Tag: capital

The art of using all those small financial margins

 

One of those days when ideas flow so quickly that I can almost see smoke rising from my keyboard. So, first things first, that business plan for the EneFin project. I have just passed in review the balance sheets of four FinTech companies – PayPal, Square Inc, Fintech Group AG, and Katipult – in order to make myself an idea of what the balance sheet of EneFin should look like. Surprise! By the look of their balance sheets, there is very little Tech in those FinTech companies, and a s**tload of Fin. How do I know that? Well, when I am reading a balance sheet, I start by paying attention to assets. The account of assets is a financial expression of the economic value present in the proprietary resources of a business. In other words, the structure observable on the active side of a balance sheet informs about what’s really valuable in the given business.

Moreover, when I see a lot of value accumulated in a given category A of assets, and quite little value in category B, I gather that people in that company want to have a lot of A and care a lot less about B. Stands to reason: they have accumulated a lot of A and little B. In any balance sheet, technological assets are to be found mostly under the heading of ‘Property, plant and equipment’. Depending on the accounting practices in use with the given company, intellectual property can be kicked out of this general category, into a separate one, labelled ‘Intangible assets’.

As I dug through the balance sheets of those FinTech companies, the value of those typically technological assets is ridiculously low, way below 10% of the total capital engaged. The lion’s part of said capital is allocated in financial assets. These split into two, functionally distinct categories: customer accounts and investments. This is, by the way, that tiny little detail that I completely overlooked before, as I had been nurturing my enthusiasm for my own idea, i.e. EneFin. In FinTech, you need to process financial transactions, and in order to process them, you need to maintain the corresponding current accounts, commonly called ‘customer accounts’.

The more customers I have in my EneFin project, the more transactions I process, and, consequently, the greater is the aggregate value reported on those customer accounts. Here comes the hard conclusion that I have made as I read those balance sheets: I need to rethink the business process of EneFin under that specific angle, i.e. as the creation of and capitalisation on the customer accounts, which will accompany transactions.

The second thing I need to think about, and which I found in those balance sheets, is hedging. Besides the financial assets that back up customer accounts, FinTech companies hold large amounts of low-risk, low-yield, debt-based financial assets, like sovereign bonds. This is the kind of thing you hold in order to hedge risks that you have in other assets. Those other assets must be those financial ones engaged in customer accounts. It looks as if every $ on customer accounts needed to have at least one sibling in hedging. Once again, something to ponder in the development of my business concept.

Thus, I need to figure out the core process of EneFin, its component customer relations, and the process of starting up the whole business precisely as a process of capital accumulation in customer accounts and in hedging. This is just part of the story I need to rethink. As I read those balance sheets, I am cross-reading the corresponding statements of income. The latter show important, current expenditures on technology, for example on the development of company’s software. Still, those current expenses do not reflect in the value of proprietary assets. In other words, those expenses do not capitalize. This is the money you need to spend in order to stay in the race, but you can hardly expect any durable return on it. It is a typical example of what we, economists, use to designate as ‘sunk costs’: you can hardly live without them, and you can hardly expect to recoup them later.

Right, so I need to figure out them processes. As any living organism, I do with what I have and what I have are those balance sheets. So I go and I am having a look at grandpa PayPal’s annual report. The first thing I do when I am having a stroll at the passive side of the balance sheet is to measure equity. In a balance sheet, equity is what is really yours, out of what you think is yours, i.e. out of your assets. At PayPal, by the end of 2017, shareholders’ equity was equal to $15 994 million. In other words, each dollar earnt in terms of revenues in 2017 ($13 094 mln) needed a puff cousin of $1,22 in equity. From another point of view, that equity of $15 994 million makes 37,5% of the total assets ($40 774 mln). That 37,5% is the coefficient of financial liquidity in PayPal. As financial institutions come, 37,5% is a lot. Banks start moaning when they are legally forced to go over and above 10%; PayPal looks really well-rooted in comparison.

The next thing I do on the passive side of a balance sheet is to look for things that sort of mirror similar things on the active side. On the active side of PayPal’s balance sheet, the biggest category is ‘Funds receivable and customer accounts’: $18 242 mln out of the total $40 774 mln of assets. On the passive side, in the dark forest of liabilities, I am spotting a similar beast. It has ‘Funds payable and amounts due to customers’ written on it, and it makes $19 742 mln. In probabilistic terms, each single $1 paid in on a customer account and held on this account has a mirror in some $0,94 held in assets that PayPal labels ‘Funds receivable and customer accounts’. The remaining $0,06 from that $1 are held in other assets.

Here, I am getting into the business process. A customer opens an account with PayPal. They can do it in two ways, or rather with two distinct purposes: for making payments or for receiving payments. When a customer wants to use the PayPal account mostly to make payments – let’s call them active payers – they will take care of transferring some money to this account from some other one, like from the personal bank account, of from a credit card. This happens frequently with people who buy and pay a lot online, and want their sort of financial crown jewels well protected. They open a PayPal account, and transfer there the amount of money necessary for those payments they think they will be doing like over the month to come. Even if one of those payments is traced back by some malware, the amount at risk is the amount transferred to the PayPal account, not the money on the person’s main bank account or on their credit card. Of course, really nasty malware can also trace back the transfer from my main account to the one I have on PayPal, and can be sort of tempted to attack that main account as well. Still, it makes at least one more firewall to cheat their way through.

Other customers, which I provisionally label as passive receivers, will open and hold a PayPal account mostly for receiving payments. For example, I maintain such an account for the purposes of this blog and as an adjacent functionality to my Patreon profile. The operational distinction between active payers and passive receivers is that the former are more likely than the latter to hold significant monetary balances on their PayPal account.

Let’s see how does PayPal handle those customers. I found an interesting passage on page 132 of their last annual report: ‘We hold all customer balances, both in the U.S. and internationally, as direct claims against us which are reflected on our consolidated balance sheet as a liability classified as amounts due to customers. Certain jurisdictions where PayPal operates require us to hold eligible liquid assets, as defined by the regulators in these jurisdictions, equal to at least 100% of the aggregate amount of all customer balances. Therefore, we use the assets underlying the customer balances to meet these regulatory requirements and separately classify the assets as customer accounts in our consolidated balance sheet. We classify the assets underlying the customer balances as current based on their purpose and availability to fulfill our direct obligation under amounts due to customers’.

OK, so I can see the first choices that a FinTech company can make in that respect. The monetary balances written on customer accounts can be held either directly by the operator of the FinTech platform, or their holding can be underwritten to a third party, a bank, for example. We call it a fiduciary contract. PayPal chooses the first option, i.e. holding customer accounts directly.

What’s the difference? If you hold directly the customer balances, they are your liability vis a vis your customers. You need to figure out, then, how to allocate those balances into some assets. Once you underwrite the holding of those balances to that fiduciary institution, you have a claim on that institution. Your customers have a claim on you, and this is your liability, and you have a claim on your underwriter, and this is your asset. The balance sheet balances itself.

Another choice that I can see kind of underneath that passage is the choice of jurisdiction. See there? ‘Certain jurisdictions […] require...’. Your choice is between the jurisdictions that require, and those which just don’t. It is about flexibility in your assets. In jurisdictions, which require to mirror the balances on customer accounts with ‘eligible assets’, the ‘eligible’ part is bound to be narrowed down somehow, either in the legal rules strictly spoken, or in some guidelines, or even in adjudication. It all tells you, how you should structure your financial assets.

Now, something that is not exactly a choice, but more of an imperative: liquidity of assets as functionally connected to the liquidity of liabilities. I am referring to the last sentence in that passage above. When a customer keeps money on a payment account – such as those at PayPal – the customer can withdraw their money any minute. Hence, if you want to mirror that on the asset side of the balance sheet, you need to place that money from customer accounts, waiting in full gear all the time, in placements that allow just as swift a withdrawal.

All that makes me think about the business process of the EneFin project. The supplier of energy issues the simple contracts that make the base for the complex EneFin contract, i.e. the futures on the supply of energy, and the participatory deed, e.g. shares. Now, those simple contracts have to be combined into the complex contract, EneFin way: whoever buys the futures on energy, buys the participatory deeds attached.

Question: how is that complex contract written into the balance sheet of EneFin? Option (I): all the rights attached to the complex contract remain with the supplier of energy and EneFin just provides a digital token to be put in circulation. EneFin acts on behalf and in the name of the supplier of energy. Financially, in such case, EneFin has a bundle of conditional claims on the supplier of energy, and this is an asset endowed with conditional value.

Those claims are conditional on the behaviour of buyers (consumers of energy). As long as nobody acquires the digital token registered with EneFin, there is no claim with EneFin on the supplier of energy. Once somebody buys the thing, EneFin has a claim on the supplier of energy to transfer the rights from simple contracts (future claim on energy at fixed price + claim on the supplier’s capital) onto the buyer of the token.

This option raises a secondary question: if the complex contract is an asset with EneFin, and it has a conditionally determined value, what sort of capital should mirror that asset on the passive side of the balance sheet? A liability? A share in equity?

Option (II): all the rights attached to the complex contract are entrusted with EneFin, i.e. EneFin becomes the fiduciary (not just the agent) of the primary issuer, i.e. of the supplier of energy. In this case, the contract becomes a liability with EneFin, and we need some assets to mirror its value.

The value, this time, is not as conditional as in Option (I). As a matter of fact, it is not conditional at all. There is the plain value defined as the quantity of energy (QE) encompassed by the contract multiplied by the price of that energy in the households-oriented pricing PHE. It is like V = QE[kWh]*PHE[kWh] and this value turns up in EneFin’s balance sheet as a liability. It needs being mirrored with assets of similar liquidity.

What’s similar liquidity? In general, liquidity of capital is measured with a coefficient of turnover divided by nominal value of the deeds being traded. Logically, the lower the turnover in a given nominal value V = QE[kWh]*PHE[kWh] of contracts entrusted with EneFin, the less liquid those mirroring assets have to be. As the transactional platform warms up and as trade spirals up, liquidity should increase on the asset side. Something to ponder carefully.

how is the complex contract written into the balance sheet of EneFin

Now, I switch to the buyer side, i.e. to relations with the consumers of energy. A buyer of energy – supposedly a household – needs to open an account with EneFin in order to be able to buy complex contracts on energy. They can: a) put money on that account and use it to pay for complex contracts b) not to put money on the account and buy complex contracts with a short-term loan offered by EneFin. In case (a) they create a liability in EneFin’s balance sheet, whilst (b) creates an asset with EneFin.

In case (a), EneFin has the choice between (a)(i) directly holding the monetary balance, and (a)(ii) commission an external financial institution as fiduciary, who will hold that balance. In case (a)(i), this is a liability, with a mirroring asset to be figured out on EneFin’s own. When in (a)(ii), that asset figures itself out, as the EneFin’s liability vis a vis the owner of the account is automatically mirrored by EneFin’s claim on the underwriter who holds the corresponding monetary balance on the base of the fiduciary contract.

Kind of a similar choice appears in case (b): EneFin can (b)(i) lay out that credit from its own balance sheet, or (b)(ii) just resell a loan financed by an external institution.

How does EneFin hold the balances on customers’ accounts

These are loose thoughts, for the moment. Sort of a brainstorm with myself. I hope the storm will rain with some good ideas, soon, but now, it makes me aware of some subtle distinctions I have not been noticing so far. ‘Cause so far, I thought that EneFin would just earn money on transactional fees, and on periodical subscription fees. Now, a different landscape appears under those brainstorm clouds. There are fees for the possible fiduciary services, to be paid to EneFin by the suppliers of energy, and the fiduciary fees to be possibly paid by EneFin to the underwriting financial institution who holds the balances from customers’ accounts. There is a commission that EneFin could have on reselling credit offered by an external agent. There are all the particular rates of return on financial assets of different kinds. After all, you can have an interest even on an overnight deposit.

Intuitively, I guess that the difference between sort of profitable and really profitable, and thus between just possibly sustainable and really sustainable, in that EneFin projects, lies very much in the art of using all those small financial margins.

I am consistently delivering good, almost new science to my readers, and love doing it, and I am working on crowdfunding this activity of mine. As we talk business plans, I remind you that you can download, from the library of my blog, the business plan I prepared for my semi-scientific project Befund  (and you can access the French version as well). You can also get a free e-copy of my book ‘Capitalism and Political Power’ You can support my research by donating directly, any amount you consider appropriate, to my PayPal account. You can also consider going to my Patreon page and become my patron. If you decide so, I will be grateful for suggesting me two things that Patreon suggests me to suggest you. Firstly, what kind of reward would you expect in exchange of supporting me? Secondly, what kind of phases would you like to see in the development of my research, and of the corresponding educational tools?

 

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Traps and loopholes

 

My editorial via You Tube

I am focusing on one particular aspect of my EneFinconcept, namely on what exactly will the consumers of electricity acquire under the label of ‘participatory deeds in the supplier of energy’. For those, who have not followed my blog so far, or just haven’t followed along this particular path of my research, I am summing the thing up. In practically all the European countries I have studied, the retail sales of energy, i.e. to its final users, take place at two, very different prices. There is the retail price for households PH, much higher than the retail price for PIpracticed with big institutional consumers. The basic EneFinconcept aims at making energy accessible to households at a price just as low as or close to the PIlevel, and, in the same time, at promoting small, local suppliers of renewable energy. The basic concept is that of complex contracts, which combine a futures contract on the supplies of electricity with the acquisition of participatory deeds in the supplier of that electricity. For a given, small user who consumes QHkilowatt hours, we have QH(t+z)*PH= QH(t+z)*PI+ K(t)and K(t) = QH(t+z)*(PH– PI), where ‘t’ is the present moment in time, ‘t+z’ is a moment in the future, distant from the present by ‘z’ periods, and K(t)is investment capital supplied today, to the provider of electricity, by the means of this complex contract.

EneFin Concept

Now, the issue of those participatory deeds purchased together with the futures contracts on electricity. I am advancing step by step, just to keep an eye on details. So, I need something freely tradable, endowed with high liquidity. EneFinis supposed to be a FinTech business, and FinTech means finance, and finance means giving liquidity, i.e. movement, to the otherwise lazy and stationary capital goods. The imperative of liquid, unimpeded tradability almost automatically kicks out of the concept the non-securitized participatory deeds: cooperative shares in equity, and corporate shares in partnerships. These are tradable, indeed, but at a very slow pace. If you have cooperative shares or those in a partnership, selling them requires a whole procedure of formally expressed consent from the part of other members (in a cooperative) or partners (in a partnership). Can take months, believe me. Problems with selling those types of participatory deeds find their mirroring image in problems with buying them.

Securitized shares in a joint stock company give some hope regarding my concept: they are freely tradable and can be highly liquid if we only want them to. As the aim of the EneFinproject is to promote new suppliers of renewable energies, or the creation of new capacity in the existing suppliers, the first issuance of those complex contracts (futures on energy + capital participation) would be like an Initial Offering of corporate stock. I see an opening here, yet with some limitations. As soon as I offer my stock to a sufficiently large number of prospective buyers, my initial offering becomes an Initial Public Offering, and my stock falls under the regulations pertaining to the public exchange of corporate stock. The ‘sufficiently large number’ depends on the exact legal regime we are talking about, but is does not need to be that large. The relevant regulations of my home country, Poland, assume a public offering as soon as more than 300 buyers are being addressed. The targeted size of the customer population in the EneFinproject depends on the country of operations, but even for a really small, 1 MW local power installation, it takes certainly more than 300 (see This is how I got the first numerical column).

The thing is that in the legally understood public exchange of corporate stock I can trade only that stock. A complex contract in my line of thinking – futures on energy plus participatory deeds – would require, in such a case, to carry out two separate transactions in two separate markets: one transaction in the market of futures contracts, and another one in the public stock exchange. Maybe it is feasible, but looks sort of clumsy. Mind you, what looks clumsy when handled simultaneously can gain in gracefulness when turned into a sequence. First, I buy futures on energy, and then I present them to my provider, and they give me their corporate stock. Or another way round: first, I buy the stock of that provider, in an IPO, and then, with that stock in hand, I claim my futures on energy. That looks better. I’ll keep that avenue in mind.

Another caveat that comes together with the public exchange of corporate stock is that only licensed brokerage houses can do it. In the EneFinproject, that would mean the necessity of signing a contract with such a licensed entity. Right, if I have professional stock brokers in the game, I can entertain another option, that of offering that stock in secondary exchange, not in an IPO. A provider of energy does an ordinary IPO in the stock market, their stock comes into the system. Then, they offer the following deal: they buy their stock back and they redeem it, and they pay for it with those futures on energy. With good pricing, could be worth some further thinking.

Everything I have passed in review so far pertains to the equity of the energy provider. I might venture myself into the realm of debt, now. Customers can participate in the balance sheet of their provider via what the French call ‘the bottom part’, namely via liabilities. Along with the futures on energy, customers can acquire bonds or bills of exchange of some kind. Fixed interest rate, no headache about future profits in that energy provider, only some headache left about future liquidity. Debt has the reputation of being more disciplining for the corporate executives than equity.

F**k (spell ‘f-asterisk-asterisk-k’), my mind starts racing. I imagine a transactional platform, where customers buy futures contracts on energy, accompanied by a capital deed of their choice. I buy some kilowatt hours for my future Christmas cooking (serious business over here, in Poland, trust me), and the platform offers me choice. ‘Maybe sir would dare to have a look at those wonderful corporate shares, quite fresh, issued only two months ago, or maybe sir wants to consider choosing that basket with half corporate bonds, half government bonds inside, very solid, sir. Holds money well, sir. If sir is in a genuinely adventurous mood, sir could contemplate to mix Bitcoins with some corporate stock, peppered with a pinch of corporate options, and some futures on gold’.

Right, now I understand the deep logic of the business concept introduced by that Canadian company: Katipult. They have created a financial structure made of an investment fund, whose participatory shares are being converted into a cryptocurrency traded at their internal transactional platform. I understand, too, why they pride themselves with the number of distinct legal regimes they have adapted their scheme to. I see that I should follow the legal regime of my market very closely, in order to find traps and loopholes.

My mind keeps racing. There are three, internally structured and mutually connected sets of financial deeds: a) A set of futures contracts on energy, priced at the retail, non-household rate b) A set of capital deeds issued by the providers of energy, and c) A set of tokens, in some cryptocurrency, which can be purchased for the price of energy at the retail, household rate, and give a claim on both the energy futures and the capital deeds.

A new customer enters that transactional platform and buys a certain number of tokens. Each token can be converted, at a given exchange rate, against the futures on energy and/or the capital deeds. The customer can present the basket of tokens they are holding to any provider of energy registered with that platform, and make a choice of futures on energy and capital deeds.

I think I am progressively coming up with the core process for the EneFin project. Here, below, I am giving its first graphical representation.

EneFin Core Process First Approach

I am consistently delivering good, almost new science to my readers, and love doing it, and I am working on crowdfunding this activity of mine. As we talk business plans, I remind you that you can download, from the library of my blog, the business plan I prepared for my semi-scientific project Befund  (and you can access the French versionas well). You can also get a free e-copy of my book ‘Capitalism and Political Power’ You can support my research by donating directly, any amount you consider appropriate, to my PayPal account. You can also consider going to my Patreon pageand become my patron. If you decide so, I will be grateful for suggesting me two things that Patreon suggests me to suggest you. Firstly, what kind of reward would you expect in exchange of supporting me? Secondly, what kind of phases would you like to see in the development of my research, and of the corresponding educational tools?

Those new SUVs are visibly purchased with some capital rent

My editorial

I am collecting empirical data regarding my idea of local power systems, 100% based on renewable energies. I took a metric published by the World Bank, namely the renewable energy consumption as a percentage of total final energy consumption (see https://data.worldbank.org/indicator/EG.FEC.RNEW.ZS ). I combined it with the database I already have, built on the frame of Penn Tables 9.0 (Feenstra et al. 2015[1]). I did some preliminary rummaging in that data, notably computing the mean, national value of that indicator over years  putting it against the global, weighted average provided directly by the World Bank. Another piece of rummaging consisted in using the already existing content of my database to compute the mean national consumption of renewable energies, as an aggregate, and comparing it, as a fixed-base index, with the average national stock of fixed capital, which you can see under this link. Before I present any more applications of this ‘% of renewable energy’ metric, a little methodological explanation is due. We are talking, in the case of this precise indicator, about the final consumption of energy, not about its primary output. We are talking about the energy we use in everyday life, not about electricity produced in power plants. About 1/3rd in the global consumption of energy corresponds to transportation, which, in turn, represents mostly the fossil fuels burnt in vehicles. As you explore that dataset as provided by the World Bank, you will notice many countries, especially the developing ones and some emerging economies, who display a strongly descending share of renewables in the final consumption of energy. This is not a conspiracy from the part of oil companies: this is simply me, my neighbour, and his son-in-law buying (and driving around) a second car, or replacing a Ford Fiesta with a fancy SUV, in our respective households. This is very much what I could observe in China.

Anyway, now that I have this metric, my internal happy bulldog starts serious sniffing and digging through that data. I hypothesise that the share of renewable energies in the final consumption, or ‘%Ren’, depends essentially on the GDP per capita, in the presence of population size ‘Pop’, as a scale factor, and with a possible residual freedom in the explained variable. I take it all down to natural logarithms (much safer, tends to calm down those moody swings in my variables), and thus, mathematically, it looks like that:

ln(%Ren) = a1*ln(GDP per capita) + a2*ln(Pop) + residual

Good, and so I am waltzing. My internal happy bulldog dug out n = 4 151 valid observations in my database, and still this is not really the height of explanatory power: my coefficient of determination is just R2 = 0,326. Nothing to write home about. Anyway, the table of coefficients looks as presented below (Table 1):

Table 1

variable coefficient std. error t-statistic p-value
ln(Pop) 0,061 0,011 5,551 0,000
ln(GDP per capita) -0,795 0,018 -44,88 0,000
constant -1,399 0,103 -13,591 0,000

So far, it unfolds more or less logically. My share of renewable energy in the final consumption is negatively correlated with GDP per capita. See? What did I tell you? More bucks per head means more cars per village, and more cars per village means more fossil fuels burnt. The scale factor does not really kill: significant, but modest in its impact. Now, it is my internal curious ape who grabs the bulldog by the head and directs its nose on the constant residual: ‘Good dog, search for correlations in that residual’. The bulldog barks just by one variable: the share of labour compensation in the Gross National Income, or ‘Labsh’ in the nomenclature of Penn Tables 9.0. The residual of my first model is correlated with that variable at r = 0,3. Once again, nothing to put on Instagram, and still interesting. That would mean that labour-intensive economies tend to develop a relatively larger share of renewables in their energy consumption. Logical: as they are busy working, they don’t drive to much around. Anyway, I rephrase my model and I hypothesise that:

           ln(%Ren) = a1*ln(GDP per capita) + a2*ln(Pop) + a3*ln(Labsh) + residual

The bulldog, when called, fetches n = 3 111 observations, which, in turn, yield an R2 = 0,359. Weeeeell, maybe not a quantum leap I have here, but some modest advancement is to notice. The table of coefficients (Table 2) shows interesting outcomes of this little experimentation. The inclusion of labour-intensity in my model essentially drove crazy the residual – there is a more than 40% probability that it is different from that (– 0,096) shown – and put the scale factor of population slightly below the level of respectability in its p-value. Less than p = 0,05 is generally bad taste. The labour-intensity in itself seems to be a potent explanatory factor, with the highest coefficient of regression in the model, and rock-solid in its p-value.

Table 2

variable coefficient std. error t-statistic p-value
ln(Pop) 0,024 0,014 1,79 0,074
ln(GDP per capita) -0,773 0,019 -40,417 0,000
ln(Labsh) 1,517 0,129 11,767 0,000
constant -0,096 0,117 -0,821 0,412

My internal curious ape tries to repeat the same trick with the bulldog: ‘Fetch me some correlations in the residual’. It doesn’t work this time, though. This particular residual is small, random and, on the top of that, it is lonely. The ape does not give up, mind you. It sends the bulldog to rummage in the probability of being struck by an asteroid whilst driving around without your seat belts on, and it calls my internal austere monk: that guy who walks around with the Ockham’s razor in his pocket. Woosh! The monk swings that razor and carves two more variables out of the dataset: the stock of fixed capital available per capita, and the depth of food deficit. The more capital is there per person, the more it is likely being invested in the generation of renewable energies, and the more likely it is to make people less in need of new cars. On the other hand, the food deficit has already proven to be an interesting variable in my earlier research, and it is a measure of poverty, potentially correlated with the unfulfilled need for transportation. Still, the monk reminds gently: food deficit is reported as a non-null value only in cases when it is really present. When I include food deficit in my model, I automatically shift towards developing and emerging countries. At this point, it is prudent to split my model into two versions:

Version A, general:

  ln(%Ren) = a1*ln(GDP per capita) + a2*ln(Pop) + a3*ln(Labsh) + a4*ln(Capital stock per capita) + residual

and Version B, with food deficit, oriented on developing countries and emerging markets:

           ln(%Ren) = a1*ln(GDP per capita) + a2*ln(Pop) + a3*ln(Labsh) + a4*ln(Capital stock per capita) + a5*ln(Food deficit) + residual

The results, this time, are ambiguous. The general model brings nearly nothing in terms of general explanatory power. With n = 3 111 observations, the coefficient of determination changes at the third digit after the decimal point, and makes R2 = 0,360 now. Not really an earthquake. The capital stock per capita, or the capital-intensity of the economy, essentially gets in the way of labour intensity and wastes some of that labour. The more capital is there per capita, the lower the share of renewables in the final basket of energy consumption. Those new SUVs are visibly purchased with some capital rent. My internal monk was right to pick up that variable – it is significant – but he was dead wrong as for how it works. What do you want, austere monasticism is not a job devoid of risk. Still, the position of labour intensity in the model seems rock-solid.

Table 3

variable coefficient std. error t-statistic p-value
ln(Pop) 0,025 0,014 1,854 0,064
ln(GDP per capita) -0,618 0,061 -10,206 0,000
ln(Labsh) 1,521 0,129 11,796 0,000
ln(Capital stock per capita) -0,135 0,049 -2,772 0,006
constant 0,133 0,148 0,896 0,370

Now, I switch to the specific model, with food deficit inside, applied to the developing countries and partly to emerging markets (like early South Korea, for example). With n = 1 680 valid observations, I get R2 = 0,424 in terms of determination. Here, that Ockham’s razor has brought some change. Razors tend to, when used properly. Table 4 below shows the coefficients of regression thus obtained. The depth of food deficit works interestingly but predictably: the greater it is, the greater the share of renewables. Poor people burn less fossil fuels and can do just with some wind, water, and sun, harnessed properly. I can notice, as well, that in those relatively poor populations, their size stops mattering. With the p-value at 0.146, its impact tends towards random.

Table 4

variable coefficient std. error t-statistic p-value
ln(Pop) -0,021 0,014 -1,455 0,146
ln(Depth of the food deficit) 0,252 0,036 7,08 0,000
ln(GDP per capita) -0,395 0,068 -5,809 0,000
ln(Labsh) 1,397 0,149 9,364 0,000
ln(Capital stock per capita) -0,257 0,046 -5,539 0,000
constant -0,203 0,215 -0,942 0,346

I can feel my brain sizzling. Enough science for now.

[1] Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), “The Next Generation of the Penn World Table” American Economic Review, 105(10), 3150-3182, available for download at http://www.ggdc.net/pwt

C’est compliqué, mais gardons notre calme

Mon éditorial

J’hypothèse. Ça veut dire que je crée des classeurs pour ranger la réalité dedans. Après la revue de littérature que j’ai faite avant-hier (consultez “It warms my heart to know I am not totally insane” ), je pose l’hypothèse suivante : la création de systèmes énergétiques locaux avec 100% d’énergie renouvelable est significativement influencée par les coûts de transaction qui accompagnent la transition du capital vers de tels projets. Je sais, ça a l’air plutôt simpliste, mais il faut bien que je commence avec quelque chose. En fait, j’essaie de généraliser sur les faits présentés par Karen Wendt[1]. En termes de rangement de réalité, cette hypothèse a l’air spacieuse, comme ces sacs de marin : juste un gros sac, sans pochettes de rangement à l’intérieur, mais avec un espace respectable pour fourrer des trucs dedans et en plus, ça se porte bien sur l’épaule. Comment puis-je savoir que ça se porte bien ? Ben voilà, je peux la transporter rapidement presque n’importe où à travers les sciences sociales et je trouverai toujours un endroit pour l’accrocher. Dans le cadre des sciences économiques c’est facile comme tout, puisque les coûts de transaction sont une notion admise et même dotée d’un prix Nobel pour Oliver Williamson. En sociologie, je l’accroche pratiquement à tout ce qui concerne les structures sociales. Si je décide de naviguer la psychologie, je peux prendre ce gros sac sur un voyage à travers la psychologie évolutive et son truc de hiérarchisation.

Bon, maintenant je survole rapidement les faits. Tout d’abord, je vérifie les faits de base en ce qui concerne la consommation d’énergies renouvelables. Je prends les données de la Banque Mondiale en ce qui concerne la part d’énergie renouvelable dans la consommation totale (https://data.worldbank.org/indicator/EG.FEC.RNEW.ZS ) et je les mixe avec ma base de données que j’ai bâti sur l’ossature de Penn Tables 9.0 (Feenstra et al. 2015[2]). Ce que je calcule en premier lieu c’est comment cette part d’énergie verte a changé dans le temps. Sur mon site https://discoversocialsciences.com j’ai placé un fichier Excel correspondant, en anglais . La première chose qui frappe, c’est que ce pourcentage d’énergie en provenance de sources renouvelables avait à peine changé sur les 30 dernières années, si on le calcule comme valeur agrégée globale (donc si nous tenons compte des parts respectives de chaque pays dans le bilan énergétique global) : c’est juste monté de 17,9% en 1990 jusqu’à 18,9% en 2014. Pas vraiment un tremblement de terre. En revanche, si je calcule ce pourcentage comme moyenne arithmétique entre pays, ça fait plus et ça plonge, de 36,04% en 1990 vers 32,3% en 2014. La variance autour cette moyenne, donc la variabilité de notre indicateur, a l’air plutôt stable, si on la mesure comme le quotient de la variance par la moyenne. La médiane – donc le niveau en-dessous duquel on trouve exactement 50% des pays observés chaque année – suit une trajectoire encore différente, un peu fluctuante entre 21 et 30%.

Les changements globaux en termes de participation d’énergies vertes dans le cocktail énergétique de notre société suggèrent quelques régularités. Il y a une sorte de schéma spatial, ou les économies nationales les plus volumineuses en termes de consommation totale d’énergie – donc surtout les pays développés ainsi que ceux du BRIC – se déplacent systématiquement vers une base énergétique de plus en plus verte, pendant qu’un nombre relativement grand de pays en voie de développement ainsi que certaines économies émergentes montrent des signes d’accroître la participation d’énergie non-renouvelable dans le total. Là, une clarification s’impose. Nous parlons du pourcentage d’énergie renouvelable dans la consommation finale d’énergie et non pas dans sa génération primaire. Ce serait donc un malentendu d’interpréter ce pourcentage comme la part relative de centrales électriques vertes dans la production totale. C’est la consommation, pas la génération, et en ce qui concerne la consommation finale d’énergie il y a un facteur à ne pas négliger : la bagnole. La graaande majorité des voitures sont des bons vieux classiques à combustion interne. Plus de voitures par une centaine d’habitants veut dire plus de carburant fossile brûlé. L’une des composantes de base d’avancement social dans les pays en voie de développement et dans les économies émergentes est l’achat de plus de voitures par ménage. C’est surtout ça le secret des pays qui – suivant cet indicateur de pourcentage de renouvelables dans le total – semblent aller à rebours de ce que nous percevons comme « révolution verte ».

Si je retourne donc à mon hypothèse, je peux dire qu’à l’échelle globale, la finance, elle se decarbonise à un rythme de tout ce qu’il y a de plus respectable. Sans à-coups, mollo. Ce sont plutôt les idiosyncrasies nationales et régionales et termes de decarbonisation qui sont intéressantes. Quel rapport avec mon hypothèse de départ ? A première vue, ces coûts de transaction dont je parle, ils suivent des régularités globales plutôt qu’un schéma universel. Je la reformule, mon hypothèse :  la création de systèmes énergétiques locaux avec 100% d’énergie renouvelable est significativement influencée par les coûts de transaction qui accompagnent la transition du capital vers de tels projets et qui sont spécifiques aux économies nationales.

Bon, je continue avec cet aspect embarrassant de la science, donc avec les faits. Je transforme mon pourcentage d’énergie renouvelable en quantité absolue, en le multipliant par la consommation moyenne d’énergie par tête d’habitant, en kilogrammes d’équivalent-pétrole (consultez https://data.worldbank.org/indicator/EG.USE.PCAP.KG.OE  ). Un kilo d’équivalent-pétrole équivaut, en fait, à 11,63 kilowattheures, en fait. J’obtiens donc, pour chaque pays et chaque année dans ma base de données, la consommation totale d’énergie renouvelable en milliers de tonnes d’équivalent-pétrole. Ensuite, j’ai calculé la moyenne nationale de consommation d’énergie renouvelables pour chaque année et je l’ai mis côte à côte avec le stock moyen national de capital fixe, en millions de dollars constants 2011, aux parités courantes de pouvoir d’achat. Voilà une autre portion de faits que vous pouvez trouver dans un autre fichier Excel en anglais, sur mon site https://discoversocialsciences.com. J’ai facilité la digestion de ces faits en transformant les deux valeurs absolues en indexes, basées sur la valeur observée, dans chaque cas, en année 2000. Cette méthode, appelée indexation à base fixe, est utile lorsqu’on veut tracer, graphiquement, les tendances suivies par des variables qui ont des quantités très différentes l’une de l’autre. Si une variable dénote des valeurs absolues 10 fois plus grandes que l’autre, par exemple, le graphe peut être difficile à lire. J’indexe avec base fixe et mes deux courbes suivent le même ordre de grandeur.

Alors, comme je compare l’index de consommation nationale moyenne d’énergies renouvelables avec celui du capital fixe accumulé à l’échelle nationale, les deux montent, mais le capital monte plus vite. Cela veut dire que le stock de capital accumule plus vite que la consommation d’énergie renouvelable. A ce point-là, je peux illustrer mon train de raisonnement de façon suivante : si je pose l’hypothèse qu’il ait un lien quelconque entre la consommation d’énergie renouvelable et le stock de capital, j’imagine chaque tonne d’énergie renouvelable comme accompagnée, en quelque sorte, par une certaine quantité de capital. En absence de coûts de transaction, cette quantité de capital par tonne d’énergie verte devrait être plus ou moins constante, ou tout du moins oscillante légèrement autour d’une constante. Seulement voilà, ce ratio de capital par tonne d’équivalent-pétrole, il a une tendance clairement croissante : en 2014, il était deux fois plus grand qu’en 1990. Si un sou a le choix entre s’attacher à une tonne d’équivalent-pétrole d’énergie renouvelable ou bien s’attacher à quoi que ce soit d’autre, il choisira plutôt ce quoi que ce soit d’autre. Il y a quelque chose qui empêche ce sou d’aller de son libre gré vers les énergies renouvelables. Dans les sciences économiques, ce quelque chose qui gêne le mouvement des sous – hormis bien sûr le manque des sous – ce sont précisément les coûts de transaction.

Vous pouvez remarquer que je viens d’utiliser la logique Bayésienne : j’ai imaginé un monde parfait (à quoi tout le monde à droit) et une courbe correspondante. J’ai donc jeté ma première balle « W », en des termes originels de Thomas Bayes (Bayes, Price 1763[3]). Ensuite, je vérifie à quel point la réalité correspond à ma vision – je jette la seconde balle « O » et je regarde sa distance de la ligne établie par la balle « W ». En fait, si je regarde bien ces deux lignes que vous pouvez trouver dans ce fichier Excel , mon index de consommation d’énergies renouvelables s’éloigne de l’index de capital. Avec chaque année, les chances Bayésiennes de les voir à égalité diminuent : il y a de moins en moins de façons d’avoir un sou de capital fixe attaché avec une probabilité de 50% à une tonne d’équivalent-pétrole d’énergie renouvelable.

Bon, je sais que c’est compliqué, mais gardez votre calme. On va avancer mollo, jour après jour, jusqu’au but. A bientôt.

[1] Wendt, K., 2016, Decarbonizing Finance – Recent Developments and the Challenge Ahead, Available at SSRN: https://ssrn.com/abstract=2965677

[2] Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), “The Next Generation of the Penn World Table” American Economic Review, 105(10), 3150-3182, available for download at http://www.ggdc.net/pwt

[3] Mr. Bayes, and Mr Price. “An essay towards solving a problem in the doctrine of chances. by the late rev. mr. bayes, frs communicated by mr. price, in a letter to john canton, amfrs.” Philosophical Transactions (1683-1775) (1763): 370-418