A Quantum Theory of Money and Value, Part 2: The Uncertainty Principle

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Abstract

Economic forecasting is famously unreliable. While this problem has traditionally been blamed on theories such as the efficient market hypothesis or even the butterfly effect, an alternative explanation is the role of money – something which is typically downplayed or excluded altogether from economic models. Instead, models tend to treat the economy as a kind of barter system in which money’s only role is as an inert medium of exchange. Prices are assumed to almost perfectly reflect the ‘intrinsic value’ of an asset. This paper argues, however, that money is better seen as an inherently dualistic phenomenon, which merges precise number with the fuzzy concept of value. Prices are not the optimal result of a mechanical, Newtonian process, but are an emergent property of the money system. And just as quantum physics has its uncertainty principle, so the economy is an uncertain process which can only be approximated by mathematical models. Acknowledging the dynamic and paradoxical qualities of money changes our ontological framework for economic modelling, and for making decisions under uncertainty. Applications to areas of risk analysis and economic forecasting are discussed, and it is proposed that a greater appreciation of the fundamental causes of uncertainty will help to make the economy a less uncertain place.

Posted for comments on 10 Oct 2016, 8:36 am.

Comments (4)

  • Menno Rol says:

    The article deals with an interesting theme in social ontology. It is well thought, well documented by the literature about money, well written and mature. It persuades the reader of an interesting point and could be published in this form right away. If Orrell disagrees with me with what I mention below and is of the opinion that it need not be taken in consideration, I would certainly not want to suggest that the paper were not to be published.

    I do have one comment that may perhaps be important enough for consideration to the author. He says that the contrast of Newtionian versus quantum physics ‘inspired’ him to adopt the view on money as outlined. That may well be the case, but comparing the two is somewhat far-fetched. The point is more or less (Orrell develops this point in a more sophisticated way than I do here) that in quantum mechanics objects of study are and at the same time somehow are not, or not ‘really’. But this is the case always when we deal with institutions in the way for instance John Searle developed the concept of an institution. A reference to his social ontology would be much more appropriate than to physics.

    Searle convincingly shows that institutions often start with a physical thing and then continue to exist after the thing has disappeared, if there is collective intentionality leading to some generally accepted deontic power. No governments are needed for them to exist. Bitcoins are an example of such an institution, but as the author points out, one that did not start with a physical thing – at most with the mere idea of a physical thing – and yet it matches Searle’s analysis perfectly. To my lights, it is therefore somewhat disappointing that the author does not refer at all to this work on social ontology (that became famous by the book ‘the construction of social reality’, but which, if the author happens to be unfamiliar with it, is brilliantly summarized in 22 pages in ‘What is an institution’, see:
    https://www.cambridge.org/core/journals/journal-of-institutional-economics/article/what-is-an-institution/3675101CE15BE2A7681CD5783C01F6D0).

    The article under review here would really turn more interesting if the reference to physics were to be substituted by a reference to the social ontology that philosophy already disposes of. So how well does Searle’s analysis fit in here? Beautifully, I would say. Or the analysis of critics of Searle’s ontology (like Frank Hindriks)? After all it is an exercise in social ontology.

    • David Orrell says:

      Thanks very much to the reviewer Menno Rol for taking the time to read the paper and for this useful and encouraging review, and also for suggesting the connection with the article by Searle, which I found very interesting and relevant.

      As the reviewer points out, “Searle convincingly shows that institutions often start with a physical thing and then continue to exist after the thing has disappeared, if there is collective intentionality leading to some generally accepted deontic power.” There is indeed a strong connection here with money, for example in the way that Roman money continued to be used as a unit of account in Medieval times, even after the actual coins were no longer in circulation.

      Searle compares ownership of money with possession of a queen in the game of chess. The latter “is not a matter of my having my hands on a physical object, it is rather a matter of my having certain powers of movement within a formal system … relative to other pieces. Similarly, my having a thousand dollars is not a matter of my having a wad of bills in my hand but my having certain deontic powers. I now have the right, i.e. the power, to buy things, which I would not have if I did not have the money.”

      However my aim in this paper (and the preceding one, of which this is the second part) is to show that money is a special kind of institution, and has a special kind of power, because of its association with number. In particular, because money is based on number, money objects combine properties of an object that can be owned, with numbers that are universal. These two aspects are very different, and it is this which gives money objects their fundamentally dualistic nature, as well as their unique and confounding properties.

      The special nature of money can be demonstrated by pursuing this analogy a little further. The association of money with number means that it has a unique set of rules and properties which differentiate it from a chess piece. This is why currencies used in games can quite often cross over and be used as a form of money to buy things in the real world (Castronova 2014), but chess pieces can’t.

      The reviewer notes that “in quantum mechanics objects of study are and at the same time somehow are not, or not ‘really’. But this is the case always when we deal with institutions in the way for instance John Searle developed the concept of an institution. A reference to his social ontology would be much more appropriate than to physics.” I agree that Searle’s social ontology nicely captures this idea of things existing in both a physical sense and a virtual sense. However as mentioned above the quantum analogy is broader than this real/virtual split, and is related to the properties of number, and the fact that money is treated as a fundamental quantity rather than a measure of something else. (This argument is developed in more detail in the first paper, but is only summarised briefly in the paper under review.)

      It is also part of a broader argument, which is that we have failed to absorb or understand the lessons of quantum physics, and that these lessons – including the idea of irreducible uncertainty – are relevant to fields such as economics. I therefore agree it would be good to point out the connection with Searle’s work. However I am not sure it fits well with the main text of this paper which takes the theory as stated, and explores the implications for uncertainty in economics, so perhaps a note would be more appropriate.

      Edward Castronova (2014). Wildcat Currency: How the Virtual Money Revolution Is Transforming the Economy. New Haven, Conn.: Yale University Press.

  • James Culham says:

    Although I have sympathy with many of the arguments, it seems to me that in a few cases they need more justification to avoid seeming like empty assertions. These will be presented below. Overall, however, my main concern is that it is not clear how money arises. In some cases, it seems that the author is claiming that money arises along the lines of the spontaneously most tradeable good theory (Kiyotaki & Wright, 1989); and in others, it is due to a network or legal authority effect. I suspect that this part of the theory is: not well developed; is part of the duality of money put forward here; or is more fully outlined in previous works. Whichever it is, perhaps some clarification of the author’s view on how money arises would be helpful. Especially as this may well provide more idea of why the author holds the view that cryptocurrencies are money.

    As for the need for more justifications: first, the author asserts in several places that economic models must include money, debt and the finance sector. But it is not made clear why. It is recognised, and cannot be denied, that debit and credits cancel themselves in aggregate, so why exactly do they need to be included? Yes, banks create money, but what exactly is the amplification effect that is related to this observation? How does it differ from, say, the ‘financial accelerator’ of the model of Bernanke, Gertler and Gilchrist (1999), which was developed within a moneyless DSGE framework? What is the author’s opinion of the post-GFC attempts to add a financial sector to DSGE models?

    Second, the rejection of prices directly measuring, or being derived from, utility resembles a straw man. General equilibrium models only determine relative prices from ratios of marginal utilities. They do not determine nominal prices in terms of money. The value of money is largely indeterminate without either an additional quantity theoretic or Wicksellian assumption. As such, money is often introduced or imposed as being ‘created by a trusted authority’ as the author also suggests (p. 2). The idea that the value of money, or overall price level, is an ‘emergent property’ of the system is not incompatible with relative prices determined from marginal utilities. The author’s position does not seem to be sufficiently different from the one being criticised.

    Finally, the criticism of the efficient markets hypothesis, as presented, is a victory over another straw man. The efficient markets hypothesis represents the idea that ‘security prices reflect all available information’ – a proposition that cannot be tested, but does not imply that prices always match some fundamental or intrinsic value, because of the ‘joint-hypothesis problem’ (Fama, 1991). The literature on efficient markets, rightly or wrong, has reconciled itself with a rejection of random walks and the apparent predictability of returns (see, for instance, Cochrane, 2011).

    In summary, the paper could do with some clarification on how money arises and more accurate presentations of the alternative theories being questioned.

    Bernanke, B. S., Gertler, M., & Gilchrist, S. (1999). The financial accelerator in a quantitative business cycle framework. Handbook of macroeconomics, 1, 1341-1393.
    Cochrane, J. H. (2011). Presidential address: Discount rates. The Journal of Finance, 66(4), 1047-1108.
    Fama, E. F. (1991). Efficient capital markets II. The Journal of Finance, 46(5), 1575-1617.
    Kiyotaki, N., & Wright, R. (1989). On money as a medium of exchange. The Journal of Political Economy, 97(4), 927-954.

    • David Orrell says:

      Thanks very much to the reviewer James Culham for his thoughtful comments, and for suggesting a number of useful revisions. My detailed response is below:

      Comment: “perhaps some clarification of the author’s view on how money arises would be helpful. Especially as this may well provide more idea of why the author holds the view that cryptocurrencies are money.”

      Reply: My view on how money arises was detailed in The Evolution of Money, so I will add a paragraph along the lines that, while the paper argues that price is an emergent feature, this is not to say that money itself is best seen as an emergent property. Indeed, a distinguishing feature of any form of money seems to be that it is very carefully designed. Money originated in ancient Mesopotamia as a credit system in a highly-centralised urban society run by temples. Coin money in ancient Greece was initially used by the army as a payment system and imposed on others as a means for obtaining supplies. One might argue whether cybercurrencies such as Bitcoin are a good or stable form of money, but a great deal of effort was certainly spent in designing them in such a way that they might serve as money (note that here the ‘trusted authority’ backing the currency is the computer algorithm, combined with continuous network surveillance).

      Comment: “the author asserts in several places that economic models must include money, debt and the finance sector. But it is not made clear why. It is recognised, and cannot be denied, that debit and credits cancel themselves in aggregate, so why exactly do they need to be included? Yes, banks create money, but what exactly is the amplification effect that is related to this observation? How does it differ from, say, the ‘financial accelerator’ of the model of Bernanke, Gertler and Gilchrist (1999), which was developed within a moneyless DSGE framework? What is the author’s opinion of the post-GFC attempts to add a financial sector to DSGE models?”

      Reply: On why money is important, I will clarify in section 3 that private banks act as a kind of amplifier on the system, by accelerating money creation when times are good, and deaccelerating it when times are bad. I will also add some text in section 2 to note that another effect of money and debt is to act as a sort of entanglement device. The creation of money entangles the user of the currency with the issuer, so for example users of the euro currency are affected by events in the eurozone. Most money today is created by private banks through issuing loans, which entangle the debtor and creditor so that a change in the status of one (such as bankruptcy) instantaneously affects the status of the other. Financial instruments such as derivatives create a complex web of entanglements which sits above the financial system.

      On DSGE models in section 3, I will add that some DSGE models do make steps towards including a financial sector. An early attempt was the ‘financial accelerator’ of (Bernanke, Gertler and Gilchrist,1996), which accounted for the fact that borrowing costs are inversely related to the borrower’s net worth. However, while this addressed changes in credit allocation, it did not address the issue of credit creation by banks, i.e. the new money produced by making loans. Some more recent models include this aspect, but here the greatest challenge is that ‘banks that create purchasing power can technically do so instantaneously and discontinuously, because the process does not involve physical goods, but rather the creation of money through the simultaneous expansion of both sides of banks’ balance sheets’ (Jakab and Kumhof, 2015). As discussed further below, this does not fit easily with the core idea of DSGE models, which is that the economy is inherently self-stabilising.

      The DSGE approach also ignores the entangling effects of money and debt. While debts may cancel out in a numerical sense, the power relationships they embody do not, and nor do their vulnerability to sudden and discontinuous change. These aspects were dramatically demonstrated during the crisis, when some massive firms at the center of the financial network such as AIG went bust instead of paying off their debts, and were then bailed out by the government. The nominal value of all derivatives in existence has been estimated at over a quadrillion dollars; it is unlikely that this will simply aggregate out in the next crisis (Wilmott & Orrell, 2017).

      In section 4, on the discussion of model complexity, I will also add that DSGE models do not escape this problem when a financial sector is added: ‘The existence of nonlinearities, and of evolving financial sector policies to guard against financial crises, poses some very difficult estimation issues. It is well known that the estimation of nonlinear models can require much larger sample sizes to identify functional forms and to detect the very existence of nonlinearities’ (Benes, Kumhof & Laxton, 2014).

      Comment: “the rejection of prices directly measuring, or being derived from, utility resembles a straw man. General equilibrium models only determine relative prices from ratios of marginal utilities. They do not determine nominal prices in terms of money. The value of money is largely indeterminate without either an additional quantity theoretic or Wicksellian assumption. As such, money is often introduced or imposed as being ‘created by a trusted authority’ as the author also suggests (p. 2). The idea that the value of money, or overall price level, is an ‘emergent property’ of the system is not incompatible with relative prices determined from marginal utilities. The author’s position does not seem to be sufficiently different from the one being criticised.”

      Reply: I will clarify that utility can be seen as a proportional measure only. Models assume that we can optimise utility through relative price, while my point is that there is no map between price and ‘utility’. It doesn’t make sense then to say that a particular solution of a model is ‘Pareto optimal’ in terms of utility.

      Comment: “the criticism of the efficient markets hypothesis, as presented, is a victory over another straw man. The efficient markets hypothesis represents the idea that ‘security prices reflect all available information’ – a proposition that cannot be tested, but does not imply that prices always match some fundamental or intrinsic value, because of the ‘joint-hypothesis problem’ (Fama, 1991). The literature on efficient markets, rightly or wrong, has reconciled itself with a rejection of random walks and the apparent predictability of returns (see, for instance, Cochrane, 2011).”

      Reply: I will modify this section along the folowing lines: methods such as VaR were inspired by Eugene Fama’s efficient market hypothesis, which assumed that ‘in an efficient market at any point in time the actual price of a security will be a good estimate of its intrinsic value’ (Fama, 1965, p.4). While ‘in an uncertain world the intrinsic value of a security can never be determined exactly’, it still follows that ‘the actions of the many competing participants should cause the actual price of a security to wander randomly about its intrinsic value.’ Fama later noted that due to the ‘joint-hypothesis problem’ (Fama, 1991) one can’t actually test the intrinsic value without making further hypotheses about future returns, but that didn’t detract much from the notion that the current price was the best estimate of intrinsic value.

      As a sidenote, I would argue that this description of the efficient market hypothesis, based on Fama’s original paper, is not a straw man – the hypothesis was clearly stated along these lines and was interpreted at face value by people working in quantitative finance, with very real consequences. Rather than critics distorting the central idea of a theory to make it easier to attack, I think here the problem is that for too long the theory’s defenders have been slightly altering it to make it technically more demanding to attack, instead of addressing its fundamental flaws.

      Comment: “In summary, the paper could do with some clarification on how money arises and more accurate presentations of the alternative theories being questioned.”

      Reply: These comments and references are very useful and I will make the revisions described above.

      Jaromir Benes, Michael Kumhof, and Douglas Laxton, Financial Crises in DSGE Models: A Prototype Model, IMF WP/14/57, p. 48

      Zoltan Jakab and Michael Kumhof (2015), ‘Banks are not intermediaries of loanable funds – and why this matters’, Bank of England Working Paper No. 529, May 2015.

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