The output gap is a concept in simplistic Keynesian economics. It was most widely used fifty years ago. It never worked very well as a policy tool. Moreover, it has become much less relevant as the economy has moved away from concentration in automobile and steel production toward a highly diverse set of industries, with high technology as well as health care and other services particularly important.
The idea of an output gap is easy to explain. Suppose that the economy consists of a single factory. For some reason, demand for output falls. The factory will lay off workers and operate at less than full capacity. The difference between full-capacity production and actual production is the output gap.
When the concept of the output gap is applied to our nation’s data, the implicit assumption is that the economy is like a single factory, producing GDP. The capacity of the GDP factory is estimated using a trend line connecting years in which the unemployment rate is near its minimum. When GDP is below this trend line, that is said to signify an output gap.
But the economy is most certainly not a single factory. This makes the output gap an increasingly problematic calculation. Perhaps the measured output gap was a decent approximation in the 1950s, when most job losses consisted of temporary layoffs at large manufacturing firms that had accumulated too much in inventory. Once the excess inventory had been sold off, workers could be recalled to their same jobs and the output gap could be closed. In that sense, the economy operated somewhat like a single GDP factory.
In today’s economy, most job losses are permanent, due to reconfiguration of industries. Unemployed workers cannot simply be recalled to their old jobs. Instead, entrepreneurs must create new jobs, and then matches must be found between these new jobs and unemployed workers.
Each month in the United States, approximately four million jobs are destroyed and about the same number are created. When slightly more jobs are destroyed than created, the measured output gap goes up. When slightly more jobs are created than destroyed, the measured output gap goes down.
In recent years, the main challenge with job creation has been the mismatch between the skills and reliability desired by employers and the characteristics of people who are unemployed or not in the labor force. This is a much more nuanced problem than the concept of the output gap would suggest.
I recommend Nicholas Eberstadt’s recent article “Education and Men without Work”. He points out that the problem for low-skilled men in our economy is not one of demand. Instead, data on job openings show that we are
a country awash in low-skill jobs at a time when millions of men with high-school diplomas or less are out of the workforce. . .positions go unfilled because of a lack of interest by non-workers, or because of unreliable applicants who do not show up for work regularly and on time, or because applicants cannot stay sober or pass drug-screening tests.
Eberstadt would argue that the most important problem in our economy is not a generic output gap that can be treated by the Federal Reserve. Instead, it is a breakdown in families and social norms more generally as well as an education system that has not adapted to current realities.
Perhaps we should consider the economy and human flourishing as two separate measures instead of a strict linear relationship. If we think about the economy of an affluent nation-state, it is mostly the top three quintiles that define it; the bottom two quintiles come along for the ride. When it comes to human flourishing, the variation is contained in the bottom three quintiles; the top two quintiles only suffer at the angry hands of the bottom two but otherwise their flourishing is guaranteed by their economic success/standing. The middle quintile is in play in both the economic and human flourishing calculations.
I always thought the idea that the economy (or the political environment, or anything else for that matter) was being held back by the lack of human talent available was an absurd perspective.
Yes there is lots and lots of demand for low-skilled labor at wages just above and below subsistence. Yes, 75 years ago, more low skilled workers would have been OK with that. We have plenty of first person accounts of just how difficult those times could get.
The demand still must meet the supply curve.
I can guarantee you that workers further up the skills ladder have demanded more from the market too. The economy would do much better if electrical engineers would only toughen up and accept $50K per year. This is what progress looks like. People expect better.
I’ve found that econometric models that rely on some kind of latent variable, like output gaps or natural interest rates, to be very difficult. I would rather focus on observable relationships that are stable over time. Disaggregation can help with this, but it also makes like more difficult.
Talk about scapegoating.
What does “low skilled” even mean other than a slur against a significant component of the Trump base?
And why the sexist and hateful assumptions about the 7 million men out of the workforce ? According to BLS:
“Among the OCED regions listed (United States, France, Germany, Italy, Sweden, United Kingdom, and European Union), U.S. women with college degrees had the lowest labor force participation rate in 2016 compared to women with degrees from the other regions. Participation rates for both men and women without college degrees in the United States fell by at least 5.0 percentage points each during the 1996–2016 period… …
Employment rates for men with no college degree fell 4.7 percentage points, to 80.2 percent, and the rates for women with no college degree fell sharply over the same period, from 67.8 percent to 62.4 percent. This was the only decrease for women without a college degree among the OCED regions.
Among all OCED regions, prime-age participation rates for men in the United States ranked 23rd out of 33 countries in 1996, and fell to 31st in 2016. For U.S. women, the rank fell from 11th to 27th. Employment rates fared no better, with men falling from 15th to 22nd and women dropping 15 spots, from 10th to 25th.”
https://www.bls.gov/opub/mlr/2018/beyond-bls/pdf/labor-force-participation-and-employment-rates-declining-for-prime-age-men-and-women.pdf
A better documented explanation for non-participation is job polarization:
“ I argue that “job polarization,” a phenomenon that describes declining demand for middle-skill workers in response to ad- vancements in technology and globalization, has been a key contributor to the increase in nonparticipation among prime-age men. I show that if job polarization had not changed the composition of jobs in the labor market in the past two decades, 1.9 million more men would likely be employed in 2016, representing a 3.6 percent increase in overall em- ployment of prime-age men. However, the effects of job polarization are unlikely to unwind any time soon—survey evidence suggests non- participating prime-age men are unlikely to return to the labor force if current conditions hold.”
See Duden Tuzeman, KC Fed.
All the hate can’t hide the fact that in the improved Trump economy, large numbers of people are being drawn back into the workforce: https://www.bls.gov/web/empsit/cpseea38.htm
“as well as an education system that has not adapted to current realities.”
Add “and is partially responsible for” after “has not adapted”.
Robin Hanson has proposed that some of the value and reason for maintenance of the universal public education system was that it was a useful system to condition self-control in impulsive, barbaric children and make them comfortable with or at least tolerate the unnatural habits, routines, behavior patterns, and deference and submission to authority figures needed to prepare them to fit in to the requirements of the workplace in industrial-age civilization.
To which a parent of young kids in the contemporary public school system might reply, “If only!” To the extent they once served this function, for whatever reason, they seem to be actively giving up on it.
I often think that k-12 school kids would be better served by being able to transition in and out of formal schooling almost impulsively, rather than being warehoused at school under duress. Starting at the age of about 14, is my offhand year to allow this.
My best guess for why k-12 school kids are warehoused and confined and kept in custody is the producer interests associated with the k-12 schooling system, which seeks to maximize enrollment and thus revenue. Also, to keep school kids out of their parents hair while parents are working (so it’s supervised day care), and to keep the kids out of the full time 9-5 labor market.
Perhaps this guess simply reflects paranoia or cynicism on my part.
We can also recall the aphorism “This is a situation of the well-meaning but poorly informed, being led by the well-informed but poorly intentioned.”
A big problem is that students are a heterogeneous group so that it is tough to generalize about what is good for them.
Bowles and Gintis suggested that way before Robin Hanson. They even claimed it was a bad thing!
Right, I cite Hanson because he’s the most likely to be known around this sphere having mentioned it recently.
There is also Paul Willis’ “Learning to Labour: How Working Class Kids Get Working Class Jobs” which was published around the same time as “Schooling in Capitalist America.”
Willis complained about “counter-school culture”, which was a kind of reverse-psychology “induced self-sabotage” way of getting new working class workers out of – he implies – potentially higher skill workers, not by teaching them to actually be good at being working class workers, but by teaching them to hate school and thus do poorly at school, thus being good for nothing else except working class work. That’s like taking a bunch of potential lawyers and doctors, convincing themselves to hit themselves in the head with a hammer, in order to relieve the itinerant farm labor shortage crisis. Not exactly the Occam’s Razor explanation, but a clever and amusing narrative.
Today the problem is even worse, since the people we have who would be good for nothing else except working class work, aren’t taught in such a way so that they could be good at it, that is, at their only chance.
Instead of misleading potential doctors into messing up so they can only do low-skill work, we tell potentially successful low-skill workers they could be doctors if only they really tried and the man wasn’t keeping them down, which leads to counter-school and counter-work attitudes, and then they are good for neither doctoring nor low-skill work.
The working class are worth more to the top as voters and spenders than as laborers is probably the answer.
If a single mother of two gets $40,000 grand worth of beanies that is something like $20/hour, more than low wage labor. And that doesn’t count indirect benefits ($18k/kid/year spent on educating their kids that they don’t pay taxes for).
An unemployed person, if they have kids and/or are sick, can direct six figures worth of government spending a year easily. They can’t spend it on discretionary consumption, but they can spend it.
Perhaps we are being to cynical about the education system in affluent nation-states. Many of the core functions of K12 education are emergent. Secondary education serves both as a proxy for IQ and as the formal structure in which modern informal courtship occurs. Modern courtship does a much better job of matching than what was possible historically with formal courtship processes. Not only does maximum education attainment define the place where you are most likely to meet your spouse, it also defines the market size for potential mates. Dating apps may displace this function and it’s hard market size limits.
Eventually evolution wins. The unprepared American male eventually ends up in a rural cabin with a steel pipe and pile of fentanyl pills.
I am a bit surprised by our willingness to exterminate the American delusional, homophobic male. No one likes them, including me obviously. But one might consider the cost of replacement, we would have to bring in like 20 million Chinese, the more intelligent of the species.
Dunno the answer, this one is a puzzle.
One wonders what part of this situation is due to the provision of welfare benefits. Many people using various stratagems find it possible to get by without working.
They have already been rejected by natural selection. We can fake it, pretend, but that just humiliates the losers.
Like those jobs in Chain that are’t coming back, the decision was made in the past, already decided, they cannot come back, there is no path home.
Natural selection is for reproductive efficiency, not economic success. The poor are doing quite well from a Darwinian standpoint. OTOH Hillary Clinton has one offspring, so she didn’t do so well (her wealth and fame notwithstanding).
It has often seemed to me that many of those speaking of the economy still believe it is like ‘Route 66’ television show. Couple of guys roll into town and can find work for a short term without much trouble. That hasn’t happened in 50 years.
Government regulation has made it to much trouble and costly to hire stochastic labor. Even more so when that labor may leave town before you can get their final check to them. (In rolls the state labor agency to fine the employer when they can’t deliver the check even if due to the worker not being locatable).
Perhaps economists need to look at the idea of Capacity Factor used in power generation. Capacity factor is the actual ability produce divided by the full capacity (24/7 possible operation without maintenance or repair downtime). For instance, a solar plant is by its very nature at less than 50% capacity factor right off the bat since the sun doesn’t shine half the possible operation time.
Economists need to add some nuance and they could possibly develop capacity factors for various segments of the economy.
https://www.youtube.com/watch?v=w3cqkMkte2w
The Capacity Factory is exactly what Kling is arguing against:
Output-Gap = (1 – Capacity-Factor)
These metrics are useful in judging the efficiency of operations but they are just one part of a larger model and sometimes a different model has superior characteristics overall without an increase in internal efficiency. Kling’s lesson is not to lose sight of the core assumptions underlying your model; don’t focus exclusively on optimizing a specific measure that once proved useful.
The classic example, in my mind, is Fred Smith’s proposed business model for FedEx. From the perspective of anyone involved in commercial flight, a business model that ignored the Capacity Factor of airplanes (immense capital/operating costs) was doomed.
Since I’m being contrarian, I wonder if the obvious friction caused by government regulation is an emergent characteristic of any institution that grows larger than the Dunbar Number and must protect against gamification, both internal and external. Is an employee getting setup with the HR department more complicated than a small business getting setup with a large organization’s Accounts Payable department?
Federal Express: the Memphis connection [1981 article – original article at link is gone]