Why Linear Emission Schedules Are a Design Flaw

Linear emission schedules are flawed because they create a predictable, inelastic supply of new tokens that consistently outpaces organic demand. This mechanic forces protocols like SushiSwap and early Avalanche subnets into a perpetual cycle of subsidizing usage with inflation, which dilutes existing holders.

The counter-intuitive insight is that a predictable decline in rewards, as seen in Bitcoin's halvings, creates stronger long-term alignment than a fixed linear schedule. A cliff-and-vest model for team tokens, while common, simply delays the same problem and leads to concentrated sell events.

Evidence from DeFi shows protocols with aggressive linear emissions, like many Curve wars participants, experience severe price decay despite high TVL. The sell pressure from mercenary capital becomes the dominant market force, decoupling token price from protocol utility.

Linear schedules misprice incentives. They pay the same reward for securing an empty network as a congested one, creating a permanent subsidy for security that inflates away token value. This is the core economic failure of Proof-of-Work and many early DeFi farms.

Emissions are a network cost. They must be treated as a dynamic expense, not a fixed liability. A protocol's emission rate must be a function of state—like network usage, fee revenue, or validator load—to align cost with value generated.

Static emissions create predictable attacks. Projects like Sushiswap and early OlympusDAO forks demonstrated that predictable, high emissions attract mercenary capital that exits at schedule cliffs, collapsing tokenomics. Dynamic schedules obfuscate exit timing.

Evidence: Ethereum's EIP-1559 is a state-dependent fee burn, not an emission, but it proves the principle. The burn rate dynamically adjusts with network demand, directly linking the network's monetary policy to its utility. This is the model for next-gen emissions.

Linear schedules are predictable decay. They create a known, declining subsidy that front-loads sell pressure and guarantees a decreasing reward for providing the same service, which disincentivizes long-term participation.

They ignore network utility curves. A protocol's value accrual is rarely linear; it follows an S-curve with phases of bootstrapping, growth, and maturity. A fixed emission schedule is mismatched to these phases, wasting tokens during saturation.

This creates mercenary capital cycles. Projects like early SushiSwap and countless DeFi 2.0 forks demonstrated that predictable, high initial APY attracts yield farmers who exit upon the first emission cliff, destabilizing the treasury and token price.

Evidence: Analyze the TVL charts of any major 2021-era farm. The inevitable post-emission cliff collapse proves the model fails to convert subsidized liquidity into sustainable usage, unlike veToken models (Curve, Balancer) that better align incentives.

Linear schedules guarantee predictable sell pressure. They create a clockwork market where insiders and farmers front-run the inflation, dumping tokens on new entrants. This predictable dilution erodes the protocol's security budget by devaluing the very asset used to pay validators or stakers.

Exponential decay models real-world adoption. Network growth follows an S-curve, not a straight line. A decaying emission schedule, like Bitcoin's halvings or Curve Finance's veCRV model, front-loads incentives for bootstrapping and reduces inflation as usage scales. This aligns long-term tokenholder and protocol health.

The flaw is ignoring time preference. A linear schedule pays the same reward tomorrow as today, failing to compensate for the risk of early participation. Projects like Axie Infinity demonstrated how predictable, unadjusted emissions lead to hyperinflation and economic collapse when user growth stalls.

Evidence: Look at stablecoin yields. Protocols with linear emissions, like many early DeFi farms, see their APYs collapse to zero as TVL grows. In contrast, Ethereum's transition to proof-of-stake uses a dynamically adjusting, non-linear issuance that responds to the amount staked, preserving the security-to-inflation ratio.