An Analysis of Ethereum’s Proof of Stake Incentive Model

Originally published July 16, 2020 on Medium. By Tanner Hoban and Tom Borgers. Both authors work in Corporate Development at ConsenSys. This report was an independent research effort to review the network economics of Ethereum 2.0 spec v0.12.

In March of this year, we were awarded a grant by MolochDAO for an economic review of Ethereum 2.0, which originated as a response to this RFP:

Since then, we have been hard at work analyzing the Eth2 network and its Proof of Stake-based economic incentive system. Our conclusions are based on our own research, an economic model we built to reflect the inputs and outputs of the Eth2 network, and a series of stakeholder interviews representing the key participants in the Ethereum ecosystem.

All our findings are synthesized in the following report:

Ethereum 2.0 Economic Review: An Analysis of Ethereum’s Proof of Stake Incentive Model

We would like to thank MolochDAO, the stakeholders who we conversed with, and the Ethereum Foundation for their support throughout this project. Thank you especially to Danny Ryan, Barnabe Monnot, Trent Van Epps, and Vitalik Buterin for their comments and suggestions on drafts of this report.

While we highly recommend reading through the whole report, below we have included our executive summary. For any inquiries, please contact us through Twitter — @thomasborgers and @tehoban1 — DMs open!

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The Ethereum 2.0 network upgrade is an ambitious and gradual shift towards a Proof-of-Stake consensus algorithm and incentive system, which has far-reaching implications on the economic properties of the network. The design of the system is complex — the incentive mechanism rewards honest network participants for validating transactions and finalizing historical states of the network, while penalizing offline and malicious validators. In this paper, we define, measure, and analyze Eth2’s cryptoeconomic security using a detailed economic model of the network and new economic evaluation tools.

First, to support an economic review, we constructed an economic model, built in Excel, for interpreting outputs of the system under current specifications and for select scenarios. Over the course of this project, we incrementally developed and leveraged this model to articulate expectations and form data-driven conclusions on validator revenues, costs, yields, and network issuance. The Eth2 system is reliant on nearly 100 variables that have a material impact on these outputs. With this model, we dynamically illustrate validator profitability at varying ETH prices and total ETH staked, underscoring the variability of impact on network security.

We define a required and sufficient level of economic security in Eth2.0 Phase 0 using a set of assumptions around the cost to attack the network. The objective is to make attacks costlier than the potential benefits of an attack and to achieve a similar level of security to the current Ethereum blockchain (Eth1). We identify two main categories of economic attack vectors, each with variants and differing levels of risk: Supermajority Attacks and Finality Attacks. In Phase 0, we are primarily concerned with attacks that aim to sabotage the network; we find the network is at risk of sustaining such attacks, but are more concerned about further phases. We estimate an ETH stake rate target of 13.8%, which provides adequate security from potential attacks under historical ETH price and hashrate conditions.

Security in Eth2 is highly dependent on ETH staked, which itself will be a function of yields. We form a model to understand the motivation of capital efficient investors, which we term the Required Serenity Active Validator Yield (RSAVY) model, addressing the risks and costs of staking and the corresponding required rate of return (RRR). Based on our results, we expect a required revenue yield (which we use as a proxy for a minimum yield) from validators under an optimized network (endogenous and exogenous) of 3.3% for validators to consider participation. Under a more bearish yet stable scenario, this revenue yield requirement increases to 11.6%.

The RSAVY model is leveraged not only to calculate required rate of returns, but also to form a picture of the network under select scenarios. We apply different parameters in these scenarios to support our conclusions and recommendations, which are summarized below.

Conclusions:

• Ethereum 2.0’s Proof of Stake is highly complex relative to Proof of Work. Eth2 is a highly complex and elaborate system. It is elegantly constructed and thoughtfully designed, but from a validator’s perspective can be difficult to grasp, contributing to a sense of uncertainty and unpredictability, presenting a practical and narrative barrier for potential capital efficient validators.
• Security of the network in Eth2 is dependent upon three key variables: ETH staked, the price of ETH, and volatility. Each of these variables has a direct or indirect impact on the cost of attacking the network. Total ETH staked is the most controllable variable, while the price of ETH has a direct and potentially large impact on network security but is outside the control of the system. Volatility can come from different sources and impacts both ETH stake and price of ETH indirectly.
• Attacks on Eth2 are easier to scale than on Eth1. In Eth2, the physical and hardware-driven burdens of network participation recede to essentially minimal hardware and power consumption. Moreover, the flourishing of DeFi and eventual connectivity to Eth2 can vastly accelerate and magnify this trend.
• Capital efficient validators are more predictable. While participation from Ethereum enthusiasts is important for a successful Beacon Chain launch, it is ultimately inadequate to reach sufficient levels of security. Attracting capital efficient validators will lead to higher fidelity in targeting a sufficient level of ETH staked.
• Targeting 13.8% ETH staked will match security levels of Eth1 at historical prices. We calculate that the target ETH stake rate for adequate security under historical price fluctuations is 13.8%.
• Economies of Scale for validating exist but are reduced at higher ETH prices. Unlike Proof of Work environments where profitability can only be accomplished by increasingly large-scale operations, Eth2 validating becomes progressively less expensive as the price of ETH increases. We generally find the network economics highly favorable for more decentralized network participation, meeting Eth2’s design objectives.
• 77.7% of the current ETH supply is in validator ‘qualified’ wallets (holding over 32 ETH). Approximately 86.6mm ETH (77.7% of total supply) is being held by non-exchange wallets with over 32 ETH. An additional 18.7mm ETH is managed by exchanges subject to staking services. This is a compelling serviceable addressable market, and a key objective of the incentive program to maximize network participation should be to convert these wallets into active validators.
• Eth2 is paying significantly less for security than Eth1. Using current beacon chain specs and 15.5mm ETH staked (13.8%), we estimate network inflation of 0.55% per year, far less than the current 4–4.5% from Ethereum’s Proof of Work network.
• Network security is heavily reliant on the price stability of ETH. Our primary concern with regards to the economic stability and security of Eth2 is the resilience of the network at low ETH prices. Combined with the ability for an adversary to rapidly scale attacks, we consider this a cause for concern.
• The lack of liquidity in Phase 0 and 1 might cause unpredictability and centralization. Given the lack of a two-way bridge between Eth1 and Eth2, and the lack of transaction capabilities in Phases 0 and 1, we expect a secondary market to form facilitated through derivatives and centralized exchanges. A high concentration of validators leveraging these platforms creates centralization risk and unpredictability.
• Beware of Derivative attacks. The Ethereum ecosystem is rapidly evolving and so is Ether as an asset class, with options volume increasing and unique financial instruments like “flash loans” being used in malicious exploits. With this momentum, derivatives could become the favored avenue of attack for adversaries.

Recommendations:

• Increase the Base Reward Factor to at least 128: We acknowledge the implications of increasing the network’s payment for security, but at a Base Reward Factor of 64, we believe the network is underpaying for security — and it would be prudent for the network to err on the side of caution during its phased migration to proof of stake.
• Explore a more dynamic method to changing Rewards in the event of a shock, such as an ETH price collapse (i.e. explore the implementation of a safety net). We recommend exploring a more dynamic method for scaling rewards or altering the Base Reward Factor in the case of network shocks. This could include using threshold triggers, step functions, or functions related directly to ETH price.

Please refer to the report for disclosures.