Thin Air’s Money Isn’t Created Out Of Thin Air

A recurring conversation I have with clients concerns the ability of banks to create credit, and of governments to monetize debt, and whether this ability is the solution to or the cause of financial instability and economic crisis. Monetarists and structuralists (to use Michael Hudson’s names for the two sides, whose centuries-long debate pretty, exemplified by Thomas Malthus and David Ricardo during the Bullionist Controversy, dominates the history of economic thinking) have very different answers to that question, but I will suggest that each side disagrees because it implicitly assumes an idealized version of an economy.

We are normally taught that banks allocate credit by lending the money that savers have deposited in the banking system, but in fact banks create deposits in the banking system by creating credit, so it seems to many as if they can create demand out of nothing. Similarly, if governments are able to create money, and if they can borrow in their own currency, they can easily monetize debt, seemingly at no cost, by “printing” the money they need to repay the debt (actually by crediting bank accounts, which amounts to the same thing). This means that when they borrow, rather than repay by raising taxes in the future, all they have to do is monetize the debt by printing the money needed to repay the debt. It seems that governments too can create demand out of nothing, simply by deficit spending.

There is a rising consensus – correct, I think – that the misuse of these two processes – which together are, I think, what we mean by “endogenous money” – were at the heart of the debt surge that was mischaracterized as “the great Moderation”. For example in a book published earlier this month, Between Debt and the Devil, in which he provides a description of the rise of debt financing in the four decades before the 2008-09 crisis, along with the economic risks that this has created, Adair Turner specifies these two as fundamental to the rising role of finance in the global economy. He writes:

…in modern economics we have essentially two ways to produce permanent increases in nominal demand: either government fiat money creation or private credit money creation.

I am less than half-way through this very interesting book, so I am not sure how he addresses the main characteristics of debt, nor whether he is able to explain how much debt is excessive, or identify the main ways in which the liability side of the macroeconomic balance sheet intermediates behavior on the asset side to determine the growth and volatility of an economy. He invokes the work of Hyman Minsky often enough, however, to suggest that unlike traditional economists he fully recognizes the importance of debt.

And it is because of this importance that the tremendous confusion about what it means to create demand out of nothing is dangerous. When banks or governments create demand “out of this air”, either by creating bank loans, or by deficit spending, they are always doing one or some combination of two things, as I will show. In some easily specified cases they are simply transferring demand from one sector of the economy to themselves. In other equally easily specified cases they are creating demand for goods and services by simultaneously creating the production of those goods and services. They never simply create demand “out of thin air”, as many analysts seem to think, and doing so would violate the basic accounting identity that equates total savings in a closed system with total investment.

I had originally intended this blog entry to be a response to questions in some of the comments following my last blog post, but because my response turned out to be too long to submit as a comment, and because the questions lead to a far more complex answer than I had originally planned, it has become a blog entry in its own right. The questions arise in the context of a discussion of some of Steve Keen’s work among several regular commenters on my blog. Keen is an Australian post-Keynesian who heads the School of Economics, History and Politics at Kingston University in London.

I’ve known of Keen’s work for many years, and last year he spoke at my PKU seminar on central banking (as has Adair Turner, by the way). He is one of the most hard-core proponents of Hyman Minsky, and regular readers know that I think of Minsky as one of the greatest economists since Keynes. In the third chapter of my 2001 bookThe Volatility Machine, I explain the ways in which developing countries designed balance sheets that systematically exacerbated volatility – and which eventually led to debt-based contractions or financial crises – in terms of a framework that emerges from the work of Minsky and Charles Kindleberger. This framework – something that many Latin American economists have no trouble understanding but which has been ignored by nearly all Chinese and foreign economists covering China – explains why three decades of economic expansion in China, underpinned by rapid growth in credit and investment, would lead almost inevitably to destabilizing debt structures.

Hyman Minsky’s balance sheets

Minsky is important not so much for the “Minsky Moment”, a phrase he never used, but rather because of his profoundly intuitive balance-sheet oriented understanding of the economy, something that set him completely apart from most contemporary academic economists who, for the most part, have barely begun to incorporate balance sheet dynamics into their analyses. Minsky’s insights include his now-well-known description of accelerating financial fragility, along with his explanation of why instability is inherent to the financial sector in a capitalist economy.

Most insightful of all, Minsky characterized the economy as a system of interlocking balance sheets, and because he taught us to think of every economic entity as effectively a kind of bank, with one entity’s assets being another’s liabilities, it follows that economic performance is partly a function of the direction and the extent in which the two sides of each balance sheet are mismatched. Because these mismatches vary as a consequence of past conditions and future expectations, when institutional distortions are deep, balance sheet mismatches in the aggregate can be systemic, in which case they determine how an economic system behaves and responds to exogenous and endogenous shocks.

Minsky’s framework made it especially easy to predict the difficulties that China would face once it began to rebalance its economy. China can be described as an extremely muscular illustration of Minsky’s famous dictum that “stability is destabilizing”. Its financial system was designed to meet China’s early need for rapid credit expansion, and it evolved around what seemed like permanently high growth rates and uninterrupted access to financing. Two decades of “miracle” levels of investment-driven growth, the role of the financial sector in that growth, and the unrealistic expectations that Chinese businesses, banks, and government entities had consequently developed, reinforced by sell-side cheerleaders, made it obvious that the interlocking balance sheets that make up the Chinese economy had added what was effectively a highly “speculative” structure onto the way economic entities financed their operations.

This would sharply enhance growth rates during the expansion phase, much like margin borrowing enhances returns when market prices are rising faster than the debt servicing costs, but at the expense of sub-par performance once conditions reverse. The process is actually quite easy to describe, and the fact that it caught nearly the entire community of analysts by surprise should indicate just how unfamiliar economists are with the approach championed by Minsky.

Ignoring the balance sheet framework does not always result in bad economics. When debt levels are low, and the economy close to a kind of Adam Smith type of economy, in which there are no institutional constraints and no entities large or important enough to affect the system as a whole, it makes sense to ignore liabilities and to analyze an economy only from the asset side in order to understand and forecast growth. Evaluating only the asset side would still be conceptually wrong, because both sides of the balance sheet always matter, but the difference between analyses that ignore the liability side and analyses that incorporate the liability side are small enough to ignore.

When conditions change in certain ways, however, the differences can become too large to ignore. The more deeply unbalanced an economy, the higher its debt levels, or the more highly systematically distorted its balance sheets, the more the two forecasts will diverge and the more urgent it is that economists incorporate the balance sheet in their analyses.

In a way it is like an engineer who builds a bridge using Newton’s equations rather than Einstein’s. In a motionless world, or in the close approximation in which most of us live, Newtonian errors are insignificant, and the bridge the engineer builds will carry traffic almost exactly as expected. As objects accelerate, however, these small errors eventually become vast, and the Newtonian bridge risks becoming useless.

In the early 1990s the models that most economists used to analyze and explain Chinese economic growth were good enough, like the Newtonian bridge in the slow moving world in which humans operate. By the late 1990s, however, the sheer extent of bad debt within the banking system should have provided a warning that mismatches and imbalances might have become large enough to invalidate the old models. They clearly did invalidate the old models over the next few years as credit misallocation accelerated, along with the depth and direction of now-unprecedented imbalances and highly self-reinforcing price changes in commodities, real estate, stock markets, and other variables – what George Soros might have cited as extreme cases of reflexivity.

Violating identities

To get back to the discussion in the comments section, a very brisk and active debate broke out among a number of readers over Keen’s claim that next period growth is a function of both this period’s economic conditions as well as this period’s change in debt. I won’t summarize the discussion, which is long and wide ranging, but part of the disagreements have to do with whether Keen’s dynamic model, which incorporates changes in debt, implies that the accounting identities I use are somehow invalid.

One reader, Vinezi, wrote “Michael has been repeatedly saying that he is using the same identities as the basis of his research for the last 10 years. All his insights presented on this blog, which, in my opinion, are spectacularly correct, are derived from the application of these very identities”. Vinezi then goes on to ask for my response to Keen’s rejection of these identities, most importantly the identity between savings and investment.

I don’t know if Keen actually rejects the identity, but I doubt that he does because he is too good a mathematician not to know that identities cannot be “accepted” or “rejected” like hypotheses or models. More generally I would never say that I am using this (or any other) identity as the basis for my research, as Vinezi states, because the point of research is, or should be, to test hypotheses (or, in a common but sloppy practice, to discover hypotheses). You cannot “test” accounting identities, however, because they are not hypothetical. They are true either by definition or as a logical necessity (which may well be the same thing), and there is no chance that they can be wrong.

I do refer often to basic accounting identities, but mainly because too many economists and analysts allow themselves to become so confused by balance of payments arithmetic, money creation, and so on, that they try to explain the relationships among different variables by proposing hypotheses that violate accounting identities. In that case their hypotheses are simply wrong, and rejecting them does not require any empirical support. Rather than use empirical data to “test” the identities, it is more accurate to use the accounting identities to “test’ the data. If the data seems to violate the identities, then it must be the case that the data is incorrectly collected or incorrectly interpreted.

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Author: Travis Esquivel

Travis Esquivel is an engineer, passionate soccer player and full-time dad. He enjoys writing about innovation and technology from time to time.

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