Can “education as signaling” models explain recent changes in labor markets?

Acemoglu and Autor present a few non-controversial stylized facts about labor markets, including falling wages of low-skill workers, flattening of the wage premium for workers with less education than college completion, non-monotone shifts in inequality, polarization of employment in advanced economies, and skill-replacing technologies (and don’t forget the new Brynjolfsson and MacAfee book; it is important).

The simplest model is that, because of information technology, employers demand more skills.  The job market responds accordingly, and eventually the education system responds too.  The major shifts are driven by changing productivities of human capital, and that is one reason why the human capital model of labor markets has proven so robust.  It accounts (mostly) for the big changes in labor market returns.

What would a signalling model predict as the results of skill-biased technical change?  I am never sure.  Those models are tricky with comparative statics predictions for at least three reasons:

1. Multiple equilibria are common and arguably essential,

2. It is assumed that employers cannot in the short run (medium run?) observe the marginal products of workers, and

3. The (supposed) relevant factor for employers, the degree, is past history and, if not quite carved in stone, credentialed retraining remains the exception in many market segments.   It hardly drives wage outcomes or observed changes in wages.

The simplest (non-signaling) model is that wages follow MP, albeit with some lag, and adjusting for a suitably sophisticated notion of marginal revenue product, including morale effects on other workers.

Again, how should skill-based technical change matter in a signaling model?  In the model, no employer observes (across what time horizon?) that the MPs of some workers have gone up and that other workers’ MPs have gone down.  Yet it seems that changing MPs matter at margins.  And if employers can sniff out changing MPs, this implies they can sniff out large MP differences more generally, which limits the scope of educational signaling.

It is a strong result these days that occupation and also job tasks predict earnings better than before (see pp.26-27 in the first link), including relative to level of education.  That also seems to run counter to what signaling theories predict.  Most likely we are now better at measuring the quality of workers and their educational signals don’t matter as much as they used to.  The higher returns to post-secondary education, which account for most of the recent growth in the returns to college degrees (p.145 and thereabouts), are skill-based and they are tightly connected to occupation and job tasks.

These are all reasons why the signaling model for education is not growing in popularity, namely that  it does not speak well to current comparative statics and to the current big stories in labor markets.

It is an embarrassing question for signaling models to ask: with what lag do employers get a good estimate of a worker’s marginal product?  If you say “it takes 37 years” it is hard to account for all the recent changes in wage rates in response to technology, as discussed above.

Alternatively, let’s say the lag is two years.  There are several RCT estimates of the return to education, based on earnings profiles measured over twenty or thirty year periods.  The estimated returns to education are high, and if those returns were just signaling-based you would expect the IV-elevated individuals to show up as underskilled and for the credentials-based wage gains to fall away with a few years’ time.  That doesn’t happen (if you are wondering, the IV-elevated individuals are those who for essentially random reasons end up getting more education, or an instrumental variable proxies as such, without the elevation being correlated with their underlying quality as workers,).

In other words, the signaling model is caught between two core results — high long-term measured returns to the education of IV-elevated individuals, and technology drives wage changes in the medium-term.  It is hard for a signaling model to explain both of those changes at the same time.

There is a way to nest signaling models within human capital models, rather than viewing them as competing hypotheses.  Using matching theories, let’s say employers learn the quality of workers they have, but find it hard to estimate the quality of workers they don’t have.  IV-elevated workers can’t fool the market/the employer for very long, and so their high pecuniary returns from education really do measure productivity gains.  Nonetheless there can be undervalued “diamonds in the rough.”  Think of them as geniuses, or at least good workers, who hate getting the education.

From the point of view of these students (or dropouts, as the case may be), the signaling model will appear to be true.  They will resent the education and they won’t need the education.  If it is costly enough to sample worker quality from the “outsiders bin,” it will remain an equilibrium that a degree is required to get the job, at least provided workers of this kind are not too numerous.  If there were “lots and lots” of such workers, more employers would scrounge around in the outsider’s bin.  In other words, the anecdotal evidence for signaling fits into a broader model precisely because such cases aren’t too common.


'It is assumed that employers cannot in the short run (medium run?) observe the marginal products of workers
This, more than any single sentence, sums up the reality that the U.S. no longer actually sees itself as a society that makes things.

Marginal product need not have anything to do with physical, "makeable" products.

No, but it's a lot easier to measure.

Even in a company that "makes things," many of the workers won't be making the things. Ford spends more money on advertising than it does on direct labor. What's the marginal product of the assistant video editor of a Ford ad?

Sounds pretty darn convoluted.

He loves hyper-meta-analyses.

But if there were piles of data making it easy to separate the inputs from the outputs we'd have fixed it already. We collectively argue as a nation (which is amazing in itself) over standardized testing for kids less than 10 (which is also amazing) which is the easiest thing in the world and still manage to get it wrong.

It's a little bit like talking about all the places that nukes weren't to prove they must have been in Iraq.

Personally, I just thought it was funny when some showed up in Syria and were promptly blown to smithereens by Israel.

Ah, good times.

See Altonji and Pierret (2001) for evidence of employer learning with education being used as a signal. Fabian Lange (2007) extends their work to show that this learning happens very quickly.

I think because economic models are, in the main, designed by those with 8 or so years of economics at university behind them.

These people quite rationally believe that they could learn the same amount in a shorter period of time if so much of econ as college wasnt pitched at the lowest common denominator.

Hence an increased bias towards anecodatal signalling theories.

... of course this entire comment is anecdotal!

This model looks simple enough to not worry about #1:
She finds it takes about 4 years for employers to learn and fire lemons. I like it though, because wages don't rise until OTHER employers learn. That makes more sense to me than the wage = MP model, but maybe not as good as some bargaining protocol.

One possible way for the market to respond to changes in productivity in the short term, but for measurements of individual productivity to be slower, is if measurements are noisy.

Suppose the noise in the measurements is large enough that it takes at least 37 person/years to measure worker productivity. An employer might observe in one year that his 37 college-degreed employees have a higher average productivity than his 37 high school dropout employees.

On the other hand, it would take the employer 37 years to measure *which* of his college employees were better, and which dropout employees were better than the college average.

Thus, markets would adjust to *average* productivity in the short run, but would not be able to measure individual performance absent a degree.

Here's a simpler model:

Future employees did a bunch of useless stuff U because "that's what we always did" and "that's what always worked". Employers hired based on U-specific metrics because, "that's what we always did" and "that's what always a predictor of good performance".

Then, slowly, some employers increasingly find U to be less and less informative, whiel future employees are slow to recognize these. "U" by itself produces no value, but rather, only value to the extent that employers ultimately value it.

Eventually, reality has to set in, and people have to fundamentaly change how they prepare for employment, but herding/weirdness effects prevent people from acting on this new reality.

So, can I get a good publication out of this?

I agree with this completely, so I hope you were not being sarcastic.

Has anyone ever done a study tallying how many occupations now "require" a college degree but originally did not? I was fascinated to learn a few years ago that for at least a generation, air traffic controllers were not required to have any college training at all. There must be more examples like this.
I was born in 1963, and I'm old enough to remember a time when more and more jobs tried to restyle themselves as "professions." I may be wrong, but I seem to recall during the early 70's that people would get defensive while describing this or that occupation and start arguing, "There's more to it than you think. You can get a college degree in it now."
I myself worked for 15 years in a library job that originally required "some college, one or two years," and by the time I left, was requiring an actual college degree in that specific area of work- a degree that had not existed just 2-4 years earlier.
Yet the work was largely being performed by a staff without such a degree, even as that degree was being required from new staff.
Who would be trained by the old staff.

Interesting points, thanks for sharing.

"In other words, the anecdotal evidence for signaling fits into a broader model precisely because such cases aren’t too common."

That makes a lot of sense to me. Also maybe worth keeping in mind is that the primary mission of the colleges themselves -- promoting exclusivity via admissions standards -- tends to ensure that graduates are picked from a pool that will produce merit, thus validating their signal.

That signalling seems to be fading anyway is interesting, perhaps partly an unintended result of affirmative action?

Still people who have a job for which they suddenly need to learn a new skill e.g desktop COBAL programmers who needed to lean C, Java etc. mostly do not go to universities to learn those skills. It is too costly in time and money. So how could college be more about learning that signalling?

But they do learn those skills in college initially, and then typically once you become proficient in one language, it's easier to learn another language. Also, in college you learn database and programming theory, which is broadly applicable across languages/databases.

Tyler, does cumulative advantage get us out of this mess?

Let's say it is very difficult and expensive to judge non-employee's MP before hire, especially at entry level positions for younger workers. So employers rely on signaling based on University degrees. There is some discovery by the firm over time within this hired cohort and some employees are promoted faster or slower or fired.

However, let's say that the median college degree holding worker only started with a very modest advantage over a median non-degreed workers but that there is significant learning by employees while on the job, which has been increased by tech change. So that due to their differing initial employment by the time employers can make a determination of employee effectiveness the MP of even originally equivalent college degreed and non-degreed workers has moved significantly further apart. In that case, technological change merely makes the first placement and initial signaling more important.

As semi-support I'd add the finding that the condition of the economy when one enters the labor market has been shown to have statistically significant results for life time earnings, whether one has a degree or not.

Signaling works more like a bar to entry to professionals for non-credentialed people who don't need what they acquired with the credentia to do the job than it is an "insurance policy". A degee gets you in the door, but doesn't mean you can stay there.

In that respect, the time it takes an employer to observe MP is irrelevant. People who could have high MP and don't have the credential never get a chance to prove themselves and that operates pre-observation of MP.

One plausible explanation for the rise and fall of American labor unions is that they arose because people with the aptitude to be managers were shut out of management roles for want of credentials. For example, one study (crusty and not easily at hand) found that in the 1950s, union leaders and college graduate managers had the same average vocabulary, in both cases much higher than that of rank and file workers. When higher education took a meritocratic turn through a combination of the GI Bill and then changes in admissions policies a decade or so later, the ranks of the shut out smart people were dramatically thinned as they attained the relevant credentials and were coopted into management, and unions without quality leadership became much less effective, to the detriment of the workers that they represented.

Also, taking the fact that credentialed workers may be more skilled than non-credentialed workers doesn't mean that signaling theory iis wrong. It simply means that the signals conveyed by credentials tend to be accurate ones. The point of signaling theory is that what is learned during college isn't what is adding value - the value was there when they got into college, not as a result of what they acquired in college. If people with credentials are more skilled in their jobs yet are using skills that they didn't learn in college, that is a classic proof of signaling theory. And, among the bits of evidence that tend to support signaling theory empirically is the evidence that liberal arts graduates, particularly from prestigious colleges, have a higher return to their educational investment than college graduates who earned pre-professional degress (e.g. marketing).

Another recent bit of empirical evidence in support of signaling theory as an alternative to the theory that education itself actually adds value was a study showing that on the job performance by lawyers was better predicted by the best law school to which they were admitted than by the particular law school that they actually attended.

The policy implication of signaling theory is that for a significant subset of college students, we are wasting immense amounts of time and money by having them spend four years getting a college degree (and incurring opportunity costs from not having these smart people in the labor force) that could just as easily be achieved with an application not to a college but to a "smart person certification" credential right out of high school.

Now, clearly, this isn't true of all college students. We are getting lots of value added out of engineering schools where graduates have far more capabilities to perform coming out than they did going in. But, it is very much true in the case, for example, of journalism, where a smart high school graduate isn't particularly more qualified to do the job after four years of college than he or she would have been if a newspaper had been willing to hire him or her right out of high school and that person had four years of on the job experience instead. Similarly, if you are looking a pure skills, why would anyone ever high a college graduate with a major in French or Spanish or Arabic for a language skill related job when one could hire a bilingual native speaker instead?

Given these premises, the optimal situation for signaling cost is for jobs that require a considerable on the job training investment before one can determine if a candidate's probable MP (e.g. associate attorneys in big law firms with specialized practices, or medical specialists), but once that training cost is incurred it is pretty easy to identify low MP individuals and weed them out. Excluding clearly unskilled people with a high credential bar is an inexpensive way to limit wasted training cost risks, and the commitment is short enough that a more in depth analysis isn't economically valuable.

In addition to the wasted time, money and opportunity costs, a down side of signaling theory is that attaining credentials necessarily bars entry to lots of people who don't get the credential due to a lack of financial means, but have the ability to do so. While this lost opportunity cost may be an economically rational sacrifice for individual employers, it is bad for the macroeconomy because it prevents the society from utilizing as much as possible of our human capital resources, destablizes the society because highly skilled outsiders won't have the same stake in the status quo, and is just plain unfair and inconsistent with our national ideals. The economic barriers to attaining credientials is well demonstrated empirically (even controlling for academic ability, see, e.g., the Intel Semi-Finalist who this month found out she won the award while she was in a homeless shelter), but if signaling via expensive credientials can be replaced by signaling via inexpensive credentials, then we can get equity without spending as much money subsidizing higher education.

“Another recent bit of empirical evidence in support of signaling theory as an alternative to the theory that education itself actually adds value was a study showing that on the job performance by lawyers was better predicted by the best law school to which they were admitted than by the particular law school that they actually attended.”

Do you (or does anyone) have a link to that study, or a title or author? I’m interested.

"Another recent bit of empirical evidence in support of signaling theory as an alternative to the theory that education itself actually adds value was a study showing that on the job performance by lawyers was better predicted by the best law school to which they were admitted than by the particular law school that they actually attended."

Do you (or does anyone) have a link to that study, or a title or author? I'm interested.

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