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

THREAD: How is it possible to train a well-performing, advanced Computer Vision model 𝗼𝗻 𝘁𝗵𝗲 𝗖𝗣𝗨? 🤔

At the heart of this lies the most important technique in modern deep learning - transfer learning.

Let's analyze how it


2/ For starters, let's look at what a neural network (NN for short) does.

An NN is like a stack of pancakes, with computation flowing up when we make predictions.

How does it all work?


3/ We show an image to our model.

An image is a collection of pixels. Each pixel is just a bunch of numbers describing its color.

Here is what it might look like for a black and white image


4/ The picture goes into the layer at the bottom.

Each layer performs computation on the image, transforming it and passing it upwards.


5/ By the time the image reaches the uppermost layer, it has been transformed to the point that it now consists of two numbers only.

The outputs of a layer are called activations, and the outputs of the last layer have a special meaning... they are the predictions!
Next.js has taken the web dev world by storm

It’s the @reactjs framework devs rave about praising its power, flexibility, and dev experience

Don't feel like you're missing out!

Here's everything you need to know in 10 tweets

Let’s dive in 🧵


Next.js is a @reactjs framework from @vercel

It couples a great dev experience with an opinionated feature set to make it easy to spin up new performant, dynamic web apps

It's used by many high-profile teams like @hulu, @apple, @Nike, & more

https://t.co/whCdm5ytuk


@vercel @hulu @Apple @Nike The team at @vercel, formerly Zeit, originally and launched v1 of the framework on Oct 26, 2016 in the pursuit of universal JavaScript apps

Since then, the team & community has grown expotentially, including contributions from giants like @Google

https://t.co/xPPTOtHoKW


@vercel @hulu @Apple @Nike @Google In the #jamstack world, Next.js pulled a hefty 58.6% share of framework adoption in 2020

Compared to other popular @reactjs frameworks like Gatsby, which pulled in 12%

*The Next.js stats likely include some SSR, arguably not Jamstack

https://t.co/acNawfcM4z


@vercel @hulu @Apple @Nike @Google The easiest way to get started with a new Next.js app is with Create Next App

Simply run:

yarn create next-app

or

npx create-next-app

You can even start from a git-based template with the -e flag

yarn create next-app -e https://t.co/JMQ87gi1ue

https://t.co/rwKhp7zlys

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The first likely historical reference to Ethiopia is ancient Egyptian records of trade expeditions to the "Land of Punt" in search of gold, ebony, ivory, incense, and wild animals, starting in c 2500 BC 🇪🇹


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References to the Queen of Sheba are everywhere in Ethiopia. The national airline's frequent flier miles are even called "ShebaMiles". 🇪🇹