Category Archives: Economics of Education

Upward-Sloping Demand Curves

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Why are big cities becoming expensive places to live? One answer is that they have good jobs and restrictions on housing construction. That may be right.

But one possibility I want to throw out there is that people want affluent neighbors. If I want an affluent neighbor, and an affluent neighbor is going to live in a neighborhood with high prices, then in some sense I want to live in a neighborhood with high prices. In the extreme, this makes my demand for neighborhoods upward-sloping. Higher prices make me want to live there.

I first considered this possibility many years ago when thinking about school vouchers. I thought that if what people really want for their children is to have them go to school with affluent children, then vouchers would not work as well. Instead of allowing non-affluent parents to send their children to good private schools, the result would just be that good private schools would raise prices so that only affluent children can attend.

I also think that some colleges that are not in the top tier may face upward-sloping demand. George Washington University, which is hardly an academic icon, may benefit from charging very high tuition. Affluent parents come and see a student population that is predominantly affluent, and this gives them comfort that sending their children to GW is a high-status thing to do.

Back to cities. Suppose that an important “urban amenity” is having a lot of affluent people around. Young singles may wish to meet potential marriage partners who are affluent. People who have acquired affluent tastes (sushi, yoga, wine) may want to be around people with similar tastes.

If that is the case, then there is not much that a mid-sized midwestern city can do to lure affluent people. The cost of living there is not high enough to create a barrier to non-affluent people living there. And that means that affluent people will not want to live there.

The Low-skilled Labor Market

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Andre Spicer claims,

The fastest-growing jobs are low-skilled repetitive ones in the service sector. One-third of the US labour market is made up of three types of work: office and administrative support, sales and food preparation.

The majority of jobs being created today do not require degree-level qualifications. In the US in 2010, 20% of jobs required a bachelor’s degree, 43% required a high-school education, and 26% did not even require that. Meanwhile, 40% of young people study for degrees. This means over half the people gaining degrees today will find themselves working in jobs that don’t require one.

Some thoughts:

1. Too often, popular discussions of labor markets speak as if “supply” and “demand” are fixed, with no equilibrating mechanism. Instead of upward-sloping supply intersecting with downward-sloping demand, these accounts implicitly depict vertical supply and demand curves.

If it is true that colleges are dumping an excess of high-skilled workers into the market, then the wages of highly skilled workers should fall until supply and demand balance there. Meanwhile, if there are so many excess jobs for low-skilled workers (recall Conor Sen predicting a shortage of construction workers), then wages should rise there.

2. I doubt that it is true that colleges are dumping an excess of highly skilled workers into the market. Instead, I think that our society is dumping an excess of non-college-ready students into college. There, some of them at best may be upgrading their skills to those of a high-school graduate.

3. If the imbalance is real, what are entrepreneurs doing about it? They should be working on ways to eliminate low-skilled jobs, while figuring out ways to use workers with college degrees (the latter supposedly in abundance). I see the first taking place. The second, not so much.

Null Hypothesis Watch

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Scott Alexander takes a look at it.

In summary: teacher quality probably explains 10% of the variation in same-year test scores. A +1 SD better teacher might cause a +0.1 SD year-on-year improvement in test scores. This decays quickly with time and is probably disappears entirely after four or five years, though there may also be small lingering effects. It’s hard to rule out the possibility that other factors, like endogenous sorting of students, or students’ genetic potential, contributes to this as an artifact, and most people agree that these sorts of scores combine some signal with a lot of noise. For some reason, even though teachers’ effects on test scores decay very quickly, studies have shown that they have significant impact on earning as much as 20 or 25 years later, so much so that kindergarten teacher quality can predict thousands of dollars of difference in adult income. This seemingly unbelievable finding has been replicated in quasi-experiments and even in real experiments and is difficult to banish. Since it does not happen through standardized test scores, the most likely explanation is that it involves non-cognitive factors like behavior. I really don’t know whether to believe this and right now I say 50-50 odds that this is a real effect or not – mostly based on low priors rather than on any weakness of the studies themselves. I don’t understand this field very well and place low confidence in anything I have to say about it.

The modesty he expresses at the end goes to far, in my opinion. I think that the right way to put it is that no one should pretend to know very much or have great confidence about claims about how teaching affects outcomes, particularly in the long term.

I actually think that Alexander’s post is the best discussion of this issue that you will find. I have more confidence in what he has to say than I have in any what Raj Chetty’s groupies have to say.

For newcomers to this blog, the null hypothesis is this:

Take any educational intervention. Measure its effects.

1. The effects are likely to be zero in the year that the intervention is introduced.

2. If they are not zero in the year they are introduced, the effects are likely to fade out quickly.

3. If the effects do not fade out quickly, the results are not likely to be replicable using rigorous experimental methods.

4. If the effects are replicable, they are not likely to be replicable at scale.

In short, the null hypothesis is that educational interventions have no effect, if you study them carefully. This includes interventions involving trying to measure and reward teacher quality. On that point, I agree with the teachers’ unions that measures of teacher quality are mostly noise and not signal.

In other service businesses, we let the customer make a subjective judgment of quality. You do not pick your hair stylist or your doctor or your auto mechanic based on some distant economist’s regression analysis. The reason we don’t use customer judgment in education is that we let government, rather than the customer, pick the service provider.

Entertaining Debate on the Economics of Education

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I recommend this EconDuel between Tyler Cowen and Alex Tabarrok, with the latter channeling Bryan Caplan, on whether education is content or signaling.

Tyler argues that students pick up valuable intangible forms of knowledge in college. One might term this cultural learning.

When I showed the debate to my high school students, they were somewhat put off by Tyler saying that students learn to “submit to authority.” I think that a better formulation would be to say that students learn to please authority in ambiguous situations. That is, a skilled worker in today’s economy needs to meet expectations in a setting where instructions are not precise. Your boss does not want to spend time telling you exactly how to do your job. Instead, the boss wants to set some general expectations and have you figure out how best to meet or exceed those expectations. In college, writing a paper or trying to prepare for a test requires similar skills–the ability to anticipate and satisfy what the professor is expecting without being given a precise set of step-by-step instructions.

When I gave job interviews, the crucial point in the interview was when I said, “Tell me what questions you have.” I took the view that someone who was going to do a good job would have the ability to ask relevant, probing questions. Someone who lacked that ability would be too passive and create too many opportunities for communication failures between me and the employee.

In theory, a better educated person would do better in my interview. That person would have a better sense of the right questions to ask in order to be successful as an employee.

On the other hand, the cultural learning aspect of college education might be nothing but an Eliza Doolittle effect. Because you are able to speak with the proper intonation and express the views of a well-educated individual, you ingratiate yourself with people who can hire you into or connect you with well-paying jobs. But someone with more lower-class conversation patterns might actually be as good or better at doing the work.

Alternatives to the GPA

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Mark Oppenheimer writes,

If grade inflation is bad, fighting it is worse. Our goal should be ending the centrality of grades altogether. For years, I feared that a world of only A’s would mean the end of meaningful grades; today, I’m certain of it. But what’s so bad about that?

I think that the best approach is to unbundle teaching from assessment. An enterpreneurial idea would be to start a national collegiate assessment service. This company would administer at least three types of examinations.

1. Exams for generic courses, such as calculus or freshman economics or freshman psychology. These exams would work like AP exams.

2. Assessments for more specific courses, such as the economics of sports, or 20th-century Japanese poetry. For these, the professor will provide a syllabus that includes a set of objectives for the students. The company will design and implement an assessment geared toward the syllabus. (At Swarthmore College, the honors exams used to work that way, with professors from other institutions writing and administering exams.)

3. Assessments of general areas of competence. Examples might be: the ability to read an essay and summarize its key points; the ability to read how a study was conducted and assess the weaknesses of the methods used; the ability to trace the historical roots of a contemporary political or economic phenomenon.

If this sort of enterprise could get off the ground, I think it holds the potential for radical change in the academy. My hope is that many students might decide that the best way to do well on third-party assessments is to take more control over their own learning.

RCT’s as Slow Learning

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Ricardo Hausmann writes,

Consider the following thought experiment: We include some mechanism in the tablet to inform the teacher in real time about how well his or her pupils are absorbing the material being taught. We free all teachers to experiment with different software, different strategies, and different ways of using the new tool. The rapid feedback loop will make teachers adjust their strategies to maximize performance.

Over time, we will observe some teachers who have stumbled onto highly effective strategies. We then share what they have done with other teachers.

Notice how radically different this method is. Instead of testing the validity of one design by having 150 out of 300 schools implement the identical program, this method is “crawling” the design space by having each teacher search for results. Instead of having a baseline survey and then a final survey, it is constantly providing feedback about performance. Instead of having an econometrician do the learning in a centralized manner and inform everybody about the results of the experiment, it is the teachers who are doing the learning in a decentralized manner and informing the center of what they found.

Pointer from Mark Thoma. Emphasis added.

Read the whole thing. I had never before thought of randomized controlled trials as embedded in a top-down approach to learning. He is suggesting the decentralized learning could be faster. Might the same be true in medicine? And is this also a case against MOOCs?

Anti-market Bias on Campus

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Check out the 2016 conference about entrepreneurship at Swarthmore College.

When the conference was initiated in 2003, I think that the idea was to expose students to the world of business. Over the years, it seems to have degenerated into another exercise in expressing anti-market ideology. I wonder how the donors would feel about a conference devoted to debating the issue of

companies reconceiving their products and markets to address unmet social needs, redefining productivity in their value chain to build in environmental and societal gains, and working strategically to build local clusters of development within regions and communities to support the overall skills set and competitiveness

(and that is the pro-market side!)

I think it is pretty common for philantropists to throw money at colleges and universities to try to encourage positive thoughts toward business and markets. My guess is that in most cases the results backfire.

I believe that it is a worthwhile goal to seek to raise the status of capitalism and of profit-seeking enterprises. But I am not sure that the best way to address the anti-market bias on campus is to put your philanthropic dollars there.

What Students Actually Are Told to Read

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Peter Berkowitz writes,

The books that dominate are “recent, trendy, and unchallenging.” Racism has been the most popular subject the last two years. Many books feature adolescent protagonists. Works dealing with immigration and environmentalism or, to use the trendier term, sustainability, were featured frequently. Several colleges selected works about transgender identity. Books about military and diplomatic history, particularly ones that depict valor on the battlefield and prudence and statesmanship in government, are rare.

To me, the lesson from the typical recommended reading list is one of dogmatic conformity. If you go back to my list, I think you will find a lot more diversity. My goal is to stimulate someone to think, not to drive home a particular set of beliefs.

Faculty Inequality

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Liang Zhang and Ronald G. Ehrenberg write,

The share of part-time faculty among total faculty has continued to grow over the last two decades, while the share of full-time lecturers and instructors has been relatively stable. Meanwhile, the share of non-tenure track faculty among faculty with professorial ranks has been growing. Dynamic panel data models suggest that employment levels of different types of faculty respond to a variety of economic and institutional factors. Colleges and universities have increasingly employed faculty whose salaries and benefits are relatively inexpensive; the slowly deteriorating financial situations at most colleges and universities have led to an increasing reliance on a contingent academic workforce.

Slowly deteriorating financial situations? Then why are the salaries of tenured faculty so high?

The amazing fact about the economics of college teaching is that a subset of professors is completely insulated from the excess supply that is all around them. Between subsidies to demand handed out by the government and restrictions to supply imposed by limitations on tenured faculty, salaries are maintained far above where they otherwise would settle.

I’ll say again. Ask people if they would rather have 1975 health care at 1975 prices or current health care at current prices, and many will admit that they would prefer what we have today. But many people would say that although college education costs far more today, the quality of what students get is actually worse. Of course, the benefits of a college education appear to be higher today, until somebody figures out alternative ways of providing assortative mating and credentialing.

Significance Comparisons and Measurement Error

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Leilan Shu and Sara Dada report,

We first use a simple linear regression model of average test score and average household income to first establish a positively correlated relationship. This relationship is further analyzed by differentiating for other community-based factors (race, household type, and educational attainment level) in three multiple variable regression models. For comparison and to evaluate any consistencies these variables may have, the regressions were run on data from both 2007 and 2014. In both cases, the final multiple regressions found that average household income was not statistically significant in impacting the average test scores of the counties studied, while household type and educational attainment level were statistically significant.

Pointer from Tyler Cowen. If this were credible, it would seem to suggest that “schooling inequality” is really ability inequality.

BUT…Whenever somebody says that “X1 does better than X2 at predicting Y,” watch out for the impact of measurement error. A variable that is measured with less error will drive out a variable that is measured with more error.

In this case, suppose that the variable that matters is “parents’ resources.” Income could measure that variable. Educational attainment could predict that variable. Income has many sources of measurement error–if nothing else, one year’s income could be high or low due to volatility. Educational attainment has fewer sources of measurement error. So even if parents’ resources is the true cause of children’s test scores, you could wind up with a zero coefficient on income, particularly if you include another regressor with lower measurement error.

And this is one of many reasons to prefer experimental data to regressions.