How Web3’s ‘programmable commerce layer’ will transform the global economy

World Economic Forum, 28 November 2022. Originally published here. With Justin Banon, Jason Potts and Sinclair Davidson.

The world economy is in the early stages of a profound transition from an industrial to a digital economy.

The industrial revolution began in a seemingly unpromising corner of northwest Europe in the early 1800s. It substituted machine power for animal and human power, organized around the factory system of economic production. Soon, it created the conditions to lift millions of humans from a subsistence economy into a world of abundance.

The digital economy began with similarly unpromising origins when Satoshi Nakomoto published his Bitcoin white paper to an obscure corner of the internet in late 2008. We call this the origin of Web3 now – with the first blockchain – but this revolution traces back decades as the slow economic application of scientific and military technologies of digital communication. The first wave of innovation was in computers, cryptography and inter-networking – Web1.

By the late 1990s, so-called “e-commerce” emerged as new companies, which soon became global platforms, built technologies that enabled people to find products, services and each other through new digital markets. That was Web2, the dot-com age of social media and tech giants.

But the actual age of digital economies was not down to these advances in information and communications technologies but to a very different type of innovation: the manufacture of trust. And blockchains industrialize trust.

Industrial economies industrialized economic production using physical innovations, such as steam engines and factories. Such institutional technologies organize people and machines into high production. What the steam engine did for industry, the trust engine will do for society. The fundamental factor of production that a digital economy economizes on is trust.

Blockchain is not a new tool. It is a new economic infrastructure that enables anyone, anywhere, to trust the underlying facts recorded in a blockchain, including identity, ownership and promises represented in smart contracts.

These economic facts are the base layer of any economy. They generally work well in small groups – a family, village or small firm – but the verification of these facts and monitoring of how they change becomes increasingly costly as economic activity scales up.

Layers of institutional solutions to trust problems have evolved over perhaps thousands of years. These are deep institutional layers – the rule of law, principles of democratic governance, independence of bureaucracy etc. Next, there are administrative layers containing organizational structures – the public corporation, non-profits, NGOs and similar technologies of cooperation. Then we have markets – institutions that facilitate exchange between humans.

It has been the ability to “truck, barter and exchange” over increasing larger markets that has catapulted prosperity to the levels now seen around the world.

Information technology augments our ability to interact with other people at all levels – economic, social and political. It has expanded our horizons. In the mid-1990s, retail went onto the internet. The late 1990s saw advertising on the internet. While the mid-2000s saw the news, information and friendship groups migrate to the internet. Since their advent in 2008, cryptocurrencies and natively digital financial assets have also come onto the internet. The last remaining challenge is to put real-world (physical) assets onto the internet.

The technology to do so already exists. Too many people think of non-fungible tokens (NFTs) as trivial JPEGs. But NFTs are not just collectable artworks; they are an ongoing experiment in the evolution of digital property rights. They can represent a certificate of ownership or be a digital twin of a real-world asset. They enable unique capital assets to become “computable,” that is, searchable, auditable and verifiable. In other words, they can be transacted in a digital market environment with a low cost of trust.

The internet of things can track real-world assets in real-time. Oracles can update blockchains regarding the whereabouts of physical assets being traded on digital markets. For example, anyone who has used parcel tracking over the past two years has seen an early version of this technology at work.

Over the past few years, people have been hard at work building all that is necessary to replicate real-world social infrastructure in a digital world. We now have money (stablecoins), assets (cryptocurrencies e.g. Bitcoin), property rights (NFTs) and general-purpose organizational forms (decentralized autonomous organizations (DAOs)). Intelligent people are designing dispute-resolution mechanisms using smart contracts. Others are developing mechanisms to link the physical and digital worlds (more) closely.

When will all this happen? The first-mover disadvantage associated with technological adoption has been overcome, mostly by everyone having to adopt new practices and technology simultaneously. Working, shopping and even entertaining online is now a well-understood concept. Digital connectedness is already an integral part of our lives. A technology that enhances that connectedness will have no difficulty in being accepted by most users.

It is very easy to imagine an interconnected world where citizens, consumers, investors and workers seamlessly live their lives transitioning between physical and digital planes at will before the decade concludes.

Such an economy is usefully described as a digital economy because that is the main technological innovation. And the source of economic value created is rightly thought of as the industrialization of trust, which Web3 technologies bring. But when the physical parts of the economy and the digital parts become completely and seamlessly join, this might well be better described as a “computable economy.” A computable economy has low-cost trust operating at global market scale.

The last part of this system that needs to fall into place is “computable capital.”

Now that we can tokenize all the world’s physical products and services into a common, interoperable format; list them within a single, public ledger; and enable market transactions with low cost of trust, which are governed by rules encoded within and enforced by the underlying substrate, what then?

Then, computable capital enables “programmable commerce,” but more than that – it enables what we might call a “turing-complete economy.”

Repugnant innovation

With Darcy WE Allen and Sinclair Davidson. Journal of Institutional Economics, published online 11 October 2022. Working paper at SSRN

Abstract: Repugnant innovation is a form of evasive entrepreneurship that occurs in repugnant markets. Repugnance is an informal institution – controlled by long-lived norms, attitudes, customs and traditions – and repugnant innovation acts to shift institutions at the lowest level of the institutional stack. The paper considers three examples of repugnant innovation: e-cigarettes, online gambling, and webcam modelling. Each repugnant innovation challenges the complex mixture of material and moral concerns that contributes to repugnance in their respective markets. The paper adds to and expands on a body of evidence about innovation in apparently unsupportive institutional environments.

Buyback and Burn Mechanisms: Price Manipulation or Value Signalling?

With Darcy WE Allen and Sinclair Davidson. Available at SSRN

Abstract: A core finding in traditional corporate finance is that manipulating funding instruments does not increase the value of a firm. Several Web3 projects have mechanisms to buy their tokens on the market and burn those tokens. If the finding from corporate finance holds in the Web3 environment then this manipulation of the value of tokens should not increase the value of those projects. This paper asks if these mechanisms serve more of a purpose than price manipulation. We provide an efficiency explanation for buyback and burn mechanisms: value signalling. A buyback and burn enables projects to signal that their business model has genuine network effects, and that it is not a Ponzi scheme. This finding has implications for the motivation, justification and design of buyback and burn mechanisms across Web3.

Crypto-macroeconomics

With Jason Potts and Sinclair Davidson. Book chapter, available at SSRN.

Abstract: This chapter presents a Wagnerian vision of macroeconomics as a hybrid of several schools of thought and analytic frameworks, including public choice theory, constitutional economics, complexity economics, and evolutionary economics. We then review recent economic analysis of emerging crypto-economic systems. Toward synthesis, we propose that Wagnerian macroeconomics is a useful framework to understand how blockchains and crypto assets provide economic infrastructure and institutions for new private order economies, a new research field we call crypto-macroeconomics. We explore four proposed subfields of crypto-macroeconomics: technology, constitutions, money, and policy.

On Coase and COVID-19

With Darcy WE Allen, Sinclair Davidson and Jason Potts. European Journal of Law and Economics volume 54, page 107–125 (2022)

Abstract: From the epidemiological perspective, the COVID-19 pandemic is a public health crisis. From the economic perspective, it is an externality and a social cost. Strikingly, almost all economic policy to address the infection externality has been formulated within a Pigovian analysis of implicit taxes and subsidies directed by a social planner drawing on social cost-benefit analysis. In this paper, we draw on Coase (1960) to examine an alternative economic methodology of the externality, seeking to understand how an exchange-focused analysis might give us a better understanding of how to minimise social cost. Our Coasean framework allows us to then further develop a comparative institutional analysis as well as a public choice theory analysis of the pandemic response.

Published here. Working version available at SSRN or in PDF here.

Building a grammar of blockchain governance

With Darcy Allen, Sinclair Davidson, Trent MacDonald and Jason Potts. Originally a Medium post.

Blockchains are institutional technologies made of rules (e.g. consensus mechanisms, issuance schedules). Different rule combinations are entrepreneurially created to achieve some objectives (e.g. security, composability). But the design of blockchains, like all institutions, must occur under ongoing uncertainty. Perhaps a protocol bug is discovered, a dapp is hacked, treasury is stolen, or transaction volumes surge because of digital collectible cats. What then? Blockchain communities evolve and adapt. They must change their rules (e.g. protocol security upgrades, rolling back the chain) and make other collective decisions (e.g. changing parameters such as interest rates, voting for validators, or allocating treasury funds).

Blockchain governance mechanisms exist to aid decentralised evolution. Governance mechanisms include online forums, informal polls, formal improvement processes, and on-chain voting mechanisms. Each of these individual mechanisms — let alone their interactions — are poorly understood. They are often described through sometimes-useful but imperfect analogies to other institutional systems with deeper histories (e.g. representative democracy). This is not a robust way to design the decentralised digital economy. It is necessary to develop a shared language, and understanding, of blockchain governance. That is, a grammar of rules that can describe the entire possible scope of blockchain governance rules, and their relationships, in an analytically consistent way.

A starting point for the development of this shared language and understanding is a methodology and rule classification system developed by 2009 economics Nobel Laureate Elinor Ostrom to study other complex, nested institutional systems. We propose an empirical project that seeks conceptual clarity in blockchain governance rules and how they interact. We call this project Ostrom-Complete Governance.

The common approach to blockchain governance design has been highly experimental — relying very much on trial and error. This is a feature, not a bug. Blockchains are not only ecosystems that require governance, but the technology itself can open new ways to make group decisions. While being in need of governance, blockchain technology can also disrupt governance. Through lower costs of institutional entrepreneurship, blockchains enable rapid testing of new types of governance — such as quadratic voting, commitment voting and conviction voting — that were previously too costly to implement at scale. We aren’t just trying to govern fast-paced decentralised technology ecosystems, we are using that same technology for its own governance.

This experimental design challenge has been compounded by an ethos and commitment to decentralisation. That decentralisation suggests the need for a wide range of stakeholders with different decision rights and inputs into collective choices. The lifecycle of a blockchain exacerbates this problem: through bootstrapping a blockchain ecosystem can see a rapidly shifting stakeholder group with different incentives and desires. Different blockchain governance mechanisms are variously effective in different stages of blockchain development. Blockchains, and their governance, begin relatively centralised (with small teams of developers), but projects commonly attempt to credibly commit to rule changes towards a system of decentralised governance.

Many of these governance experiments and efforts have been developed through analogy or reference to existing organisational forms. We have sought to explain and design this curious new technology by looking at institutional forms we know well, such as representative democracy or corporate governance. Scholars have looked to existing familiar literature such as corporate governance, information technology governance, information governance, and of course political constitutional governance. But blockchains are not easily categorised as nation states, commons, clubs, or firms. They are a new institutional species that has features of each of these well-known institutional forms.

An analogising approach might be effective to design the very first experiments in blockchain governance. But as the industry matures, a new and more effective and robust approach is necessary. We now have vast empirical data of blockchain governance. We have hundreds, if not thousands, of blockchain governance mechanisms, and some evidence of their outcomes and effects. These are the empirical foundations for a deeper understanding of blockchain governance — one that embraces the institutional diversity of blockchain ecosystems, and dissects its parts using a rigorous and consistent methodology.

Embracing blockchain institutional diversity

Our understanding of blockchain governance should not flatten or obscure away from its complexity. Blockchains are polycentric systems, with many overlapping and nested centres of decision making. Even with equally-weighted one-token-one-vote blockchain systems, those systems are nested within other processes, such as a github proposal process and the subsequent execution of upgrades. It is a mistake to flatten these nested layers, or to assume some layers are static.

Economics Nobel LaureateElinorOstrom and her colleagues studied thousands of complex polycentric systems of community governance. Their focus was on understanding how groups come together to collectively manage shared resources (e.g. fisheries and irrigation systems) through systems of rules. This research program has since studied a wide range of commons including cultureknowledge and innovation. This research has been somewhat popular for blockchain entrepreneurs, in particular through using the succinct design principles (e.g. ‘clearly defined boundaries’ and ‘graduated sanctions’) of robust commons to inform blockchain design. Commons’ design principles can help us to analyse blockchain governance — including whether blockchains are “Ostrom-Compliant” or at least to find some points of reference to begin our search for better designs.

But beginning with the commons design principles has some limitations. It means we are once again beginning blockchain governance design by analogy (that blockchains are commons), rather than understanding blockchains as a novel institutional form. In some key respects blockchains resemble commons — perhaps we can understand, for instance, the security of the network as a common pool resource — but they also have features of states, firms, and clubs. We should therefore not expect that the design principles developed for common pool resources and common property regimes are directly transferable to blockchain governance.

Beginning with Ostrom’s design principles begins with the output of that research program, rather than applying the underlying methodology that led to that output. The principles were discovered as a meta-analysis of the study of thousands of different institutional rule systems. A deep blockchain-specific understanding must emerge from empirical analysis of existing systems.

We propose that while Ostrom’s design principles may not be applicable, a less-appreciated underlying methodology developed in her research is. In her empirical journey, Ostrom and colleagues at the Bloomington School developed a detailed methodological approach and rule classification system. While that system was developed to dissect the institutional complexity of the commons, it can also be used to study and achieve conceptual clarity in blockchain governance.

The Institutional Analysis and Development (IAD) framework and the corresponding rule classification system, is an effective method for deep observation and classification of blockchain governance. Utilising this approach we can understand blockchains as a series of different nested and related ‘action arenas’ (e.g. consensus process, a protocol upgrade, a DAO vote) where different actors engage, coordinate and compete under sets of rules. Each of these different action arenas have different participants (e.g. token holders), different positions (e.g. delegated node), and different incentives (e.g. to be slashed), which are constrained and enabled by rules.

Once we have identified the action arenas of a blockchain we can start to dissect the rules of that action arena. Ostrom’s 2005 book, Understanding Institutional Diversity, provides a detailed classification of rules classification that we can use for blockchain governance, including:

  • position rules on what different positions participants can hold in a given governance choice (e.g. governance token holder, core developer, founder, investor)
  • boundary rules on how participants can or cannot take part in governance (e.g. staked tokens required to vote, transaction fees, delegated rights)
  • choice rules on the different options available to different positions (e.g. proposing an upgrade, voting yes or no, delegating or selling votes)
  • aggregation rules on how inputs to governance are aggregated into a collective choice (e.g. one-token-one-vote, quadratic voting, weighting for different classes of nodes).

These rules matter because they change the way that participants interact (e.g. how or whether they vote) and therefore change the patterns that emerge from repeated governance processes (e.g. low voter turnout, voting deadlocks, wild token fluctuations). There have been somestudies that have utilised the broad IAD framework and commons research insights to blockchain governance, but there has been no deep empirical analysis of the rule systems of blockchains using the underlying classification system.

The opportunity

Today the key constraint in advancing blockchain governance is the lack of a standard language of rules with which to describe and map governance. Today in blockchain whitepapers these necessary rules are described in a vast array of different formats, with different underlying meanings. That hinders our capacity to compare and analyse blockchain governance systems, but can be remedied through applying and adopting the same foundational grammar. Developing a blockchain governance grammar is fundamentally an empirical exercise of observing and classifying blockchain ecosystems as they are, rather than imposing external design rules onto them. This approach doesn’t rely on analogy to other institutions, and is robust to new blockchain ecosystem-specific language and new experimental governance structures.

Rather than broadly describing classes of blockchain governance (e.g., proof-of-work versus proof-of-stake versus delegated-proof-of-stake) our approach begins with a common set of rules. All consensus processes have sets of boundary rules (who can propose a block? how is the block-proposer selected?), choice rules (what decisions do block-proposers make, such as the ordering of transactions?), incentives (what is the cost of proposing a bad block? what is the reward for proposing a block), and so on. For voting structures, we can also examine boundary rules (who can vote?), position rules (how can a voter get a governance token?) choice rules (can voters delegate? who can they delegate to?) and aggregation rules (are vote weights symmetrical? is there a quorum?).

We can begin to map and compare different blockchain governance systems utilising this common language. All blockchain governance has this underlying language, even if today that grammar isn’t explicitly discussed. The output of this exercise is not simply a series of detailed case studies of blockchain governance, it is detailed case studies in a consistent grammar. That grammar — an Ostrom-Complete Grammar — enables us to define and describe any possible blockchain governance structure. This can ultimately be leveraged to build new complete governance toolkits, as the basis for simulations, and to design and describe blockchain governance innovations.

An economic theory of blockchain foundations

With Jason Potts, Darcy WE Allen, Sinclair Davidson and Trent MacDonald

Abstract: Blockchain (or crypto) foundations are nonprofit organizations that supply public goods to a crypto-economy. The standard theory of crypto foundations is that they are like governments with respect to a national or regional economy, i.e. raising a public treasury and allocating resources to blockchain specific capital works, education, R&D, etc., to benefit the community and develop the ecosystem. We propose an alternative theory of what foundations do, namely that the treasury they manage is a moat to raise the cost of exit or forking because the benefit of the fund is only available to those who stay with the chain. Furthermore, building and maintaining a large treasury is a costly signal that only a high quality chain could afford to do (Spence 1973). We review these two models of the economic function of a blockchain foundation – (1) as a private government supplying local public goods, and (2) as a moat to raise the opportunity costs of exit. We outline the empirical predictions each theory makes, and examine the implications for optimal foundation design. We conclude that foundations should be funded by a pre-mine of tokens, and work best when large, visible, transparent, rigorously managed, and with a low burn rate.

Available at SSRN.

DeFi governance needs better tokenomics

With Sinclair Davidson, published in Coindesk, 13 April 2021

The controversy surrounding the launch of the Fei stablecoin protocol last week reveals a lot about DeFi’s problems with tokenomics. We know what a governance token offers its holders – the right to vote on changes to fees, and the protocol itself. But what should these rights be worth? 

The Fei protocol is engineered to maintain stability against the U.S. dollar by charging a penalty for selling and a bonus for buying the Fei token when it is below the $1 peg. It is an innovative design, albeit highly experimental. But as Fei has drifted further and further from the peg since launch, early buyers found themselves in the unfortunate position of being unable to liquidate their positions without taking substantial loss. 

By the end of the week, Fei suspended the penalties and rewards to try to stabilize the protocol. Until then, these mechanisms were functioning exactly as intended. Careful investors would have seen everything spelled out in the Fei white paper.

We might say this is a simple “buyer beware” story. But it is complicated by the simultaneous airdrop and distribution of Fei’s governance token, TRIBE, that was intended to allocate control rights over the protocol itself. In practice, buyers were trading an appreciating asset (ETH) for a stablecoin (FEI) to get access to the real prize: TRIBE.

In the crypto and DeFi industry many think that governance is just about voting. Voting is important of course – it is the governing part of governance. But it is only a part. In the traditional corporate world, governance rights come with a complex and coherent set of rights and obligations clearly tied to the underlying value of the firm. 

Share ownership represents a right to the cash flow of the company, and a residual claim over the company’s assets if, for whatever reason, it is wound up. The structure of these rights are the result of hundreds of years of evolution in corporate governance. 

If voting rights and the rights over the cashflow and the assets of the firm are misaligned, there can be perverse results. In crypto, we shouldn’t just want governance token-holders to vote. We should want them to vote well  making governance choices that are shaped by their interest in increasing the value produced by the protocol, and their knowledge that they will benefit directly from those choices. 

The initial “investors” in Fei are not really investors in FEI at all. They are customers who spent ETH to buy FEI. And there is an important difference between being a customer and an owner. The difference between being able to complain – to Tweet about how you’ve been wronged – and the ability to do something to recover your money. Because of the design of Fei’s “protocol controlled value” pool of ETH, FEI holders have no residual ownership claim over the ETH, just the right to sell their new FEI on a secondary market.

What governance rights FEI holders have is only as a result of being airdropped TRIBE, a fork of Compound’s COMP token. Like COMP and many other DeFi governance tokens, TRIBE gives voting rights, but does not allocate cash flow rights. 

True, TRIBE holders might in the future vote for protocol amendments that allocate those rights. Even so, the token at best represents an option to participate in unspecified governance that might result in cash flow, but might not. 

The crisis happened because an unexpectedly large number of people bought into FEI to get TRIBE, and then tried to sell out of FEI. That’s understandable: nobody wants to hold a stablecoin in a bull market. This rush for the exits triggered Fei’s penalty and reward nosedive. 

There is a subtle but critical lesson here. If the unique selling proposition of your crypto-economic system is predictability and stability – as it must be for a stablecoin – having the initial demand for that coin driven by a highly speculative governance token that will offer ambiguous future rights is asking for trouble. 

Indeed, it is a lesson that ought to be considered by all token designers in the DeFi world, not just stablecoins. The decision not to specify how value accrues to governance tokens is not just risky for investors. It is risky for the protocol itself.

For example, online chatter suggests that if Fei’s future had been put to a governance vote over the course of the week, there would have been substantial support for distributing its enormous ETH treasury back to FEI buyers. This would have recouped individual losses, but probably also have wound the protocol up entirely.

The Fei protocol is trying to do a lot of innovative work at once. If it turns out to be a success, it won’t have been the only successful protocol that had a rocky bootstrapping phase. But it should offer future protocols a critical lesson in tokenomics. 

Governance tokens are one of the most interesting innovations in DeFi. They seem to offer a fast path to decentralization, handing over control from entrepreneurs to a distributed community as quickly as possible, at, after, or even before launch. But the role of governance cannot be an afterthought – a bolt-on that can be pushed to a governance token and left to unknown future decision-makers.

Governance is the philosophical and economic heart of the blockchain and cryptocurrency industry. After all, decentralization is nothing if not the decentralization of governance. As Fei shows, dumping protocol governance onto a speculative token with unclear cash flow and ownership rights introduces a lot of instability into already ambitious protocols.   

Tracer: Perpetual Swaps

With Ryan Garner, Lachlan Webb, Jason Potts and Sinclair Davidson

Abstract: To date no platform offers permissionless market deployment of perpetual swaps. Existing offerings require governance approval and/or developer support to deploy new markets. Herein we propose a generalised perpetual swap protocol that avoids all third party requirements. The Tracer Perpetual Swap system is a Factory compatible template that offers customised market deployment without permissions. The smart contracts contain mechanisms that allow markets to operate at significantly lower cost to participants. We have designed a riskless liquidation mechanism via a slippage reimbursement receipt, rendering the act of liquidation risk-free and the cost to liquidated traders competitively inexpensive. As a result, users can trade at higher leverage and open positions with minuscule investment sizes. The Tracer Perpetual Swap is a piece of financial infrastructure that can be accessed by anybody with an internet connection. Using this infrastructure, any graphical user interface, financial institution or individual can access global market exposure in the decentralised economy.

Available at the Tracer website and in PDF here.

Tracer: Peer-to-Peer Finance

With Ryan Garner, Lachlan Webb, Jason Potts and Sinclair Davidson

Abstract: In this paper we introduce Tracer: peer-to-peer financial infrastructure for the decentralised economy. Tracer lowers the costs of participating in financial markets, using blockchain technology to enforce property rights and settle financial contracts without the need for a trusted
third party. Tracer’s Factory smart contract hosts an ecosystem of standardised financial contracts. The Tracer DAO can install proposed contract templates into the Factory, which can be accessed and deployed by anyone with a connection to the Internet. Once deployed, a contract is permissionless and not subject to DAO governance unless specified. A Reputation System allows users to identify financial risk and assess under-collateralised financial opportunities. Oracle financing is introduced as a novel model that incentivises the discovery and standardisation of new data for use in decentralised financial contracts. Tracer’s financial infrastructure stands to be the backbone of a secure, global financial network and provides strong foundations for future financial innovation.

Available at the Tracer website and in PDF here.