Exit, Voice, and Forking

With Alastair Berg. Published in Cosmos + Taxis, Volume 8, Issue 8-9, 2020

Abstract: This paper offers a new framework to understand institutional change in human societies. An ‘institutional fork’ occurs when a society splits into two divergent paths with shared histories. The idea of forking comes from the open-source software community where developers are free to copy of a piece of software, alter it, and release a new version of that software. The parallel between institutional choice and software forking is made clear by the function and politics of forking in blockchain implementations. Blockchains are institutional technologies for the creation of digital economies. When blockchains fork they create two divergent communities with shared transaction ledgers (histories). The paper examines two instances of institutional forks. Australia can be seen as a successful fork of eighteenth-century Britain. The New Australia settlement in Paraguay can be seen as an unsuccessful fork of nineteenth century Australia.

Available at Cosmos + Taxis and in PDF hereEarlier version available in working paper 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.

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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.

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 innovationinstitutional 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.

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.

Trustless architecture and the V-form organisation

With Sinclair Davidson and Jason Potts

Abstract: Blockchain (distributed ledger technology) is an institutional technology that allows trust to be manufactured instead of being earned. Trust is an important component of business and trade and has previously been subsumed into information costs. It is only now that the importance of trust is being fully appreciated. Arun Sundarajaran has suggested that the creation of new forms of trust has driven the expansion economic activity throughout history. In this chapter we argue that the industrialisation of trust is going, again, to drive a massive expansion in economic activity through the emergence of new organisation forms that will deliver high-powered market incentives deep into what would appear to be hierarchical organisations. We are labelling these (as yet speculative) organisations forms the ‘V-form’ organisation. In this chapter we discuss the importance of trust, the evolution of trust, and the industrialisation of trust. We argue that current organisational forms have exhausted the levels of trust that have previously sustained them. Blockchain technology offers a new industrialised form of trust that can drive further economic activity.

Available in PDF or at SSRN.

Look at our history: protectionism doesn’t work

With Vijay Mohan

We rarely think about supply chains – those immensely complex networks of production and logistics that structure the economy. 

That has changed. Early in the COVID-19 crisis, we learned that Australia imports much of its basic medical equipment like facemasks and other protective gear. As borders were being closed importing this high-demand equipment got suddenly very hard.  

Now there is an unsurprising clamour for the government to take more of an interest in how our supply chains actually work, and to use the traditional tools of protectionism to encourage domestic production of medical equipment and pharmaceuticals.  

Prime Minister Scott Morrison said in April that “we need to look very carefully at our domestic economic sovereignty”. 

But neo-protectionism to secure Australia’s supply chains would be a grave mistake – and it fundamentally gets the supply chain challenge wrong. 

First, the obvious but necessary point. We actually had a protectionist economy for most of the twentieth century. And we didn’t build facemasks. We built cars. We built cars because cars had a certain romance in the twentieth century and Labor and the union movement wanted to lock in prestigious manufacturing jobs for their supporters. 

This has always been one of the central planks of the case against protectionism. The choice of what industries to protect is not made by all-knowing and benevolent leaders, but by self-interested politicians. They get to the top of their profession not because they are skilled production managers or supply chain coordinators, but because they’re great at navigating political factions and going on television. 

Of course, our national leaders will come out of this crisis more focused on the risk of future pandemics, and more motivated to prepare our economy for this now-known risk. But as they say in the military, generals too often prepare for the last war, not the next one. We don’t need an economic system that is prepared for a crisis that looks exactly like COVID-19. We need an economic system that is prepared for an unexpected crisis – which, definitionally, could be anything. 

Indeed, it is the fact that the pandemic was unexpected to most in government that makes the strongest case for free trade. The crisis has caused a lot of market disruption. But global supply chains have adjusted remarkably well to new demands and routed around new constraints. For example, airlines have been doing temporary conversions of passenger planes to cargo planes – particularly important because medical equipment, which in normal times would be leisurely transported by ship, needs to get to new COVID-19 hot spots urgently. 

Protectionism invariably makes the industries it protects brittle and highly politicised, not agile and adaptable to sudden economic shocks. And it is a fantasy to suggest that a small, wealthy, highly-educated nation like Australia could or should ever be self-reliant in the production of all low-value goods that might be needed in unexpected crises. 

There are things the government can do to be prepared for the next crisis. Rather than making essential products, we can buy them and store them. This requires no more foresight than full-blown protectionism and is a lot cheaper. The idea of keeping extensive national stockpiles of equipment for emergencies is uncontroversial. By all accounts, the National Medical Stockpile has been an immensely valuable asset during COVID-19. 

With our RMIT colleague Marta Poblet, we have been looking at the problems consumers had getting reliable information on supply chain security in the first weeks of the crisis.  

Before the pandemic, Australian industry was interested in using new technologies (such as blockchain, 5G communication, and smart devices) to better combat food fraud in export markets or to how to prove to their customers that their products were organic or fair trade certified.  

But the pandemic revealed a more basic problem with about supply chain information. Consumers were not worried about quality or fraud. They were worried there were not enough goods available to meet demand at all – hence the panic buying of toilet paper, hand sanitizer, and dried pasta.  

This panic buying looked a lot like the sort of panic withdrawals you see in a bank run. If depositors aren’t convinced their bank is solvent, they rush to be the first to get their money out. And as we saw, Scott Morrison was no better able to convince shoppers that there were adequate domestic supplies of toilet paper in March 2020 than South Australian premier Don Dunstan was able to convince the customers of the Hindmarsh Building Society that there were adequate funds to cover deposits October 1974 — despite standing in the street outside its headquarters with a megaphone.  

In moments of high-stress consumers just don’t trust the political assurances they are given. Do we really blame them? 

Ultimately within a few weeks supply chains adjusted. Coles and Woolworths lifted their toilet paper sale limits. 

But the toilet paper panic symbolises the choice we now face when it comes to supply chain resilience. To go protectionist would be to trust our supply chains to the same political class that we simultaneously accuse of being underprepared for COVID-19. Or we could lean into free trade and open markets. We should encourage entrepreneurs to adapt rapidly to new circumstances, to experiment with new technology, and let them figure out how to operate in a disrupted global economy. 

Australia has a long history of protectionism. Let’s try to remember what we learned. 

Panic, Information and Quantity Assurance in a Pandemic

With Vijay Mohan and Marta Poblet

Abstract: During a pandemic or other disaster, public visibility of the supply chain can be useful for controlling the symptoms of coordination failure, such as panic and hoarding, that arise from the desire for quantity assurance by various sectors of the economy. It is also important for efficient coordination of the logistics required to tackle the disaster itself, with vital information flows to centralized agencies leading the response as well as to decentralized agents upstream and downstream in a supply chain. Publicly visible information about the supply chain at the time of a crisis needs to be secure, timely, possibly selective in terms of access and the nature of information, and often anonymous. Recent advances in distributed ledger technology allow for these characteristics to be met. Building digital infrastructure that permits visibility of the supply chain when needed (even if dormant during normal times) is essential for economies to be more resilient to black swan events.

Available at SSRN or in PDF here