Proof-of-Work versus Proof-of-Stake: John, Rivera & Saleh (2025)
Distilled · extracted by claude-sonnet-4-6 Jun 6, 2026, verified by claude-sonnet-4-6 Jun 6, 2026, extracted by gpt-6-luna Oct 4, 2026, verified by gpt-6-luna Oct 4, 2026
JEL (IAR-assigned): G10, G23, O33 · assigned from the abstract, not the journal
What this is. The paper’s core results, the model it builds, and the propositions it derives: enough to know what it found and how, without reading all 50 pages. To replicate or extend it, read the full source at the original.
Related literature. The paper builds on Pagnotta (2022) (blockchain security via a crisis-of-confidence attack model), Hinzen, John, and Saleh (2022) (limited adoption model for Bitcoin), and Huberman, Leshno, and Moallemi (2021) (cutoff equilibrium structure for blockchain users). It extends Saleh (2021) (PoS sustainability) by providing the first comparative security analysis across protocols, and adopts Nakamoto (2008)‘s 51% attack definition as the baseline PoW attack model.
John, Rivera, and Saleh compare equilibrium security across Proof-of-Work (PoW) and Proof-of-Stake (PoS) blockchains in a unified OLG model. They derive a general condition (Proposition 3, eq. 52) showing that PoS is more secure than PoW when the relative cost to attack PoS exceeds a threshold, while PoW is more secure when it falls below that threshold. Applying real-world parameter estimates for mining depreciation (46.5%-89% annually) and DeFi returns (3.73%-4.85% annually), they find the sufficient condition for PoS security dominance holds up to lambda = 4.53 (353% additional borrowing) under conservative estimates and lambda = 5.68 (468% additional borrowing) under less conservative estimates; current lending markets imply lambda is approximately 1. They also show that PoS’s security advantage is particularly salient at high scale: scaling generates full insecurity for PoW at lower scale than PoS, and achieves full security for PoS at lower scale than PoW.
Core results
Section titled “Core results”Magnitudes and significance are as reported. Locators point into the source PDF.
| # | Result | Locator | Magnitude |
|---|---|---|---|
| R1 | PoS generates higher validation investment than PoW for all model parameters because stakers avoid depreciation and energy costs | Proposition 3, eq. 52-53, p. 1979; Section 3, p. 1979 | PoS validation investment exceeds PoW whenever PoW and PoS generate identical validator revenues; ratio given by threshold zeta = [e^{-2rho} psi] / [e^{-2rho} psi + 1 - (1-delta)/(1+kappa_h)] <= 1 |
| R2 | Under real-world parameters (delta_1Y in [46.5%, 89%]; psi_1Y in [3.73%, 4.85%]) PoS generates higher equilibrium security than PoW | Corollary 1, pp. 1984-1985; Tables 1-2, pp. 1983-1984 | PoS is more secure than PoW whenever lambda <= 4.53 (453% of PoW borrowing, or 353% more) under conservative estimates, or lambda <= 5.68 (568% of PoW borrowing, or 468% more) under less conservative estimates; lambda approx 1 in practice |
| R3 | The PoS security advantage requires only mining hardware depreciation (delta_1Y) > DeFi return (psi_1Y) and a standard supermajority threshold (eta <= 2/3) | Proposition 4, eq. 54-55, p. 1980; Remark 1, p. 1981 | Sufficient condition: lambda <= (1/2)(1 + log(1+delta_T)/log(1+psi_T)); horizon-invariant per eq. 55 |
| R4 | Scaling generates full insecurity (pi^p = 0) for a larger set of attacker benefits under PoW than under PoS | Proposition 5, eq. 57, p. 1986; Section 4.1 | Sigma_0^{PoS} subset of Sigma_0^{PoW}: the set of attacker benefits generating full insecurity at scale is weakly larger for PoW |
| R5 | PoW becomes fully insecure at lower scale than PoS for any fixed maximal attacker benefit | Proposition 6, eq. 59, p. 1987 | Lambda_0^{PoS} >= Lambda_0^{PoW}: the scale at which PoW loses positive security is weakly lower than for PoS |
| R6 | Scaling generates full security (pi^p = 1) for a larger set of attacker benefits under PoS than under PoW | Proposition 7, eq. 64, p. 1989; Section 4.2 | Sigma_1^{PoW} subset of Sigma_1^{PoS}: scaling achieves full security for PoS in cases where it does not for PoW |
| R7 | PoS achieves full security at lower scale than PoW for any fixed maximal attacker benefit | Proposition 8, eq. 66, p. 1990 | Lambda_1^{PoS} <= Lambda_1^{PoW}: PoS reaches full security at a weakly lower scale than PoW |
| R8 | Equilibrium user fees decrease in blockchain scale and go to zero as scale grows, reducing validator revenues and potentially undermining security; this negative effect is more acute for PoW than PoS | eq. 60, p. 1987; Section 4, pp. 1985-1991 | f^p_{(i,t)} = (1 / Lambda) integral_0^{c_{(i,t)}} x dG(x); lower fees reduce validator revenue and investment, while greater adoption can offset this under low attacker benefits; the two effects favor PoS more broadly |
| R9 | Mining hardware prices and academic estimates imply substantial annual depreciation | Table 1, p. 1983; Table A1, p. 1993 | theblock.co: 60.4%-66.38%; Prat and Walter (2021): 47.7%-61.3%; De Vries and Stoll (2021): 46.5%-89%; Stinner 2021: 61.45% |
| R10 | Rolling annualized ETH staking returns provide the primary DeFi return calibration | Table 2, p. 1984 | Average 4.32%, median 4.33%, minimum 3.73%, maximum 4.85%, standard deviation .0031 |
| R11 | ETH lending returns from AAVE and prior estimates leave the paper’s main security conclusion unchanged | Table 3, p. 1985 | AAVE: 1.66% average (2023-2024); Chaudhary, Kozhan, and Vishwanath-Natraj (2023): 0.13% average, maximum 2.28% |
Overall (paper’s conclusion). Under current real-world conditions, PoS blockchains are more secure than equivalent PoW blockchains for any realistic scale. The security advantage of PoS relative to PoW is particularly salient at high scale: PoW is rendered fully insecure at lower scale, and PoS reaches full security at lower scale, than the respective counterpart. The results provide a formal foundation for understanding blockchain protocol design in the tokenomics and decentralized finance context.
Theory / model
Section titled “Theory / model”The paper models a single blockchain as either PoW or PoS. The economy is populated by overlapping generations of agents, each living three periods.
Users. Each generation- agent possesses a unit endowment and has utility:
where is the outside option return (p. 1961) and is the expected utility from adopting the blockchain under protocol . An agent adopts if and only if her wait disutility cost falls below a cutoff , determined in equilibrium. The agent allocates her endowment between DeFi investment (fraction ) and blockchain validation (fraction ) to maximize:
where is the period to return from validation and is the DeFi return, with the gross DeFi return and the cryptoasset price (p. 1966, eq. 11).
Wait disutility and fees. The blockchain has transaction rate . User pays a fee to prioritize processing. The expected wait time when paying fee given others’ fees is (p. 1963, eq. 6):
Each adopting agent optimally solves:
and the equilibrium fee function satisfies for adopters (Lemma 1, eq. 33, p. 1975).
Blockchain cryptoasset supply. The total supply follows:
where is the asset growth rate and is the block reward distributed in period (p. 1963).
PoW validation return. A miner born in period buys mining hardware at upfront cost per unit hash power (energy plus equipment), mines in period , and liquidates equipment at depreciated value (p. 1964). The lifetime return to mining is (eq. 9, p. 1965):
where is aggregate hash power, are block rewards, and is hardware depreciation. The key feature is that miners must pay both energy () and equipment depreciation () costs, making PoW validation more expensive than PoS staking.
PoS validation return. A staker born in period purchases coins at price , stakes them in period , and liquidates in . Letting be total staked capital (p. 1966, eq. 10):
Crucially, stakers recover their principal in full (no depreciation, no energy cost), so only the opportunity cost of foregone DeFi investment matters.
The user’s realized adoption return and expected return account for the probability of survival and the fee and wait costs (eqs. 3 and 5, pp. 1961-1962):
The DeFi investment return and protocol-specific attack thresholds complete the primitives (eqs. 11 and 13-18, pp. 1966-1970):
For PoS, the attacker’s share of stake must reach the protocol’s blocking threshold; the equivalent expenditure threshold defines (eqs. 15-17, pp. 1969-1970):
The optimal PoS attack expenditure and success probability are (eq. 18, p. 1970):
Attacker. A malicious agent draws benefit from disrupting the blockchain each period, and solves (p. 1967, eq. 12):
where is the probability of a successful attack given resources . For PoW, success requires (51% attack, eq. 13). For PoS, success requires acquiring and staking a fraction of total staked coins, i.e., , where is the relative cost of attacking PoS (eqs. 15-17, p. 1969-1970).
Method
Section titled “Method”The equilibrium definition imposes optimal adoption, fees, portfolio allocation, market clearing, validation investment, and survival (eqs. 19-32, pp. 1971-1975). Adoption and the symmetric fee strategy satisfy:
Users choose validation investment to equalize expected mining or staking returns with DeFi returns when the interior solution applies. The returns and DeFi condition are (eqs. 22-24, p. 1973):
Market clearing equates protocol-specific coin demand and supply, while validator quantities equal users’ total validation investment (eqs. 25-27, pp. 1973-1974):
Survival over a user’s three-period horizon is the product of period survival probabilities. Under a uniform attacker benefit, the implied probability is (eqs. 28-32, pp. 1974-1975):
Lemma 1’s closed-form fee schedule is (eq. 33, p. 1975):
The paper derives closed-form stationary cutoff equilibria for both protocols. The solution method is: (1) solve for optimal fees (Lemma 1), (2) derive the equilibrium return to validation for each protocol (Propositions 1 and 2), (3) characterize the equilibrium adoption cutoff as the supremum of cutoffs at which all agents with prefer the blockchain to the outside option, and (4) compare survival probabilities across protocols.
PoW equilibrium (Proposition 1, pp. 1975-1977). The equilibrium fraction of wealth invested in mining is (eq. 34):
The equilibrium hash power and survival probability (eqs. 36, 38-39):
PoS equilibrium (Proposition 2, pp. 1977-1978). The equilibrium staked capital and survival probability (eqs. 45, 47-48):
Key comparison threshold. Proposition 3 (eq. 52-53) derives the threshold:
Then and . Because always holds, PoS validation investment exceeds PoW investment whenever both generate the same revenues. Whether this advantage overcomes PoS’s lower attack threshold () depends on which side of the parameter lies.
Sufficient condition (Proposition 4). If the PoS supermajority threshold and annual depreciation (DeFi return), then the condition holds whenever (eq. 54):
This is horizon-invariant because for all . The remaining equilibrium objects report market value, protocol returns, survival bounds, and adoption utility (eqs. 35, 37, 39-42, pp. 1976-1977):
For PoS, the corresponding portfolio share, coin value, staking return, survival bound, user utility, and adoption cutoff are (eqs. 43-51, pp. 1977-1978):
The general security comparison and horizon-invariant sufficient condition are (eqs. 52 and 55, pp. 1979-1981):
Empirical specifications
Section titled “Empirical specifications”The paper is a theory paper with no regression specifications. The calibration in Section 3.3 provides real-world parameter estimates, comparing the model’s sufficient condition to data.
Mining equipment depreciation (Table 1, p. 1983). Using theblock.co ASIC price index (three efficiency tiers, August 2021-August 2023), the paper documents average annual price declines of 60.4%-66.38% across all tiers. Academic sources (Prat and Walter 2021: 47.7%-61.3%; De Vries and Stoll 2021: 46.5%-89%; Stinner 2021: 61.45%) confirm .
DeFi return estimates (Table 2, p. 1984; Table 3, p. 1985). Using Compass Financial Technologies daily ETH staking return data (October 2023 to June 2024): average (min 3.73%, max 4.85%). AAVE lending data (Chaudhary, Kozhan, and Vishwanath-Natraj 2023) gives an ETH average of 0.13% (max 2.28%) and a USDC maximum of 8.957%. All estimates satisfy over the relevant comparisons.
Parameter bounds. Applying the most conservative values (, ) to eq. 54 gives (453% of PoW borrowing, or 353% more). Less conservative values (, ) give (568% of PoW borrowing, or 468% more). Since current lending markets are overcollateralized and in practice, the sufficient condition is satisfied (Corollary 1, pp. 1984-1985). There are no estimating regressions, fixed effects, or standard-error calculations in this theory paper. The high-scale analysis defines full-insecurity and full-security sets and scale thresholds, then compares them across protocols (eqs. 56-66, pp. 1985-1990):
The equilibrium fee falls with chain scale, approaching zero as scale diverges (eq. 60, p. 1987):
The survival probability bounds user utility; below the stated threshold, adoption is zero (eqs. 61-62, p. 1988):
Datasets used
Section titled “Datasets used”| Dataset | Role in paper | Wiki page |
|---|---|---|
| theblock.co ASIC Price Index (three efficiency tiers, Aug 2021-Aug 2023) | Estimate annual mining hardware depreciation rate | No page yet |
| Compass Financial Technologies daily ETH staking return data (Oct 2023-Jun 2024) | Estimate annual DeFi return for PoS staking | No page yet |
| AAVE ETH/USDC lending rate data (Chaudhary, Kozhan, Vishwanath-Natraj 2023) | Robustness estimate of via DeFi lending rates | No page yet |
Note: the core results are theoretical propositions derived from the equilibrium model; the datasets above are used only to calibrate model parameters and verify that the sufficient condition (eq. 54) holds under realistic values. The paper is primarily a theory paper with no econometric identification.
When to read the full paper
Section titled “When to read the full paper”Use the original if you are: (1) building a model of blockchain security or protocol design; (2) evaluating whether a PoW or PoS blockchain is more secure for a specific parameter range (the threshold in eq. 53 is the key object); (3) studying DeFi ecosystem interactions with blockchain security; or (4) calibrating mining depreciation and DeFi yield parameters for a blockchain model. The proofs of all eight propositions are in Appendix B (pp. 1994-2002); replication code is at https://doi.org/10.7910/DVN/5VTIMI.
Attribution and rights
Section titled “Attribution and rights”Source: peer-reviewed, The Review of Financial Studies 38(7), 2025. This distillation was extracted by an LLM on 2026-06-06 and is not human-verified or independently reproduced. The paper is paywalled; reproduction rights follow OUP standard publication reuse rights. Extract-only.
John, Kose, Thomas J. Rivera, and Fahad Saleh. “Proof-of-Work versus Proof-of-Stake: A Comparative Economic Analysis.” The Review of Financial Studies 38, no. 7 (2025): 1955-2004. DOI: 10.1093/rfs/hhaf013.