Debt crises in a monetary union: the case of Indiana

As Europeans we tend to think of America as new, young, and modern, whereas in Europe everything is old and traditional. At least that’s what I thought, until I noticed this while driving around in the American Midwest:


The license plate celebrates the 200th birthday of the State of Indiana in 2016. 200 years! This means, in a sense, Indiana is older than many of the states of the European Union. In 1816, Germany was still a patchwork of small territories, loosely connected through the German Confederation – of which Austria was a part. Italy was merely a geographical description – the process of Italian unification had not even begun. Greece was just a province of the Ottoman empire. Belgium, until 1815 known as „Austrian Netherlands“, was part of the United Kingdom of the Netherlands. France did exist as a nation then, however, while the people of Indiana lived for 200 years under the same political system and only once made marginal changes to their constitution (more about this below!), the French during the same time went from the post-Napoleonic Bourbon monarchy to the Second Republic to the Second Empire, then back to the Third Republic, then to totalitarian rule under the Nazis, and finally back to Fourth and now the Fifth Republic. As far as I am aware, there is no European country which has had the same constitution for the past 200 years without interruptions or major changes – the single exception I can think of is the United Kingdom which always had the same constitution: none.

There is another striking fact about the history of Indiana. Indiana has been in a monetary union with the rest of the United States for as long as it existed. And during its early history, it has had its own debt crisis which bears a striking resemblance to the recent history of the much younger European monetary union.

When Indiana became a State in 1816, it was mostly a wilderness at the margin of civilization. The only major road in the country was the Buffalo Trace – literally a trace created by migrating bison herds. Population was only 65,000 initially, but growing fast. The government of the young state decided to take the country’s infrastructure into the 19th century. And 19th century infrastructure, they figured, was going to be canals. So, they launched a giant public investment program, called the Mammoth Internal Improvement Act, spending 10 million dollars (equivalent to 260 million current dollars, roughly 100% of GDP at the time) on canals and toll roads. The heart of the project was the Wabash & Erie Canal connecting the Great Lakes with the Ohio River. „Crossroads of America“  was the official state motto of Indiana.

To finance these projects, the governor of Indiana, a certain Noah Noble, had a plan: some money was to be raised by selling public lands, some by raising taxes, and some by borrowing from the Bank of Indiana, which was partly state-owned. The Bank of Indiana refinanced itself by issuing bonds, backed by the state, at the London exchange.

Initially, the plan looked like a big success. The construction works employed many thousands of people and provided a stimulus for the economy. Borrowing costs were low and spirits were high. But soon, problems started to appear. It turned out that the government had greatly underestimated the costs of building the canals, mostly because they failed to take into account the damage done by muskrats who burrowed through the walls of the dams. Critical voices in the State Congress regarded the canals as a total waste of money. Railroads, they argued, were the future! Nobody seemed to listen.

And then, in 1837, a financial crisis broke out. The crisis was triggered by the Bank of England which, in an attempt to curb the outflow of gold and silver reserves, raised interest rates. This had a direct impact on Indiana whose borrowing costs skyrocketed. It also had an indirect effect: since the United States was on a gold and silver standard, American banks were forced to follow the Bank of England in raising interest rates, which led to a credit crunch and a nation-wide recession. (A classic example of a monetary policy spillover effect!)

The combination of stagnant tax revenues, exploding construction costs and rising interest rates meant that State of Indiana was effectively bankrupt at the end of 1841. So they sent the head of the Bank of Indiana to London to negotiate a restructuring of the debt. The creditors agreed to a haircut of 50% of the debt. In exchange, Indiana handed over control of most of the canals and roads, many of them still unfinished. The Wabash and Erie Canal was held in trust to pay off the remaining debt. It operated until the 1870s yielding a low profit, but was soon made obsolete by – the railroads which turned out to be the key infrastructure of the 19th century.

The conclusion Indiana drew from this was that the long-run costs of government borrowing far exceed the short-run benefits. Which is why in 1851, they adopted an amendment to their constitution, forbidding the State government to get into debt (except in cases of emergency).

I’d say there is a thing or two our modern European states can learn from this story.


On Lying, III

In my previous post I argued that a person can be kept truthful (in a repeated setting) by the threat of never believing this person again once this person has been caught lying even once. This is a strategy that, as I have pointed out in my previous post and in one comment, many proverbs suggest.

In this post I want to ask the question whether this threat is a credible one. I will have two answers to this question. Yes and no.   Continue reading

A side remark on lying: the boy who cried wolf

You probably know the story of the boy who cried wolf. A boy is charged by his elders to watch their flock of sheep and to call them as soon as he sees a wolf approaching. The wolf supposedly would want to kill one of the sheep, and the boy’s cry of “wolf” would bring the elders running to fend of the wolf to protect their sheep. In the story the boy on two occasions cries wolf when there is no wolf, with the effect that the elders come running both times and being very upset at his “lying” (and the boy pleased). But when he does cry wolf for a third time, this time when there actually is a wolf, the elders do not believe him and stay away. This, of course, has the disastrous (?) effect that the wolf kills one of the sheep.

The nappy-changing game as I have written it down in my post on lying (which you may need to read before you can read this post) can also be seen as the game between the boy and his elders. There are two states of nature. Either there is a wolf or there is not. The boy, who is watching the sheep, knows which state it is and the elders, who are somewhere else, do not. The boy has four (pure) strategies: never say anything, be honest (cry wolf when there is one, be quiet when there is none), use “opposite speak”, and always cry wolf. The elders who listen to the boy’s cry also have four (pure) strategies: always come running, trust the boy, understand the boy as if he was using opposite speak, and never come running. Supposedly, the elder’s preferences are just as mine are in the nappy-changing game. They would like to come running if there is a wolf, and they would like to keep doing whatever it is they are doing when there is no wolf. The boy’s preferences seem to be the same as Oscar’s in the nappy-changing game. If there is a wolf the boy would like to see his elders to come running to help, but the boy would like the elders to come running even when there is no wolf (he gets bored I suppose). The one slight difference between the two games seems to be that the assumed commonly known probability of a wolf appearing,  \alpha is now less than a half (if we assume that the payoffs are still just ones and zeros). Well, what matters is that the ex-ante expected payoff of coming running is lower than the ex-ante expected payoff of staying put. We infer this from the elders’ supposed actions of staying where they are when they do not believe that there is a wolf. If the elders had found a wolf attack really disastrous and at the same time sufficiently likely, then after finding the boy not trustworthy, they would have decided to come always, that is to watch out for wolves themselves. The fact that they let the boy do the watching (and to then ignore his warnings – because they do not believe him) tells us that without further information about the likelihood of the presence of a wolf, they prefer to stay where they are (probably doing something important) and risk losing one sheep to a wolf over keeping constant watch for wolves.

In any case the same model as the nappy-changing game, but now with  \alpha < \frac12 , now takes account of the supposed (long-run) behavior in this story. The game still has only two pure equilibria and they involve the boy either crying wolf in both states (or not doing so in both states), but now with the effect that the elders never come.

On Lying, II

There is a German saying about lying: “Wer einmal lügt, dem glaubt man nicht, und wenn er auch die Wahrheit spricht.” The closest corresponding idiom in English is probably this: “A liar is not believed even when he speaks the truth.” This is good enough for the moment but there is a little bit more information in the German saying than in the English one and this little bit more will become interesting in my discussion further below.
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On Lying, I

There are many forms of lying, from so called white lies that are really just a form of politeness to deliberate attempts to misrepresent the truth to fashion policy (of some institution) in your own interest. I am here interested in something somewhere in the middle of the lying spectrum, children lying about something to avoid a slightly unpleasant duty. We all know that a child’s answer to “Have you brushed your teeth?” is not always necessarily completely truthful.

In this and the next two blog posts, using the language of game theory, I want to discuss the incentives to lie and how one could perhaps teach children not to lie.

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Intro to Econ: Fourth Lecture – Market Allocations and Market Values (or Prices)

The fourth lecture begins, as usual, with a review of the key ideas of the previous lecture. I then discuss what economists call a market, market prices or, better, market values, and a market allocation. The difference between the idea of a market and bilateral trade is that bilateral trade is, well, bilateral (i.e. always between two people), whereas a market is, at least in some form, a central meeting place in which all participants interact at the same time in this one place by making offers and counteroffers to possibly many other participants. We have two options of how to deal with such a market. One is to try and capture the dynamic protocol of interaction that underlies the market place. This is difficult and probably depends on the exact market we are interested in. So we will not do this here. I also do not know of any very convincing general model of this kind, but there are some for special cases. The other option is to simply state what we think will be the likely outcome of any such market interaction. Note that what we write down next is an assumption or definition and not derived from any more basic set of assumptions.

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Why our models are models of models and what that means for the current debate about the future of macroeconomics

In the latest issue of the “Oxford Review of Economic Policy”, Simon Wren-Lewis has written an interesting contribution concerning the shortcomings of contemporary macroeconomic models. In his article, he argues that the “microfoundations hegemony” is among the core problems that hold back progress. I want to add an argument to this debate which shall support the beginning collapse of this dogma.

Historically, the idea of basing macroeconomic models on explicit microfoundations initiated in the 1970s leading to the demise of old-style Keynesian models which relied heavily on ad-hoc restrictions such as a constant aggregate savings rate. With the famous Lucas-critique declaring that ad-hoc restrictions cannot be considered invariant to changes in economic policy, a methodological standard came to dominance in the profession which demands explicit microfoundations as a pre-condition for doing proper macroeconomic modelling. The subsequent points are central to this doctrine:

I. Explicit microfoundations are needed to make models “robust” to the Lucas-critique.

II. Explicit microfoundations provide the basis for “checking” the internal consistency of the underlying thought.

III. As a pre-condition to be certain on i) and ii), the microfoundations have to be expressed using the precise language of mathematics.

Although this all seems quite convincing at first sight, the whole idea nevertheless rests on one particularly troublesome misconception of what (macro?)economic models usually represent. In the standard view, we see them as simplified representations of reality – as approximations to a complex world. “Think of it like a map! If you design a map of the Austrian highway system, you leave out irrelevant aspects like the trees guarding the highway.” – Right? Ok…, so our models are approximations! Approximations of what? Of the real world! Which looks how? Well, of course we cannot know everything in perfect detail – the reality is rather complex, but…but you know how to design proper approximations to it? How do you make proper approximations to something you do not really know because it is too complex?

In my view, the majority of (macro)economic models are indeed best seen as approximations, but as approximations of what somebody thinks about the real world rather than of the real world itself. They are formal models of the fuzzy “models” that we have in our brain – models of models, approximations of simplifications. To see this, consider the example below which you may easily find in a standard macro-paper.

“For sake of simplicity, suppose that an infinity of identical firms produce according to Y=f(K,L) with Y giving output, K denoting the capital stock and L the amount of labour.” How do we proceed on this if we read that?

a. Translate the equation Y=f(K,L) into words: “Ok, so…production uses capital and labour as inputs.”

b. Guess what the author might want to say about the real world:

  1. “So there is an infinity of firms in the model. Does he/she mean that there is an infinity of firms in the real world? – I guess not. So how many firms does he/she mean – 1000, 1 000 000?
  2. “Does he/she mean that all firms are the same in the real world? – I hope not!”
  3. Ah…“for sake of simplicity” – so the assumption was taken although he/she anyway means something else – if so…what?! Hm…
  4. “Maybe he/she means that analyzing market power of firms is not necessary for the respective purpose of the model?” – Sounds better. Or maybe, he/she means that market power is generally negligible…– whatever. I just stick to the latter interpretation.

Note that this is a pretty simplified example. In macro models you typically have various actors and feedback effects between consumers, producers, the central bank etc. If you let 10 people conduct the upper steps for such models you will usually get 10 different interpretations. To overcome this, you may introduce some form of heterogeneity in the model, try to get a slightly more realistic expression of competition and so on. You will nevertheless end up with mathematical expressions that do not correspond to what you actually want to say about people´s behavior and their respective interactions. In other fields, the difference between the formal model and the model you have in mind may be small, in macro, the gap is usually rather pronounced.

What does that imply now for the future of macroeconomics? I assume here that one is willing to follow some form of McCloskey´s view of economists as “persuaders”, i.e. we are interested in changing the fuzzy “models” in our brain or in other peoples´ brainswhile the formal ones are only tools for achieving this. It follows:

i) Explicit microfoundations may help to address the Lucas-critique, but they cannot make it immune since other people may simply not interpret the parameters of the formal microfoundations as structural. More importantly, a model that is not explicitly microfounded may be reasonably interpreted by people to be robust by adding an informal story. Both proceedings end up with an informal judgement. Explicit microfoundations are therefore neither necessary nor sufficient to address the Lucas-critique and by using them we do not overcome the final step of informal, fuzzy, subjective judgements.

ii) Since the formal model on paper and the fuzzy model in our brain are distinct, the internal consistency of the formal structure is neither necessary nor sufficient for the consistency of the underlying thought.

iii) Mathematical models are not an intrinsically precise way of communicating economic ideas. Ordinary speech may promote clarity since it describes the fuzzy models in our brains directly rather than approximating them with the often pretty rough formal elements available.

With all this, I neither want to say that we should completely depart from explicit microfoundations nor that we should abandon mathematical representations. I think both are powerful tools for bringing macroeconomics forward. There is just no reason to apply them dogmatically without thinking about whether doing so makes sense for the purpose at hand and it is certainly unjustified to impose this standard on others when judging their contributions, at least if one´s arguments in favor of this standard are based on I)-III). Finally, given that the gap between the formal and the fuzzy model is often pretty sizeable, we cannot stick to simply throwing models at each other. They can be great tools for thinking but in the end, somebody will have to give the actual argument about the source of e.g. the recent financial crisis. This necessitates using and describing the relevant parts of his/her fuzzy model that would have optimally advanced using the formal ones. And: Doing so requires fuzzy, ordinary language, not math!