What happens when a skill you have becomes obsolete? No, this isn't a R vs. Stata thread---it's a thread about a working paper w/ @sonnytambe!
https://t.co/w6nLf1tnST

The skill we look at is Adobe Flash, which @apple decided to no longer support back in 2010, which in turn caused demand/interest to plummet, as measured on @StackOverflow and in online labor markets, one of which is our empirical context
Despite the big fall-off in Flash jobs posted, very little else appeared to change in the market for Flash skills: wages for Flash jobs didn't fall, jobs didn't become easier to fill & openings weren't inundated with out-of-work Flash programmers
What happened was that (a) new entrants stopped specializing in Flash and (b) at least some existing Flash specialists started moving to other skills. In short, the demand shock quickly became a supply shock
At the level of the individual Flash worker, using a matched sample, we find (a) no fall-off in their wages, (b) some decline on-platform hours-worked. The most-focused on Flash workers had substantial increases in application intensity and a movement towards new skills
In short, despite Flash skills being expensive to acquire, workers abandoning a skill with no perceived future create a de factor highly elastic supply curve, keeping wages "flat." We show how this is possible with a little toy model, of course.
We also conduct a survey of Flash workers affected by the decline. They confirm many of our stylized facts & give color to the adjustment process. For one, they report being highly-forward looking and market-oriented & deciding what skills to pick up
They also emphasize how critical on-the-job learning is to acquiring new skills. Sadly for us teachers, formal classroom learning gets almost no love
Anyway, lots more in the paper & thanks for reading this far- check it out! https://t.co/w6nLf1tnST Comments, feedback, suggested citations (even to/esp to your own papers) most welcome!

More from Tech

Recently, the @CNIL issued a decision regarding the GDPR compliance of an unknown French adtech company named "Vectaury". It may seem like small fry, but the decision has potential wide-ranging impacts for Google, the IAB framework, and today's adtech. It's thread time! 👇

It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details):
https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha

I've read it so you needn't!

Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.

The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.

Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.

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