500) = 9,500
• Result: supply 13,500, demand 9,500 → supply exceeds demand by 1.4x

Variant C (Expensive NFT)

• Buyers: 100 × 20% = 20 people
• Supply: 20 × 5 × 120 = 12,000
• Demand: NFT purchase (20 × 400 = 8,000) + expenses (20 × 2 × 120 = 4,800) = 12,800
• Result: supply 12,000, demand 12,800 → demand exceeds supply

Analysis Framework: Three Categories

Any tokenomics system can be decomposed into three categories of factors:

External Factors

What the project does not control:

• Participant decision-making (buy probability, lifespan)
• Market conditions (if BTC drops, the native token drops too)
• Marketing and product inputs (how many users arrive)

Internal Factors

What the project designs:

• Supply model — how tokens are created and distributed
• Demand model — what the token is spent on and why
• System parameters — specific numbers (NFT price, reward size, fee rate)

Sustainability

The result of external and internal factors interacting. Key questions:

1. What is the supply-to-demand ratio for the token?
2. How much capital is in the treasury?
3. What is the expected token price in each period?
4. Is it beneficial for all participants to acquire and hold the token?

The Stakeholder System

Stakeholders are everyone who interacts with the system and affects the supply-demand balance. Each stakeholder simultaneously wants something from the system and is needed by the system for something. Tokenomics works when these interests align.

Short-Term Stakeholders

Long-Term Stakeholders

The full stakeholder composition depends on the project type. An L1 blockchain will have validators and builders. A GameFi project — players and content creators. A memecoin — traders and insiders. But the principle is the same: every stakeholder affects the supply-demand balance.

Stakeholder Utility Function

To predict a participant’s behavior, you need to understand their utility function — a formula describing what they value. An analogy: let d = donuts, c = cream:

• Alice: U = d + c (both equally valuable)
• Bob: U = d + 3c (cream is 3x more valuable)
• Carol: U = d + c + d·c (synergy — together worth more than apart)
• Dave: U = d + 0·c (cream is irrelevant)
• Eve: U = d − c (cream reduces utility)
• Frank: U = d / (1 + c) (donuts only valuable without cream)

In a real project, utility functions are identified three ways:

How to determine the utility function