One of the spots my internal bulldog keeps sniffing around is the junction of monetary systems and technological change, and one of the most interestingly smelling bones in that spot is labelled ‘cryptocurrencies and renewable energies’. There is that Estonian project called WePower and there are those loose thoughts I have been weaving for months, now, about a cryptocurrency pegged to local markets of renewable energies. I named that currency ‘The Wasun’ (see for example ‘Conversations between the dead and the living (no candles)’ or ‘Giants invisible to muggles, or a good, solid piece of research work’ ). Now, I am putting together a research project concerning the broadly spoken industry of FinTech, and one of the threads in that scientific fabric is the possible way of experimenting with the idea of cryptocurrencies connected to the market of renewable energies.
And so I imagine the most basic experimental framework for this specific case: a trading environment, designed with the Blockchain technology, and in this environment, a token of cryptocurrency equivalent to 1 kWh (kilowatt hour) of energy from renewable sources. Just for the sake of having fun with my own ideas, I return to that old name for the token: 1 Wasun = 1 kWh from renewable energies. In order to be scientifically honest, if I want that Wasun to be really well experimented about, I need its dark sibling, the antithetic shadow: 1 Fossil = 1 kWh from fossil fuels. Pushing my scientific honesty even further, I introduce one more token: 1 WTH = 1 kWh from whatever source comes the first, indiscriminately.
Now, I do what every curator in every art exhibition fears a bit: I let people in. People can buy and sell Wasuns, Fossils, or WTH. The initial price for each will be the same, i.e. the market price for one 1 kWh of electricity. The experiment has two plans: the purely economic one, involving the observation of prices and quantities, and the behavioural – anthropological one, which assumes the observation of human behaviour. We observe, how do the exchange rates of those three tokens change over time, together with the quantities issued and traded. Note: each of the three tokens can be, technically, traded against the other two, as well as against a reference currency: euro, dollar etc. At the behavioural plan, we observe the way that participants make up their mind, and the way they pass from innovative behaviour to more and more ritualized patterns.
At this stage, two versions of the experiment come to my mind: market-constrained, and unconstrained. The market-constrained experiment would involve real kilowatt hours being traded in that experimental environment. At some moment (to be defined), participants could get real electricity for their Wasuns, Fossils, or their WTH, or the equivalent of that electricity in a fiat currency. Fiat currency is a name frequently given to what we call “normal money”. Fiat comes from Latin, and means ‘benediction’. In this case, the benediction comes from a central bank. In this constrained version, participants to my experiment have relatively strong a motivation to make realistic decisions, and this is a plus. Just as in electricity, a plus has sort of a symmetrical minus, and the minus means that somebody has to pay those bills at the end. More realistic a motivation in participants equals higher costs of the experiment in the organizing entity. In the market-unconstrained version, the tokens are purely virtual: no participant earns any claim on any kilowatt hour or on its market value. It allows driving down the costs of the experiment, but takes a lot of real motivation away from the participants.
Any experiment should bring useful results. Creating and maintaining an experimental environment is an effort, which deserves a reward. When I say ‘useful’, one of the most immediate questions that pops up in my mind is ‘useful to whom?’. Who could be deriving substantial gains from well-tested solutions in this specific domain? Cryptocurrencies enter into the broad category of FinTech, and they are based on a specific technology called Blockchain. Financial institutions, and providers of FinTech digital utilities are the most obvious beneficiaries of a good, solid experiment with cryptocurrencies connected to the market of renewable energies. Still, suppliers of energy, as well as the suppliers of technologies for producing energy could have something to gain in that experiment.
An experiment should test something hard to peg down in other ways, a factor of risk, kind of uncertain in its happening, and kind of valuable in its variance. Here, really, Bob’s my uncle. The answer is simple: human behaviour is the main factor of uncertainty both in finance and in technological change, and it is a bearer of value. The most obvious experiment in that field consists in prototyping several, alternative solutions of a cryptocurrency attached to the market of renewable energies, and observing the users’ behaviour when they get the possibility of testing these solutions. The basic characteristics of such a prototype are: a) the technological platform used to convey the whole financial scheme b) the initial valuation of the cryptocurrency and the way it is supposed to change c) the essential financial function of the cryptocurrency, i.e. payment (liquidity) or accumulation d) the amount of energy, in kilowatt hours, attached to the amount of cryptocurrency issued, and, as I think about it, there would be an (e) as well, namely e) how is the given cryptocurrency being issued (mining, contract etc.) and what additional, financial services are going to be attached.
Testing uncertain things, in the prospect of making them more predictable, can always do with a set of sensible hypotheses. Looking for anything that can happen is interesting, but when you think about it, anything that can possibly happen is actually anything we think can happen, and so it is useful to phrase explicitly what we think. Formulating hypotheses is a smart way of doing it. I start hypothesising with something kind of most elementary in my view: the distinction between massive, systematic absorption of innovation, on the one hand, and the incidental absorption at the fringe of social fabric. Thus, I formulate my first experimental hypothesis as a dichotomy of two claims: the absorption of any given prototype of cryptocurrency attached to the market of renewable energies is going to be [claim #1.1] massive and dominant in the behaviour of users, so as to create a structurally stable, ritualized pattern of behaviour, or [claim #1.2, antithetic] incidental and sporadic a pattern of behaviour in users, essentially unstable as a structure. As for the connection between the frequency of happening and structural stability, you can consult what I wrote recently in ‘Fringe phenomena, which happen just sometimes’ .
That first hypothesis is something elementary regarding the absorption of any innovation whatsoever. Innovative behaviour in users is just one of the horses in the team that pulls that cryptocurrency-to-be. There is another: financial behaviour. The most elementary distinction that comes to my mind in this respect is the classical Keynesian ‘to be liquid or not to be liquid, that is the question’, or, in slightly more scientific terms, the dichotomy between liquidity and speculative accumulation. We can go and grab some cryptocurrency in order to pay with right now, or, conversely, in order to accumulate it for unspecified, future liquidity. John Maynard Keynes used to make that distinction referring to propensities in human behaviour. Whilst I find those Keynesian distinctions elegant and well-rounded, I find them hard to apply in practice. Propensity is something I can hardly pin down empirically, I mean how frequently do I have to do something in order to name it ‘propensity’? If I follow the given pattern of behaviour fifteen times out of one hundred, does it already deserve the name of ‘propensity’, or, maybe, should I add some more incidences?
That graceful indefiniteness in the Keynesian thought makes me think about something more precise in terms of theory, and so I turn to Milton Friedman and his quantitative monetary equilibrium, P*T = M*V for those somehow closer friends, where P is the current index of prices, T stands for the volume of transactions in the units of real output of the economy, M is the monetary mass supplied, and V is the velocity of said monetary mass. If people generally use money for paying, the velocity of money, measured as V = [P*T]/M, remains fairly constant. It means, in other terms, that any change in the amount of monetary mass supplied should, logically, cause a proportional change in prices. On the other hand, when money is being hoarded, and users build speculative positions with it, the velocity of money decreases. The link between the supply of money and prices weakens. My money, in this case, is the cryptocurrency I am testing, and is nominal amount, i.e. the number of tokens issued, corresponds to the M variable. The volume T is the number of kilowatt hours of renewable energy traded for those tokens, and P stands for the (average) price of one kilowatt hour.
My second, experimental hypothesis regarding that monetary side of the thing is, once again, antithetic. It says that [claim #2.1] that the freedom of issuing a cryptocurrency attached to the market of renewable energy, combined with unconstrained supply of said energy, is going to produce speculative behaviour, i.e. the hoarding of tokens and decreasing velocity in their circulation, without direct leverage upon the price of energy. I am grounding that claim, somehow intuitively, both in my own research and in the article by Dirk G. Baur, Kihoon Hong and Adrian D.Lee . Antithetically, I formulate [claim #2.2], namely that the issuance of cryptocurrencies attached to the market of renewable energies is going to produce just liquidity in users, i.e. those tokens will have constant velocity, without significant speculative positions.
You can notice that when I formulate experimental hypotheses, I do so in slightly different a manner from my normal hypothesising, i.e. I use that construct of antithetic, internally structured set of claims. This is a very intuitive approach from my part, and from the part of most human beings as a matter of fact. The habit of classifying phenomena in two antithetic categories, sometimes designated as the rule of excluded third, is very deeply rooted in our culture. The classical, Aristotelian logic is based on this pattern (you can find a lot of interesting stuff about it in the writings of my great, and defunct compatriot, Alfred Korzybski). It is just that thing about experiments: you don’t really know what kind of results they are going to bring, and, basically, the more ambitious is the scientific design of an experiment, the more surprises it produces.
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