Do robots destroy jobs and cause mass unemployment?
No, they don’t!
Happy to share that our paper
“The Adjustment of Labor Markets to Robots”
has been accepted for publication in the Journal of the European Economic Association.
Here’s a little thread about it. (1/18)
It’s been a long journey – starting in Sept. 2017, when we first published this widely read @VOXEU column (the older ones on #Econtwitter might still remember).
The paper received in media attention in >25 countries.
A personal highlight was my double interview @faznet with popstar philosopher Richard David Precht, where I argued that his claim – robots cause mass unemployment – is, well, not true. /3
I won’t do the usual summary thread of methods & findings – please read the paper 😉
Instead, I'll focus on just one (potentially policy-relevant) aspect: how have German labor markets handled big transformations in the past? Maybe as a guide for the future. /4
Starting in the 1990s, robots entered German manufacturing.
This has led to displacements of tasks. Many production steps previously carried out by humans, such as the assembly of cars, were now entirely performed by robots. /5
Obviously, this has raised *many* concerns about technological unemployment
But our key finding is that firms did *not* fire those displaced workers. Instead, they retained & retrained (most of) them, and the majority ended up performing new & more complex tasks on their jobs /6
I.e., the same guy who used to bolt cars was turned into a maintenance, software, marketing… person.
Sure, firms could have fired the car screwers, and looked for young specialists to fill the new jobs. But they decided differently, and went for “firm-specific human capital” /7
Was that voluntarily? Sure, but with a twist.
We find evidence that the ret(r)aining strategy was chosen more often in regions with higher density of union members. That probably reflects some sort of deal between management and works councils... /8
Like: “Ok, we hang on to the old guys, but then you moderate your future wage demands”. This stabilized jobs for incumbents
At the end, Germany seems to have digested the rise of the robots better than the US, despite the fact that 🇩🇪 is *much* more robotized than 🇺🇸 /9
In a related paper, @DrDaronAcemoglu and Pasqual Restrepo find that robots caused severe job and wage losses in the American “hire&fire” labor market.
No such thing in 🇩🇪 - thus, the corporatist German model has apparently delivered pretty well. /10
Another positive news is what happened to the young generation in Germany in response to the robots.
Since firms mostly went for the ret(r)aining of old incumbents, this meant that fewer new factory jobs were created in the manuf sector. /11
Young entrants, thus, had to start their careers elsewhere. And they did! Mostly in business-related services at comparable starting wages.
We even find that young students, in anticipation of all the changes, responded to the “robot shock” by investing more in education. /12
The unlucky ones were those incumbents for whom the ret(r)aining strategy did not play out, possibly because they worked for relatively weak, non-robotized firms that lost market shares.
Obviously, quite massive transformations are ahead in many industries, in manuf and beyond.
No longer from robots, but from other digital technologies, and from the need to reduce carbon emissions. The concerns are similar. /14
What will happen to workers who currently produce combustion engines, or parts thereof? What will happen to small cities like Kirchheimbolanden, whose local economy depends heavily on just one firm that happens to produce Diesel turbochargers? /15
On a positive note, our robot paper raises the hope that German manuf could manage this transformation in a similar, non-disruptive fashion. But for this to work, on-the-job training and education will probably be crucial elements.
We’ll see if this works out. /17
For the time being, we’re very happy that our paper has landed in a nice journal such as #JEEA, and we hope you’ll enjoy reading it.
And remember it the next time you see headlines such as theses ones 🤖
PS: A side remark. One reason why it took almost 4y is that we tried different journals before.
My favorite response from #Referee2 was: "oh yeah, your results are really interesting and convincing, but they are specific to the German case. What can we learn from it?" 😐
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Ich beginne mit einer Analogie. Reden wir zunächst über Löhne, statt über Zinsen.
Genauso wenig wie es "den Zins" gibt, gibt es auch nicht "den Lohn". Es gibt in einer Volkswirtschaft Millionen von Löhnen, die alle von zig (mikro- und makroökonomischen) Faktoren abhängen. /2
Diese Löhne ergeben sich zunächst mal - ganz natürlich - über Angebot und Nachfrage. Aber der Staat beeinflusst diese Preisbildung auf mannigfaltige Art und Weise, zB über Mindestlöhne, Arbeitsrecht usw.
Der Staat setzt ("macht") also keine Löhne, aber er beeinflusst sie. /3
Erwartungsgemäß starke Verluste 2020 im Gastgewerbe und keine Erholung in 2021. Viele Gastro-Jobs sind also erstmal weg
Ebenso starke Verluste 2020 im Verarbeitenden Gewerbe, die sich 2021 sogar noch fortsetzen. Sorgenkind laut Studienautor Enzo Weber: die Autoindustrie /2
Welche Branchen bauen dagegen Jobs auf, so dass es insgesamt zu einem "V" kommt?
Laut IAB hängt der Wiederaufstieg an vier Branchen:
1. Bau (+26T Jobs in 2021) 2. Unternehmens-DL (+41T) 3. IKT (+48T)
"Staatsverschuldung belastet kommende Generationen" - dieses altbekannte Argument wird im Zuge der Diskussion um die Corona-Schulden auf jeden Fall kommen.
Aber es ist ökonomisch falsch und sollte deshalb aus dem politischen Raum verschwinden. Hierzu ein kurzer Thread.
Der Grund ist einfach: zu jeder Staatsschuld gehört ein Vermögenstitel.
Wenn der Staat sich verschuldet, verkauft er eine Staatsanleihe. Aber dazu gibt es halt auch einen Käufer, der sie erworben hat.
Die Schulden werden vererbt, die Vermögenstitel auch. /2
Staatsverschuldung ist also keine Lastenverschiebung *zwischen* Generationen, sondern *innerhalb* einer Generation: vom Steuerzahler (der für Zinsen aufkommen muss) an die Eigentümer der Staatsanleihen (die Zinsen kassieren).
Everybody knows that an effective strategy against #Covid_19 is to have *many* more (quick-)tests and protective FFP-face masks.
But this stuff isn’t easily available.
Two ways to get it are:
- source internationally
- produce it at home
But both are problematic. /thread
The world market for tests&masks is empty, because many countries try to buy at the same time.
Prices are soaring, which is a big problem for developing countries in urgent need of this stuff, and even efficient sourcers like 🇩🇪 hit capacity constraints. /2
That’s why many countries (incl 🇩🇪) have started to increase supply by pushing domestic production rather than just relying on imports from Asia where the comp advantage lies.
But this also proves to be damn hard. Why? Because jump-starting production from scratch isn’t easy. /3
Key question for anyone thinking about the economic consequences of #COVID19 :
For how long will the current (almost complete) shutdown of the economy have to last?
Just 1-2 months? 6 months? A year? Even longer?
Nobody knows for sure, but recent studies give some hope. /Thread
Obviously, the longer the shutdown will go on, the deeper the recession, and the harder the design of policies to insure workers and firms.
Also the acceptance in the general public will evaporate over time, because not all agree with it and are willing & able to bear the costs.
Take Germany as an example: schools are closed and are scheduled to re-open on April 19. This closure was controversial, because it keeps many adults away from work.
For now, most people seem to accept it. But this will change if the "exit day" is pushed into the gray future. /3