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.

The Hart asset at the heart of your organisation

With Sinclair Davidson and Jason Potts

Abstract: What assets does a firm need to hold to develop a profitable business model? A ‘Hart asset’ is an asset that a firm cannot strategically afford a rival firm to own or control due to the risk of hold up, and therefore must be held within the firm, and upon which a profitable business model can be built. We tie the Hart asset to the problem of complementarities in profitable innovation, and conclude with an example Hart asset in digital platforms.

Available in PDF and at SSRN

What we think we know about defi

This essay follows an RMIT Blockchain Innovation Hub workshop on defi. Contributions by Darcy WE Allen, Chris Berg, Sinclair Davidson, Oleksii Konashevych, Aaron M Lane, Vijay Mohan, Elizabeth Morton, Kelsie Nabben, Marta Poblet, Jason Potts, and Ellie Rennie. Originally a Medium post.

The financial sector exists solely to smooth economic activity and trade. It is the network of organisations, markets, rules, and services that move capital around the global economy so it can be deployed to the most profitable use.

It has evolved as modern capitalism has evolved, spreading with the development of property rights and open markets. It has grown as firms and trade networks became globalised, and supercharged as the global economy became digitised.

Decentralised finance (defi) is trying to do all that. But just since 2019, and entirely on the internet.

Any business faces the question of “how do I get customers to pay for my product?” Similarly consumers ask the question, “Where and how can I pay for the goods and services I want to buy?” For the decentralised digital economy, defi answers this question. Defi provides the “inside” money necessary to facilitate transactions.

But what in traditional, centralised finance looks like banks, stock exchanges, insurance companies, regulations, payments systems, money printers, identity services, contracts, compliance, and dispute resolution systems — in defi it’s all compressed into code.

From a business perspective trade needs to occur in a trusted and safe environment. For the decentralised digital economy, that environment is blockchains and the dapps built on top.

And as we can see, defi doesn’t just finance individual trades or firms — it finances the trading environment, in the same way that taxes finance regulators and inflation finances central banks. If blockchain is economic infrastructure, defi is the funding system that develops, maintains and secures it.

These are heavy, important words for something that looks like a game. The cryptocurrency and blockchain space has always looked a little game-y, not least with its memes and “in-jokes”. The rise of defi has also had its own cartoonified vibe and it has been somewhat surreal to see millions of dollars of value pass through tokens called ‘YAMs’ and ‘SUSHI’.

Games are serious things though. A culture of gaming provides a point around which all participants can coordinate activity and experimentation — what we’re seeing in defi is the creation of a massive multiplayer online innovation system. The “rules” of this game are minimal, there are no umpires, and very little recourse, where the goal is the creation and maintenance of decentralised financial products, and willing players can choose (if and) to what extent they participate.

Because there is real value at stake, the cost of a loss is high. Much defi is tested in production and the losses from scams, unethical behaviour, or poor and inadequately audited coding are frequent.

On the other side, participation in the game of defi is remarkably open. There are few barriers to entry except a small amount of capital that players are willing to place at risk. Once fiat has been converted into cryptocurrency, the limit on participation in decentralised finance isn’t regulatory or institutional — it is around knowledge. (Knowledge is a non-trivial barrier, excluding people who could be described as naive investors. This is important for regulatory purposes.)

This is starkly different from the centralised financial system, where non-professional participants have to typically go through layers of gatekeepers to experiment with financial products.

The basic economics of defi

The purpose of defi is to ensure the supply of an ‘inside money’ — that is, stablecoins — within decentralised digital platforms and to provide tools to manage finance risks.

In the first instance defi is about consumer finance. It answers basic usability questions in the blockchain space: How do users of the platform pay native fees? Which digital money is deployed as a medium of exchange or unit of account on the platform?

In the second instance defi concerns itself with the operation of consensus mechanisms — particularly proof of stake mechanisms and their variants. The problem here is how to capture financial trust in a staking coin and then how to use that trust to generate “trust” on a blockchain. Blockchains need mechanisms to value and reward these tokens. Given the (potential) volatile nature of these tokens, risk management instruments must exist in order to efficiently allocate the underlying risk of the trading platform.

As we see it, the million yam question is whether the use of these risk management tools undermine trust in the platform itself. It is here that governance is important.

Which governance functions should attach to staking tokens and when should those functions be deployed? Should they be automated or should voting mechanisms be used? If so, which voting mechanisms and what level of consensus is appropriate for decision making.

Finally defi addresses the existence of stablecoin and staking tokens from an investor perspective. Again there are some significant questions here that the defi space has barely touched. How do these instruments and assets fit into existing investment strategies? How will the tax function respond? How much of existing portfolio theory and asset pricing applies to these instruments and assets?

Of course, we already have a complex and highly evolved centralised financial system that can provide much of the services that are being built from the ground up in defi. So why bother with defi?

The most obvious reason is that the blockchain space has a philosophical interest in decentralisation as a value in and of itself. But decentralisation addresses real world problems.

First, centralised systems can have human-centric cybersecurity vulnerabilities. The Canadian exchange QuadrigaCX lost everything when the only person with access to the cryptographic keys to the exchange died (lawyers representing account holders have requested that the body be exhumed to prove his death). Decentralised algorithmic systems have their own vulnerabilities (need we mention yams again?) but they are of a different character and unlike human nature they can be improved.

Second, centralised systems are exposed to regulation — for better or worse. For example, one of the arguments for UniSwap is that it is more decentralised than EtherDelta. EtherDelta was vulnerable to both hackers (its order book website was hacked) and regulators (its designer was sued by SEC).

Third, digital business models need digital instruments that can both complement and substitute for existing products. Chain validation instruments and the associated risk management tools presently do NOT have real world equivalent products.

Fourth and finally, the ability to digitise, fractionalise, and monetise currently illiquid real-world assets will require a suite of instruments and digital institutions. Defi is the beginning of that process.

In this sense, the defi movement is building a set of financial products and services that look superficially familiar to the traditional financial system using a vastly different institutional framework — that is, with decentralisation as a priority and without the layers of regulation and legislation that shape centralised traditional finance.

Imagine trying to replicate the functional lifeforms of a carbon-based biochemical system in a silicon based biochemical system. No matter how hard you tried — they’d look very different.

Defi has to build in some institutions that mimic or replicate the economic function provided by central banks, government-provided identity tech, and contract enforcement through police, lawyers and judges. It is the financial sector + the institutions that the traditional finance sector relies on. So, initially, it’s going to look more expensive, relative to “finance”. But the social cost of the traditional finance sector is much larger — a full institutional accounting for finance would have to include those courts and regulations and policymakers and central banks that it relies on.

Thus defi and centralised finance look very different in practice. Consider exchanges. Traditional financial markets can either operate as organised exchanges (such as the New York Stock Exchange) or as over-the-counter (OTC peer-to-peer) markets. The characteristics of those types of market are set out below.

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Defi exchanges represent an attempt to combine the characteristics of both organised exchanges and over-the-counter markets. In the very instance, of course, they are decentralised markets governed by private rules and not (necessarily) public regulation. They aim to be peer-to-peer markets (including peer-to-algorithm markets in the case of AMM).

But at the same time they aim to be anonymous (in this context meaning that privacy is maintained), transparent, highly liquid, and with less counterparty risk than a traditional OTC market.

Where is defi going?

Traditional finance has been developing for thousands of years. Along with secure private property rights and the rule of law, it is one of the basic technologies of capitalism. But of those three, traditional finance has the worst reputation. It has come to be associated with city bros and the “Wolf of Wall Street”, and the Global Financial Crisis. Luigi Zingales has influentially argued that the traditional finance system has outgrown the value it adds to society, in part because of the opportunities of political rent seeking.

This makes defi particularly interesting.  Defi is for machines. Not people. It represents the automation of financial services.

A century ago agriculture dominated the labour force. The heavy labour needs of farming are one of the reasons we were poor back then. As we added machines to agriculture — as we let machines do the farming — we reduced the need to use valuable human resources. Defi offers the same thing for finance. Automation reduces labour inputs.

Automation of course has been increasingly common in financial systems since at least the 1990s. But it could only go so far. A lot of the reason that finance (and many sectors, including government and management) resisted technological change and capital investment, was at the bottom, there had to be a human layer of trust. Now that we can automate trust through blockchains, we can move automation more deeply into the financial system.

Of course, this is in the future. Right now defi is building airplanes in 1902 and tractors in 1920. They’re hilariously bad and horses are still better. But that’s how innovation works. We’re observing the creation of the base tools for entrepreneurs to create value. Value-adding automated financial products and services comes next.

What we’ve learned from working with Agoric

With Sinclair Davidson and Jason Potts. Originally a Medium post.

Since 2017 we (along with our colleague Joe Clark) have been working with Agoric, an innovative and exciting smart contract team, who are about to launch a token economy model we helped design.

At the RMIT Blockchain Innovation Hub we’ve long been thinking about how blockchain can drive markets deeper into firms, resolving the electronic markets hypothesis and giving us new opportunities for outsourcing corporate vertical integration.

What we’ve discovered from working with the Agoric team is the possibilities of driving markets down into machines. Mark Miller’s groundbreaking work with Eric Drexler explored how property rights and market exchange can be used within computational systems. Agoric starts economics where we start economics — with the institutional framework that secures property rights.

This has been one of the most intellectually stimulating collaborations of each of our careers, and has shaped much of how we think about the economics of frontier technologies.

We first met the Agoric team through Bill Tulloh at the Crypto Economics Security Conference at Blockchain @ Berkeley in 2017, just as we were forming the RMIT Blockchain Innovation Hub. CESC was the first serious attempt we were aware of to bring the blockchain industry and social science together — such as our disciplines of economics and political economy.

In the presentation to CESC, we applied some of Oliver Williamson’s thinking to understand the economic properties of tokens and cryptocurrencies.

Bill — who had thought along similar lines — came over to chat during a break. We met again at the 2018 Consensus Conference in New York. Bill introduced us to Mark Miller. What started out as a quick chat to say hello over breakfast turned into a long discussion about Friedrich Hayek, Don Lavoie, and market processes in computer science. Through Bill and Mark we then met Kate Sills and Dean Tribble.

It is true that economic thinking is everywhere in the blockchain and cryptocurrency community. There’s a lot of lay reasoning about Austrian economics, monetary policy, central banks, and inflation. These ideas have brought a lot of people into the cryptocurrency space. Some of the thinking that brought them here is good economics (we’re very passionate about how Austrian economics can inform the blockchain industry ourselves — see here and our colleague Darcy Allen here) but unfortunately a lot of it is not-so-good economics. Many developers have self-taught economics, many have intuited economics from first principles, and we have observed a combination of brilliant insight, economic fallacy, and knowledge gaps.

Developers, however, tend to be very good at game theory; if only because unlike our colleagues in academia, the blockchain community is testing the assumptions of game theory and applying it in the real world for business models with real value at stake. Reality can be bracing. Only invest what you can afford to completely lose. This is still a highly experimental industry.

But economics has much, much more to contribute to our understanding of the blockchain economy than just Hayekian monetary theory and textbook game theory. Our friends at Agoric know this — they already had an economist in their team. They know and understand that it isn’t enough to have good code — to succeed, you need to have economically coherent code.

To that end, we have developed a new field of economics: institutional cryptoeconomics. In this field, we apply the transaction cost economics of Ronald Coase and Oliver Williamson to explore blockchain as an economic institution competing with and complementing the schema of firms, markets, states, clubs and the commons.

The economic foundation of our institutional cryptoeconomics is broad and solid. In addition to economics Nobel laureates like Hayek, Ronald Coase, and Oliver Williamson, we have also incorporated the work of other laureates such as Herbert Simon, Douglass North, Elinor Ostrom, and Jean Tirole into our blockchain research. Then we’’ve drawn on should-have-been-laureates such as Joseph Schumpeter, William Baumol, Armen Alchian, and Harold Demsetz are included. Economists such as Andrei Shleifer and Israel Kirzner could still win a Nobel.

Merton Miller — himself an economics laureate — once argued that there was nothing more practical than good theory. Our experience working with Agoric has convinced us of the value of very good theory. We have had plenty of help — actual practitioners trying to solve immediate real-world problems are hard task masters. Ideas cannot remain half-baked — they must be fully explained and articulated. Working with Agoric has been an intellectually intense, extended interactive academic seminar where ideas are taken from vague hunch to ‘how can this be implemented’ and back again. From whiteboard to business model.

As academics we have learned which ideas, models and tools are of immediate use and value in the blockchain world. There have been some surprises here. Whoever would have thought that edgeworth boxes would have a practical real world application? Or indifference curves? But here we are. When building an entire economic ecosystem — the Agoric economy — we have had to draw upon the full breadth of our economic training. We suspect that having an economics team on board will become an industry standard in the years to come.

We have benefited as educators too. Of course, explaining complex ideas to highly intelligent laypeople is a large part of our day job. The stakes, however, are much higher. The Agoric team aren’t seeking information to pass a class test. They are seeking information to pass a market test — that the market will grade. As another favorite economist of ours Ludwig von Mises explained, consumers are hard task masters.

Our own students particularly have benefited from our Agoric experience. We now have a deeper understanding of industry needs and thought in the blockchain space. We know which ideas interest them and which don’t. The Agoric team questioned us closely on some topics. Our students will know how to answer those questions.

It also turns out that financial engineering is far more important than we thought it would be when we first started working on blockchain economics. The work with Agoric has coincided with the defi boom — a richly anarchic and innovative movement within the blockchain space. As a consequence, the blockchain for business degree programs that we have launched at RMIT have huge dollops of finance in them.

We share with Agoric a vision of the future where technology leads to an improvement in human flourishing and an enhancement of our capacity to lead full lives.

In a new book published by the American Institute for Economic Research we’ve argued that blockchain and other frontier technologies offer us the tools to actively take back liberties we may have lost.

With Agoric, it is incredibly exciting to be able to actually build the economy of the future that we’ve been studying.

The New Technologies of Freedom

With Darcy WE Allen and Sinclair Davidson. American Institute for Economic Research, 2020

We are on the cusp of a dramatic wave of technological change – from blockchain to automated smart contracts, artificial intelligence and machine learning to advances in cryptography and digitisation, from Internet of Things to advanced communications technologies.

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Blockchain innovation and public policy

Introduction to Journal of Entrepeneurship and Public Policy special issue ‘Blockchain innovation and public policy’, with Jason Potts and Sinclair Davidson. Available at Emerald.

Blockchain, or distributed ledger technology, invented by Satoshi Nakamoto (2008), has quickly and somewhat surprisingly emerged as one of the most disruptive new technologies of the early twenty-first century; it is facilitating an entirely new decentralised architecture of economic organization (Narayanan et al., 2016; Davidson et al., 2018; Rauchs et al., 2018; Werbach, 2018; Berg et al., 2019). While still an experimental technology, shrouded in technological, economic, regulatory and legal uncertainty, blockchain is nevertheless moving from being a proof-of-concept innovation to early-stage pilots that will likely significantly disrupt sector after sector in the coming years. This process of what Joseph Schumpeter called “creative destruction” first started with money (with Bitcoin, the world’s first cryptocurrency) and then payments, and is now moving through banking and finance (decentralised finance, or defi), logistics, health, and generally across the digital economy. Like other digital and internet-based technologies, such as virtual reality and machine learning, we are still in the early phases of an economy-wide disruption that is being driven and shaped by new entrepreneurial startups (since 2017 funded through initial coin offerings, although increasingly now through venture capital financing) and also by industry dominant firms who are working to reimagine and rebuild their business models and services on a more decentralised organisational architecture and business infrastructure (Rauchs et al., 2019).

A key challenge for all entrepreneurs, whether in start-ups or in large incumbent firms, is policy uncertainty in relation to this radical new technology. Blockchain technology facilitates an entirely new architecture for money and payments, for establishing ownership and storing value, for making contracts and recording data and facts. This means that legal and regulatory frameworks, tax models and economic policy settings are not designed for this technology and will need to be adapted (De Filippi and Wright, 2018).

This special issue aligns scholarship and analysis towards a better understanding of the nature of entrepreneurship in relation to the development and innovation of this new technology, and the way in which that entrepreneurship interacts with current public policy settings. The papers in this special issue broadly seek to explore particular problem domains where public policy is either failing or succeeding in this context, and also to explore new frameworks for public policy that are conducive to entrepreneurship and innovation.

These papers cover a broad set of questions, ranging from consideration about the shifting role of government and economic policy in a world with widespread blockchain adoption, to seeking to provide a global map of the policy dimensions upon which governments are acting with respect to blockchain technology, to exploring how public policy interacts with entrepreneurial discovery of blockchain use cases and commercial applications. Papers also explore the implications for constitutional experimentations and monetary policy reform.

In the first paper in this special issue, Berg, Davidson and Potts explore the long run policy equilibrium associated with the consequences of wide-spread blockchain adoption, drawing on theories of institutional cryptoeconomics (Berg et al., 2019). They argue that the long run policy implication of the industrial revolution and the era of modern economic growth through the twentieth century was for competition policy and industry policy to counterbalance the power of large hierarchical organizations (or the rise of very large firms as a basic dynamic of industrial capitalism). Berg, Davidson and Potts argue that blockchain technology predicts both market disintermediation and organizational “dehierarchicalisation”, which they then infer unwinds the economic justification for a large range of economic policies implemented through the twentieth century that sought to control the effects of market power and organizational hierarchy. “Capitalism after Satoshi” predicts widespread blockchain technology adoption could reduce the need for counter-veiling economic policy, and therefore shrinking the role of government, and therefore a new public policy equilibrium with reduced demand for economic policy. This shows the long-run relationship between digital technological innovation and the regulatory state.

In “Cryptofriendliness”, Mikayla Novak explores the chief aspects of policy interest in blockchain technology, and maps these to an index-based policy measure that she calls “cryptofriendliness” (see Novak et al. 2018). Novak is particularly interested in using national case studies of blockchain policies to identify “policy entrepreneurship” that seeks to foster and promote the discovery and development of entrepreneurial opportunities in the emerging, but still nascent, blockchain economy. Novak argues that so-called “crypto-friendly” jurisdictions are more likely to attract entrepreneurs and investors in the crypto-economic blockchain space.

Brendan Markey-Towler builds on the idea of blockchain as an “institutional technology”, a concept first developed by Davidson et al. (2018), in order to propose an evolutionary model of institutional competition. Markey-Towler shows how blockchain development is a form of institutional evolution that then interacts with national systems of innovation (which are themselves institutional systems), furnishing a macro-level concept of how blockchain technology interacts not only with economic administrative and organizational infrastructure (e.g. money and payments, supply chains, and specific sectors), but also with higher-order knowledge and innovation institutions. He argues that institutional competition from blockchain technology predicts superior performance from national systems of innovation, which in turn predicts greater opportunity space for entrepreneurs.

In “Governing entrepreneurial discovery” Darcy Allen explores how entrepreneurs discover opportunities in blockchain applications, which is a specific instance of the general problem of entrepreneurial discovery in early stage technologies. Allen focuses on the institutional mechanisms that facilitate the pooling of the broad information set that entrepreneurs require, and how policy choices that affect the institutional environment in turn affect entrepreneurial transaction costs. Elaborating on Novak’s argument that specific policy choices shape the viability of blockchain entrepreneurial development (what she calls crypto-friendly policy), Allen further argues that an important way that crypto-friendly policy is operationalized is through channels that lower the cost of opportunity discovery for entrepreneurs.

In “The market for rules” Nick Cowen builds on the constitutional tradition in economics (as pioneered by James Buchanan as a hybrid of New Institutional Economics and political theory) to observe that the entrepreneurial opportunity space of blockchain is fundamentally in the provision of rules for governance that are in effect hard-coded into blockchain platform infrastructure. Cowen therefore argues that blockchain technology facilitates competition between the entrepreneurial supply of governance rules – encoded in “private order” platform or protocol mechanisms – with the government or legislator supply of “public order” policy rules. Whereas Davidson, Berg and Potts argue in “Capitalism after Satoshi” that blockchain technology will reduce demand for public policy, via the mechanism of disintermediation and dehierarchicalisation, Cowen makes a different argument but with the same broad direction of prediction, namely, that competition from private-order rules (what Cowen calls “the market for rules”) will reduce demand for public-order rules.

In “Cryptoliquidity”, James Caton examines the connection between blockchain technology adoption and broad monetary stability. Caton observes that macroeconomic fluctuations tend to be in significant part a monetary phenomena, and therefore monetary policy stabilisation works through exogenous changes in money supply. He then shows that cryptocurrencies can create endogenous liquidity creation mechanisms through rules-based asset liquidation (assuming real-asset backed cryptocurrencies) as triggered by changes in macroeconomic variables. Entrepreneurial development of novel cryptocurrency instruments such as stablecoins can therefore also be potentially developed at the level of monetary aggregates in order to automate the supply of liquidity. This predicts that blockchain technologies can further facilitate the evolution of market economy institutions.

The six separate and distinct papers in this special issue each deal with different aspects that connect the economic study of entrepreneurship to both the immediate practical implications (e.g. Novak, 2019; Allen, 2019) and broadly philosophical implications (e.g. Berg et al., 2019; Cowen, 2019) of blockchain adoption for public policy. Yet taken together these papers all broadly point in the same direction, in terms of the predicted effect: blockchain technology, which is an institutional technology, offers institutional competition with public policy rules, and this entrepreneurial competition is expected to improve the overall quality of economic rules and governance. Taken together, these six papers predict that blockchain technology will, on the whole, induce a better institutional environment for entrepreneurial action.

References

Allen, D. (2020), “Governing the entrepreneurial discovery of blockchain applications’”, Journal of Entrepreneurship and Public Policy, Vol. 9 No. 2, pp. 194-212.

Berg, C., Davidson, S. and Potts, J. (2020), “Capitalism after Satoshi”, Journal of Entrepreneurship and Public Policy, Vol. 9 No. 2, pp. 152-164.

Berg, C., Davidson, S. and Potts, J. (2019), The Blockchain Economy: Introduction to Institutional Cryptoeconomics, Edward Elgar, Cheltenham.

Cowen, N. (2020), “The market for rules: the promise and peril of blockchain distributed governance”, Journal of Entrepreneurship and Public Policy, Vol. 9 No. 2, pp. 213-226.

Davidson, S., de Filippi, P. and Potts, J. (2018), “Blockchains and the economics institutions of capitalism”, Journal of Institutional Economics.

De Filippi, P. and Wright, A. (2018), Blockchain and the Law: The Rule of Code, Harvard University Press, Cambridge, MA.

Nakamoto, S. (2008), “Bitcoin: a peer-to-peer electronic cash system”, available at: https://bitcoin.org/bitcoin.pdf

Narayanan, A., Bonneau, J., Felten, E., Miller, A. and Goldfeder, S. (2016), Bitcoin and Cryptocurrency Technologies, Princeton University Press, Princeton, NJ.

Novak, M. (2020), “Cryptofriendliness: understanding blockchain public policy”, Journal of Entrepreneurship and Public Policy, Vol. 9 No. 2, pp. 227-252.

Novak, M., Davidson, S. and Potts, J. (2018), “The cost of trust: a pilot study”, Journal of British Blockchain Association, doi: 10.31585/jbba-1-2-(5)2018.

Rauchs, M., Glidden, A., Gordon, B., Pieters, G., Recanatini, M., Rostand, F., Vagneur, K. and Zhang, B. (2018), Distributed Ledger Technology Systems, Cambridge institute for Alternative Finance, University of Cambridge.

Rauchs, M., Blandin, A., Bear, K. and McKeon, S. (2019), “2nd Global Enterprise blockchain benchmarking study”, Cambridge institute for Alternative Finance, University of Cambridge.

Werbach, K. (2018), The Blockchain and the New Architecture of Trust, MIT Press, Cambridge, MA.

Further reading

Catalini, C. and Gans, J. (2017), “Some simple economics of the blockchain”, MIT Sloan Research Paper No. 5191-16, available at: https://ssrn.com/abstract=2874598

Caton, J. (2019), “Cryptoliquidity: how innovation and blockchain and public policy can promote monetary stability”, Journal of Entrepreneurship and Public Policy.

Markey-Towler, B. (2020), “Blockchains and institutional competition in innovation systems”, Journal of Entrepreneurship and Public Policy, Vol. 9 No. 2, pp. 185-193.