TITLE:
Shifts in the Relationships between Gas Price and User Activity in Ethereum Following Ethereum Improvement Proposal 1559
AUTHORS:
Christopher Adiguna Ginting
KEYWORDS:
Ethereum, EIP-1559, Gas Price, User Activity, Blockchain
JOURNAL NAME:
Open Journal of Business and Management,
Vol.12 No.5,
September
18,
2024
ABSTRACT: Ethereum 2.0 introduced several significant upgrades, one being Ethereum Improvement Proposal 1559 (EIP-1559), which changed how gas price is determined. This study examines the relationship between gas price and user activity on the Ethereum protocol following EIP-1559 sampled every minute from December 1, 2023, 00:00:00 to December 15, 2023 23:59:59. This study shows a weak positive Pearson correlation between gas price and user activity with a bidirectional Granger causality between them. In other words, an increase in gas price does not decrease user activity, and vice versa. This contrasts with an earlier study before EIP-1559, which showed a moderate to strong negative Pearson correlation between gas price and user activity, as well as an only unidirectional Granger causality from gas price to user activity. The explanation asserted in that earlier study was that when gas prices were high, users waited to submit a transaction, possibly to avoid overpaying. The shift observed in this study, where increases in gas price no longer decrease user activity, shows that EIP-1559 appears to have enhanced user confidence in gas price calculations. This in turn influences their decision-making. Specifically, users are generally more assured in continuing their transactions under the new mechanism, as can be shown from the observation that the raising in gas prices does not cause user activity to decrease. On the other hand, the new observation of Granger causality in which increases in user activity slightly increases gas price is likely a result of the new gas price formula introduced by EIP-1559, which takes into account the network congestion and caps the extent of gas price adjustments. This formula introduces a predictable link between user activity dynamics and gas prices, thereby providing greater certainty for users.