Cryptoeconomics as Commons Economics

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* Text: Putting Economics back into Cryptoeconomics. By Dick Bryan & Akseli Virtanen & Robert Wosnitzer. ECSA ECONOMIC IDEAS [1], May 2018 (Draft, Version 0.4)



By Dick Bryan & Akseli Virtanen & Robert Wosnitzer:

"The mounting literature on cryptoeconomics shows an interesting but also alarming characteristic: its underlying economics is remarkably conventional and conservative.

It is surely an anomaly that many people who have gone outside the mainstream to disrupt and develop alternative visions of the future and economy so readily adopt, apparently uncritically, the conventions of the ‘dismal science’.

The problem is that this framing blocks the real potential for cryptoeconomics and cryptographically enabled distributed economic-social system to facilitate the building of a radically alternative politics and economics.

At the core of this view are two realizations:

1. In their money role, cryptocurrencies can be an alternative unit of account, not just a means of exchange. They can invoke a new measure of value, not just facilitate new processes of trade. As such, they can have a ‘backing’ in the value of output they facilitate, not present as simply tools of speculative position-taking.

2. In their ownership role, they can be derivatives (purchases of risk exposure, not just asset ownership) designed so that people risk together, not individually. They can invoke collective approaches to dealing with risk, not individualistic ones.

Which economics?

Economics is a broad and contested discipline. It is also an old one, with Adam Smith’s Wealth of Nations almost 250 years old, and Marx’s economics 150 years old. Its dominant discourse is ‘neo-classical’ economics, dating from the late 19th century. It has, of course, significantly evolved over the past century, but the current dominant thought remains relatively coherent. It is dominated by an orthodoxy, quite unlike the rest of the social sciences that are conceived in theoretical and methodological debate. The dominance of neoclassical economics is not unchallenged. There are criticisms from both the ‘right’, in the name of libertarianism (e.g. Hayek) and from the left (both a statist left like Keynesianism and an anti-capitalist left like Marxism). In that sense it is hardly surprising that there is no definition of ‘economics’ that is generally agreed.

Here are a couple of ‘standard’ definitions that come from the likes of Economics 101 textbooks that to some degree cover multiple positions in debates:

1. Economics is the study of allocating scarce resources between alternative uses.

This is a definition that points to price formation and decision making. It opens up agendas of optimisation. It is framed to privilege ‘microeconomics’ (the workings of particular markets), not ‘macroeconomics’ (the totality of economic processes, understood as more than the sum of market processes).

Here is another one:

2. Economics is the study of the processes of production, distribution and consumption of goods and services.

This is a definition with wider social meaning and context. It is not specifically about markets and certainly not focussed on optimisation. Its focus is the social, not the individual, and on systems. It is more likely to be historical and less mathematical than the economics created under the first definition. It implicitly acknowledges that the economic is difficult to disentangle from other facets of social life.

By contrast, the first definition isolates ‘the economic’ to a greater extent by focussing on price formation and decision making. In most of the 20th century, this was achieved by treating economic agents as autonomously rational, later enhanced by game-theoretic strategic rationality and later still challenged somewhat by propositions of ‘systematic irrationality’ (behavioural economics). These developments have enabled economics to become mathematically advanced and subjectable to formal modelling.

Both definitions have something to say to the token economy community, where we can recognise concurrently a potential epochal change in the way of doing economic activity and the new potential of mathematical modelling. But the two emphases need to be kept consciously in balance.

Perhaps this recognition is part of the success of Ethereum, where we can see each style of economic focus in play.

Ethereum inventor Vitalik Buterin, consistent with the first definition of economics, has defined cryptoeconomics as about:

· Building systems that have certain desired properties

· Use cryptography to prove properties about messages that have happened in the past

· Use economic incentives defined inside the system to encourage desired properties to hold into the future. [2]

Ethereum developer Vlad Zamfir, embracing more the second definition (and citing Wikipedia), says that cryptoeconomics might be:

A formal discipline that studies protocols that govern the production, distribution, and consumption of goods and services in a decentralized digital economy. Cryptoeconomics is a practical science that focuses on the design and characterization of these protocols. [3]

But it is apparent that, in the broad scoping of cryptoeconomics, it is the first definition that is the focus. The cost of this bias is to both limit the social and economic significance of a cryptoeconomics.

The limited working definitions of cryptoeconomics

Specifically, the focus in cryptoeconomics on reducing transactions costs and creating individual incentives to operate optimally is in danger of not just neglecting wider social issues of production, distribution and consumption of goods and services, but of building a framework that actually makes impossible a systematic engagement with the wider issues.

If you Google cryptoeconomy/cryptoeconomics, the sources that appear have a remarkable consistency. The various blogs/primers/newsletters start with almost the same sentence. They break the term ‘cryptoeconomics’ into its two component elements. They explain processes of cryptography with some precision, but when it comes to explaining the associate economics, the depiction is remarkably narrow.

For example:

- Cryptoeconomics comes from two words: Cryptography and Economics. People tend to forget the “economics” part of this equation and that is the part that gives the blockchain its unique capabilities. . . .Like with any solid economic system, there should be incentives and rewards for people to get work done, similarly, there should be a punishment system for miners who do not act ethically or do not do a good job. We will see how the blockchain incorporates all these basic economic fundamentals.

(Ameerr Rosic’s ‘What is Cryptoeconomics: The ultimate beginners guide. [4] )


- Cryptoeconomics . . . combines cryptography and economics in order to create huge decentralized peer-to-peer network. On the one side, the cryptography is what makes the peer-2-peer network secure, and on the other side, the economics is what motivates the people to participate in the network, because it gives the blockchain its unique characteristics.

(Introduction to Cryptoeconomics through Bitcoin [5] )

The limited framing of economics is, perhaps, because the world lacks people with background in both cryptography and (a broad) economics. We thought it was quite funny when Nick Szabo tweeted some time ago about economists and programmers: “An economist or programmer who hasn’t studied much computer science, including cryptography, but guesses about it, cannot design or build a long-term successful cryptocurrency. A computer scientist and programmer who hasn’t studied much economics, but applies common sense, can.” Because, in a sense he is absolutely right, but then on the other hand, you do not create anything new from doxa (common sense), but just repeat the same. The idea that the economy (society) is common sense will create an economy that looks like a computer, taking the existing power structures as given. In good economics, the issue of power, and who holds it, how its use it governed, is the key issue.

Cryptoeconomics is, perhaps, being frequently projected by people who are highly qualified in programming and engineering, but often self-taught in economics. And it’s not just the bloggers and tweeters. Within the academy, there is the same sort of emphasis emerging, including from qualified economists.

The MIT Cryptoeconomics Lab [6] presents a couple of papers that centre on transaction costs and networking.

For example, in “Some Simple Economics of the Blockchain” Christian Catalini and Joshua Gans contend as their central proposition:

- In the paper, we rely on economic theory to explain how two key costs affected by blockchain technology – the cost of verification of transaction attributes, and the cost of networking – change the types of transactions that can be supported in the economy. . . . The paper focuses on two key costs that are affected by blockchain technology: the cost of verification, and the cost of networking. For markets to thrive, participants need to be able to efficiently verify and audit transaction attributes, including the credentials and reputation of the parties involved, the characteristics of the goods and services exchanged, future events that have implications for contractual arrangements, etc.

The Cryptoeconomics research team at Berkeley is another example.

Zubin Koticha, Head of Research and Development at Blockchain at Berkeley, begins his ‘Introduction to blockchain through cryptoeconomics’ like this:

- Although Bitcoin’s protocol is often explained from a technological point of view, in this series, I will convey the incentives existing at every level that allow for its various comprising parties to interact with cohesion and security. This study of the incentives that secure blockchain systems is known as cryptoeconomics. [7]

It is important to be clear here. The objective of our evaluation is not a critique of these specific contributions: they may well be exemplary expositions within their chosen agenda. It is to say that if we limit the conception of cryptoeconomics to these sorts of framings, then we can imagine and theorise cryptoeconomics only in the language of optimized individual transactions and incentives. The issues of production, distribution and consumption of goods and services – the bigger picture issues – slide off the analytical agenda. The same thing with the conclusions.

The Hayekian turn: the integrity of market processes

For some, this slide is most welcome, for they see the world in terms of interacting individuals and markets as both an efficient and a moral mode for individuals to engage. If we attach an economics and philosophy to it, the most obvious is Friedrich von Hayek. Hayek was a relatively marginal figure in economic theory and policy till his ideas were embraced by UK prime minister Margaret Thatcher. Hayek was an admirer of markets and prices as modes of transmitting information, arguing they generate spontaneous self-organization. And he was an advocate of limited roles of government in money creation and management, and in social policy too, citing what Friedman later depicted as the ‘the tyranny of the majority’ as the danger of government interventions. In 1976 he published a book called ‘The denationalization of money’, arguing that governments messed up money systems when they intervene, and we would be better off with private, competitively driven monies.

There is certainly a strong tradition in the blockchain community that would confirm this Hayekian view. But it is important that we do not fall into this discourse by accident. (It is not the role of this text to debate this or any specific philosophy of economics.) Let’s recall in this context that while Hayek was an opponent of state money, he did not at all advocate that money should be freely issued. He believed that money should reflect, and its quantity and value should be tied to the ‘real’ economy. In 1930s and 40s debates about the post WWII global monetary system, Hayek, following von Mises and others, argued against the Keynesian proposal for a state-backed global money. The alternative he supported was that the system should be backed by reserves of commodities (lumbar, coal, wheat, etc). This requirement seems to be ignored by many cryptoeconomic commentators who invoke the relevance of Hayek to advocate non-state ‘currencies’ without material backing. Yet, the issue of token backing is very important, and we consider it a little bit more below.

For the non-Hayekians, there remains the option of a tradition of neo-classical economics that embraces optimisation, transaction costs, and incentives, but also pays more attention to the limitations of market solutions. A significant number of Nobel Prizes for Economic Science in the past 30 years have been awarded for engagement with these sorts of problems. It all points to the proposition that markets do not work in a simple, idealised way.

Neoclassical economists identify two broad limitations of market solutions. One is ‘imperfect’ markets, where the capacity to secure forms of control over a market generate returns above the norm.

Historically, this issue has focussed on the inefficiencies of monopolies and oligopolies. More recently, attention has been paid to asymmetrical information, and especially the fact that sellers generally know more about a commodity than buyers. (Joel Monegro’s ‘Fat Protocols’ is in this tradition, engaging what sorts of control at what point of the stack (value chain) generate best long-term returns.)

The other factor in the neo-classical approach is the condition of ‘market failure’: where markets cannot effectively allocate prices because collateral costs and benefits are not borne by individual producers and traders. Hence there is in neo-classical economics greater engagement with the roles of government in overcoming market failure than is found in Hayek, albeit that there is also debate whether the cure is worse than the disease. Whether the computational systems built on smart contracts can significantly diminish market failure stands as a moot point. (ADD CALLON, FOUCAULT).

Much of the rest of economics covers a wider range of views, but a smaller number of economists. Yet here, the broader and more cultural and socio-historical questions come to the fore. Let us focus on two broader issues, still very ‘economic’ in framing, that maybe are sufficient to capture the flavour of these broader agendas. They both appeal to broader social perspectives in cryptoeconomic analysis, but embody rather different political agendas. One comes from treating cryptotokens as not just a new means of exchange (the transaction view) but also a new unit of account (a production and distribution view); the other is played out through debates about the valuation of cryptotokens.

Cryptotokens: means of exchange or units of account?

Going back to our definitions of economics, the first one – about optimization, incentives and transaction costs – conceives of tokens as either means of exchange or, in the case of utility tokens, types of commodity futures contracts (rights to future conversion into commodities).

They are that, but they also are more than that, when framed in the context of the second definition of economics. From the perspective of the second definition we can see cryptotokens as providing the possibility for new units of account, and hence new ways to measure the economy.

In the first definition, the answer to the question ‘what counts’ in the economy is answered by reference to the discipline of market calculus. In the second definition, what gets counted as ‘production’ and ‘consumption’ is more open ended. What is counted - and what is valued - opens as a design question.

It has been well established that market criteria are blind to some critical economic processes. Roughly (for it is complex to specify) anything not produced for sale is systematically excluded.

In the mainstream capitalist world of fiat currencies, incorporating these excluded forms of production and consumption has been a virtually insurmountable challenge. There we see the dominance of a culture of production for profit and a history of data collection based on that principle. Beneficial things that do not make revenue are difficult to measure and hence to incorporate.

Of course we are not the first to recognise this limitation. The neglect of household production, both nurturing activities in the home and the economic activities of peasant economies, are widely-recognised limitations. And within neo-classical economics there is debate about how far into wider social analysis the notion of externalities extends (and how they might be priced). In a similar vein, the appeal of ideas like ‘triple-bottom-line accounting’ and ‘ethical investing’ also embrace alternative visions of counting. But, and this is critical, they all presume the ontological primacy of profit-centred measurement: they are critiques of and qualifiers to that system and rarely present alternative modes of calculation.

Cryptotokens enable us to re-open this measurement question. Cryptotokens as means of exchange enable us to trade in new ways. Cryptotokens as new units of account enable us to measure output in new ways. The challenge in the cryptoeconomy is to open discussion about how we measure this broader conception of ‘production’ and ‘consumption’, consistent with our aspiration of incubating not just in new ways of organizing, but also the production of new things and new (social, political, aesthetic, environmental...) relations.

But it is critical here that this imagining of new ways of doing economy and economics is not just fuzzy and feelgood: we need ways to measure and to socially validate these new horizons. It means that we cannot, in the first instance, reduce all forms of production to a monetary price. We can treat monetary price as one index of measurement (for a price is merely an index since the base unit of measure is arbitrary with respect to the thing being measured), but we will need other indices of production too, targeting measurement of the different ways in which goods, services and intangibles get acknowledged socially – for example, measurement of replication, social inclusion and recommendation (ADD GABRIEL TARDE IN MORE DETAIL).

Such alternative measures are not a simple processes, and there are certainly challenges, most notably of measurement across indices and dealing with gaming of the measurement system. But we believe these are challenges are interesting and definitely worth taking up.

The valuation of cryptotokens

This issue is of importance because it gets to the heart of the question whether markets can effectively price tokens as more than speculative objects. This was certainly an issue for popular debate in late 2017 when the price of bitcoin spiked. In this context, prominent crypto investor Fred Wilson said: In times like this, I like to turn to the fundamentals to figure out where things stand and how I should behave. . . You need to have some fundamental theory of value and then apply it rigorously. [8]

For those who believe that markets create spontaneous order, the search for something ’fundamental’ is a non-question: price captures all information, it is an expression of supply and demand and finds its own level. So the very act of posing the question of an ‘underlying’ or ‘fundamental’ value is to move outside the Hayekian view. It is to suggest that there is and can be a value to cryptotokens beyond current price. It takes us beyond that first definition of economics in terms of markets and incentives and into some wider, social and historical issues of economics.

(See Valuation crisis and crypto economy [9]; and Whose stability? Reframing stability in the crypto economy. [10])

The issue under consideration here is not whether the measurement of ‘fundamentals’ is a good guide to trading strategy in cryptomarkets. (There is a standard debate in trading strategy about fundamentals VS. technical analysis of patterns of price movements. Warren Buffet stands out as an advocate of fundamentals analysis.) Nor is it about developing the capacity to forecast an income and expenditure model for the future, important though this is.

(See for example, Brett Winton, How to Value a Crypto Asset – A Model [11] )

The issue here is how we might measure the crypto economy if not by current token price. It matters because fundamental value points to the longer-term viability of a token and the activities that underlie it and potentially gives tokens an integrity which will be recognised in wider capital markets. Fundamental value is not simply a long-term average price, around which the spot price varies. It is a value that can be measured by criteria which link to the capacity of an asset to produce new value. In neoclassical, equilibrium theory, the ‘efficient markets hypothesis’ postulates that long-term market price will spontaneously gravitate to the valuation of this capacity to generate new (future) value. But it is only a view specific to neo-classical economics.

The challenge of fundamental value is to find a mode in which to measure the current value of an asset, especially when that value requires projection of the future. It was once a relatively straightforward calculation: a staple (and stable) measure of accounting, when manufacturing industry was the ‘model’ corporation, and capital was physical (factory sites, machinery, stock). It has become a more challenging issue for accounting since corporate assets became increasingly intangible – intellectual property, brands, goodwill, etc.. Some leading accountants claim that the profession is in something of a crisis because of an incapacity to measure the value of intangible assets.

(See Valuation crisis and crypto economy [12] )

So we should recognise that, in a cryptotoken context, the idea of calculating a fundamental value is experimental. We should also be aware that there is a propensity in cryptoeconomics to engage valuation via an over-simplified interpretation of what a token actually is and can do. That is, there may be consensus that tokens are complex, hybrid, novel things. But in the complexity of the valuation process, there is a proclivity to treat them as one thing; in particular as money or as equity, and especially the former.

Some of the debate here occurs via analogy. For example, it can be argued bitcoin could do the credit card provisioning of Mastercard or Visa, so we could estimate a corporate value for bitcoin based on the value of these companies.

(See critical evaluation of this by Andy Kessler, The Bitcoin Valuation Bubble, Wall St Journal, August 27, 2017 [13] )

But that doesn’t really work, because analogies don’t hold. We can’t claim the crypto economy to be different, yet benchmark its value to assets and processes we seek to disrupt.

Another approach, we think laudable in its desire to capture cryptotokens as derivatives (see more below), contends that the Black Scholes options pricing model can be adapted to explain token values.

(see J. Antos and R. McCreanor ‘An Efficient-Markets Valuation Framework for Cryptoassets using Black-Scholes Option Theory’, [14] )

The essence of this proposition is that cryptotokens hold exposure to a future of potentially such monumental significance, so that cryptoassets themselves are call options on the utility value of what that cryptoasset might someday provision. Volatility of token values may then be seen as an efficient reflection of the a rational estimation of the probability of realising some real utility value of a future - perhaps distant future - product that results from current cryptoassets.

Framed within the efficient markets hypothesis (Eugene Fama), this approach does bear the critical proposition that ‘efficient’ outcomes are a reflection of some ‘fundamental value’. But outside that assumption it is not really persuasive as an explanation of current asset values. However, valuable in its approach is that it focuses on changes in estimated variables, not on the static value of underlying assets. In this way the approach does capture a derivative dimension in valuation (an issue addressed shortly more below).

Some innovative agendas of measurement are coming via the old quantity theory of money proposition, expressed as ‘the equation of exchange’.

The formula states:



M = the quantity of money in circulation,
V = its velocity of circulation of money,
P = the general price level in the economy and
Q = the quantity of goods and services sold in the economy.

It is worth spending a little time giving context to this formula, both because of its application in the existing literature on cryptoasset valuation and because it is where ECSA too looks to frame fundamental value, albeit in a way different from current debates.

The equation MV = PQ comes from a long economic lineage, mostly identified with 18th century Scottish philosopher David Hume. It presents the ‘real’ economy on the right hand side and its money equivalent on the left hand side. Its lineage is long, but its functionality in economics is challenged (e.g. is it merely an identity; can it be read causally and if so from right to left as well as left to right?). In late 20th century policy application it has been used to focus on the relationship of M and P, and to argue that states should be passive in economic management, minting just enough money to keep prices stable (with V constant, money supply should expand in proportion to Q) . It became popular in the 1970s economics of Milton Friedman (broadly aligned to Hayek). It was called ‘monetarism’ and contended that state fiscal and monetary expansion were not solving recession, but causing inflation.

Monetarism became central bank policy orthodoxy in many Anglo countries for just a brief period in the early 1980s, expressed as ‘money supply targeting’. It was quickly abandoned and one of the reasons, with new significance for the world of cryptotokens, was that the state’s various definitions of money (cash, trading bank deposits, etc.) moved in different sorts of directions: there was no single state money to be targeted. More recently, the non-inflationary impact of US quantitative easing (so far) may be some further indication of the practical limits of the equation in state policy formation. QE also raises the challenge that the equation may only work for goods and services outputs and prices, but not for financial assets. Indeed, it is ambiguous as to which side of the equation liquid financial assets should be located: are they commodities (RHS) or money (LHS)?

With that brief background, let’s take a quick look to the use of the quantity theory of money in cryptotoken valuation.

The initial figure of note here is Chris Burniske, who observes that tokens have both asset and money attributes and are currencies in the context of the programs they support. But in that role they don’t generate cash flow, so they can’t be valued by discounted future value - however that would be measured. (Cryptoasset Valuations

For this purpose Burniske re-defines the variables of the equation:

M = size of the asset base
V = velocity of the asset’s circulation
P = price of the digital resource being provisioned (note: not the price of crypto assets)
Q = quantity of the digital resource being provisioned (note: not the quantity of crypto assets.

He then solves for M, which enables an individual token valuation.

This is indeed a novel approach and for a reason opened up a significant debate. But it has a couple of problems:

· It finishes up displacing the valuation problem from the token to the valuation of digital resources being provisioned, and the ambiguity of how that is being measured

· moving V to the RHS so as to solve for M turns the equation from being a logical identity (that money values equal commodity values) into a historical proposition of individual variable valuation. (If, for example, velocity doubles, it doesn’t thereby halve the size of the asset base.)

· In wider discussion there is recognition of the problematic valuation of V (actually, it is the volatility of V).

There is a literature addressing the question of velocity. There are debates here, but, as summarised by Alex Evans, its common proposition is that:

- tokens that are not store-of-value assets will generally suffer from high velocity at scale as users avoid holding the asset for meaningful periods of time, suppressing ultimate value. [15]

A problem with the valuation literature seems to be that it conflates the equity dimension and the monetary dimension of tokens.

The focus on the fact that

(a) tokens will be turned over rapidly because they are not a good store of investor value is different from the issue of

(b) tokens turning over in their use as a means of exchange inside projects/businesses.

The latter matters, the former does not. To give attention to the former would be like saying the turnover of corporate equities impacts the long-term price of corporate equities. The underlying issue here is that tokens blur the categories of equity and money, and the velocities of these attributes have different drivers.

In other words, the V measure we need here is the velocity of tokens within the crypto economy; not the velocity of token circulation in the ‘outside’ capital market.

We are interested in this approach and its criticisms not for the purpose of ‘disproving’ the approach – for probably any proposal in this domain is somewhat easy to critique. The point is that cryptoaccounting, like mainstream accounting, simply doesn’t have good tools to measure in this domain. But it is an area where we should explore, and it requires creativity, such as shown by Burniske and the debate to which his work has given rise. Indeed, we are thinking that the novelty of cryptoassets gives us opportunities to invent valuation procedures that could well be actually of benefit to the mainstream accounting profession.

We are working intensively on the ECSA token valuation system, as it could be posed as an engagement with this debate, returning to the original meaning of


as the depiction of an economy which balances the monetary side of an economy (MV) with the so-called ‘real’ side (PQ). Let’s think about this for a moment. From our perspective, the measurement process means that P is too limited a category. We want to treat price as just one index of ‘value’ measurement amongst a range.

So we respecify:

MV= I(1-x)Q


M = the quantity of tokens issued under the auspices of ECSA ecosystem
V = the velocity of circulation of tokens within ECSA ecosystem projects
I(1-x) is the range of indices of valuation, of which price is just one
Q is the quantity of output (tangible and intangible) produced within ECSA ecosystem projects.

If we measure the ECSA economy in the way described, we can make a simple use of this formula, or at least the underlying sentiment, both economic and social. For ECSA itself, this mode of measurement gives a means to define both fundamental value and set some governance agendas.

As an identity, the LHS and RHS are equal.The monetary policy position of ECSA is that the RHS (the total value of output within ECSA ecosystem) will drive the LHS (token issuance qualified by velocity). As velocity is measurable (and will undoubtedly change while the ECSA economy establishes), ECSA can oversee token issuance to ensure MV=IQ, and the economy can be run on non-inflationary tokens. The key here is to concurrently have an internal, ‘working token’ and ‘market token’ traded on the capital market. The equation of exchange should only apply to the internal ‘working token’, not the ‘capital market token’, for it is the internal token which articulates with production and distribution. Fundamental value for investors comes from interpreting the relationship between the internal token and the value of goods and services produced.

A question, of course, is how do we reduce I to a single figure? The answer we’ve been thinking is that ECSA does not need to do that. ECSA can measure and report to the ECSA token market in terms of multiple criteria. ECSA is not seeking to replicate the role of a national statistical agency or a corporation reporting its profit and loss position. In the crypto economy, our role is to provide full information to the market, and no more. It is the job of the token market to make this evaluation across indices; not of ECSA itself. The ECSA token market will, in its own way, reconcile these diverse indices to a single measure, expressed by whether the ECSA token price goes up or down (relative to the rest of the market). That the outcome will see token market participants involved in subjective weightings of output reported in multiple indices is not just an unavoidable consequence of the proposed measurement process; it is one of its purposes. It intentionally opens a tangible debate about what we produce and how we measure. It intentionally opens the question of the value of value.

ECSA token buyers (the capital market) are thereby provided with a measure of the ‘fundamental value’ of output within the ECSA economy and assurance of a non-inflationary issuance of internal tokens. More broadly, we think that this valuation process gives a material integrity to the ECSA token. A fundamental value to back it up.

Reframing tokens as financial derivatives for risking together (i.e. building the social crypto economy) The second proposal of this analysis is that cryptotokens can be financial derivatives.

The essence of the issue here is that:

  • There can be widespread agreement about what tokens are not (they are not just equity; they are not just debt; they are not crowdfunding, etc.) but it is not agreed what they are
  • There is a widespread embrace from the cryptoeconomic community of the issue of a transformative potential: tokens give exposure to an unverified but exponential future.
  • A distributed, decentred economy suggests notions of ownership that are different from the past: people hold exposures to assets diffused in networks that are themselves fluid. Hence tokens give exposures to ‘performance’, not some underlying assets themselves.

The latter two signal the capacities of derivatives. The challenge is that cryptotokens don’t come into being already as formed derivatives: they must be consciously configured as derivatives - as purchases of risk exposure (not just asset ownership) designed so that people risk together, not individually. What is the agenda here in recasting tokens as derivatives? Two issues stand out. The first is historical. It is to note that in important ways all monies are derivatives: they are a contingent claim on ‘real’ resources. The second, which follows, is to note the politics of framing tokens as derivatives.

Part A: A historical digression, but of some significance

The problem of our radical measurement proposal is that all the language of money, markets, prices and profit is dominated by a discourse that equates money with the state, markets with a profit-centred mode of calculation and profit as a surplus defined by reference to extraction of individual benefit. Cryptoeconomics has been strong in challenging the first of these, but less effective in the latter ones. But they need to be challenged too.

John Maynard Keynes, the economist most associated with the principles of state issuance and management of fiat money in advanced capitalist economies, said in his 1930 Treatise on Money:

- The age of chartalist or State money was reached when the State claimed the right to declare what thing should answer as money to the current money of account—when it claimed the right not only to enforce the dictionary but also to write the dictionary. Today all civilised money is, beyond possibility of dispute, chartalist.

Ninety years on, cryptocurrencies are the counterfactual to this proposition, but Keynes’ proposition about the State writing the dictionary is right. Part of cryptoeconomics is to challenge the dictionary: to open up new ways of thinking money and price.

That challenge is broad, but in this context, let us go to Keynes and Hayek. The object is quite specific: to note how certain categories that are now assumed theoretical, indeed axiomatic (the ‘dictionary’), are actually historically specific and contingent and should be challenged in the light of cryptotoken development. Moreover, within each of these significant economists, we can find the derivative dimension that is repressed in the interests of conveying a culture of theoretical certainty.

We start with Keynes.

In Chapter 17 of the General Theory he challenged his own premise and introduced the hypothetical idea that money may not be unique in its economic characteristics:

- The money-rate of interest — we may remind the reader — is nothing more than the percentage excess of a sum of money contracted for forward delivery, e.g. a year hence, over what we may call the “spot” or cash price of the sum thus contracted for forward delivery. …Thus for every durable commodity we have a rate of interest in terms of itself, — a wheat-rate of interest, a copper-rate of interest, a house-rate of interest, even a steel-plant-rate of interest.… Money is the greatest of the own-rates of interest (as we may call them) which rules the roost.

Keynes, in essence, depicts money as the greatest own interest rate because

a) it does not itself produce a use value (like say wheat or copper) and get diverted to those uses;

b) there is no issue of wastage

c) it is the most liquid asset, and

d) its quantum is managed.

Two things are interesting here. First, these criteria identified by Keynes as integral to the ‘greatness’ of (state) money do not persuasively apply today: indeed all financial derivatives have the liquidity and fungibility of state money, and cryptytokens are not constrained by nation- (or group-of-nation-) specific acceptability.

Second, Keynes uses the language now associated with derivatives to depict the rate of interest. Money is the underlying of which interest is the derivative. And for Keynes, money is axiomatically state money. Money is a put option on the state: the right to sell out of the state’s unit of account.

For Hayek, the origins of his thinking on the social and economic virtues of market processes comes from an early to mid 20th century debate with advocates of Soviet-inspired and other variants of central planning. It is known as the Socialist Calculation Debate. Hayek, following von Mises, argued that central planning, even at its best, has a range of insensitivities to detail: it can only work with highly aggregated, and outdated, data and impose these generalized decisions on individuals. The market, on the other hand, runs by processing decentralized information. It can synthesise complex forms of social and economic information into a single index, enabling economic relations to be conducted in simple and orderly processes.

It is worth quoting Hayek at some length, because what he says does indeed resonate with the capacities of a crypto economy:

- It is in this connection that what I have called the "economic calculus" proper helps us, at least by analogy, to see how this problem can be solved, and in fact is being solved, by the price system. Even the single controlling mind [the central planner], in possession of all the data for some small, self-contained economic system, would not—every time some small adjustment in the allocation of resources had to be made—go explicitly through all the relations between ends and means which might possibly be affected. It is indeed the great contribution of the pure logic of choice that it has demonstrated conclusively that even such a single mind could solve this kind of problem only by constructing and constantly using rates of equivalence (or "values," or "marginal rates of substitution"), i.e., by attaching to each kind of scarce resource a numerical index which cannot be derived from any property possessed by that particular thing, but which reflects, or in which is condensed, its significance in view of the whole means-end structure. In any small change he will have to consider only these quantitative indices (or "values") in which all the relevant information is concentrated; and, by adjusting the quantities one by one, he can appropriately rearrange his dispositions without having to solve the whole puzzle ab initio or without needing at any stage to survey it at once in all its ramifications. Fundamentally, in a system in which the knowledge of the relevant facts is dispersed among many people, prices can act to coördinate the separate actions of different people in the same way as subjective values help the individual to coördinate the parts of his plan. So price is the condensation of a multiplicity of determinations (to borrow from Althusser). The market can incorporate and process all different forms of information (create knowledge) to create spontaneous order. The most significant fact about this system is the economy of knowledge with which it operates, or how little the individual participants need to know in order to be able to take the right action. In abbreviated form, by a kind of symbol, only the most essential information is passed on, and passed on only to those concerned. It is more than a metaphor to describe the price system as a kind of machinery for registering change, or a system of telecommunications which enables individual producers to watch merely the movement of a few pointers, as an engineer might watch the hands of a few dials, in order to adjust their activities to changes of which they never know more than is reflected in the price movement.

(F.A. Hayek, ‘The Use of Knowledge in Society’, American Economic Review. XXXV, No. 4. 1945, pp. 519-30. [16])

This 1940s advocacy of ‘the market’ may stand strong as an alternative to 1940s central planning, but 70 years on the argument is and should be different. There are now ‘big data’, access to vast amounts of information to inform individual decisions, and computational capacities to process this information instantly. The ‘imperative’ to have complex variables reduced to price no longer holds. Decentralized decision making does not have to articulate simply via price formation in markets. Indeed, one potential of cryptomarkets is to challenge the use of Hayekian price as the decentralized object of calculation.

Hayek says price embodies complex information – it creates knowledge of society - and its great functionality is that it is a simple representation of that complexity. Blockchain and cryptotokens present us with other ways of processing complex information. To get to this 21st century engagement, we can frame Hayek’s analysis in the context of risk and derivatives. There are two dimensions here.

In the era of blockchain and big data, and in the language of Gilles Deleuze, we can dividuate knowledge: break it down into its underlying, determining elements (that Hayek thought were too complex to code), but without necessarily aspiring to see those elements combined so as to ontologically privilege the totalised category of ‘knowledge’ Knowledge is a synthetic asset; an assembly of information.

It follows that, in the era of derivatives, we can think of price as itself a derivative on those underlying forms of information of which price is said to be the condensate. In Hayek’s analysis of The Price System as a Mechanism for Using Knowledge ‘price’ is really the strike price on the option on a synthetic asset called ‘knowledge’. (Individuals in this framing hold out-of-the-money options where they are priced out of the market and the return on in-the-money options is what neoclassical economists call the ‘consumer or producer surplus’.)

It follows that if price is now an excessive reduction of information to a single, totalising unit of measure (‘price’), we can ask what are the key dividuated forms of information for which price represents a derivative exposure? And once we identify what they are, we can ask how are they important beyond being the ‘underlyers’ of price? How are they important in their own right as knowledge and as social indicators for decision-making?

The significance of these forays into Keynes and Hayek is profound: more so than might at first appear. For Hayek, if it is possible to deconstruct the information behind price, why is it assumed that the objective of this information is the formation of prices rather than some other unit of measure? We can open up radically different social modes of calculation.

For Keynes, if money is a derivative exposure to the state, we might ask what cryptotokens might be a derivative of? What social and economic modes of organization may be available here?

To take on this significance, we need to back up a bit: to challenge the dictionary. Price is no more than an index: it measures relative values (between products; over time). But it gets treated socially as an absolute social measure. This is central to the idea of trust in a (fiat) money system. But the absolute measure is a social construct, and it can be changed: Francs to Euros; ‘old’ British pounds to ‘new’ (decimal) pounds. The appearance of cryptocurrencies, offering potential for so many different benchmarks for valuation, makes that social construction stark.

So why is ‘price’ currently the privileged index of valuation? Why do we not use (for example) sociality (social impact) as the privileged index of valuation? Or environmental impact?

The answer, in essence, is that price is a measure that expresses the social and cultural values of a capitalist society. In using price as the privileged measure we assume that a) production for the market is valued over production for direct use (for the latter generates no price) and b) we assume that profit is embedded within price (people take things to market so as to make a profit). In a capitalist society, those priorities seem appropriate: they capture the values of that society.

So instead of allocating the generic word ‘price’ (valuation of output by means of an index) to our current (and Hayek’s preferred) index of measurement, let’s call it ‘profit price’, signalling the epistemological foundation of the index.

But cryptoeconomics provides a means to measure also in terms of post-capitalist values. It need not be presumed that ‘profit price’ is the index that best captures these values. Perhaps a ‘sociality’ index (‘sociality price’) better captures those different values, and markets could value in terms of sociality price rather than profit price. (The objective here is not to give precision to a sociality index - or indices – it is just to frame the credibility of their existence as a social alternative.)

Fanciful, many will say. Hayek would have us believe, and many passively accept, that profit price is ‘natural’ and society spontaneously gravitates to an order around the calculation of profit price. Sociality price does not exist, and it would be a complete overturning of social norms to engage it. So how do you compile a sociality index that is socially recognised and used?

Well, there is not a simple answer, but we should recognise that Hayek’s notion that price formation in markets is a spontaneous order which happens to society is simply wrong. As Karl Polanyi puts it in the context of the socialist calculation debate: markets were planned; planning wasn’t. Hayek himself highlights just how much complex and decentralized information goes into compiling price as an index. It’s about costs and market power, regulations, etc on the cost side and tastes, income, etc on the demand side. They are different for every individual, for every commodity, and at every point in time. But, and here Hayek is right in relation to current social relations, our society does, in general, bring it all together to create prices and orderly markets.

We respond that this is not a natural order, but a socially evolved one. Building an alternative sociality index, and having people value by reference to sociality price, involves a massive cultural as well as economic shift. But it is no more or less logically feasible than valuing in terms of profit price.

Cryptotokens provides us with an opportunity to experiment with a sociality index of price: indeed to develop multiple indices of valuation that reflect alternative social priorities the way that profit price reflects capitalism’s priorities. And if total income is determined by payments for contribution for sociality, we have the conditions for an alternative measure of value.

We are thinking to begin to trial this system.

To quote ECSA developers:

- Think of the token as a propositional force, a sparkle of potentiality. It is a multi-dimensional docking port that can germinate new forms of relations and value sharing. The token is an occurrence, a virtual (time) crystal expecting its transductive associated milieu. It is an instance of value capture, but only insofar as it acts, simultaneously, as a fugitive relay of anarchic shares collectively modulating and amplifying values. Conceiving of tokens as speculative pragmatic relays is a way of entertaining them as generator of collective effervescence.

(Erik Bordeleau et al at the Economic Space Agency “We don’t know yet what a token can do” [17])

(And ECSA “On Intensive self-issuance” (in MoneyLab Reader, p 232-233 [18])

But, and this is critical, what we see when we peel back some of the assumptions of both Keynes and Hayek, is that tokens have to be seen as derivatives of something. They cannot float in networks of air.

Part B: a derivative re-frame: ECSA as a Big Put

We are only working towards being able to frame what tokens are a derivative of: the evolution of cryptotokens is too rapid to tie this down in a singular way. But here is a possible perspective. The crypto economy involves shorting the established capitalist economy and its economic (and political) power structure. Those of us engaged in building (and analysing) cryptoeconomics and holding a long position on its potential. Those state regulators/commentators who decry the potential of crypto economies are using their regulatory and media power to short us.

In the words of ECSA advisor, NYU professor Robert Wosnitzer,:

- If the current system/structure of capital “shorts” the qualitative dimensions of life and society, and/or the externalized costs of production (i.e., businesses “put” the costs of, say, pollution onto society), through going “long” the current system of production and circulation, then ECSA is going long the qualitative/intangible dimensions and shorting the current system.

Said differently, a put option “puts” back the cost of the spread between the current value of something and its strike price to a counterparty in equity options, or in the case of bonds that carry a put, the right to “put” back the par value at a specific moment. This “put” option also carries the logic of securitization — that is to say, the rationale and need to securitize mortgages is due to the fact that homeowners have a “put” option that they can exercise at any time, thereby rendering the cash flows unpredictable and therefore not suitable for investment and reducing liquidity. By securitizing mortgages, the “put” option is mitigated as the risk is spread across multiple mortgages in the pool, and then tranching allows for even more precise predictability. So the “put” option has always carried some threat to the current system of capital relations, and the need for securitization arose largely to address this “threat.” Of course, the put option in mortgages has been largely reduced to interest rate sensitivities (and hence the need for strong central banking operations), whilst ignoring the real, material social contexts that often drive interest rates — unemployment, price increases by producers, health care costs, etc. etc.

And the politics is clear:

Creating “alternative” economic spaces allows the owners of tokens to own an option that could, under certain conditions, “put” back the cost of an externality to the owners of the means of production which created the externality (or injustice, if you will). It’s a long, directional play (buying a put) that is the dialectical opposition to the long, directional play of existing capital relations.

Yet there is currently no derivative product that recognises the significance of this insight, and enables it to be ‘played out’ financially, in a way that don’t express simply via the volatility of token values themselves. ADD REFERENCE TO BOB MEISTER HERE.

ECSA is currently exploring ways we might engage this logic, for example by securitizing a certain part of revenue, with the possibility of both hedging that revenue (both in quantity and currency) and also providing a liquid market tool to attract short positions on ECSA, but in a way that diverts this shorting activity from the ECSA token itself.

It must be emphasised that this is a strategy currently at the stage of exploration only, as part of engaging in a process of discovery of what cryptotokens might become. It is raised here simply to indicate the kind of exploration we feel need to emerge."



  • What is a crypto economy?

  • Whose stability? Reframing stability in the crypto economy

  • Valuation Crisis and Crypto Economy. Bringing fundamental value to economy through cryptotokens

  • Cryptoeconomics working sessions at NYU/Stern Business School