Tag: Darcy WE Allen

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 culture, knowledge 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.

Response to Questions on Notice: Senate Select Committee on Financial Technology and Regulatory Technology

With Darcy W.E. Allen and Aaron M. Lane

Response to questions on notice at Senate Select Committee on Financial Technology and Regulatory Technology.

The capital gains taxation regime as it applies to cryptocurrency
is no longer appropriate

The Australian Taxation Office’s position that cryptocurrency is an asset for capital gains tax purposes and that every exchange between two cryptocurrency tokens should be treated as a “disposal” creates substantial regulatory compliance burdens on taxpayers, hinders fintech adoption, and achieves no policy objective.

This treatment of tokens poses unique challenges for cryptocurrency users. As each tokento-token exchange is treated by the ATO as a capital gains tax event, taxpayers are required to record gains or losses in the Australian dollars. However, token-to-token exchanges often occur at multiple times removed from Australian dollar-denominated markets. For many cryptocurrency tokens, liquid token-AUD exchange markets do not exist. In addition, the volume and complexity of some of these token exchanges make precise accounting of gains and losses on a per-transaction basis unrealistic, even for honest taxpayers seeking to fully ensure compliance.

Token-to-token exchanges of cryptocurrencies and other digital assets are foundational to the development of the digital economy, contributing to price and business model discovery. The current capital gains tax treatment to token-to-token exchanges imposes significant and unnecessary uncertainty and regulatory burden on cryptocurrency users, investors and the blockchain industry more generally.

The capital gains tax regime may have been appropriate five years ago when the cryptoeconomy was smaller, less complex and when there were relatively few places to make token-to-token exchanges. However, recent developments make the current policy regime inappropriately narrow and imposing. For example, the rise of decentralised finance (‘defi’) means that token-to-token exchanges are now commonly occurring through a vast ecosystem of decentralised protocols that operate at multiple levels removed from Australian dollar-denominated markets and provide no easy-to-use tools for the granular record keeping required by the ATO.

Additionally, the tokens that are being exchanged are also changing as the cryptoeconomy has developed. Defi activity can result in tokens being locked up in exchange for ‘governance’ tokens. Tokens that represent claims on other tokens through smart contracts – often necessary to acquire in order to participate in economic activity across multiple blockchains – can trade at a premium or discount. Treating these token-to-token swaps as capital gains events serves no policy purpose, and adds significant ambiguity and uncertainty to the Australian tax system.

The current regime also risks cryptocurrency users accumulating an Australian dollar-denominated tax liability that might be tied up in illiquid tokens.

The committee should understand that compliance with this regime in the Australian public is likely to be very low and the risk of taxpayers making errors in attempting to comply with the current legislation is very high.

Recommendation:

We recommend that CGT events be limited to exchanges where it is reasonable to comply with the capital gains tax regime. These would be when:

  • Cryptocurrency is exchanged with fiat currency (most commonly the Australian dollar),
  • Cryptocurrency is used in the acquisition or disposal of a tangible good or service, or a non-fungible token (such as a piece of digital art). Depending on the CGT classification of the respective token (for example a personal use asset or collectable), these transactions may yield the normal concessional treatments.

The burden of demonstrating compliance with these rules would remain with the taxpayer. This approach would significantly simplify the capital gains tax regime while reducing regulatory burdens, encourage innovation and the expansion of blockchain and cryptocurrency jobs in Australia, and be revenue neutral to the Commonwealth government.

The managed investment scheme regime doesn’t suit autonomous (algorithmic) financial products

A managed investment scheme (MIS) is an investment structure where a “responsible entity” manages investments for unit holders. In summary, the Corporations Act 2001 (Cth) provides that a MIS will exist where (i) members contribute money or money’s worth as consideration to acquire rights to benefits produced by the scheme; (ii) any of the contributions are to be pooled, or used in a common enterprise, to produce financial benefits, or benefits consisting of rights or interests in property, for the members; and (iii) the members do not have day-to-day control over the operation of the scheme. Generally, a MIS is required to be registered with ASIC if it has more than 20 members. A registered entity is required to be a public company and hold an Australian Financial Services License.

There is a significant risk facing blockchain companies in Australia that the MIS regime will be inappropriately applied, particularly as it pertains to decentralised finance (‘defi’) products. There is approximately US$41.5 billion worth of tokens in the defi ecosystem. Inappropriate and high cost regulation threatens the viability of the defi industry in Australia and will send entrepreneurs and job-makers overseas.

For example, popular defi applications include a class of automated market makers (AMMs) that allow users to make token-to-token exchanges outside ‘traditional’ centralised exchanges like Binance or Coinbase. Investors pool tokens in these automated exchanges, earning profit through fees. The pool automatically prices exchanges in a way that rebalances the pool, guaranteeingthat each asset is always available.

It is likely an AMM would be considered a MIS within the legal definition outlined above. However, there are several regulatory problems in applying the MIS regulatory framework to defi products like AMMs:

  • These schemes have no manager – that is, there is no responsible entity on whom the obligations of a financial services licence could be meaningfully imposed or exercised. The scheme – and thus the return on the investment – is determined entirely algorithmically.
  • Automated market makers like this have no responsible agent. Amendments to the protocol (for example, varying the fee for investors) are entirely controlled by the voting behavior of governance token holders (typically investors).

Applying the rules governing managed investment schemes to these autonomous and algorithmic financial products is a category error.

In any case, treating a defi product as an MIS would not achieve the government’s policy goals. Defi products are censorship resistant and fully digital. Australian investors are able to interact with defi products developed around the world at almost zero cost. Regulatory avoidance is trivially easy because these products can be freely “forked” (that is, their code copied, modified, and re-deployed permissionlessly). Applying the MIS framework to Australia-built defi products means that Australian companies are highly reluctant to innovate in this frontier fintech field.

The committee might consider amending the government’s enhanced fintech sandbox or develop a new blockchain technology specific sandbox to deal allow for defi products. However, we do not recommend this approach. One problem is that the current sandbox rules (such as limitations on the amount of money invested, or persons involved) would be inappropriate for defi because of the absence of centralised management, the ease of forking, and the quantum of funds. For example, automated exchanges have no mechanism to limit the size of the total pool (doing so would potentially reduce the stability of the pool) and even if limits were implemented they could be avoided through forking the pool and re-deploying it. Furthermore, if regulators were to determine that the defi product no longer compliant with the sandbox rules, given the uncensorable nature of blockchain, there would be no mechanism by which regulators could insist that the product could cease trading.

Recommendation:

We recommend that the Corporations Act be amended to exempt “autonomous financial products” from the existing definition of a MIS. To qualify as an autonomous financial product, the product needs to be:

  • Fully algorithmically deterministic (that is, all investment decisions are made by an algorithm rather than a responsible human entity);
  • Governance decisions are sufficiently decentralised and made solely by those who have invested; and
  • Fully open source, with its code published on a recognised platform (such as
    GitHub), allowing investors to scrutinise the code themselves.

This change would be straightforward and is consistent with the existing legislative approach of the Act. While legislative change is preferred to provide certainty, we note that this approach could also be achieved through regulation as section 9 of the Act provides a mechanism for the Regulations to declare that a scheme is not a MIS.

PDF version with references and footnotes available in here.

Submission to Select Committee on Financial Technology and Regulatory Technology (Response to Interim Report and Second Issues Paper)

With Darcy W. E. Allen and Aaron M. Lane

A submission to the Senate Select Committee on Financial Technology and Regulatory Technology (‘Committee’) following the tabling of the Committee’s Interim Report and the publication of the Second Issues Paper, focusing on the regulatory implications of blockchain technology.

Available in PDF here.

The Political Economy of Australian Regulatory Reform

With Darcy WE Allen, Aaron M Lane and Patrick A. McLaughlin. Published in Australian Journal of Public Administration, 18 September 2020

Abstract: The problem of regulatory accumulation has increasingly been recognised as a policy problem in its own right. Governments have then devised and implemented regulatory reform policies that directly seek to ameliorate the burdens of regulatory accumulation (e.g. red tape reduction targets). In this paper we examine regulatory reform approaches in Australia through the lens of policy innovation. Our contributions are twofold. We first examine the evolutionary discovery process of regulatory reform policies in Australia (at the federal, intergovernmental and state levels). This demonstrates a process of policy innovation in regulatory mechanisms and measurements. We then analyse a new measurement of regulatory burden based on text analytics, RegData: Australia . RegData: Australia uses textual analysis to count “restrictiveness clauses” in regulation—such as “must”, “cannot” and “shall”—thereby developing a new database. We place this “restrictiveness clauses” measurement within the context of regulatory policy innovation, and examine the potential for further innovation in regulatory reform mechanisms.

Available at Australian Journal of Public Administration. Working paper available at SSRN

The Cryptoeconomics of Cities, Data and Space

With Darcy W E Allen, Kiersten Jowett, Mikayla Novak, and Jason Potts. Published in in Cosmos + Taxis, Volume 8, Issue 8 + 9, 2020

Abstract: We explore the connection between new decentralised data infrastructure and the spatial organisation of cities. Recent advances in digital technologies for data generation, storage and coordination (e.g. blockchain-based supply chains and proof-of-location services) enables more granulated, decentralised and tradeable data about city life. We propose that this new digital infrastructure for information in cities shifts the organisation and planning of city life downwards and opens new opportunities for entrepreneurial discovery. Compared to centralised governance of smart cities, crypto-cities are more emergent orderings. This paper introduces this research agenda on the boundaries of spatial economics, the economics of cities, information economics, institutional economics and technological change.

Available at Cosmos + Taxis and in PDF here. Preprint available at SSRN. (Previously titled ‘Spatial Institutional Cryptoeconomics’)

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.

Image for post

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.

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.

These are the new technologies of freedom. These tools present a historical unprecedented opportunity to recapture individual freedoms in the digital age – to expand individual rights, to protect property, to defend our privacy and personal data, to exercise our freedom of speech, and to develop new voluntary communities.

This book presents a call to arms. The liberty movement has spent too much time begging the state for its liberties back. We can now use new technologies to build the free institutions that are needed for human flourishing without state permission.

Available at Amazon.com

Deregtech: using technology to deregulate the economy

With Darcy WE Allen and Aaron M Lane. Originally a Medium post.

The Australian Prime Minister Scott Morrison wants to make deregulation and cutting red tape the centrepiece of the COVID-19 economic recovery.

This focus is not just welcome, but essential. Entrepreneurs need room to experiment with new business models without being held back by unnecessary rules — as we argue in our recent book Unfreeze: How to Create a High Growth Economy After the Pandemic.

But at the same time, developed world governments have spent at least three decades trying to cut burdensome red tape — with little obvious to show for it. The regulatory state just keeps expanding.

Existing regulatory policies such as sunset clauses have not worked to stem the steady growth in regulation and regulatory complexity. We need a new deregulation strategy.

The term ‘regtech’ describes how technologies such as blockchain, artificial intelligence and the internet of things can assist with regulatory compliance.

Now is the time for deregtech: using frontier technologies to identify, coordinate and incentivise deregulation.

Deregtech leverages technology not for compliance, but for policy reform.

Adopting the principles of permissionless innovation, institutional diversity, and private governance will be vital if we are to get a rapid recovery from the COVID-19 crisis. Deregtech is about designing specific mechanisms that governments can deploy to identify and encourage that deregulation.

At least in Australia, every government on both sides of politics has promised some form of deregulation as part of their election agenda.

It turns out that deregulation is hard. It’s hard for two reasons:

  • First: it is hard to identify regulatory reductions that are strongly beneficial but at the same time politically easy. Few regulations do not have a passionate constituency behind them. Few regulations are completely pointless. But in aggregate, regulation adds to a significant economic burden.
  • Second: policymakers might talk a good game about deregulation, but have little incentive to deregulate. All the incentives go in the other direction — towards more rules, more regulatory interventions.

To solve the identification and incentive problems of reform, governments have increasingly implemented ‘regulatory policies’. That is, policies and mechanisms directed at the regulatory process itself.

For example, sunset clauses and regulatory impact statements force legislators to more closely assess or revisit the burden of a given regulation. But these don’t propel forward deregulation. Other approaches try to use the flow of new regulation to reduce the stock of existing regulation. New regulations can be made subject to ‘regulatory budgets’ or ‘1-in, n-out’ policies. But these are highly sensitive to how we measure regulations and their burdens.

The economy is a dynamic complex adaptive system, and as it evolves so too must the regulatory state. In the wake of the pandemic, which has accelerated many economic and technological trends, this has never been more necessary.

Deregtech can be directed at regulatory analyticsto better measure and grasp the extent of the regulatory state. The RegData project, for instance, counts the number of ‘restrictive clauses’ in regulations. New measurements encourage innovation in regulatory policies and make new mechanisms possible. RegData’s associated QuantGov initiative provides the tools for open-source policy analysis, rather than this being done within government departments.

With strong regulatory analytics — analytics that can be verified by observers from outside the government — tighter controls over a regulatory budget can be introduced, and affected industries can have a better understanding of the state of regulation.

These systems are not just a way to monitor regulation — they are an infrastructure on which deregulatory efforts can be built.

For instance, can we apply machine learning to identify regulatory changes that are unobservable to humans? Can technologies be leveraged to create new measurements to analyse regulatory overlap?

At the same time deregtech can encourage regulatory experimentation to reveal the costs and benefits of rules in practice. New technologies can act as the foundation for regulatory experimentation, encouraging competition between jurisdictions.

Inserting greater competition into governance, such as in special economic zones and charter cities, encourages discovery. On a more granular level, regulatory sandboxes attempt to reveal local knowledge about where regulatory burdens fall and what they are inhibiting.

Deregtech also encompasses more extensive regulatory automation, driving the enforcement and governance of regulations into private platforms. Blockchain platforms, for instance, enable complete enforceability of particular trading rules by incorporating them into the platform.

Deregtech will reduce the regulatory barriers that hamper our transition to a decentralised, automated and digital post-pandemic economy. The technological inputs of deregtech are here with us today. Now we just need to build them.

The digital consequences of the pandemic

With Darcy WE Allen, Sinclair Davidson, Aaron M Lane, and Jason Potts. Originally a Medium post.

The global policy response to the COVID-19 pandemic has been extraordinary. We’ve seen a massive increase in government spending and social welfare programs, heavy handed policing, and some less remarked on crisis deregulation.

But the long run effect of the pandemic will be even more substantial. COVID-19 is driving far deeper, and profound, changes in the economy.

Some of these changes we can start to see already, but their full implications are still murky and distant. Nonetheless, as we argue in our book Unfreeze: How to Create a High Growth Economy After the Pandemic, the economy will not simply snap back into place. The post-COVID-19 economy will not look like the pre-COVID-19 economy.

Here we offer seven changes that have big consequences for policymakers, entrepreneurs, and employees.

1 — Digital acceleration

COVID-19 has massively accelerated the adoption of digital technology to facilitate work from home. But also shop from home, school from home, telehealth, and so on.

This digital shift is often remarked on but not well understood. Technology adoption normally follows a particular diffusion trajectory. Digital technologies that have significant scale effects must overcome behavioural and institutional resistance, and they can get stuck at take-off. This means that the productivity benefits from widespread technology adoption, especially infrastructural and production technology, can be very slow to realise.

COVID-19 arrived at a critical time in the history of technology — when a supercluster of digital technologies were forming, poised to disrupt the underlying infrastructure of the economy. This suite of digital platforms and technologies had been developing for the past several decades. But they had run into innovation constraints caused by coordination adoption problems and regulatory barriers.

In March 2020, many of these constraints suddenly vanished. The spread of online education and telemedicine, which had been until then a multi-decade process, occurred in a matter of weeks.

This was a massive, global, multisector, virtually-instantaneous coordinated adoption of digital technology. That’s utterly incredible — and perhaps unique in the history of technology adoption.

A major problem with platform technologies is to drive coordinated adoption. The pandemic did in a few weeks what decades of government effort had failed to do. Long-run that is very good. But short-run it is highly disruptive.

2 — A need for massive entrepreneurial adjustment

In Unfreeze we argue that there is an urgent need for entrepreneurs to adapt to the post-COVID-19 world. Economies are made of connections, information, contracts, webs of value, relationships. When we try to restart the economy, much of this connective tissue will be gone.

The rapid technological acceleration driven by the crisis creates its own unique needs for adaptation. We’re already seeing the formation of new consumer preferences, new types of jobs, new types of business models with new cost and demand structures, new patterns of supply, and new regulatory and legal uncertainties.

But this implies that a significant amount of human capital and physical capital (built for industrial era technologies and business models) has rapidly devalued.

The first priority for entrepreneurs in the post-COVID-19 economy will be understanding how particular markets and jobs and administrative functions have changed. For example, many restaurants have moved to take-away only. Will consumers expect those new services to continue? Much of the white-collar economy has moved to work from home. Will employees demand that continues?

Entrepreneurial skills are essential during periods of rapid change. Entrepreneurship is not something that can be supplied by governments. But it can be inhibited. Policymakers have to make sure they are facilitating — not impeding — entrepreneurial adaptation to the accelerated digital adoption triggered by COVID-19.

3 — Decentralised production and innovation

One consequence of this sudden digital uptake is increased decentralisation. With the rapid adoption of work from home — not just the technologies but the social practices — we’ve seen a shift in the locus of much economic activity from offices into homes.

This shift has several implications. One, it facilitates greater co-production of value. More household resources, including especially local information, are being mixed into production.

Two, this also shifts the sites of innovation, facilitating greater household innovation and user innovation. More innovation occurs in the commons rather than in markets and organisations. This in turn increases the need for trusted decentralised networks and, in turn, increases the demand for and use of distributed innovation technology and institutions.

Three, distributed production will require more distributed dispute resolution mechanisms. Traditional courts have been slow to adapt to the digital environment and parties will be looking to more agile forms of alternative dispute resolution.

Four, because more production and innovation is occurring in households and in the commons, this means that it is harder to measure value creation and improvements in these non-market contexts. The non-market part of the economy will increase in apparent scale. So our industrial era measurements of economic activity (like GDP) will need to catch up with these new digital era realities of value creation.

This new institutional economic order will require a new economics to make sense of these new patterns of consumption and production, and new digital forms of capital and value creation.

4 — Powered-up economic evolution

The pandemic is a selection filter. As the precursor and mechanism of many of these changes, the economic consequence of the economic policy response to the viral pandemic is a powerful evolutionary selection mechanism passing over the global economy and through each sector.

This brutal selection mechanism is causing job losses, contract terminations or renegotiations, demand reductions, business closures and bankruptcy, fire sales, credit shrinkage, asset repricing, factor substitution, and other distinct forms of economic destruction that will play out over the coming months and years.

This hard evolutionary selection mechanism is also a filter. It will kill off some things disproportionately and let other things pass through. Most obviously, digitally enabled businesses and sectors will do better, because they are more well-adapted to the new environment. Bigger firms with better capitalisation (or better political connections) will do better, and smaller firms will be selected against.

In labour markets some positions are more vulnerable than others, particularly part-time workers or contractors. While many workers and firms are on temporary support through public sector subsidy of wages or quasi-partial nationalisations, a proportion of those positions or organisations being kept alive will die as soon as support is removed. There are many zombies already.

Similarly, there will be a lot of bad debt on company books (and thereby in banks) that will be realised in market revaluations over coming periods. These collapses will release resources for subsequent entrepreneurial reconstitution and reinvention.

But we should also expect consolidation of existing markets and resources among surviving players. This may actually result in higher growth and profits among large adaptive companies — particularly technology driven companies. So a period of global economic destruction is not inconsistent with a booming share market.

5 — The twilight of conventional macroeconomic policy

At the same time, COVID-19 looks to fundamentally break the standard monetary and fiscal policy levers that have been used to manage business cycles over the twentieth century.

From a public finance perspective, the magnitude of the committed policy actions is already unprecedented. The levels of public debt that are planned in order to deal with this crisis — the policies to subsidise wages, provide rent and income relief, bail out companies, etc in order to avoid market catastrophe — are the largest that has ever been experienced. Moreover, these actions are being taken during a massive collapse in tax receipts. The implications for public finance are catastrophic, with a huge increase in public debt, a vastly worse central bank balance sheet, and looming inflation.

The result is a policy challenge that far exceeds capabilities of traditional monetary and fiscal levers. We will require institutional policy reforms to deal with the crisis. But institutional policy designed to free-up the supply side of the economy, to lower the costs and constraints on businesses, is politically much harder to achieve.

Indeed, the limits of these policy levers reveals the extent to which government administration (e.g. of money, of asset and property registries, of identity, of regulation and governance) is still the foundation of a modern economy. The pandemic has brought into sharp relief the limits and constraints of this centralised public infrastructure and the technocratic foundations of the macroeconomic policy mechanisms built upon them.

The real alternative to conventional policy levers isn’t different policies (like quantitative easing, negative interest rates, or universal basic income) but better institutional technologies. We’ve been looking in the past few years at distributed digital technology (that is, blockchain) that offers a new administrative and governance base layer of the economy (see here, here, here, here and here to start).

A digital infrastructure base layer of industry utilities and digital platforms would provide a far more agile foundation for targeted economic policy and entrepreneurial adaptation.

6 — A new global trading order

One of the most powerful institutional forces over the past several centuries, and which has underpinned global economic prosperity in the industrial era, was the development of global trading infrastructure for commodities and capital. It was built around the Westphalian system of nation-state record-keeping and intra-nation state treaty-based institutional governance (i.e. trade zones). But it has come to a virtual halt in the crisis.

In the short and medium term the global trading order will rebuild around a different order, namely provable health identity and data to facilitate the safe movement and interaction of people. Where that can safely happen, so can economic activity. Health zones can become the basis for trade zones. Australia and New Zealand are already talking about a “health bubble”. It would be easy to include other highly successful health economies — Taiwan, Japan, Germany, potentially Hong Kong and Singapore, some Pacific Island nations.

Green zones (or cordon sanitaire) have long been used in pandemics and have once again been proposed as a way to exit lockdown. As the health zone grows, so can the trade zone. Economic zones can then free ride on the decentralised identity and data infrastructure created to build a health zone. The result will be the redrawing of physical and network boundaries, even eliminating artificial economic borders, to create integrated trade zones.

7 — A new political order

The costs of COVID-19 do not fall evenly across the population. The health risks fall heavily on some groups (the elderly and those with co-morbidities), and the costs of economic lockdown fall on different groups and will be felt differently. The differential impact by sector, jobs, education, human capital investments or physical or financial capital write-downs shape how the costs are distributed across society.

The virus imposes huge private costs that will be in part socialised through political bargaining. The outcome of these politically mediated bargains and transfers that will shape politics for years to come.

But the pandemic also shifts some of the anchor points of political economy. The sudden growth of the welfare state, of unemployment insurance and wage-support, of healthcare provision and childcare, even of social housing are unlikely to be easily rolled back. So there will be a higher demand for social welfare safety nets.

But to pay for this, along with the urgent need to address the huge deterioration of public balance sheets, economic policy will need an aggressive pro-market agenda to unleash economic growth. Politically, this is a pivot to the centre with very ‘dry’ economic policy and ‘wet’ social policy — what was called ‘third way’ in the 1990s.

The counterpoint to that centre-pivot is that many of the high-cost political projects of both the right and the left will be abandoned. Reduced economic growth means we can afford fewer of the luxuries of advanced capitalism.

This is a vision of a new kind of social-digital capitalism to be built after the reset — from the government-led physical infrastructure of the industrial era, to a digital era built on private, open and communally developed technology platforms.

Finally

The economic consequences of the COVID-19 pandemic are mostly currently being discussed as a macro policy response to dealing with the economic destruction that the public health strategy necessitates. This is talk of the V-shaped, U-shaped, L-shaped or W-shaped recoveries. In Unfreeze we wrote of the need for a square root shaped recovery — after the reopening, we’ll need a long period of high economic growth to return to the prosperity of 2019.

But here we’ve gone further. COVID-19 is driving structural evolutionary change in the economy. The accelerated adoption of digital economic infrastructure during the crisis will leave a lasting mark on the political and economic system of the future.