kitchen table math, the sequel: "9-minute read" - "Recovered or not"

Monday, January 11, 2016

"9-minute read" - "Recovered or not"

I've mentioned several times that I became a macro aficionado after the crash -- a macro aficionado and a Fed watcher, heaven help me.

Macro is off-topic for kitchen table math but, then again, most of us here:

a) have jobs;
b) are married to someone who has a job;
c) used to have jobs;


d) are the parents of children who have jobs, don't have jobs, or will need to get a job one day.

So: jobs.

I've just come across this "9-minute read" from Third Way, and I think it may be the best I've seen. I say that as a person who has read approximately a gazillion articles, studies, blog posts, and white papers on the subject of unemployment in the wake of the Great Recession at this point.

According to Third Way, depending on how you measure unemployment, we are either nine-tenths, two-tenths or just over halfway to a full jobs recovery.

Recovered or Not: What’s Really Happening with U.S. Unemployment?

Meanwhile the Hamilton Jobs Gap Calculator says we are still 2.5 million jobs short.

1 comment:

Anonymous said...

The jobs gap calculator, and to some extent the whole jobs discussion, seems somewhat misleading to me. True, there are lots of people looking for jobs. However, there are also lots of open jobs that remain unfilled for various reasons.

There are the unskilled, low-wage jobs that pay very little for hazardous or dirty or back-breaking work. These are jobs that *must* be done but no one really wants to do them, such as pouring hot tar on a 100-degree day or picking up other people's rotten garbage or cleaning septic tanks or digging ditches with manual tools. In my area of the country, that means either the jobs are not done, or they are done by people who can't legally get a job elsewhere.

However, there are also jobs in the tech sector going unfilled, because we can't find people who are qualified to do the work AND want to work at an enterprise software firm working on large-scale enterprise software. Top school grads (or early leavers with mad skillz) want to work at flashy startups, preferably working on something warm and fuzzy that helps solve world hunger or global warming or saves homeless kittens or something, and preferably in the SF Bay Area. At our large, unsexy enterprise firm in flyover country, a lot of the candidates we get are generally the ones who just want a programming job, any programming job really, and they're looking in our city because that's where they have family/friends/roots. (Side note: the cost-of-living ratio is about 2:1 for Bay Area:my city; housing is about 4:1. The pay ratio is only 1.3:1 or so.)

They'll have a list of projects on their resume that they supposedly worked on using Java or Node.js or Spark or HTML5, but when you start exploring their knowledge of what they put on their own resume, they can't really explain how it works or what they've done. If they're fresh out of school (we DO hire and heavily recruit people fresh out of school), they can't sufficiently explain their projects or their classes or anything, really. Or, like the candidate I interviewed last week who graduated last month, when asked about a project from the previous semester that is on his resume, "I don't remember". It's almost as if someone else wrote the resume or sat in the classes and group projects for them. Our interviewing process typically involves some tech questions, some questions about what's on the resume, and a very simple programming task or two that anyone halfway competent ought to be able to do.

This is not a new problem, either. It goes back more than ten years. Money quote: "199 out of 200 applicants for every programming job can't write code at all".

So we can see empirically that we have a gap between available positions and people qualified and/or willing to fill those positions. The premise of the jobs discussion is that we have a gap between available positions and people who want jobs, but we don't know that because we're not measuring available positions. We're only measuring, by various metrics, people who don't have jobs.