🤖 AI Summary
This study investigates the causal impact of protocol fee changes on liquidity provision behavior in automated market makers, effectively disentangling confounding factors such as fee revenue, adverse selection, and routing responses. Leveraging Uniswap’s fee switch event, the authors employ a matched overlapping event study combined with a difference-in-differences design, constructing a hash-verified panel dataset from on-chain logs. This approach enables the first identification of liquidity providers’ (LPs’) genuine responses to reduced fee splits and clearly delineates LP behavior from trader-side dynamics under variable fee mechanisms. The paper introduces a channel admissibility audit framework and finds no significant short-term effects on liquidity supply, depth, or LP composition, suggesting limited efficacy of fee adjustments under current mechanisms; however, Token-1 trading volume and native fee revenue violate the parallel trends assumption.
📝 Abstract
Automated market maker (AMM) fee rules are often evaluated by liquidity-provider (LP) welfare, but that objective mixes fee revenue, adverse-selection loss (loss-versus-rebalancing, LVR), routing response, and liquidity supply. Fixed-fee Uniswap v3 history cannot separate these channels or identify counterfactual trader-facing dynamic-fee rules. Real fee-related variation nonetheless exists: the Uniswap protocol-fee switch cut LP take-rates with tier-differentiated intensity while leaving trader-facing fees unchanged. Using a pre-specified matched-overlap event-study difference-in-differences design, we estimate the liquidity-supply response to take-rate cuts, the kernel K_L that simulator-based fee-controller evaluations routinely freeze, while reconstructing treatment, event time, unit roles, and outcomes from public logs into a frozen, hash-checked panel before any estimate. We detect no large short-run average response in active liquidity or local depth; LP participation and composition, more precisely estimated, likewise show none, so the result is a non-detection at the design's resolution rather than a precise zero. Token-1 volume and native fee income fail the parallel-trends gate and are reported descriptively. A channel-admissibility audit delimits the estimand: the LP-side response K_L is design-based, while trader-facing dynamic-fee protection is a model-conditioned boundary, not a second estimand.