Jonathan Swift on the Laffer Curve

But I will tell you a secret, which I learned many years ago from the commissioners of the customs in London; they said, when any commodity appeared to be taxed above a moderate rate, the consequence was, to lessen that branch of the revenue by one half; and one of those gentlemen pleasantly told me, that the mistake of parliaments, on such occasions, was owing to an errour of computing two and two to make four; whereas in the business of laying impositions, two and two never made more than one; which happens by lessening the import, and the strong temptation of running such goods as paid high duties, at least in this kingdom.

From An Answer to a Paper called a Memorial of the Poor Inhabitants, Tradesmen, and Labourers of Ireland, The Works of the Rev. Jonathan Swift, Volume 9

I found this reference in David Hume’s classic essay Of the Balance of Trade which is on the reading list of my International Economics class next Fall.

Heinz D. Kurz erhält den Kurt-Rothschild-Preis!

Wie wir soeben erfahren haben wird Prof. Heinz D. Kurz den Kurt-Rotschild-Preis 2018 erhalten. Mit diesem Preis zeichnen das Karl-Renner-Institut und der SPÖ-Parlaments-Klub besondere Verdienste im Bereich Wirtschaftspublizistik aus. In den letzten Jahren ging der Preis an Marcel Fratzscher (Deutsches Institut für Wirtschaftsforschung) und Peter Bofinger (Universität Würzburg).

Als Professor an unserer Universität hat Heinz D. Kurz Generationen von Studierenden begleitet und geprägt. Der Economics Club Graz ist stolz ihn als Mitglied führen zu dürfen. Seine aufschlussreichen und oft humorvollen Ausführungen zu den verschiedensten Theorien großer Ökonomen sind legendär – mein persönlicher Favorit: das Wildlachs-Zuchtlachs-Modell aus der Theory of Production.

Wir gratulieren herzlich!


Luis de Molina on the Quantity Theory of Money

I always thought the Quantity Theory of Money was a discovery of the 18th century Enlightenment, one of the first intellectual achievements of the new science of political economy.

However, I recently stumbled across a “Treatise on Money“ by the 16th century Jesuit theologian Luis de Molina which contains, among other economic ideas, a concise statement of the quantity theory as well as some empirical evidence for it.

Molina is best known for coming up with a clever solution to the theological problem of reconciling the omniscience of God with the free will of humans: God, Molina reasoned, knows exactly how humans would behave in any given hypothetical situation (this kind of knowledge Molina called scientia media, „middle knowledge“). In other words, God is the perfect economist: He has complete knowledge of all His creatures’ preferences, their beliefs and their cognitive biases, and therefore can predict what choices they will make freely when faced with any possible budget constraint. This idea helps solving a number of important theological problems, like the issue of predestination or the theodicy.

Anyway, Molina was not only a great theologian, but also a superb economist. For instance, he clearly understood the logic of supply and demand in determining market prices and also saw the logic of no-arbitrage conditions. And here is his explanation of differing price levels in different places:

There is another way that money may have more value in one place than in another: namely, when it is more abundant. In equal circumstances, the more abundant money is in one place so much less is its value to buy things with, or to acquire things that are not money. Just as the abundance of merchandise reduces their price when the amount of money and quantity of merchants remains invariable, so too the abundance of money makes prices rise when the amount of merchandise and number of merchants remain invariable, to the point where the same money loses purchasing power.

And here is his evidence for the theory:

So we see that, in the present day, money is worth in the Spanish territories much less than what it was worth eighty years ago, due to the abundance of it. What was bought before for two today is bought for five, or for six, or maybe for more. In the same proportion has the price of salaries risen, as well as dowries and the value of real estate, revenues, benefices, and all other things. That is exactly why we see that money is worth much less in the New World, especially in Peru, than in the Spanish territories, due to the abundance there is of it. And wherever money is less abundant than in the Spanish territories, it is worth more. Neither is it worth the same in all parts because of this reason, yet it varies according to its abundance and all other circumstances. And this value does not remain unaltered as if it were indivisible, yet fluctuates within the limits defined by the people’s estimation, the same as happens with merchandise not appraised by law. This money’s value is not the same in all parts of the Spanish territories, but different, as ordinarily it is worth less in Seville—where the ships from the New World arrive, and where for that reason there is usually abundance of it—than what it is worth in other places of the same Spanish territories.

Modern macro was invented by a Soviet economist

Here’s the story.

In 1927, a Russian economist by the name of Eugen Slutsky wrote a paper entitled “The Summation of Random Causes as the Source of Cyclic Processes“. At the time Slutsky was working for the Institute of Conjuncture in Moskow. That institute was headed by a man called Nikolai Kondratiev.

This was in the early days of the Soviet Union, before Stalin managed to turn it into a totalitarian hellhole, a time when the Communist leadership was relatively tolerant towards scientists and even occasionally listened to their advice. The institute’s job was basically to collect and analyze statistics on the Russian economy in order to help the Party with their central planning. But Kondratiev seemed to take the view that it would be best to allow the market to work, at least in the agricultural sector, and use the proceeds from agricultural exports to pay for industrialization. Lenin apparently took the advice and in 1922 launched the so-called New Economic Policy which allowed private property and markets for land and agricultural goods and re-privatized some industries which had been nationalized after the October Revolution. This policy turned out to be rather successful – at least it ended the mass starvation which War Communism had caused during the years of the Russian civil war.

But then Lenin died and Stalin took over and decided that time had come to get serious about socialism again and finally abolish private property and markets for good. Dissenting voices like Kondratiev’s clearly couldn’t be tolerated in this great enterprise, so in 1928 Kondratiev was sacked and the institute was closed down. Some time later, Kondratiev was arrested, found guilty of being a „kulak professor“ and sent off to a labor camp. Even there he continued to do research until Stalin had him killed by firing squad during the Great Purge of 1938.

But I’m digressing, so back to Slutsky. His 1927 paper was written in the wake of Kondratiev’s 1925 book “The Major Economic Cycles“. That book claimed that capitalist economies exhibit regular boom-bust waves of about 50 years duration, known today as Kondratiev Waves. Other „conjuncture” researchers had claimed the existence of shorter waves.

Slutsky’s first observation was that when you really look at time series of aggregate economic output, you don’t see regular waves, but a lot of irregular fluctuations. So trying to find deterministic, sinusoidal waves in economic time series is probably not a very fruitful exercise.

Slutsky’s second observation was that when you draw a long series of independently and identically distributed random variables (modern terminology, not his) and then take some moving average of them… you get a time series that looks an awful lot like real-world business cycles!

He showed that in two ways. First, he performed simulations. Remember this is 1927 – so how did he simulate his random numbers? Well, the People’s Commissariat of Finance ran a lottery. So Slutsky took the last digits of the numbers drawn in the lottery (this is the basic series shown in figure 1). He then computed a bunch of different moving average schemes one of which is shown in figure 2. See the boom-bust cycles in that picture? Pretty cool, huh?



But Slutsky didn’t just show cool graphs. He also had a beautiful argument for why these moving averages looked like recurrent waves:

We shall first observe a series of independent values of a random variable. If, for sake of simplicity, we assume that the distribution of probabilities does not change, then, for the entire series, there will exist a certain horizontal level such that the probabilities of obtaining a value either above or below it would be equal. The probability that a value which has just passed from the positive deviation region to the negative, will remain below at the subsequent trial is 1/2; the probability that it will remain below two times in succession is 1/4; three times 1/8; ans so on. Thus the probability that the values will remain for a long time above the level or below the level is quite negligible. It is, therefore, practically certain that, for a somewhat long series, the values will pass many times from the positive deviations to the negative and vice versa.

(For the mathematically minded, there’s also a formal proof just in case you’re wondering.)

Since it was written in Russian, the paper went unnoticed by economists in the West until it came to the attention of Henry Schultz, professor at the University of Chicago and one of the founders of the Econometric Society. He had the paper translated and published in Econometrica in 1937.

And so Slutsky’s „random causes“ provided the first stepping stone for the modern business cycle theories which explain how random shocks produce, via the intertemporal choices of households, firms and government agencies, the cyclical patterns we see in aggregate time series.

P.S.: All this time you have probably asked yourself: Slutsky, Slutsky,… that name rings a bell. Oh right, the Slutsky Equation! Yep. Same guy.