Hartz-IV: Alternative Fakten

Es gibt zwei Arten von alternativen Fakten: solche, die frei erfunden sind, und solche, die wahr aber irreführend sind. Wie man letztere erzeugt,  zeigt der “Standard” lehrbuchmäßig in einem Artikel über die Hartz-IV-Reformen:

Die Reform wollte eigentlich erreichen, dass Langzeitarbeitslose zurück in den Arbeitsmarkt kommen. Daran ist sie gescheitert. In Deutschland gibt es deutlich mehr Menschen, die über Jahre keinen Job finden, als in Österreich. Und das, obwohl die Sozialleistungen hierzulande höher sind.

Wörtlich genommen stimmt die Aussage natürlich. Die absolute Anzahl der Langzeitarbeitslosen ist in Deutschland höher als hierzulande. Es gibt aber auch ungefähr zehnmal so viele Menschen in Deutschland wie in Österreich. Relevant ist das Verhältnis der Langzeitarbeitslosen zur Bevölkerung und wie sich dieses Verhältnis seit Einführung der Hartz-Reformen in den Jahren 2003-2005 entwickelt hat.

Hier der Anteil der Langzeitarbeitslosen an der Erwerbsbevölkerung in Deutschland im Vergleich zu Österreich während der vergangenen 14 Jahre (Quelle: Eurostat).

hartz4blog

Diese Grafik zeigt so ziemlich das Gegenteil von dem Bild, das der Standard-Artikel vermittelt. Die deutsche Langzeitarbeitslosigkeitsquote ist drastisch gesunken, während sie in Österreich leicht gestiegen ist. Im letzten Jahr lag sie in beiden Ländern ca. bei 1,8%.

Weiter unten im Artikel wird es noch ein bisschen “alternativer”:

Frage [sic!]: Aber immerhin ist die Arbeitslosigkeit stark gesunken.

Antwort: Das stimmt zwar, hat aber den meisten Fachleuten zufolge relativ wenig mit Hartz IV zu tun. Deutschland hat sich zur gleichen Zeit auch in vielen anderen Bereichen reformiert, die Löhne wurden schon Jahre zuvor kaum mehr erhöht und Unternehmen haben sich auf Märkte wie China spezialisiert, was sich als ein mehr als glücklicher Handgriff entpuppte. Außerdem sinkt die Zahl der Leute, die arbeiten wollen, weil es weniger Junge und Zuwanderer und mehr Alte gibt als in Österreich.

1. Wenn die Anzahl der Erwerbsfähigen bzw. -willigen sinkt, sinkt der Nenner der Arbeitslosenquote, wodurch die Quote ceteris paribus steigt, nicht sinkt. 2. Löhne und Exporte sind endogen. Die geringen Lohnzuwächse sind zum großen Teil eine Folge der Hartz-Reform. Schließlich hat sie dazu geführt, dass das Arbeitskräfteangebot gestiegen ist. Das geringe Lohnwachstum hat wiederum deutsche Exportgüter relativ billiger gemacht, was den Exportboom zumindest zum Teil erklärt. Die vom “Standard” angebotene Erklärung der gesunkenen Arbeitslosigkeit ist ungefähr so als würde man sagen: “Dass ein Kind im Laufe der Zeit größere Kleider braucht, liegt nicht daran, dass es älter wird, sondern größer.”

Diese Passage liefert Beispiele für eine weitere Subkategorie von “alternativen Fakten”, die dadurch entstehen, indem man einen Kausalzusammenhang zwischen zwei oder mehreren Fakten behauptet, der logisch inkohärent oder zumindest höchst fragwürdig ist.

Ich glaube, dass diese Art von irreführender Berichterstattung wesentlich schädlicher ist als die klassische Falschmeldung. Letztere wird nämlich für gewöhnlich rasch aufgedeckt und berichtigt. Die Art von “Fake News”, wie sie der “Standard”-Artikel enthält, bleibt in der Regel unwidersprochen und unberichtigt. Was hier nach seriöser, kompetenter Berichterstattung aussieht, ist letztendlich einfach nur Quatsch.

Can robots pay taxes?

Bill Gates thinks robots should pay taxes. My first reaction was: Mr Gates obviously doesn’t know much economics. If he did, he would know that things do not pay taxes. Only people do.

Robots, so I thought, are machines. They don’t have an income of their own, they don’t consume stuff. The income they help produce goes to whoever owns the robot. If I own a robot, my willingness to let it (him? her?) work for a firm increases with the robot wage rate, the amount of money I receive per hour of work done by my robot. A tax on robot wages would shift the supply curve of robot labor up (or, if you prefer, to the left), increasing for each given amount of robot labor the wage rate employers must pay to get it. The gross robot wage increases, although probably by less than the tax rate, depending on how elastic the demand for robot labor is. Assuming that the demand elasticity is not infinite, the tax burden will be split between the robot owners and the employers of robots. So the robot tax would just be another form of a capital tax, which would partly be shifted to other factors of production, including human labor. In no real sense would it „tax robots“.

Now there are good reasons to believe that we are approaching the “technological singularity“, a scenario in which robots become smarter than humans. Some experts on artificial intelligence reckon we might be only 30 years away from that. I have exactly zero qualifications to judge the plausibility of that claim, but I don’t see any obvious reason why it couldn’t happen.

Suppose the singularity does happen. Then it seems quite ridiculous to assume that humans own robots. More likely, it would be the robots who own humans. Indeed, we can only hope the super-intelligent robots would treat us a little better than we are treating less intelligent life-forms now. Let’s assume, for the sake of argument, that humans will co-exist with the super robots as equals, at least for a while. Then robots would effectively become another class of people competing with us in the market place for jobs and goods. In such a world, robots are capable of bearing a tax in the sense that they would have to cut back on their consumption (whatever it is robots consume) when faced with a tax. But even in this, admittedly unlikely, scenario, it would be the case that humans feel some of the burden of the robot tax. This is because even super-intelligent robots will react to incentives. Why, given that they are super intelligent, they should react much better to incentives than homo sapiens with all its cognitive biases. If we tax their labor, they will supply less of it, which hurts humans.

So yes, robots could pay taxes. But only if they are intelligent and powerful enough to resist being held as slaves by humans, and not as intelligent and powerful as would allow them to enslave humans. Not a very likely scenario I guess.

PS: If you are curious what AI is currently capable of doing, here is some AI-produced poetry.

 

In praise of internet ads

On my recent trip to the United States my flight got canceled. The airline didn’t give any reason for the cancelation, offered no compensation for the resulting delay. Plus, my baggage was lost on the way, probably due to the fact that I was rebooked on a different flight involving two other airlines.

A week after the incident I noticed that a particular ad appeared again and again on my Facebook feed. It simply said “Flight delayed or canceled? Find out if you are entitled to compensation. We can help you start your claim for free.” So I clicked on it, even though I’m usually very skeptical of internet ads. The site behind the link looked reputable to me. I quickly googled “AirHelp fraud” or some similar phrase to see if there are any warnings or complaints about the company, but couldn’t find any.

So I decided to trust the site, filled out a simple online form asking me some details about my flight and uploaded a copy of my ticket. Within a week, I received a message that the airline had agreed to pay me 163 dollars in compensation. AirHelp charged 40 dollars in service fees. The whole thing cost me no more than 30 minutes of my time.

Two things I took away from this story: 1) Annoying as internet ads may be, they sometimes are really useful. Had I not seen the ad, I probably wouldn’t have bothered to contact the airline at all, and if I did, I would have spent hours on the phone talking to some customer service agent in India or, worse, some lawyer. Take this as an example that advertisement can create value for consumers. 2) The internet really does change the service industry profoundly. It’s evident that companies like AirHelp increase competition for service providers, especially highly regulated ones such as lawyering. We (or I, at least) used to think such services require a lot of local, personal interaction which the internet can never substitute for. It turns out more and more that this is wrong, which is probably bad news for lawyers and other service providers. More competition is always harmful for suppliers, hence the fierce resistance against Uber and Airbnb.

PS: I did spend hours on the phone talking to some customer service agent in India about my bag – but that’s a different story.

Insider-Trading: Ein Rätsel

Das folgende Rätsel wurde inspiriert von einen Kommentar von David Friedman, den ich irgendwo (ich weiß nicht mehr wo) gelesen habe.

Es gibt drei Wertpapiere mit folgenden Renditen:

W1: 10%, W2: 5%, W3: -3%.

Auf dem Markt gibt es “Insider”, die über spezielle Informationen über diese Wertpapiere verfügen. Für das Puzzle ist es irrelevant, ob sie diese Informationen legal oder illegal bekommen haben. Sagen wir, Insider halten im Aggregat folgendes Portfolio:

W1: 10, W2: 0, W3: 0.

Alle anderen, die Nicht-Insider, halten folgendes Portfolio:

W1: 10, W2: 10, W3: 10.

Wie man leicht überprüfen kann, beträgt die Rendite von Insidern dann 10% und die Rendite von Nicht-Insidern beträgt 4%.

Wer wie viel von welchem Wertpapier hält, ist private Information. Aber jeder weiß, wie viel von welchem Weltpapier insgesamt am Markt gehandelt wird. Und zwar:

W1: 20, W2: 10, W3: 10.

Jedem Investor steht es frei das Marktportfolio zu halten – also ein Portfolio, in dem Wertpapiere 1,2 und 3 im Verhältnis 2:1:1 enthalten sind. Die Rendite dieses Portfolios beträgt 5,5%.

Das Rätsel lautet also: Wenn Insider überdurchschnittliche Renditen bekommen, müssen alle anderen unterdurchschnittliche Renditen bekommen. Aber jeder kann die durchschnittliche Rendite  bekommen, wenn er das Marktportfolio hält. Warum halten dann nicht alle Nicht-Insider einfach das Marktportfolio? Aber wenn alle Nicht-Insider das Marktportfolio halten, wie können dann die Insider überdurchschnittliche Renditen bekommen?

A New Keynesian toy model

I’ve been keeping a collection of “toy models” on my computer. I do this for two reasons. First, building them is a lot of fun and useful as a kind of intellectual work-out to develop the “model-building” regions of my brain. Second, I think they help clarify my own thinking about economic issues.

I’d like to share one of my favorite toy models with you. I learnt it from Cedric Tille when I was at the IfW Kiel. The purpose of this model is to show the basic intuition behind a strand of literature called “New Keynesian” macroeconomics. The NK approach can be thought of as a combination of the techniques of the “Real Business Cycle”  literature (rational expectations, continuous market clearing, dynamically optimizing agents) with “old” Keynesian economics (monetary policy has real effects, government spending has a multiplier effect, etc.). The model is simple enough to be taught to first-year econ students and at the same time rich enough to provide a basis for discussion of the effects of monetary policy, technology shocks, fiscal policy, the distinction between expected and unexpected shocks and more. It is also much closer to current macroeconomic research than the usual AS-AD model contained in most textbooks. The model has a natural extension to an open economy setting, which is contained in this paper by Corset & Pesenti.

Here goes.

Technology. An economy’s output (Y) is produced by labor (L) alone. The aggregate production function is

Y = A*L,                           (1)

where A is the technology parameter (labor productivity).

Households. Households consume output and supply labor. They trade off the marginal utility from consumption against the marginal disutility of working. Under usual assumptions about the shape of utility functions, consumption will be an increasing function of the real wage. Denoting the nominal wage by W and the price level by P, let household consumption (C) be given by

C = k*(W/P),                 (2)

where k is a positive parameter. The basic intuition behind this consumption function is that a higher real wage induces people to substitute consumption for leisure (substitution effect) and raises their real income (income effect). Both effects act to increase consumption, while the effect on labor supply is ambiguous.*

In order to purchase goods, households must hold money. Money demand (M) is a function of nominal consumption spending:

M = (1/v)*P*C,             (3)

where v is the (exogenous) velocity of money. Note that this is just a versions of the quantity theory of money. The money supply is set by the central bank and exogenous to the model. We will think of M as describing the stance of monetary policy.

Firms. Firms compete in a monopolistic way, i.e. each firm has a monopoly over the specific kind of consumption good it produces, but there is a large number of close substitutes. It can be shown that under this kind of competition, the aggregate price level will be set as a mark-up over marginal costs of production. Nominal marginal costs are equal to W/A — it takes 1/A hours to produce one unit of output and each hour costs W euros.

Crucially, firms must set prices before learning the labor productivity and the monetary policy stance. Hence, they must form expectations about nominal marginal costs. Let z be the mark-up, which indicates the market power of firms (which in turn depends on how “tough’’ competition is in the goods market). Then the price level is given by

P = z*E(W/A),               (4)

where E() denotes the expected value conditional on information available to firms when they set prices.

Closing the model. The model is closed by the goods market clearing condition:

Y = C.                              (5)

This is a model with five endogenous variables (Y, C, L, W, and P) and two exogenous variables (M and A). Let’s find the general equilibrium of this economy. First, combine (2) and (3) to get
W = (v/k)*M.                (6)
Taking expectations and inserting into (4) yields
P = (z*v/k)*E(M/A).               (7)
Next, combine (3), (5) and (6) to get
Y = (k/z)*M/E(M/A).              (8)
Re-inserting this into (1) yields
L = (k/z)*[M/A]/[E(M/A)].   (9)

Equilibrium. Suppose that, in the long run, expected values equal actual values, i.e. E(M/A)=M/A. This is just the rational expectations assumption which in this context means that firms don’t make persistent, systematic mistakes in forming expectations about productivity and monetary policy. With this assumption, (8) reduces to

Yn = (k/z)*A,

which we can call the natural rate of output or full-employment output. It increases in productivity and decreases in the degree of monopolistic distortions. The long-run (“natural”) level of employment is given via (9) by

Ln = k/z.

Using these results in (8) yields

Y/Yn = [M/A]/[E(M/A)].

This equation relates the ratio of actual to natural output (the output gap) to the monetary stance and the state of technology. What exactly does this mean?

  • An unexpected increase in money supply raises output over its natural level. The reason is that an increase in M while P is fixed makes households spend more which raises output and employment.
  • An unexpected increase in labor productivity reduces the output below its natural level. The reason is that a higher A increases potential output, but does nothing to stimulate household spending. Hence output stays the same while labor demand (and therefore employment) falls. So a positive technology shock produces underemployment in the short run.
  • Expected changes in monetary policy or technology have no effect on the output gap. In the long run, money is completely neutral with respect to Y and L.
  • If the central bank has a way of knowing A in advance (for instance, because they employ competent economists who can forecast A perfectly), they could set M in such a way as to completely stabilize the economy at the natural output level. They “simply” have to set M=b*A.

Fiscal policy. How do we get fiscal policy into the model? Easy. Just add government spending into the goods market clearing condition:

Y = C + G                                     (5*)

and assume for simplicity that the government makes spending proportional to total output G=g*Y. (You also must assume that the government finances its expenditure by lump-sum taxes on households only so that firms’ pricing decisions and households’ labor supply are not distorted.) In this case natural output becomes

Yn =(k/z)*A/(1-g),

which increases in g. Government spending doesn’t affect the output gap, though, because it moves actual and potential output by the same amount.

 

*) A utility function which gives rise to such a consumption function is U(C,L) = log(C) — (1/k)*L.

Österreichs Wirtschaftsgeschichte in einer Grafik

Wenn es eine Grafik gibt, die die wirtschaftliche Geschichte Österreichs kompakt zusammenfassen kann, dann diese. Sie zeigt das reale Bruttoinlandsprodukt pro Einwohner für Österreich zwischen dem Jahr 1870 und heute, logarithmisch transformiert, sodass die Steigung der Kurve als prozentuelle Wachstumsrate gelesen werden kann. Die Daten stammen aus der großartigen Madison-Datenbank. Das BIP-pro-Kopf ist kein ideales Maß für gesellschaftlichen Wohlstand und die Madison-Daten sind nicht perfekt. Dennoch gibt diese Grafik einen eindrucksvollen Einblick in unsere Geschichte.

loggdppc_aut

Diese Grafik legen folgende Einteilung nahe:

1870-1914: Die Zeit der Doppelmonarchie, in der das BIP pro Kopf ziemlich kontinuierlich mit etwa 1,5% pro Jahr wuchs und sich so innerhalb einer Generation verdoppelte.

1914-1945: Die Zeit der Weltkriege, gekennzeichnet von den drei große Krisen, nämlich der Hyperinflation, der Großen Depression und der Katastrophe des Zweiten Weltkriegs. Am Ende dieser Periode war Österreich wirtschaftlich gesehen da, wo es 1870 gestanden hatte.

1945-1975: Die Wirtschaftswunderjahre, in denen das Pro-Kopf-Einkommen um sagenhafte 6% jährlich anstieg und sich innerhalb einer Generation mehr als verfünffachte.

1975-heute: Die Zeit der “neuen Normalität’’, in der Österreichs Pro-Kopf-Einkommen weiterhin wuchs, aber mit deutlich langsameren Tempo, etwa um 2% pro Jahr.

Insgesamt hat sich während dieser ganzen Periode Österreichs BIP pro Kopf von 1.800 Dollar auf 24.000 US-Dollar (in internationalen Geary-Khamis-Dollar von 1990) gesteigert, also circa verdreizehnfacht. Das heißt, was ein durchschnittlicher Österreicher im Jahr 1870 jährlich verdient hat, verdient er heute in weniger als einem Monat! Mit dem Durchschnittseinkommen des Jahres 1870 (ungefähr 2,800 heutige Euros) würde man heute weit unter der Armutsgrenze (13.000 Euro pro Jahr) leben. Umgekehrt wäre man mit dem Durchschnittseinkommen von heute höchstwahrscheinlich unter den 1% der reichsten Österreicher im Jahr 1870.

Ich finde es lohnt sich diese Fakten im Blick zu behalten.

Castro’s Economic Legacy

The former Cuban dictator Fidel Castro has died. During his long rule from 1959 to 2006, he turned Cuba into a communist country with Soviet-style central planning, a strict one-party rule, rigorous oppression of political opponents and cruel persecution of “social deviants” (prostitutes, homosexuals, etc.). Most comments I have read about his death focus on his extravagant personality and his crimes against human rights, but completely neglect to mention his economic legacy.

And that was quite disastrous. Look at this:

bildschirmfoto-2016-11-27-um-19-51-10

In 1959, Cuba’s GDP per capita was about 2000 US dollars (in 1990 purchasing power parities), while the average of Latin American countries was about 3000 dollars. Today, the Latin American average has roughly doubled to 6000 dollars. Cuba’s is still 2000 dollars. The paper from which this graph is taken estimates that Castro’s communist experiment has reduced Cuba’s real GDP per capita by 40 percent in 1974 compared to what would have happened without the 1959 revolution.

If cold numbers are not your cup of tea, see George Borjas’ memories of growing up in Castro’s regime.