Back to the Future…for lunch

September 12th, 2015 at 1:52 pm

While I’m wide open to evidence that I’m wrong, I’ve been skeptical of the claim that the robots are coming for our jobs. To be technical, the economics question is this: is the pace at which labor-saving technology is entering the workforce accelerating? I’ll explain the italics in a moment.

There are various pieces of evidence suggesting that the answer is “no.” Most importantly, if the rate at which machines are replacing workers is increasing, then productivity growth—output/hours worked—should also be increasing. But it has been slowing.

One reason for slower productivity growth is diminished investment in capital goods—like machines—a trend that also doesn’t square with the acceleration hypothesis. By some measures, the lower rate of investment accounts for two-thirds of the deceleration in productivity growth (I discuss all this productivity/investment stuff here). It’s possible that businesses are investing a lot more in robotics and a lot less in everything else, but if you drill down in the investment data, you don’t see that either.

So, what we have is largely anecdote and our own observations. I don’t discount either, but an important nuance here is that when it comes to observations, humans are good at seeing first derivatives (rates of change) and less good at seeing second derivatives (changes in rates of change). We see that iPads and self-scanners are replacing waitpersons and cashiers but it’s hard for us to tell whether “labor-saving technology” (sounds benign when you put it like that) is coming more quickly than it has in the past.

Of course, this time might really be different (some smart people say it is).

Or, as this article I read the other day reminded me (h/t: KN), this time might not be very different at all. It’s about a new quinoa restaurant in San Francisco, called Eatsa, where you order and get your food without ever interacting with a person. [You may insert a quinoa joke here; I quite like it as does my 15 y.o. daughter; OTOH, my 13 y.o. would be happy if it never darkened her plate again.] See the pic below of a happy customer getting her order, placed on an iPad, out of a cubbyhole.

Now, where have I seen that before? Fifty years ago (!), I used to love to go to Manhattan automats, where, as you see in the other pic, a few coins would get you a sandwich, a veggie (not quinoa!), a slice of delicious pie, and so on. For the record, productivity growth was faster and unemployment was lower back then (though at 10, I don’t recall knowing these facts at the time).

All’s I’m saying is that tech change is always with us, and it’s really hard to tell by observation whether the pace with which it’s replacing workers is accelerating. And there are so many more moving parts to this. I’d bet a big difference between the economies in these two pictures is where the machines were manufactured. In other words, technology doesn’t historically kill labor demand. But it does move it around to different industries, occupations, and today, countries.

So before we conclude we’re all robot fodder, let’s see it in the productivity and investment data.

Now, stop hogging all the quinoa!


Source: NYT (Eatsa)



When, oh when, might we finally get to full employment?

September 10th, 2015 at 9:31 am

[This one’s by me and Ben Spielberg]

Source: BLS, Levin, our calculations.

Source: BLS, Levin, our calculations.

Here are two facts: 1) we’ve been adding jobs at an average rate of about 220,000 a month in recent months and 2) we’re not at full employment, by which I mean a very tight matchup between the number of job seekers and the number of jobs.

So, a natural question growing out of these facts would be: when might we get to full employment, assuming we keep up the pace of payroll growth.

We answer that question in the figure above. Here’s the recipe:

First, we use Andy Levin’s total employment gap, which accounts for unemployment, the “missing workforce” (the number of people out of the labor force who’d likely come back in with stronger labor demand), and the underemployed (those working fewer hours than they’d like). That gap stands at about 3.6 million FTE’s right now (full-time-equivalents).

Second, we use the historical relationship between payrolls and FTEs to get a comparable payroll number. Since there are a bunch of part-time jobs out there, we estimate that one FTE equals about 1.08 payroll jobs. Then the miracle of long division occurs and we’re done (1.08*3.6/number of payroll jobs).

Suppose something really bad happens and the pace of job gains gets cut by half. Maybe the Fed goes nuts and doesn’t just tap the breaks but slams them. Maybe we default on the national debt, or some financial bubble implodes. That would push out the time-to-full-employment until at least Dec. 2018, which would mean about a decade of slack labor markets.

At the current pace, we’re potentially looking at the spring of 2017, and if job growth were to significantly accelerate, we could be talking about the end of next year.

Obviously, there are different ways to cut this, but this approach seems the most realistic to us because it deals with various sources of labor market slack. Were one to merely reference the unemployment rate, you’d incorrectly conclude we were already at full employment, and if you were a Fed governor, that might lead you to mistakenly raise interest rates.

Under any of these scenarios, we don’t reach full employment until at least year seven of this expansion, and more likely year eight. That, in a nutshell, is the failure of macroeconomic policy both here and abroad. How to fix it is the subject for another day, not to mention a recent book you might find useful.