§12 Bitcoin and the Battle of Standards

Central-bank monopoly and CBDC experiments provide a foil for on-chain money¹; the on-chain ecosystem that begins with Bitcoin pushes the question back to issuance rules, standard interfaces, and composable design. The “battle of standards” is not only a contest of protocol versions; it is a political-economy question of who defines money, how it is constrained, and in what way it is accepted by global holders—its outcome will deeply shape the practical path of monetary popularization.

Section 1. Intellectual Lineage of the Bitcoin Standard

The Bitcoin Improvement Proposal (BIP) process shows how standards evolve without a central authority: anyone may submit a BIP; miners and full nodes “vote” by whether they upgrade software. Adoption of BIP-141 (SegWit, 2017) and BIP-341 (Taproot, 2021) are verifiable cases of “standards contests” at the protocol layer.

Bitcoin was never an idea from nowhere. Satoshi Nakamoto’s whitepaper of October 2008 took up a core problem economic thinkers had posed but not solved over two centuries: how, without a trusted intermediary, to ensure that money issuance follows predetermined rules and cannot be arbitrarily changed by any actor with political power.

Ricardo’s metallism offered an early answer: constrain money supply by the physical cost of gold extraction, separating political power from determination of the money quantity. Yet the gold standard had historical limits—gold output is governed by geological randomness and cannot flexibly answer cyclical demand; cross-border settlement required physical gold shipment at high friction cost; more fundamentally, maintaining the gold standard depended on governments’ political will to honor convertibility under pressure, and political will historically never withstood sustained stress.

Hayek in Denationalization of Money pushed the problem one step further: rather than rely on gold, rely on competitive pressure among private issuers to maintain monetary quality. Competition’s virtue is that it requires no issuer to sustain perfect moral self-discipline; it need only ensure that market participants can identify and choose more stable money; the pressure of voting with one’s feet then forces issuers to keep discipline. But Hayek conceded that the mechanism was hard to sustain under 1976 technical conditions: there was no instant trustworthy information on monetary quality, no low-cost infrastructure for switching currencies, and no issuance record fair and transparent to cross-border holders alike.

Bitcoin answered this old question with an engineering method Hayek had not imagined: cryptographic commitment replaces metallic physical scarcity; a global distributed node network replaces trust in an issuing institution; open-source, public issuance code replaces reserve statements that are hard to audit after the fact. Anyone need not first trust some issuer; they may run a node themselves and check whether every on-chain transaction and the current total supply match the issuance schedule set in code. Monetary trust thus shifts toward verifiable rule execution—in the age of public on-chain ledgers, that shift has sharp institutional meaning, yet should not be exaggerated as a historical singularity: as bookkeeping technology changes, so does what trust attaches to. The second classical premise discussed in Chapter 7—that rule changes must pass auditable procedures—has verifiable instances in the BIP process: SegWit and Taproot adoption rates and full-node version distributions can be checked off-chain; yet the power structure among miners, developers, and holders remains a governance question for research—technical verifiability is not political neutrality.

Section 2. Algorithmic Constraint and Missing Elasticity

Bitcoin’s monetary policy is among the most watched and most contested designs in its code. Roughly every four years (more precisely every 210,000 blocks), the block subsidy halves: from the initial 50 bitcoin, to 12.5, to 6.25, to 3.125 after the fourth halving in April 2024. Over time new supply approaches zero; the total cap is about 21 million coins; around 2140 miners are expected to receive no further block subsidy, and network security will then depend on fee income.

This mechanism gives Bitcoin a strong “disinflation narrative”—in an age of long-run central-bank balance-sheet expansion, an asset whose supply curve is fully fixed and alterable by no political force has natural appeal. After subsidy halvings, miner incentives rely increasingly on the fee market—Easley, O’Hara & Basu (2024) use on-chain data to depict this evolution from “mining subsidy” to “market-priced settlement,” aligned with Nakamoto’s whitepaper §6 fee design². Background on unconventional easing appears in Chapter 3, Section 2³. Against that macro backdrop, Bitcoin’s “digital gold” narrative attracted institutional allocation interest: Grayscale trusts, MicroStrategy, and others held long-term; Tesla bought about $1.5 billion of bitcoin in 2021 and sold most of the position in 2022—institutional narrative is not equivalent to sustained strategic allocation⁴.

Yet the virtue of algorithmic constraint is precisely also its limit. Money in the modern economy is asked to perform three functions: store of value, medium of exchange, and unit of account. Gold’s historical record as a store of value is strong, but precisely because of supply rigidity, gold-standard economies could not sustain employment and output through credit expansion in contractions—one lesson of the Great Depression is how gold-standard deflationary forces amplified a local financial crisis into a global catastrophe. Keynes in A Tract on Monetary Reform (1923) already called the gold standard a “barbarous relic”—monetary rules fixedly anchored to metal struggle to adjust flexibly with employment and output fluctuations⁵. Bitcoin inherits gold’s store-of-value logic and inherits this macro-level fragility: if Bitcoin truly became the primary unit of account and borrowing, its fixed supply would introduce severe deflationary pressure in credit-cycle contractions; the real burden of debt would rise with Bitcoin’s appreciation, forming a self-reinforcing deleveraging spiral.

A more immediate problem: Bitcoin’s connection to everyday economic activity remains extremely limited. Most goods and services are still priced in fiat; Bitcoin holders face FX conversion when spending; violent price volatility makes it hard to accept as an everyday unit of account. The crux is mainly path dependence: billions of people are already accustomed to fiat pricing; migration coordination costs are extremely high, far beyond what technical feasibility alone can overcome.

Bitcoin’s compliance access, however, has taken another path: top-down entry into traditional asset-allocation menus via securitization channels, rather than bottom-up rewriting of retail pricing habits. In January 2024 the U.S. Securities and Exchange Commission approved multiple spot Bitcoin ETFs; as of June 2024, cumulative net inflows into U.S. spot ETFs were on the order of about $15 billion (Bloomberg/Farside Investors daily aggregates), with BlackRock’s IBIT among the main vehicles⁴. Three observable metrics must be distinguished: compliance channels (ETF creations/redemptions, custody disclosure), on-chain settlement flow (true on-chain payments as a share of global payment flow remain marginal—three metrics and data in Chapter 1, Section 8)⁶, and everyday pricing habits (mainstream retail still quotes in fiat). ETF approval changes asset-allocation structure and some volatility patterns—deeper institutional holding may bring more stable allocative buying, or may raise Bitcoin’s correlation with traditional risk assets—it does not yet mean Bitcoin has assumed broad unit-of-account or medium-of-exchange functions; a significant gulf remains between institutions “can buy” and the public “can spend.”

Section 3. Macroeconomic Implications of Supply Rigidity

To discuss the macro implications of Bitcoin’s supply rigidity, three layers must be separated: the gold analogy as store of value, the gold-standard analogy as monetary standard, and the competing-currencies analogy as currency competition. The three are often conflated; their policy implications differ sharply.

In the store-of-value register, supply rigidity is a virtue rather than a defect. Investors buy Bitcoin with logic similar to buying gold or certain scarce assets—hedging long-run erosion of fiat purchasing power, and providing a low-correlation hedge sleeve within a diversified portfolio. This function has no direct effect on overall macro operation, just as private gold holding does not affect monetary-policy effectiveness. Bitcoin’s most solid position in the global financial system at present is precisely this layer.

In the monetary-standard register—if the global economy truly shifted to Bitcoin as the standard, all important assets priced in Bitcoin, credit extended in Bitcoin—the macro implications of supply rigidity are entirely different. Any credit expansion would have to rest on Bitcoin lending, and the total cap would mean rates would be truly positive; there would be no “zero-cost liquidity.” Supporters argue this would eliminate moral hazard and force capital toward projects with real returns; opponents note it would periodically trigger severe deflation, leave debt-crisis damage unhedgeable, and remove central banks’ buffer of last-resort liquidity in crises. The amplitude of the business cycle might increase substantially.

In the competing-currencies register, Hayek’s normative claim must be distinguished from the empirical diversity of on-chain markets. In Chapter 11, “The Possibility of Controlling the Value of a Competitive Currency,” Hayek requires each issuer to “keep the (precisely defined) purchasing power as nearly as possible constant”—competition’s pressure direction is toward stable purchasing power, not tolerating a menagerie of inflation targets⁷. On-chain ecosystems present a more mixed spectrum: Bitcoin’s fixed supply, Ethereum’s adjustable-parameter inflation, fiat-mirrored stablecoins, collateralized public-domain money—these are actual choice outcomes under markets and regulatory fences, and cannot be read backward as Hayek’s having advocated “inflation-target competition.” Within sovereign fiat systems, the Woodford–Galí New Keynesian tradition supplies the strongest welfare defense to date for an about-2% inflation target; on-chain, rule suites are left for holders to select—quality is jointly determined by liquidity, verifiable collateral, and switching costs, not by a priori judgment of which rule is welfare-optimal.

On-chain “multiple rules coexist” is an observable fact of market stratification; whether Hayekian “purchasing-power competition” has already occurred at the retail layer must be tested separately against holding structure, switching costs, and peg-maintenance data—one cannot infer that private currency competition has replaced the central bank’s objective function merely because multiple tokens are exchangeable in DeFi. Chapter 7’s fourth judgment applies equally here: post-depeg repair speed must be checked against collateral state and on-chain verifiability of redemption queues, not judged a priori as “competition already effective” merely because “rules are public.”

Section 4. ERC-20: Interface as Power

In 2015 a developer proposed Ethereum Request for Comments No. 20, the ERC-20 proposal, defining a minimal interface standard of seven functions: totalSupply (query total supply), balanceOf (query balance), transfer (transfer), transferFrom (authorized transfer), approve (approve), allowance (query allowance), plus two events (Transfer, Approval). Any token contract following this interface can be natively recognized and operated by all wallets, exchanges, and applications on Ethereum without custom integration.

ERC-20’s significance far exceeds a technical specification. It created a pool of common knowledge: market participants know how any ERC-20 token operates; infrastructure providers need implement the interface only once to support all compatible tokens; users need not relearn operations for each token. Network effects from such standardization are exponential: Ethereum token counts grew rapidly from hundreds after ERC-20’s spread to tens of thousands and hundreds of thousands, forming the largest interoperable token ecosystem to date.

Yet interface standards bring not only benefits but standardized propagation of risk. During the 2016–2017 ICO wave, ERC-20’s low threshold let anyone deploy a “token” in hours; whitepaper quality varied widely; many projects were in substance financing fraud packaged as token sales. Satis Group’s (2018) independent classification of a 2017 ICO sample judged about 81% scams or high-risk projects⁸—an open interface lowers deployment cost, not identification cost. Markets filtered most speculative projects through liquidity evaporation and price collapse to zero, but losses left to early holders were real. Schumpeter’s “creative destruction” displayed itself violently in the ICO frenzy and subsequent market clearing: the cost was high, yet it also accelerated maturation of market capacity to identify token quality—today’s professional investors analyzing tokens focus on collateral structure, unlock schedules, governance mechanisms, and real use cases, not mere whitepaper promises.

ERC-20 and its successors (ERC-721 for NFTs, ERC-1155 for semi-fungible tokens, and others) established a principle: within an open-standard framework, a fall in issuance thresholds need not cause a fall in quality thresholds—market competition and auditability can carry the quality-filtering function. For that principle to hold, prerequisites are: market participants can obtain adequate information (on-chain data transparency), and there is no mechanism of forced use of particular tokens (no compulsory licensing). When both hold, accessibility from standardization and market screening can coexist.

Section 5. Transparent Mechanisms of On-Chain Supply Adjustment

Opacity of traditional monetary policy is one deep source of controversy. Even when central banks regularly publish policy-meeting minutes, internal discussion, expected paths of future operations, and weight allocation in actual decisions remain incompletely transparent to market participants. More important, the central bank may buy and sell assets in open markets and affect money supply without prior notice; “monetary-policy transparency” in practice is a limited commitment.

On-chain token supply-adjustment mechanisms in principle offer a fundamentally different transparency. Bitcoin’s issuance curve is hard-coded at the protocol layer; anyone can query current circulating supply, mining-reward height, and blocks to the next halving in real time on a block explorer. Parameter adjustments in major DeFi (decentralized finance) protocols—Compound, Aave, MakerDAO, and others—must pass public governance voting; proposal content, voting weights, and results are all on-chain queryable; the specific content and timestamps of parameter changes are permanently auditable in blockchain history.

This auditability has produced real governance dynamics in practice. When MakerDAO lowered DAI stability fees and collateral ratios in 2020, governance discussion underwent weeks of public debate on forums and in on-chain votes⁹; when the 2022 Curve Finance vulnerability triggered emergency parameter updates, the process and reasons were fully recorded on-chain. These events are far from perfect models of democratic governance; governance-token distribution is often concentrated among a few early holders and venture institutions; the substance of “on-chain democracy” sometimes more closely resembles “on-chain oligarchy.” Yet compared with traditional monetary policy’s opacity, this is at least a transparency that can be studied, criticized, and pushed to improve.

Transparency is not stability. Excessively frequent adjustment of on-chain protocol parameters, and markets’ uncertain reactions to governance proposals, can sometimes introduce greater short-term volatility than traditional monetary policy. Extreme stablecoin cases—the UST/Luna 2022 collapse—show that even with fully transparent parameters and fully public rules, design defects can produce transparent collapse rather than transparent stability¹⁰. On-chain transparency is a necessary condition for governance accountability, not a sufficient condition.

Terra/UST’s collapse shows that transparent rules do not automatically bring stability. One must ask which mechanism class the failure belongs to: UST mainly relied on LUNA burn/mint and Anchor’s high yield to maintain the peg, lacking hard collateral always above 100%—it belongs to algorithmic stablecoin + undercollateralized expansion, not MakerDAO/DAI-style CDPs.

Death-spiral chain (Liu et al. 2023; Brunnermeier et al. 2022; CFTC Staff Report 2022; Catalini, Goren & Shah 2021 three-way mechanism taxonomy; He et al. 2023 IMF Fintech Note spectrum preface; Clements 2021 three requirements for algorithmic types; Adams & Ibert 2022 algorithmic-run empirics): UST was algorithmic (third class) rather than overcollateralized CDP (second class); its stability depended on confidence and subsidy sustainability, not hard-collateral coverage at issuance—Clements (2021) noted before the collapse that algorithmic types must simultaneously satisfy baseline demand, arbitrage participation, and reliable price feeds; failure of any one can trigger a run; UST’s Curve-pool selling was a joint failure of “oracle + depth”¹¹. Once UST’s secondary price broke below $1, the protocol algorithm minted LUNA to buy UST; LUNA supply surged and price fell; LUNA’s fall raised “LUNA quantity that must be burned per unit UST,” absorption capacity weakened, UST depegged further—a self-reinforcing death spiral, different from overcollateralized CDPs’ path under shock of “collateral market value shrinks, coverage falls”: the latter has a hard-collateral buffer; the former fills the gap with own-token inflation. Anchor attracted inflows with about 20% UST deposit APY, subsidies paid by ANC inflation; when high yields proved unsustainable, large holders exited first (on-chain data show sophisticated-first exit); liquidity pulled away before retail reaction—tokenomics and stability mechanism failed together. When Terra’s collapse contagioned other ecosystems via cross-chain bridges, Board of Governors (2023) ex-post analysis showed that after UST depegged, bridged assets and related DeFi protocols faced synchronized redemption pressure—transparent rules + high TVL can still go to zero within days, and spillovers are not limited to a single chain¹⁰. The SEC’s complaint against Terraform Labs (2023) further records from a legal-anatomy angle: UST/LUNA characterized as unregistered securities, Anchor’s high yield an unsustainable subsidy—mechanism-class error + regulatory lag can stack; one cannot ignore cross-protocol portfolio risk merely because PCIM is an overcollateralized CDP. Ortiz & Witte (2023) ex-post comparison shows algorithmic stablecoins’ redemption speed under stress significantly faster than overcollateralized types (such as DAI)—UST collapsed from nearly $18 billion circulating within days, while DAI in the same period of ETH crash, though at a premium, maintained redeemability; HKMA RM09-2022 event study distinguishes the two mechanisms’ operating stress as “confidence-collapse runs” versus “collateral-shrinkage runs.” Gadzinski et al. (2024) co-instability analysis of a multi-stablecoin panel is consistent: in Terra/LUNA and IRON/TITAN events algorithmic types were the primary receivers of shock; fiat-collateralized and crypto-overcollateralized CDPs were relatively more resilient after shock—Congressional Research Service (2022) records from a policy-anatomy angle the path of UST dual-token arbitrage failing after depeg, secondary price once falling to about $0.12¹⁰. PCIM should be classed with the latter, and must use $C_0$, $x^*$ and reserves $R$ to lengthen run time—one must not infer from UST’s transparent collapse that “all on-chain stability rules share the same fate.”

PCIM/VRC-10 deliberately demarcates from UST on the spectrum—current tier $C_0 > 100\%$ overcollateralization (upper tier about 161.8%), prohibition of filling gaps by dual-token burns alone, prohibition of high own-token yield subsidies on the stablecoin. Competitive issuance changes issuer count and rule transparency, not the VRC-10 public-domain layer’s hard constraint that “on-chain hard collateral must cover face debt” ($C_0 > 100\%$)—VRC-11’s private-domain layer is 61.8% low collateralization, with structural gap $g(0)=38.2\%$ counted separately. If Bitgold and the BTG ecosystem crash together, overcollateralization likewise faces redemption runs and falling coverage; UST’s lesson is a warning of class error, not proof that “no liquidation line” immunizes against black swans. VRC-11’s private-domain layer uses 61.8% low collateralization—another risk class, not to be conflated with VRC-10 overcollateralization. Momtazi’s (2022) ex-post survey attributes Terra’s collapse to the triple stack of algorithmic mechanism, Anchor subsidies, and governance concentration¹²—item-by-item against the pit list PCIM must avoid; Lyons & Viswanath-Natraj (2020) show that even fiat-collateralized USDC’s peg still depends on reserve redeemability and OTC depth, not reserve statements alone¹². Open questions remain: cross-protocol portfolios may still introduce undercollateralized stable assets indirectly into the PCIM ecosystem as “reserves”—red-line compliance at the single-protocol level is not system immunity.

Section 6. Spontaneous Division of Labor Between Bitcoin and the Token Ecosystem

The on-chain monetary ecosystem that evolved in reality is not the result of anyone’s prior plan, but of market selection performing layered adaptation under multiple constraints. Bitcoin, Ethereum, various stablecoins, and VRC protocols occupy different functional positions in this ecosystem, competing and complementing one another.

Bitcoin in this ecosystem increasingly firmly carries the dominant store-of-value narrative. Its community explicitly opposes any modification that would destroy fixed-supply properties; Bitcoin ecosystem development focus is on extending security and enhancing Bitcoin’s usability in the broader financial system (Lightning Network for small payments, Bitcoin ETFs for institutional access), not on extending its smart-contract functionality. That character makes Bitcoin the crypto asset with the highest degree of institutional adoption, but also leaves it relatively limited in decentralized-finance applications.

Ethereum and its compatible chains carry the vast majority of smart-contract applications, stablecoins, DeFi protocols, and NFTs. The ERC-20 standard established Ethereum as the core platform of the composable token ecosystem. Yet Ethereum’s historical evolution—from proof of work to proof of stake (“The Merge,” 2022), from high-gas single-chain architecture to Layer-2 rollup scaling—shows it is a technical and governance system in continuous change, lacking Bitcoin’s near-sacralized rule immutability. Ethereum’s flexibility is the source of its application value and also the reason its “monetary properties” are relatively constrained.

Fiat stablecoins (USDT, USDC, and others) play the de facto primary value-transfer medium role in everyday trading, DeFi yields, and cross-border remittances. They trade price stability for centralized custody (reserves of equivalent dollar assets). A prior limit: Hayek’s Chapter 11 test standard is an autonomous unit of account with purchasing power kept as constant as possible, not an extension tool mirroring fiat—by that standard, USDT/USDC remain fiat extensions rather than autonomous monetary systems; if one relaxes to “widely circulating privately issued value tools,” then the most popular on-chain stability tools are precisely those most dependent on the existing fiat system. Keynes’s systematic account of “liquidity preference” in the General Theory—in uncertain times people tend to hoard monetary assets that can be realized immediately rather than bear risk—helps explain stablecoins’ excess demand in volatile markets¹³. This reality shows that the crypto ecosystem’s present stage of development still largely takes fiat value as its reference coordinate.

Stablecoins’ sudden rise approaches, in a sense, the first step Hayek envisioned of “private money gaining wide use”: privately issued value tools have gained large-scale circulation on global chains. Tether (USDT) on-chain circulating market cap once exceeded $120 billion in 2024 (CoinGecko and Tether Transparency monthly disclosures¹⁴); USDC over the same period was on the order of about $34 billion¹⁴—scale already comparable to M2 subcomponents of several mid-sized economies, yet whether and how they pass through domestic monetary-policy transmission still lacks cross-country panel-level causal identification. Chainalysis’s 2024 Geography Report shows Argentina, Turkey, and other high-inflation economies with stablecoin on-chain receive intensity significantly above the global mean⁶—this is an observable association, not sufficient evidence that “monopoly is already broken.” Yet stablecoins have not truly realized the autonomous monetary system Hayek hoped for—they are digital mirrors of the dollar; their stability depends on dollar credit; their operations depend on tacit acceptance within U.S. regulatory frameworks. USDC issuer Circle maintains close compliance relations with U.S. regulators; USDT’s reserve composition and compliance status have long been contested. These two cases show that under the existing international monetary system, if private stablecoins are to gain sufficient scale and trust, they almost inevitably must hook to the dollar system and its regulatory framework—which precisely limits their possibility as an independent monetary order.

Openverse’s VRC protocol family attempts to build a more complete monetary-system hierarchy: VRC-10 (Bitcurrency, public-domain money standard) issued with Bitgold overcollateralization; VRC-11 (Privcurrency, private-domain stablecoin) issued at 61.8% low collateralization within permissioned domains; VRC-12 (Bitsecurity, equity-type tokens) connecting RWA; VRC-13 providing standards for time-type assets. The design ambition is, through protocol-internal anchoring on the Layer 0 value-exchange layer (Bitgold as reserve base), to build a composable multi-currency structure on the Layer 1 application layer, while lowering public-domain money’s issuance threshold through PCIM (Public Currency Issuance Mechanism)—nominally mapping to various sovereign fiat units, with supply constrained at the base by dynamic-tier collateral ratios (upper tier about $C_0 \approx 161.8\%$), rather than simply anchoring central-bank liabilities.

The Openverse whitepaper (v2.1.5) casts itself as an experiment that completes payment and stable unit-of-account capacity on Bitcoin’s legacy (official copy calls it “Bitcoin 3.0”; this book cites it only as the design’s self-description): Bitcoin’s achievements in censorship-resistant store of value are outstanding, yet energy use, throughput, confirmation latency, price volatility, and on-chain fees make it hard to bear mass payments—Poon & Dryja’s (2016) Lightning Network whitepaper tries to ease small-payment friction with off-chain channels, but the settlement layer remains anchored to BTC volatility¹⁵; USDT and other centralized stablecoins fill the “constant value” gap yet reconcentrate credit on corporate balance sheets. Public-domain money tries to realize on-chain simultaneously verifiable collateral, parallel multi-fiat units, and open participation—inheriting Nick Szabo’s “bit gold” (2005: verifiable proof of work creates unforgeable scarce bits, distributed property registration) and Hayek’s intellectual resources on competing currencies, with a Layer 0 global decentralized value-exchange layer (PoS consensus, final-settlement anchoring, VTP cross-chain routing) as base, so that in-ecosystem application chains and external Layer 1 networks can all connect, rather than a closed Hub/Zone LAN¹⁵. The whitepaper also admits frankly: the ambition of public-domain money to “partly replace fiat” far exceeds what most jurisdictions currently tolerate, belonging to the same class of institutional friction Libra once met—a gulf between thought experiment and political reality that technology alone cannot fill.

Section 7. Competition Among Cross-Chain Standards: Protocol Interoperability and Value Lock-In

As on-chain asset scale grows, multi-chain ecosystem interoperability problems become increasingly salient. Holders cannot use tokens on chain A directly in applications on chain B, giving rise to cross-chain bridges as an infrastructure category. Yet the history of cross-chain bridges is almost a history of security incidents: in 2021–2022, Ronin (about $625 million), Wormhole (about $325 million), Nomad (about $190 million), and others were successively attacked; Chainalysis (2022) tallied about $2 billion stolen in cross-chain bridge hacks that year¹⁶. Such losses reflect structural fragility in bridge design itself: bridge protocols must maintain a set of contracts and verification mechanisms on each of two chains; a vulnerability on either side can empty the bridge’s assets—Board of Governors (2023) analysis of cross-chain contagion after Terra’s depeg also shows that the bridge layer can amplify systemic risk.

This fragility prompted rethinking of cross-chain interoperability standards. IBC (Inter-Blockchain Communication) is the cross-chain communication standard developed in the Cosmos ecosystem; its design philosophy is: create no intermediate custody layer; let the two chains directly verify each other’s consensus proofs, securing cross-chain transfers with cryptography rather than intermediaries. The IBC model has clear security advantages but requires both chains to support the IBC standard; integration with large public chains such as Ethereum still faces technical challenges.

VTP (Value Transfer Protocol) is Openverse’s proposed cross-chain value-transfer standard—positioned analogously to HTTP for the internet: providing a standardized cross-chain value-transfer interface so that assets on different chains can complete transfer and settlement in standardized ways without developing bridge logic for each pair of chains. Only if VTP passes stress tests and achieves design goals might it push the on-chain monetary ecosystem toward “internetization”—just as HTTP unified data transmission among different network nodes, VTP’s goal is to unify value transmission among different value ledgers; until then, IBC and other production standards and various custodial bridges will long coexist.

Competition among cross-chain standards is in substance a power contest over “who defines the foundational rules of on-chain value transmission.” It deeply resembles early internet protocol standards wars: TCP/IP’s victory owed less to maximal technical elegance than to sufficient simplicity and openness, and adoption by critical nodes. On-chain standards’ adoption logic is similar—technical superiority is necessary but not sufficient; quality of developer tools, strength of ecosystem support, and adoption rates of critical applications matter equally.

Section 8. The First Meaning of Popularization: Issuance Thresholds Fall Sharply

At this point, the first meaning of “monetary popularization” can be summarized: issuance qualification shifts from licenses to code, from institutions to protocols, from political authorization to publicly deployable standards.

In traditional monetary systems, money issuance is among the most strictly regulated privileges. Issuing fiat requires state sovereignty; issuing bank deposit money requires a banking license, satisfying capital adequacy, reserve requirements, and strict supervisory review; issuing money-like instruments (checks, bills of exchange, payment tokens) requires corresponding payment-service licenses. These thresholds have institutional logic—preventing over-issue, protecting holders, maintaining system stability—but they are also powerful barriers to market entry, in practice confining money issuance to a few licensed institutions.

ERC-20 lowered the threshold for “issuing interoperable tokens” to: a computer, tens of dollars of fees on Ethereum, and publicly available contract templates. The EIP-20 specification hardens interface semantics for transfer/approve/balanceOf and related functions; Wood’s Yellow Paper §4.2 casts token transfers as state-machine transitions; Buterin’s (2014–2015) Design Rationale clarifies account-model and gas-metering trade-offs—individuals, organizations, or protocols need no license, capital review, or regulatory approval to deploy a fully functional token contract within hours¹⁷²—money issuance shifts from privilege to open engineering choice. Protocolization of thresholds releases part of the issuance impulse formerly locked inside institutional licenses; consequences are mixed and must be screened by markets after the fact, not by prior approval.

This openness brings not only efficiency but chaos that needs new filtering mechanisms: among hundreds of thousands of tokens, the vast majority are destined to go to zero. Filtering relies mainly on markets’ ex-post screening—liquidity depth, holder dispersion, protocol audit reports, real application scenes, developer-ecosystem activity—rather than regulators’ ex-ante approval. These indicators jointly constitute a new threshold of “on-chain market access,” with logic entirely different from traditional regulatory licenses: it is open but costly, observable but also manipulable, decentralized but also productive of new information asymmetries.

PCIM (Public Currency Issuance Mechanism) pushes this logic to the public-domain money layer: through a standardized Bitgold collateral process, any participant meeting collateral conditions can participate in Bitcurrency issuance, opening to a broader set of market participants the money-creating capacity that once belonged only to banking—namely “on the basis of collateral assets, issue circulating money.” What is opened is participation qualification and rule visibility, not abolition of collateral constraints; money creation must still obey on-chain verifiable staking and redemption conditions.

Compared with traditional banks’ credit creation, the core difference PCIM claims at the documentation layer lies in information symmetry and rule predictability. Traditional banks expand monetary credit to borrowers through internal credit approval on a deposit base; the process is almost opaque to external observers—asset quality, reserve status, credit concentration all sit in banks’ internal systems; outsiders can glimpse only through quarterly reports and regulatory disclosure. PCIM’s collateralized issuance process, when deployed as designed, is recorded end-to-end by on-chain contracts: collateral type and value, issuance amounts, real-time changes in collateral ratios—any node can verify. Issuance rules do not vary by issuer identity; all participants operate under the same protocol constraints. Whether this transparency suffices to support public trust and to compete with traditional banking on macro stability still requires testing after scaled operation, and cannot be extrapolated from a whitepaper alone as a completed institutional experiment.

The first meaning of popularization—the fall in issuance thresholds—is the most perceptible dimension of on-chain monetary change, and the one that most directly touches traditional monetary institutions, but it is only the first layer. Whether holding rules can be publicly audited, whether governance rights can be substantively exercised, whether the monetary system can be imagined as public infrastructure—all build on this layer. The standards contest Bitcoin opened is fundamentally about who sets monetary thresholds and to whom they open; after standards land, incentive structure determines whether participants stay.

The fall in issuance thresholds itself also does not equal a rise in monetary quality. In traditional systems, licensing, though monopolistic, also bound some degree of compliance requirements and financial-soundness review into issuance rights. The opened on-chain environment removes that binding: anyone can issue, anyone can hold; market filtering replaces regulatory screening. This mode is more efficient, but the reality of harm is also higher—countless ordinary users have paid real losses before immature market mechanisms. The challenge for PCIM and the VRC protocol system is how, while keeping open participation, to build sufficiently robust protocol-native constraints so that falling thresholds truly evolve into improved accessibility of quality money, not merely a flood of junk assets.