Articles

Backing blockchain with strong policy

[This article was published at Policy Forum]


Blockchain technology offers several benefits for the world’s industries and supply chains, but as investment grows, there must be a simultaneous increase in robust international policy coordination, Darcy Allen writes.

Blockchain technology will bring the next wave of globalisation by radically upgrading the world’s trade infrastructure.

We are now seeing intense competition to replace laborious centralised processes of tracking goods with more decentralised supply chain platforms powered by blockchains.

Discovering what policy changes are necessary to facilitate this new economic infrastructure, however, will require significant policy entrepreneurship through a new dedicated international policy coordination body.

The new body would facilitate experimental trials of regulatory recognition, coordinate new free trade agreements, and encourage the emergence of technical and information standards.

Blockchain technology also offers a new way of governing information along the supply chain – especially amongst those that lack a degree of trust.

While most modern records are maintained and updated by centralised third parties – such as banks or governments – information stored in blockchains are managed through tamper-resistant and decentralised processes.

Some information currently entrusted with third parties will shift to decentralised blockchain governance. Recent surges in interest and investment in the technology attempt to gauge where the technology will be useful and how organisational boundaries will shift.

The modern global economy is ultimately made of supply chains. These supply chains link together the mining of raw materials – through their transformation and production – and the final retail process. All of this must be tracked, often across several countries and between parties where strong business relations are yet to be forged.

Understandably, governments, consumers, and producers demand a wide variety of information about goods. Questions may range from whether a product falls under fair trade standards to how fresh its ingredients are.

But accurate answers are sometimes difficult to come by because of the logistical difficulties involved in recording individual bits of information. Tracking the millions of parts in a modern aeroplane or the production conditions of a sub-component in an old building, for example, may prove challenging.

Today, we attempt to answer these questions by passing information between hundreds of supply chain participants. Those communications are often paper-based bills of lading, certificates of origin, and ship manifests. This results in fraud, errors, and information loss. Indeed, global food fraud is estimated to cost over $50 billion each year.

A lack of visibility down supply chains also risks safety. One memorable example is when Australia’s strawberries were found to be contaminated with needles just last year and frantic efforts to recall them followed.

There have been some welcome efforts to digitise supply chain information. But without blockchain, the integrity of this information remains reliant on third party maintenance and provision of databases.

Blockchain can act as a new infrastructure for modern supply chains. Accurate measurements of temperature, quality conditions, and locations are all examples of data that can be captured using sensors. Once updated to a decentralised blockchain, it is extremely difficult to change.

What can we do with this more detailed, cheaper, and trusted supply chain data?

Better supply chain data won’t just make it easier for goods to cross borders. The world can expect more niche product offerings with premium prices, shifts in the capture of value, and a movement away from storing information in closed companies towards platform-based decentralised storage. It will also see a greater use of artificial intelligence to optimise supply chain coordination.

What, then, is the role of government? To be sure, blockchain supply chains are being privately built by companies such as IBM and Maersk, as well as Australian companies such as AgriDigital, BeefLedger, and UCOT.

But supply chains must interact with regulation. Governments demand information about goods as they cross borders, including their labour conditions and biosecurity risks. This raises many questions around blockchain supply chain policy.

Will governments recognise blockchain-based information as proof of the quality and origins of a good? How will smart contracting technology interact with preferential trade deals? What are the implications for competition policy? These are only a few of the issues that policymakers and industry members must discuss together.

We can’t know the precise answers to these policy questions given the nascent nature of the technology. But we do know that regulatory environments that enable testing and experimentation will see inflows of investment, and that discovering this must occur at an international level, in a dedicated international policy coordination body.

This article is based on the author’s paper with Chris Berg, Sinclair Davidson, Mikayla Novak, and Jason Potts published in the Asia & the Pacific Policy Studies (APPS) journal. You can read the full paper, ‘International policy coordination for blockchain supply chains’, here.

This article is published in partnership with DevPolicy Blog.

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Articles

For Tassie exporters, paper trail risks vital trust

[This article was published in the Hobart Mercury]


Tasmania’s producers are perfectly placed to receive higher export prices by taking advantage of blockchain technology.

Applying blockchain to Tasmanian supply chains will deliver more trustworthy information to consumers, boosting prices of high-quality super-premium exports.

The State Government recently announced Brand Tasmania as a statutory body, tasked with promoting tourism and exports.

Building Tasmania’s brand is important. But this approach must be coupled with a way to ensure consumers trust the legitimacy of products

Supply chains connecting Tasmania to the world don’t just transport physical products like cherries, wild abalone or lobsters. They carry information about those products. As a customer in a Beijing restaurant, how can I know the lobster on my plate is true Southern Rock Lobster, not some cheap knock-off?

I must trust the restaurant owner, who trusts their supplier, who trusts their importer, and so on.

Particularly for high-information premium produce, there is an often-neglected type of supply chain infrastructure, one that carries trusted information between companies and across borders.

Today’s supply chains are riddled with problems. Pieces of paper pass between distributors, exporters, shipping companies and governments. This messy web of communications tries to connect hundreds of parties.

Some information is added along the way, but much is lost or tampered with.

Global food fraud estimates range to tens of billions of dollars a year. This comes from bad actors taking advantage of poor information flows. This has even happened with Tasmanian cherries. Cherries being sold in China and Vietnam were recently outed as fakes, sold in fraudulent “Tasmanian-grown” boxes.

The result is deeply damaging to a premium brand. Eventually prices will fall as premium produce is contaminated with fakes.

After the cherry controversy the industry responded by making more intricate boxes. Gold embossing and unique stickers helped deter fake cherry boxes. But this approach also cut deep into profit margins.

Luckily there’s now an alternative. Blockchain technology can carry detailed transparent information from producer to consumer.

Blockchain was invented in 2008 to power the cryptocurrency bitcoin. The technology enables data to be inputted and stored in a way that doesn’t rely on a central third party. Distributed ledger technologies are important and unique because we constantly use centralised companies and governments to update and hold information about our citizenship, medical records, bank balances, property titles.

Blockchains are different because they store information across a decentralised network. The word blockchain comes from the data structure — blocks of information chained together chronologically using cryptography. Blockchains aren’t stored and updated by a central party, making it extremely difficult to tamper with it. This is perfect for situations like supply chains where many parties need to share information who don’t necessarily know or trust each other.

What does this new distributed ledger technology mean for Tasmanian supply chains? Rather than passing pieces of paper between opaque organisations, a blockchain can act as a new digital infrastructure for supply chain information.

Each product or shipment can be given a blockchain-based digital representation.

As the lobster physically moves, information about it can be added to its blockchain-based record, forming a deeper digital identity.

This begins with the provenance of the product, but extends into its temperature and conditions during transport, such as its time at a distributor or waiting in a port.

Some information will be inputted manually by producers, or even governments as the goods cross borders. Other information will come from Internet of Things (IoT) infrastructure that automatically uploads information such as about location and whether the container has been opened.

For consumers, producers and governments, this new digital infrastructure creates a richer digital identity that can be viewed by all stakeholders.

This viability increases product integrity. Through a simple scan of a QR code, consumers can consult a tamper-proof record of a lobster all the way back to Tasmanian shores. Blockchains can provide the information that consumers are increasingly demand, such as proof of single origin or organic production.

Current supply chain processes are simply too fragmented and expensive to provide trusted information.

Thankfully there is an enormous amount of private investment in building new digital infrastructure using blockchains. IBM and shipping company Maersk have built a product called TradeLens. Australian companies and platforms such as AgriDigital, Agrichain and UCOT are also leading the charge. Given we can only expect more examples in coming months, what steps should Brand Tasmania take?

This experimental technology upgrade will require new trials and tests. New industry consortia will need to be co-ordinated and formed. And regulatory barriers and red tape removed, including at the border.

Only then will we see the full potential of this new blockchain-based digital infrastructure for Tasmanian producers, and the brand value and price premiums that come with it.

Dr Darcy Allen is with the RMIT Blockchain Innovation Hub and the Worldwide Blockchain Innovation Association.

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Articles

Blockchain and the manufacturing industry

[Together with Chris Berg and Jason Potts this article was published in the Australian Technology Manufacturing Magazine]


Bitcoin was invented in 2008 by Satoshi Nakamoto as a censorship-resistant cryptocurrency built for the internet. With regular fiat money centralised bodies such as banks and governments control the records of who owns what. For bitcoin those records are held in a decentralised blockchain. Blockchains are updated and maintained by a decentralised network. To ensure the transactions and records are correct, economic incentives to continually drive the blockchain network towards consensus.

Applications of blockchain extends beyond records of money. We rely on trusted third parties to maintain our registries, enforce our contracts, and maintain our records. Entrepreneurs are now discovering which roles carried out by third parties such as governments and firms will be shifted towards blockchain-based decentralised networks.

Blockchain is now being applied to trace goods along supply chains, to give control of medical records to patients, and to create decentralized identities that help people move across borders.

What does blockchain mean for Australia’s manufacturing industry?

At first glance manufacturers produce physical products and then transport those goods to consumers. More deeply, the manufacturing process is heavily reliant on databases of information in multiple directions along their supply chains. This is especially true for advanced manufacturing. When goods and inputs move, information about them must move too. This includes information about the provenance of sub-components and intermediate parts, information about the integrity of rare products prone to counterfeit, and information about ethical standards in production.

It’s harder to produce this supply chain information than you think. The information must be coordinated between hundreds of parties in the supply chain. Most of those parties don’t know or trust each other. And this information is still often paper-based or siloed within organisational hierarchies. The result is a trail of information about manufactured goods that is prone to error, fraud and loss. And these problems only get worse as supply chains get longer in a globalised world, and manufactured goods become more complex.

Blockchain technology presents a different way to govern supply chain data that centres on the movement of the good itself. Rather than passing pieces of paper between supply chain participants to track goods, information can be recorded in a decentralised blockchain. In practice goods are given a digital representation. Then as the goods move, information about them is timestamped in an immutable blockchain. Importantly this information is stored outside of organisational boundaries, making blockchain an alternative mechanism to solving the age-old problems of provenance and quality. What information is stored in a blockchain could be the historical location of a good, who produced it, how it has been stored, and who has finance on the goods.

Supply chain information extends beyond a single supply chain. To produce a complex product involves first mining raw materials, transforming those into intermediate parts, before manufacturing of the final good. Blockchains are critical here because they can track goods and components across multiple supply chains, giving more visibility and traceability deeper into complex manufactured goods.

Blockchain supply chains will leverage other frontier technologies such as the Internet of Things (IoT). Containers and products will contain sensors to record information such as GPS location and temperature. This information won’t be sent to a centralised party, but recorded cryptographically into a blockchain. This information can help consumers in verifying genuine products, assist producers in creating analytics of consumer demand and ensuring their inputs are legitimate, and governments in ensuring compliance with domestic rules and regulations.

The first and most obvious application of blockchain in supply chains has been in agricultural products such as wine, meat and seafood. The common characteristic of these goods is that they are information-rich. Information about their provenance and stewardship is often hard to verify by observing the final goods, but radically affects the price that consumers will pay.

This means the next wave of applications is likely to be other high-value information-high goods. Goods that are highly-customised, such as 3D printed medical devices, aeroplane parts and pharmaceuticals, are perfectly poised to apply blockchain technology.

Blockchain in advanced manufacturing is more than just tracking goods once they’ve been produced. We can use blockchains to coordinate the highly valuable digital files that sit behind many of these products. How can you ensure that the CAD file being 3D printed was the one originally intended? Similarly, blockchains are being used for intellectual property rights, helping to ensure compliance in an increasingly digital world.

In the physical manufacturing process itself blockchain can be used to record information about the lifecycle of manufacturing equipment. We can now have more cost-efficient and credible auditable ledgers that extend beyond organisational hierarchies.

What we have proposed here is a general movement away from intermediaries being trusted to maintain information about goods and their production, towards information governance through decentralised blockchain platforms. To be sure, many of these applications are in the trial and experimental phase. But they represent an early fundamental shift in how we organise information across the entire manufacturing supply chain.

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Articles

Why blockchain technology could be the key to solving the developing world’s biggest problems

[Together with Chris Berg this article was published at FEE.org]


The core of the free market explanation for global poverty is simple and compelling: much of the world’s poor are poor because of institutional failure.

The court systems that service the bottom billion are unreliable or hard to access. The governments impose extractive taxation. The bureaucracies are corrupt.

And some institutions are simply missing in the developing world. A lack of reliable identity services makes it hard to access financial markets. A lack of property titles, as Hernando de Soto famously wrote, makes it hard to use the capital embodied in homes.

Corruption and Monopolies

These explanations are all true. But the free market response to global poverty is insipid to the point of uselessness. Faced with evidence that institutions in developing countries are corrupt, classical liberals respond: well, don’t be so corrupt.

There are other responses, of course. We sometimes adopt the Washington Consensus approach—use the levers of political globalization to force reform on unwilling populations. Or maybe we just hope for a revolution that might turn out liberal. Neither alternatives have good track records.

The problem here is that institutions tend to be monopolies. One country has one court system, one bureaucracy in charge of property titles, one authority giving out birth certificates. To get better institutions, we have to replace the corrupt old ones, and that’s hard to do, especially given the intransigence of rent-seekers who benefit from them.

Institution Innovation

What the developing world needs is a technology of institutions—a way not to replace institutions but to create more of them, experimentally and entrepreneurially.

This is what we see in the blockchain. Blockchain technology is an institutional technology that allows multiple institutions to operate in one place. It is perfectly suited to hostile institutional environments.

There’s been a lot of work, unsurprisingly, on individual blockchain applications that might be helpful for the world’s poor: supply chains, democratic governance, and identity management for example. With these applications, blockchain might allow poor countries to leapfrog some of the stages of development—a poor country might skip the creation of the centralized institutions characteristic of the rich world and instead adopt immediately decentralized ones.

These applications don’t need to replace their competitors, and they are virtually impossible for the beneficiaries of the old order to prevent.

But we think blockchain technology offers something more fundamental than these specific applications.

It offers the possibility of creating new institutions—new algorithmic legal systems, contract dispute resolutions systems, identity technologies, mutual welfare and insurance, and public goods provision—in competition with the existing set of institutions.

For instance, the invention of a smart contracting platform could compete with existing court systems, helping to overcome the problems of hold-up or counterparty risks. The contracting parties to decide which institutional structure they wish to use—the terrestrial one or a near-infinite number of new digital alternatives.

These applications do not need to replace their competitors to function. And they are virtually impossible for the beneficiaries of the old order to prevent.

Institutional Layering

We call this process institutional layering. Blockchain institutions co-exist with existing institutions, effectively layering on top.

Blockchain entrepreneurs in developing economies don’t require international aid agencies or development experts to define economic problems and try to solve them. Rather, they apply their entrepreneurial judgment and skills to define institutional problems and use blockchains to design and test new institutional solutions.

William Easterly famously outlined the distinction between “planners” and “searchers” in economic development. Development economics has been plagued by planners implementing top-down institutions that don’t match local conditions and have a raft of unintended consequences.

Instead of working within the existing institutions, entrepreneurs can use blockchain to operate more effectively.

The capacity of entrepreneurs to search, however, is constrained by the transaction costs they face and the technologies they have available. Rather than propelling institutional change through centralized planners (whether it be through conquest or special economic zones), blockchain enables a new decentralized process of search.

Rather than forming businesses within the existing institutions, entrepreneurs can use the blockchain to more effectively operate on the level of the institutions themselves. Blockchain enables institutional entrepreneurs to search by operating on the governance or “protective-tier” level of entrepreneurship.

Now entrepreneurs can search, discover, and deploy new governance mechanisms. They can attract users by better economizing on transaction costs than alternatives.

Polycentric Institutions

The process of institutional layering will also be more polycentric. Rather than having centralized institutions attempting to fit over broad groups of people within a geographical nation-state, entrepreneurs will, over time, discover the necessary levels of institutional rules within regions and across borders.

Another ongoing problem of institutional change in the developing world is aligning formal institutions with the underlying informal norms. Blockchain-based institutional layering—using governance approaches developed by local entrepreneurs—might better match the underlying norms, or what James C. Scott describes as metis.

New, digital, uncensorable, trustful institutional technologies open up enormous opportunities for decentralized economic development.

Because blockchain institutions are built from the bottom-up and draw on local entrepreneurial knowledge, we might see greater levels of institutional stickiness, where formal blockchain institutions better match underlying norms and therefore are embedded and longer-lasting.

Our argument risks techno-utopianism. We are confident that blockchain—or successor distributed ledger technologies not yet invented—might solve several institutional problems within the developing world. It will not, of course, solve all of them.

Nevertheless, the invention of a class of new, digital, uncensorable, trustful institutional technologies opens up enormous opportunities for decentralized economic development.

And it allows the same entrepreneurial creativity that has driven prosperity in the rich world to be turned to the causes of poverty in the developing world.

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Articles

Predictions for trade in a blockchain world

[Together with Alastair Berg and Brendan Markey-Towler this article was published at Machine Lawyering]


As goods move from producers to consumers, information about those goods must travel with them. Where did a product come from? Is this wine fake? How fresh is this lobster? Modern supply chains, however, are remarkably long and complex. This complexity makes it costly to produce trusted information about goods. Blockchain and other distributed ledger technologies are poised to help lower information costs, potentially expanding and reshaping global trade.

At first it isn’t clear why we should care about trade costs. Reducing trade costs might make our goods a bit cheaper, but what is the potential longer term impact? Finding new ways to bring down the costs of trade is important because it expands the number of trades that are possible, propelling growth and prosperity.

The standardised shipping container was invented mid-way through the last century. Alongside other new technologies such as air freight, it helped transportation costs plummet. Other technologies, such as the formation and success of international trade negotiation bodies (e.g. the World Trade Organization) lowered the regulatory costs of trade. Average worldwide import tariffs fell from around 8.6% in 1960 down to 3.2% in 1995.

Today a different form of costs dominates the frictions in global trade: information costs. We can think about goods as having different attributes: provenance, age, quality, physical location, and so on. Consumers often want to know a product’s provenance. Producers want to know who their final market consumers are. Governments want to know if goods comply with domestic regulations like biosecurity laws.

But where does this information come from? Who produces it and ensures its accuracy? Today we tend to rely on paper-based communications between hundreds of companies along a supply chain. Even when those communications are digitised, they spend much time within, and moving between, confined hierarchies.

As a new institutional governance technology for decentralised ledgers, blockchain might provide a better way. Coupled with other technologies such as the Internet of Things (IoT), blockchain can be applied as a governance mechanism to store and validate a ledger of information about goods.

It would be easy to suggest that blockchains will simply decrease the costs of supply chains and make consumer goods cheaper. In our recent working paper at the RMIT Blockchain Innovation Hub, we draw on economic theory to predict how blockchain might shift how and where we trade, leading to fundamental changes to globalisation.

First, we anticipate de-commoditization of economic goods. Many of the goods we buy are sold for the same price even where their underlying characteristics differ. Those goods are not sold in the same market because they are objectively the same, but because they cannot be economically or reliably differentiated due to information costs. We expect this over-commoditization to be most prominent in markets for luxury or perishable goods, where uncertainty is built into a single market price.

To the extent blockchain trade infrastructure provides deeper and more reliable information, goods can be de-commoditized and be sold in separate markets. Over time we expect price signals to disaggregate—put simply, there will be more prices—and ultimately facilitate better market coordination.

Second, blockchain trade infrastructure might shift economic power and therefore value to the polar ends of supply chains. Supply chains are plagued by information asymmetries—where some party holds information that another does not. These information asymmetries lead to market power. For instance, a primary producer of coffee in a developing economy might lack information about their final consumers or the price at which their coffee is eventually sold, restraining them from seeking new markets.

Information asymmetries persist for many reasons, one of which is a lack of incentives for actors along a supply chain to provide that information. By providing more transparency along the supply chain, blockchain might reduce information asymmetries for producers and consumers.

As a result producers of premium products might be able to charge premium prices, while consumers could more dynamically shift between different supply chains, for instance based on their appetite for organic produce. This suggests greater competition between suppliers of similar goods regardless of existing trade relationships.

Our final prediction is a reduced reliance on quality proxies, including national borders. As consumers we regularly rely on proxies to determine the quality and legitimacy of a product (such as brand reputations and production within national borders).

As uncertainty declines over the precise characteristics of a production, however, we would anticipate that the reliance on proxies as a measure of the quality of a product will diminish. Consumers will be able to more effectively rely on the specific attributes of a product. The longer-term effect might be to shift what products are produced within economies who currently suffer discrimination due to their reputation (perhaps for food and safety regulations).

We have outlined three predictions in this post. Those predictions are necessarily speculative and will play out through as an entrepreneurial and evolutionary process of search and discovery. What can we do in the meantime? Elsewhere our colleagues have suggested the need for open standards and a crypto-friendly policy sentiment, enabling entrepreneurs to build this new blockchain-based trade infrastructure—only then will we see if our predictions are correct.

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Articles

Clause for concern

[This article was published in the IPA Review]


It is time for a new approach to red tape reduction. Governments seeking to systematically reduce red tape need a metric by which they can measure their success or failure.

In particular, we need to focus on ‘regulatory restrictions’ or ‘restrictiveness clauses’ in regulations—providing a nuanced and granulated approach which complements targeted reforms.

The commonwealth and state governments must address Australia’s over-regulation and red tape problem. Typically, governments reform particular sectors or regulations, but this can and should be complemented by a process which measures the regulatory burden and places institutional constraints on the regulatory process itself.

The former approach is characteristic of the first of three phases of regulatory reform in Australia, which were:

  • Hawke-era reforms of the 1980s
  • National Competition Policy framework in the 1990s
  • Howard-era reforms, with COAG

The first was fundamentally backward-looking—aimed at the stock of existing regulations. It was reliant on political will and appetite for reform, and required
subjectively-evaluated decisions by fallible policy makers. There is also the incentive problem: regulatory costs are dispersed but the benefits of political action are concentrated in the hands of the few, leading to interest group formation and rent-seeking.

Partly in response to this, a new complementary approach to regulatory reform emerged: red tape reduction policies and procedures. These institutionalised mechanisms include:

  • dedicated parliamentary sitting days
    to repeal legislation
  • implementation of regulatory
    budgets
  • one-in-two-out policies.

Unlike the traditional reform approach, which relies on identifying and reforming specific regulations driven through political will, institutional red tape policies and procedures force the cutting of existing regulatory burden and preventing the future growth of burden by containing the actions of policymakers themselves.

This is achieved by shifting regulatory incentives—that is, changing the rules of the game within which regulators may regulate—and ultimately binding regulators to behave in certain ways.

In this way red tape policies and procedures can be understood as a set of constitutional rules that are implemented above the regulatory process.

Alongside this shift, governments and think tanks have sought to measure and quantify the regulatory burden through a range of measures including pages of legislation, complex calculations of the cost impact of regulation, the time needed to comply with regulation, and the file size of regulation. This focus on quantification enables reform success or failure to be benchmarked.

In the early 1980s Australian economic reform was characterised by specific sectoral reforms. Then, in the late 1980s and early 1990s, Australian policymakers shifted away from emphasising specific areas of reform to a more generalised focus on the introduction and management of the regulatory process itself. For instance, the first Commonwealth regulatory assessments were introduced in 1986—which were the first form of what are now called Regulation Impact Statements (RIS).

With the Howard government came a further push for regulatory oversight and reform of ministerial portfolios. This push was in part due to the influence of business groups, culminating in the Banks Inquiry, which recommended more than 100 specific reforms to existing regulation and also recommended more effective processes for regulatory reform, including a cost-benefit approachto regulation and the strengthening of RIS processes.

From 2014 there was a greater focus on measurement and quantification of the regulatory burden. The process established a $65 billion baseline measurement of regulatory burden, which is likely to be a significant underestimate of the entire cost of the regulatory burden.

This was coupled with red tape reduction mechanisms (such as biannual red tape repeal days) and commitments to reduce red tape (cutting the cost of regulation by $1 billion annually). These red tape repeal days were modelled on an earlier Western Australian approach, but were later abandoned in 2016. This red tape repeal push, while focusing more heavily on mechanisms of red tape reduction and claiming to have made decisions to cut red tape by over $4 billion, has since been criticised as only cutting the low hanging fruit of the regulatory burden.

What is clear from this evolution of regulatory reform is a movement away from specific sectoral reform to the rise of institutionalised mechanisms to cut red tape. Furthermore, with this rise in institutionalised red tape reduction policies and procedures has come the need for measurement of regulatory burden.

All measurements of regulatory burden, owing to the problem of subjective costs and an uncertain future, are necessarily proxy measures (that is, an indirect measure of the desired outcome which is itself strongly correlated to that outcome). Red tape costs are an indirect measure of the burden of regulation, and can never wholly take into account the entire opportunity cost, which is all of the social and economic benefits which could have occurred if the red tape had not been present.

Nevertheless, various government departments and other organisations such as think tanks have developed proxies for the regulatory burden as the first step in the red tape reduction process, establishing a baseline against which progress can be measured. To date the major focus has been on creating dollar cost estimates of red tape burden as the Regulatory Burden Measurement Framework.

Other proxies of regulatory burden include the number of pages of legislation, number of Acts passed, or the file sizes of regulatory instruments. Each of these measurements are useful, but face various shortcomings. For instance, a common proxy for regulatory burden is the number of pages of legislation. In Australia, the Commonwealth has more than 100,000 pages of federal legislation, with 4094 pages of legislation passed through the federal parliament in 2016 alone, continuing on a persistent upward trajectory. While the page count approach is (and verifiable by third parties), not all pages of legislation are equal. One page that introduces a carbon tax may be much more burdensome than a page of redundant legislation with no effect. Furthermore, this type of measure does not support sophisticated models of institutional red tape reform — such as the one-in-two-out approach.

Recently, variations on a new type of baseline red tape measurement have emerged in Canada, the United States and briefly here in Queensland, Australia. This new measurement involves counting the number of ‘restrictive clauses’ found in legislation. These are clauses that restrict, prohibit or compel individuals and businesses from or to certain actions, with words such as ‘shall’, ‘must’ and ‘cannot’.

A new measurement of red tape burden must complement existing measures in some way. Developing a baseline of restrictive clauses overcomes many of the shortcomings of other forms of red tape measurement for several reasons. Restrictive clauses may be more representative of the effect of regulatory burden because they are directly associated with the impact a rule has on human decision making. Further, restrictive clauses may be more nuanced for political operationalisation because they enable regulators to operate at a lower level of reform than repealingentire Acts or pages of legislation. Creating and updating a baseline of restrictiveness clauses can also be undertaken by third parties and at a relatively reasonable cost. Perhaps most importantly, however, a restrictiveness clauses approach to red tape reform has been demonstrably successful over the long term in the Canadian province of British Columbia.

British Columbia’s efforts at institutionalised red tape reform began in 2001 when a newly elected government aimed to reduce the regulatory burden by a third. One of the tasks of the appointed minister of state for deregulation, Kevin Falcon, was to develop a new measurement of red tape off which the government could determine its success. Falcon decided to use ‘regulatory restrictions’ as a way to measure and benchmark regulatory reform. This unique form of measurement was defined as any ‘action or step that a citizen, business, or government must take to access government services or programs, carry out business or pursue legislated privileges’. Each ministry was required to count all of their regulatory requirements within their statutes, regulations and policies. This data was then fed into a database, and portfolios were given regulatory budgets of regulatory restrictions which they must cut.

These red tape reform efforts were remarkably successful. From 2001 to 2017 British Columbia reduced the number of regulatory restrictiveness clauses from 330,812 to 170,140—a 48 per cent reduction.

In approximately a decade, it went from being one of the worst-performing provinces to one of the best in Canada. Furthermore, this reform success has lasted across changes in government with policies such as one-in-two-out (which at one stage went up to one-in-five-out, but has since been decreased to one-in-one-out). Furthermore, the success of the red tape restrictiveness clauses in the province of British Columbia led to the Canadian government being the first country in the world to legislate a one-in-one-out policy in 2015, following the success of the policy from 2012 to 2014. These successes led to a similar approach to red tape reduction in Queensland.

For a short time, the Newman government (2012-2015) adopted a similar restrictiveness clauses approach. Its adoption followed a Queensland Competition Authority (QCA) issues paper and interim report in late 2012, which recommended the adoption of a British Columbia-style approach to counting obligations. The QCA saw the ‘regulatory requirements’ measure as supplementing existing red tape measures, such as page counts and in dollar terms, which would all be used together to reduce the regulatory burden. The new count approach for Queensland, however, was directly modelled off the British Columbia approach—with the calculation of baseline count of ‘regulatory requirements’. The baseline count of 265,189 regulatory requirements in Queensland was first made on 23 March 2012. By 30 June 2013 that number has fallen by 4 per cent (9,404 fewer regulatory requirements). The Newman Government aimed to have a 20 per cent net reduction in regulatory burden over six years, but the approach was abandoned by the ALP Government when it took office in 2015, instead focusing on the compliance costs of regulation.

One of the critical features of a successful red tape reduction strategy is that it remains in place over changes in government. There are several potential ways to achieve this. As is the case in Canada, governments could legislate red tape reduction mechanisms rather than simply having a policy. In the absence of this, however, it is also useful to use measurements of red tape that can be effectively counted by third parties such as think tanks. The Mercatus Centre at George Mason University in the United States has recently automated a similar approach to counting regulatory restrictions called RegData 2.0.

A team of researchers has developed a panel of data of the restrictiveness of regulation through textual analysis of the Code of Federal Regulations (CFR). This approach seeks to create a time series to map the number of regulatory restrictions within US legislation as well as measuring industry-level regulatory burden using machine learning, known as RegData 2.2. This nuanced measurement approach combined with creating industry specific training documents, has enabled within and between-industry econometric analysis of the burden of regulation. Researchers at RMIT University and the Institute of Public Affairs are investigating means to apply the RegData methodology to Australian regulation. Applying this approach outside of the United States, however, requires a further step of first developing a database of existing Commonwealth legislation, given the lack of a real time equivalent of the comprehensive Code of Federal Regulation.

The benefit of such an automation is not only to provide context to the broader challenges of red tape expansion—that is, by providing restrictiveness clauses (or similar) counts across a longer time frame—but also to introduce a level of accountability and measurement that is cost effective and can be calculated even when political will for targeted economic reform is lacking.

With the increase in meta-regulation of the regulatory process through red tape policies and procedures there have been many issues of measuring the regulatory burden. While more effective measurement and red tape reduction policies and procedures should not be seen as substitutes to targeted economic reform, they are a complementary institutional approach to traditional economic reform and hold a clear place in tackling Australia’s red tape crisis.

This new approach to red tape measurement—through the counting of restrictiveness clauses— presents a fruitful path for the future red tape reduction mechanisms as a more granulated approach to the political economy challenges of red tape reduction.

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Some economic consequences of the GDPR

[Together with Alastair Berg, Chris Berg and Jason Potts this article was published at Cryptoeconomics Australia]


At the end of May 2018, the most far reaching data protection and privacy regime ever seen will come into effect. Although the General Data Protection Regulation (GDPR) is a European law, it will have a global impact. There are likely to be some unintended consequences of the GDPR.

As we outline in a recent working paper, the implementation of the GDPR opens the potential for new data markets in tradable (possibly securitised) financial instruments. The protection of people’s data is better protected through self-governance solutions, including the application of blockchain technology.

The GDPR is in effect a global regulation. It applies to any company which has a European customer, no matter where that company is based. Even offering the use of a European currency on your website, or having information in a European language may be considered offering goods and services to an EU data subject for the purposes of the GDPR.

The remit of the regulation is as broad as its territorial scope. The rights of data subjects include that of data access, rectification, the right to withdraw consent, erasure and portability. Organisations using personal data in the course of business must abide by strict technical and organisational requirements. These restrictions include gaining explicit consent and justifying the collection of each individual piece of personal data. Organisations must also employ a Data Protection Officer (DPO) to monitor compliance with the 261-page document.

Organisations collect data from customers for a range of reasons, both commercial and regulatory — organisations need to know who they are dealing with. Banks will not lend money to someone they don’t know; they need to have a level of assurance over their customer’s willingness and ability to repay. Similarly, many organisations are forced to collect increasingly large amounts of personal data about their customers. Anti-money laundering and counter-terrorism financing legislation (AML/CTF) requires many institutions to monitor their customers activity on an ongoing basis. In addition, many organisations derive significant value from personal data. Consumers and organisations exchange data for services, much off which is voluntary and to their mutual benefit.

One of the most discussed aspects of the GDPR is the right to erasure — often referred to as the right to be forgotten. This allows data subjects to use the government to compel companies who hold their personal data to delete it.

We propose that the right to erasure creates uncertainty over the value of data held by organisations. This creates an option on that data.

The right to erasure creates uncertainty over the value of the data to the data collector. At any point in time, the data subject may withdraw consent. During a transaction, or perhaps in return for some free service, a data subject may consent to have their personal data sold to a third party such as an advertiser or market researcher. Up until an (unknown) point in time — when the data subject may or may not withdraw consent to their data being used — that personal data holds positive value. This is in effect an option on that data — the option to sell that data to a third party.

The value of such an option is derived from the value of the underlying asset — the data — which in turn depends on the continued consent by the data subject.

Rational economic actors will respond in predictable ways to manage such risk. Data-Backed Securities (DBS) might allow organisations to convert unpredictable future revenue streams into one single payment. Collateralised Data Obligations (CDO) might allow data collectors to package personal data into tranches of varying risk of consent withdrawal. A secondary data derivative market is thus created — one that we have very little idea of how it will operate, and what any secondary effects may be.

Such responses to regulatory intervention are not new. The Global Financial Crisis (GFC) was at least in part caused by complex and rarely understood financial instruments like Mortgage-Backed Securities (MBS) and Collateralised Debt Obligations (CBS). These were developed in response to poorly designed capital requirements.

Similarly, global AML/CTF requirements faced by financial institutions have caused many firms to simply stop offering their products to certain individuals and even whole regions of the world. The unbanked and underbanked are all the poorer as a result.

What these two examples have in common is that they both have good intentions. Adequate capital requirements and preventing money from being cleaned by money launderers are good things, but good intentions are not enough. Secondary consequences should always be considered and discussed.

Self-governance alternatives, including the application of blockchain technology, should be considered. These alternatives use technology to allow individuals greater control over the personal data they share with the world.

Innovators developing self-sovereign identity solutions are attempting to provide a market based way for individuals to gain greater control over — and derive value from — their personal data. These solutions allow users to share just enough data for a transaction to go ahead. A bartender doesn’t need to know your name or address when you want a drink, they just need to know you are of legal age.

Past instances of regulatory intervention should make us cautious that even well-meaning regulation will achieve its stated objectives with no negative effects. Self-sovereign identity, and the use of blockchain technology is a promising solution to the challenges of data privacy.

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