Welcome to the Profit of Education website. Continuing the conversation begun in the book Profit of Education, we discuss the latest economic evidence on education reform.

It happens here, too: Lessons for universities on preventing sexual harassment

My most recent post on the BROWN CENTER CHALKBOARD at the Brookings Institution.

While school was out this summer, the National Academy of Sciences published the over 300-page report, “Sexual Harassment of Women: Climate, Culture, and Consequences in Academic Sciences, Engineering, and Medicine.” The report is what you would expect from the National Academy: lots of numbers and a couple hundred references to the scientific literature. Included are a number of positive suggestions for reducing sexual harassment in academia—more on some of these below—but the report has one finding that shocked me.

Worse than the private sector? 58 percent? (Reports of harassment of students by faculty or staff are also high, in the 20-50 percent range.) Despite surface appearances, sexual harassment in academia turns out to be a major concern. While the pervasiveness is a surprise, some of the causes are not. My observation is that, in academia, there are three elements that contribute to such pervasive sexual harassment:I think of universities as pretty decent places to work; while there are certainly individual squabbles—sometimes serious ones—academics are pretty reasonably behaved for the most part. But, shockingly, that’s not what the evidence says when it comes to sexual harassment. According to the National Academy: “[Among employees], the academic workplace … has the second highest rate of sexual harassment at 58 percent (the military has the highest rate at 69 percent) when comparing it with military, private sector, and the government, where a broad definition of sexual harassment is used.”

  • Power and silos
  • Institutional “see-no-evil”
  • Plain, old insensitivity

Something true in both the military and in the academy is that there are many relationships in which the power between two people is extremely unequal. In the private sector, usually the worst someone can do to you is fire you, and even then there are always other jobs. In academia, one person may be in a position to effectively end the other person’s academic career—not just interfere with their current position. (The power structure in the military as compared to civilian society is pretty obvious.) In most organizations, there is at least some avenue of appeal from perceived unfair treatment. In contrast, if I give a student a failing grade, tell a Ph.D. candidate that their dissertation isn’t acceptable, write a referee report judging that a journal ought to reject a submitted paper, or vote against someone’s tenure, the truth is there is little to no recourse.

The problem of power is reinforced in academia because organization is so “siloed.” When I’m advising a Ph.D. student, basically no one else knows what I’m doing and probably no one else on campus could judge whether the mentor/mentee relationship is reasonable, even if they could observe it. The fact that so much interaction is effectively private reinforces the risk of bad behavior where there is a power imbalance. Interestingly, the National Academy study finds the greatest incidence of sexual harassment happens in medicine, which is especially hierarchical: “Research on the medical environment reveals that overall ‘mistreatment’ is commonplace in all levels of the medical hierarchy, especially among medical school students, interns, and residents.”

On the second bullet point, the National Academy study says, “Too often, judicial interpretation of Title IX and Title VII has incentivized institutions to create policies and training on sexual harassment that focus on symbolic compliance with current law and avoiding liability, and not on preventing sexual harassment.”

If you are reading this from a university, when is the last time you heard about a significant punishment to a colleague for egregious sexual harassment? If you were the subject of sexual harassment (I’m hoping you find this a hypothetical question, but in light of the study’s finding I’m no longer so sure this is merely hypothetical for most readers), would you feel it worth the cost and risk to file a complaint? Here, there are two different issues. The first issue is whether the campus takes sexual harassment seriously. The second issue is whether the campus makes public the extent to which there are consequences of bad behavior. If you want to deter misbehavior, be sure that there are consequences and everyone on campus knows it. If you want victims to come forward, they need to know that complaints result in actions.

As a positive example of good reporting, the National Academy study praises Yale’s semiannual “Reports of Complaints of Sexual Misconduct”: “These reports are written to protect anonymity while also providing minimal descriptions and statistical summaries that reveal (1) the complainants and respondents role in the university …and (2) the status of the complaint (if the complainant decided to pursue a formal complaint, if investigation is pending, any action taken by the university after investigation.”

Most harassment stops short of coercion and assault. The National Academy cites a large study done at Penn State of faculty/staff-on-student harassment for female students. About 95 percent of misbehavior falls into the categories of “sexist hostility” and “crude behavior.”So reporting can be done. It’s not that hard. And frankly, making data public is an important step in bringing a university community together when improvements are needed. A university would likely prefer not to read about unsuccessful processes from an external source, such as the recent California state auditor’s report, “The University of California: It Must Take Additional Steps to Address Long-Standing Issues With Its Response to Sexual Harassment Complaints.”

So a little advice to faculty, staff, and teaching assistants who either don’t care how women feel or who—despite all the attention the subject has gotten—still don’t understand how women feel. Don’t make sexual remarks. The fact that women may laugh or go along doesn’t make it okay, because some of them won’t feel they have a choice, and you won’t know that. The issue isn’t whether sexual banter can be fun for everyone—the issue is that you won’t know if you’re making people uncomfortable (unless, of course, they file a complaint against you).

Keep inappropriate comments and “jokes” out of your professional life. Why? Because you know that you might be making someone uncomfortable when that’s not your intention at all. What’s more, you are setting an example. So keep it professional.

One final comment from the report for those who are onboard with improving the situation:

Taken together, the surprisingly sparse—yet robust—set of studies on sexual harassment trainings shows that trainings can improve knowledge of policies and awareness of what is sexual harassment; however, trainings have either no effect or a negative effect on preventing sexual harassment.

 

Given … that actions can be taken to inhibit sexually harassing behavior … and that changing attitudes is difficult, effort seems better spent on developing and using sexual harassment trainings aimed at changing people’s behaviors rather than on their attitudes and beliefs. Ultimately, it is individuals’ actions and behaviors that both harm targets and are illegal, not their thoughts.

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Tax credits can help high-poverty schools attract more teachers

My most recent post on the BROWN CENTER CHALKBOARD at the Brookings Institution. This one is with Kate Walsh of NCTQ.

Today, the federal government provides about 9 percent of the funding for K-12 public schools. The Center for American Progress (CAP) has just issued a call for raising that amount to more like 11 percent, putting the extra money into high-poverty schools in a way that doesn’t otherwise increase federal control of how states and school districts manage public education. The CAP proposal, under the title “How to Give Teachers a $10,000 Raise,” would provide federal tax credits directly to teachers who work in high-poverty schools.

Here we offer: (1) a quick review of how the idea would work; (2) an explanation of why this appears to be a way to tackle a big obstacle to ensuring that teacher talent is equitably distributed; (3) an argument as to why this might actually be politically feasible; and (4) a small, technical gotcha that needs a little attention.

The idea is simple. If a teacher signs on to a school with 75 percent or more of students on free or reduced-price lunch (FRPL), then the teacher gets a $10,000 refundable credit on her income taxes come April 15. The refundable credit part is important, because it means the teacher gets the money back no matter what else is going on with her tax return. Teachers who work in less poor schools, but still poor (>50 percent), would qualify for a reduced credit.

All told, about 57 percent of the teachers in the U.S. would be eligible for some level of substantial tax credit.

The proposed tax credit does two things: First, it would likely increase the available supply of teachers who want to work in high-poverty schools, achieving greater equity and improved education. There is a well-documented gap in average teacher quality between low-poverty and high-poverty schools (see here and here). Second, it also would provide a tax credit for teachers who are already there. That’s only fair. Teaching in high-poverty schools is an awfully tough job. CAP’s policy seeks to close what it observes as an existing $4,000 pay gap between teachers in the highest-poverty and the lowest-poverty schools, although part of that gap is due to a higher proportion of high-poverty schools being located in low-income areas (where all salaries are lower), and part is due to teachers in high-poverty schools having less experience and therefore sitting at a lower line on the salary scale.

A $10,000 tax credit is equivalent to just under a 20 percent raise for a teacher at the national average. In low-income states and in low-income districts, because teacher salaries are low, the raise is likely to be more than 20 percent. Analogously, the percentage increase may be less in low-income urban schools that are located in school districts that pay above the national average.

There is, however, at least a question as to whether a tax credit is as salient to teachers as a direct salary increase. We know from different studiesthat pension enhancements are less attractive to teachers than are equivalent increases in salary. However, a tax credit is much closer to a current salary boost than the promise of a better pension many years in the future. Still, it might make sense for districts to emphasize that eligible teachers can reduce their tax withholding in order to get an immediate increase in take-home pay.

Enticing strong teachers to move to disadvantaged schools won’t be a panacea for all the education problems associated with poverty: The teacher quality gap is significant, but it is not always as huge as some believe.

Still, jobs that pay more tend to be more competitive, drawing more applicants. Even a healthy-sized tax credit does not mean that all teachers will gravitate toward these opportunities. But unless teaching is exempt from basic labor economics, more teachers will almost certainly apply than would otherwise. It’s worth noting that district experience with such enticements have been mixed—with some succeeding better than others at convincing teachers from less challenging jobs to more challenging ones—but we’re also not aware of any other effort where the salary increase was both large and permanent.

This targeted tax credit also manages to walk a fine line between those who advocate paying some teachers higher salaries with those who advocate that an across the board raise is what is needed. The CAP proposal would apply only to teachers who are making a very specific extra contribution by working in high-poverty schools. While performance isn’t ostensibly a factor, we presume competition for these higher paying positions would allow principals in these schools to become a lot more selective about whom they hire, as well as reducing expensive teacher turnover and reliance on long-term substitutes or out-of-field teachers. (A North Carolina study by Charles Clotfelter and co-authors found that an $1,800 annual bonus lowered turnover rates by 17 percent.) That suggests that districts might do well to review their hiring systems in the face of a changed landscape.

Another reason the proposal makes sense is that tax credits are “off-budget” in the same way that the deductibility of mortgage interest is. That means that Congress doesn’t have to re-fight about the topic each year (and even avoids fickle state legislatures and school district budgets which can go from riches to rags overnight). Congress can make changes—as they have recently with the deductibility of mortgage interest—but once in place refundable credits are likely to be stable for a number of years. Stability is important for teachers making long-term career choices.

What’s more: $10,000 is actually worth more than $10,000. That’s because a tax credit is after-tax income. A typical teacher is likely in the 22 percent tax bracket on her federal return (a bit higher in states with a state income tax). In order to take home an extra $10,000, that teacher would need to earn $12,505.51 more. So a $10,000 credit actually comes with a $2,500 (plus change) take home bonus.

Key to its political viability is the fact that “high poverty” is as helpful to rural areas as urban—maybe more so where $10,000 is a higher percentage increase because salaries and the cost-of-living is low. In fact, high-poverty counties are more likely to have voted for President Trump in the last election than are low-poverty counties. Here’s a little scatterplot. (Note: Vote data is from Tony McGovern; poverty data is from the Census Bureau.)

Trump vote by percentage below poverty line, by county (2)
Source: Dick Startz and Kate Walsh; data from Tony McGovern and the Census Bureau.

The correlation between red votes and areas of poverty is not terribly strong (although it is strongly statistically significant), but it’s positive—not negative. In other words, there is a bunch of red state members of Congress who should have a strong interest in funneling money into high-poverty schools. Eventually, such a proposal has to be paid for of course, which should be a concern for everyone. CAP calculates the cost of the program to be about one-tenth the size of the recently passed federal tax cuts.

Now to that small, technical gotcha. Looking at FRPL is not such a good measure of poverty, in part because a number of districts now provide free lunches to all students, in response to an anachronistic system which is dependent upon families submitting a form declaring themselves to be poor. (See Brookings-based discussions here and here and here.) Fortunately, a better measure would be simple to implement. Eligibility for FRPL corresponds roughly to income below 185 percent of the poverty line. So change the credit-eligibility criteria from FRPL to a set fraction of students below the poverty line equivalent. You don’t need to know the income of individual families. If you know where your students live, then a poverty measure can easily be put together from Census data. Using such poverty data directly really gets right to the heart of where teachers should be getting an extra (tax) credit.

The high-poverty-school-refundable-tax-credit idea is a good idea that should have wide appeal, if ideas were still judged on their merits. While CAP is a left-of-center organization, we’ve pointed out why the idea should appeal to both sides of the aisle. Given the income distribution across the country, much benefit would end up in low-income and rural states that are often conservative strongholds. And using tax cuts rather than policy mandates ought to appeal to the conservative agenda. Bipartisanship may be a quaint notion in the current political context, but this is an idea well worth consideration from all sides.

 

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Teachers have been moonlighting in Texas—and elsewhere—to make ends meet

My most recent post on the BROWN CENTER CHALKBOARD at the Brookings Institution.

Last month, we talked about the fact that teachers are more likely than others to work second jobs. Since then, there have been all sorts of stories about teachers in Oklahoma working multiple jobs—as many as six! And the stories are neither new nor limited to Oklahoma.

Presumably, teachers who take second jobs do it mostly—like anyone else—in order to supplement their salaries. Of course, low teacher salaries are a central issue in the teacher strikes that have swept the nation in recent months, so keep these teachers in mind when thinking about who might be working these second jobs. Thanks to work by Dr. Sam Sullivan and Dr. Robert Maninger at Sam Houston State University (SHSU), there’s quite a bit more to be said about teachers’ attitudes toward moonlighting.

For more than three decades, SHSU has conducted a biennial survey of Texas teachers under the auspices of the Texas State Teachers Association, the Texas affiliate of the National Education Association. Even though the survey results are from just one state, it’s an exceptionally large and diverse state and should help shed light on teachers’ attitudes that likely apply in other states as well. Also, as background, Texas teacher pay adjusted for cost of living is smack dab in the middle among all the states.

A first point: The survey results show that second jobs are way up. While the responses vary from year-to-year, both summer and school-year second jobs have increased noticeably—particularly around the Great Recession.

The survey asked moonlighting teachers how much of a raise would be needed to get them to drop their school-year jobs. As the next figure shows, the answers have been quite stable at a touch under 20 percent of salary. To me that suggests that dollars really are an important issue.

We can say something more about what predicts whether a teacher chooses to moonlight during the school year. Professors Sullivan and Maninger provided me with the underlying data from their 2016 survey. While teachers each have individual reasons for deciding about moonlighting, there are some clear average tendencies.

First, money matters, but it may not be the only thing that matters. It is noteworthy that the amount teachers say would be required to quit moonlighting is generally larger than the amount they actually make moonlighting; about 60 percent larger in fact. (A separate survey by Brown, Sullivan, and Maninger finds the same qualitative result.)

Second, supporting your family matters. Teachers who identify as the major breadwinner in their household are 12 percentage points more likely to report taking on a second job. In other words, the probability of moonlighting rises by over a third if you are the primary breadwinner.

Third, teachers’ attachment to teaching matters. Those who say they are considering leaving teaching are 9 percentage points more likely to report moonlighting. Some caution is needed here. We don’t know if teachers who moonlight actually do leave teaching, and we don’t know if teachers are moonlighting because they are unhappy in their jobs, or, if in the course of moonlighting, new career opportunities open up.

Finally, the reason we really care about public teachers moonlighting is whether doing so actually changes teachers’ classroom effectiveness. After all, research makes clear that quality teaching is the most important school-based input into education. We can think of ways it potentially could improve teaching (e.g., teachers bring new perspectives into the classroom) or make teaching worse (e.g., teachers are too tired).  From the survey results, I can tell you what teachers who moonlight say: They say it’s bad for the quality of their own teaching. (This Vox story has a nice collection of anecdotes from tired teachers.)

While we still don’t know everything we might like to know about the causes and consequences of teachers taking second jobs, thanks to the work of Sam Sullivan and Robert Maninger we do know a lot more than we would otherwise. It seems clear that money is a cause, and some loss in teaching quality is likely a consequence.

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Why are teachers more likely than others to work second jobs?

You might not think of teachers as players in our growing “gig economy.” After all, a teaching job seems like the ultimate form of guaranteed employment. Turns out, a significant number of teachers do work second jobs. In fact, teachers are more likely than others to work a second job. It’s a summer thing, right? Apparently not, but we’ll get to that below.

We know a fair amount about the extent to which teachers take second jobs. We know less about why they take jobs and not too much at all about the consequences of second jobs. A teacher with a second job raises their income, of course. Does outside work distract from teaching, or does it enrich what the teacher brings to class? Is a second job a path to leaving teaching altogether, or does a second job bring in enough extra income to allow an underpaid teacher to keep teaching as their main gig? The data shared here establishes that second jobs for teachers are an issue that deserves more attention. For some of the “whys” and “consequences,” it would be awfully interesting to hear from teachers.

To begin, how do we know who works a second job? The Bureau of Labor Statistics (BLS) conducts a year-round survey, called the American Time Use Survey, in which it asks individuals how they have spent their time both on the day of the survey and in the very recent past. In addition to asking about a person’s main occupation, the BLS asks if they worked another job in the last seven days. Our sample is made up of individuals with a college education who report being employed full-time from 2003 through 2016, giving us just over 36,000 observations.

Overall, teachers (defined as elementary and secondary teachers, excluding special ed) are about 30 percent more likely than non-teachers to work a second job based on survey responses. That comes down to about 11 percent of non-teachers and 14 percent of teachers. This figure changes when the type of teacher is considered, though. The chart below shows that elementary school teachers are only a little more likely than non-teachers to have a side job. The difference is quite a bit more for secondary school teachers.

Source: The American Time Use Survey/author’s calculations.

Among non-teachers, women and men are equally likely to hold down a second job. The situation among teachers is quite different. While female teachers are slightly more likely than female non-teachers to have a second job, male teachers are much more likely to have a second job than are their non-teaching counterparts. In fact, nearly one male teacher in five reports working a second job.

Source: The American Time Use Survey/author’s calculations.

Percentage holding a second job by month
Source: The American Time Use Survey/author’s calculations.

It would be nice to get a handle on what kind of work is involved in a second job. If a teacher is coaching football on the side while a second job for non-teachers is driving for Uber, we might feel differently than if both were driving as a second gig. While the BLS asks about the nature of second jobs, hardly anyone answers that question. (For a fun recounting of an interesting but unusual outside job, see this New York Times article.) Fortunately, the Schools and Staffing Survey (SASS; I’m using the 2011-12 results) does gather some information about the nature of second jobs. The survey is only given to teachers, so we can’t compare second-job types for teachers versus non-teachers, but we can tease out a little more about what teachers do.

First thing, SASS data confirm the fraction of teachers holding second jobs. In fact, it’s a tad higher than the BLS number, with 17 percent holding a second job outside their school system. Of those second jobs held by teachers, about half are not related to teaching. Of the jobs that are related to teaching (but remember, not for their own school system), about two-thirds are either teaching or tutoring, while the other third are “related,” but not teaching. So, no, the side jobs do not appear to be mostly coaching positions. Notably, female teachers with second jobs are relatively likely to have second jobs related to teaching. For men, it’s the other way around, where second jobs not related to teaching are more common.

The SASS data also raises the possibility that part of the reason teachers are more likely to take second gigs is that they can find positions doing extra teaching—or at least something related to teaching—relatively easily.So teachers are more likely than non-teachers to hold a second job. It’s particularly secondary school teachers and male teachers who have second jobs. Why are teachers more likely to take a second job? I suspect part of the difference is due to the fact that teachers are paid less, so they have greater incentive to increase their income. But I did a quick statistical analysis which suggests that earnings differentials only explain something over a third of the difference between the two groups. That means there is something more than pay differentials that matter. (For the record, according to the sample data teachers and non-teachers work the same number of weekly hours at their main job.) This leads to intriguing questions: Why do more teachers choose second jobs? Is it the pay differentials? Or might it be that teachers have easier access to second jobs because teachers and tutors are in demand?

And perhaps most importantly, does having a second job make someone a better teacher, or does it just make them a more tired teacher?

Note: UCSB undergraduate and Gretler Fellow Isabel Steffens provided research assistance for this post.


Footnote

  1. I do want to raise one caution about interpreting the apparent summer drop in second jobs among teachers. Respondents are asked whether they had multiple jobs in the last week. It’s possible that, in July, teachers who have a non-teaching job might answer “no,” because they aren’t in the classroom during July. There’s no way to tell for sure how much of this might be going on. Since a drop in summer jobs is what the data says, that’s our best guess, but do keep in mind the caveat.
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Sealing the border redux: American universities are losing international students

My most recent post on the BROWN CENTER CHALKBOARD at the Brookings Institution.

One year ago, I wrote on these pages: “If new border controls prevent the entry of foreign students, or simply makes them feel unwelcome so they go elsewhere, American jobs and American students pay the price.” I regret to report that we have now started down that path.

First, the fact: College enrollment of international students is down for the first time in a long time. The drop is large, but not overwhelming—at least not yet. We’ve seen a one-year decrease of about 30,000 students, which isn’t massive. However, Department of Education data suggests that foreign-student enrollment had risen consistently for the last 35 years. Here’s a picture based on NSF data. (A nice article in Inside Higher Edgives more details.)

International students in American colleges and universities

 

In the short run, losing international students is bad for what some might think of as a pretty crass reason: International students subsidize American kids because nonresidents pay higher tuition and receive less financial aid. This is especially true at public universities. For example, at the University of California—which is the world’s largest research university system—Californians pay about $14,000 in tuition and fees. International students pay more like $41,000—that’s roughly triple. And about a third of tuition is turned around and spent on financial aid, but almost none of that goes to international students. So the effective price difference is even bigger than list price would indicate.

The immediate effect of losing foreign students falls very unevenly across institutions. Unsurprisingly, international enrollments continue to climb at some universities (typically elite or flagship public universities), while international enrollments plummet at others (typically smaller, less prestigious institutions). The resulting budget cuts at the latter often hit in the areas that are already under the most financial stress, not necessarily the areas which attract the most international students. The New York Times writes, “At Wright State University in Ohio, the French horn and tuba professors are out. … At Kansas State, Italian classes are going the way of the Roman Empire.”

The immediate budget impact is bad, but I worry also about a longer-run, more serious problem. Bringing international students to the United States has two valuable way-down-the-road outcomes. One easy-to-see benefit is that we get to cream skim, keeping some of the best students in the United States. Just as an example, many tech-entrepreneurs came to the U.S. this way. Losing international students will harm the domestic economy in the long run.

A harder-to-see benefit is that many international students who return home do so with an appreciation for what America is really like. I believe that to know us is to love us. And it’s not just a matter of affection; surprisingly large numbers of foreign government officials have American degrees. Just as an economics example, the governors of the central banks of Europe, England, Israel, Argentina, India, and Mexico all have American degrees. Though the governors of the central banks of China and Russia don’t have American degrees, each did spend a year studying at an American university. Though the benefits from these educational exports are difficult to quantify, presumably some diplomatic goodwill in foreign governments across the globe is a result.

International college students bring us economic benefits today and political benefits in the future. I really hope that, a year from now, I’m not sharing with you that things have gotten worse.

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Why is minority representation lagging among STEM faculty? It could be the money.

My most recent post on the BROWN CENTER CHALKBOARD at the Brookings Institution.

Recent events in the national press have prompted new discussions of race and privilege in the institutions around us. One of these places is in universities, where minority representation among faculty lags far behind student minority representation. Today, I examine the underrepresentation of minorities among STEM faculty, with an eye toward a partial explanation based on straightforward economics: It’s the money. I’m sure money is not the only issue in play, but money differences look to be large enough to matter.

The first thing an economist looks for in this kind of situation is earnings differences. I’ll concentrate on black and Hispanic faculty while leaving gender for another day. The simple point: When compared to nonminority faculty, STEM-trained minority Ph.D.s have a greater financial incentive to seek employment in industry rather than in the academy than do non-STEM minority faculty.First, have you read Cory Koedel’s Chalkboard piece, “Examining faculty diversity at America’s top public universities”? If not, you should. Koedel carefully documents that, in top public universities, “the underrepresentation of disadvantaged minority and female professors among faculty overall is driven predominantly by a lack of diversity in STEM fields.”

I’ve taken data from the American Community Survey from 2009 through 2015 and have pulled out the observations for the 130,000 Ph.D. recipients who are observed to be working, and who are over 25 and under 66 years old. Ph.D. recipients are defined as having a STEM background if their bachelor’s degree was in STEM—that being what the data reports.[1] Finally, I’ve defined “minority” as black or Hispanic. That’s not quite right, but should be pretty close in the context of looking at underrepresented minorities in higher education.

Tracking all three pieces of the puzzle takes a bit of work, as we care about whether someone with a Ph.D. is working in higher education or not; whether they are working in a STEM field or not; and whether they are black or Hispanic, or not. Underlying the “income penalty” calculation is a regression, controlling for age, gender, and state, as well as the variables of interest. But rather than leap to a bottom-line answer, I’ll deconstruct the regression used to calculate the relative financial disincentive for minority Ph.D. recipients in STEM areas to work in universities. (For those who can’t wait, the answer is minority Ph.D. recipients would be penalized about $13,000 a year for taking a career in the academy.[2])

We want to compare how different factors affect income for minority Ph.D. recipients versus everyone else. I’ll begin with a “base” which gives an average salary (rounded to the thousands) for a male, 30 year-old Ph.D. recipient working in California with neither a STEM background nor working in higher education. (Note in passing that California is a high-income state.) You will be unsurprised to learn that minority Ph.D. recipients earn less. I was surprised at how large the difference is; after all these are all people with doctorates.

  Black or Hispanic Neither Black nor Hispanic Difference
“Base” income $91,000 $120,000 -$29,000

How does this change for Ph.D. recipients with STEM backgrounds? As expected, STEM pays noticeably better than non-STEM. The difference is large, and the difference is somewhat larger for black and Hispanic Ph.D. recipients than it is for Ph.D. recipients from other groups—although only a fraction of the “base” minority/nonminority gap is offset.

  Black or Hispanic Neither Black nor Hispanic Difference
Additional effect of STEM $41,000 $36,000 $5,000

What’s the effect of working in higher education rather than industry, ignoring whether one is in a STEM area or not? Higher education pays worse, just as you expected. However, the income differential between higher education and industry is less if you are black or Hispanic, closing a good part of the “base” pay gap.

  Black or Hispanic Neither Black nor Hispanic Difference
Additional effect of being in higher ed -$7,000 -$28,000 $21,000

Koedel’s research, which prompted this Chalkboard post, showed that there is greater underrepresentation of minority faculty in STEM fields than in non-STEM fields. Going into higher education cuts your salary whether you are a minority Ph.D. recipient or not. Being in STEM raises your income either way. To see why the difference in the financial disincentive to go into academia between STEM and non-STEM majors is greater for minorities than nonminorities, look at this final table, which combines STEM majors with a career in higher education separately by minority status.

  Black or Hispanic Neither Black nor Hispanic Difference
Additional effect of being in higher ed, STEM -$48,000 -$56,000 $8,000
Additional effect of being in higher ed, non-STEM -$7,000 -$28,000 $21,000
Relative higher ed advantage, STEM vs non-STEM -$41,000 -$28,000 -$13,000

That -$13,000 in the bottom right corner—that’s the difference in the STEM income penalty for a minority Ph.D. recipient to move in to the university relative to a nonminority Ph.D. recipient. (The $13,000 estimate is significant at the 1-percent level, for those—like me—who are into that sort of thing.) Let me be clear that this is not suggesting that universities are discriminating against minority STEM Ph.D. recipients. Rather, university pay penalizes everyone, but penalizes minority non-STEM Ph.D. recipients less. Basically, universities come closer to matching outside pay in non-STEM areas than it does in STEM areas and does so especially for minority Ph.D. recipients.

While being in a university costs everyone money, there are compensating nonpecuniary differentials. (That’s econ-speak for being around students is fun.) But for black and Hispanic Ph.D. recipients in STEM fields, the dollar cost is relatively great—and the number of black and Hispanic STEM faculty (as Koedel showed us) is relatively low.

Are pecuniary considerations the only thing holding down the number of minority college faculty in STEM?[3] Almost certainly not. But is $13,000 enough to be an important piece of the explanation? Almost certainly.

UCSB undergraduate and Gretler Fellow Isabel Steffens provided research assistance for this post. Data is from IPUMS-USA, University of Minnesota


Footnotes

[1] We only know whether each Ph.D. recipient did a STEM major as an undergraduate, but that should be a pretty good indicator of whether they did a STEM doctorate as relatively few students make massive switches in field. (One can argue about what should count as a STEM field. I’ve included majors in environment and natural resources, computer science, engineering, biology and life sciences, math and statistics, physical sciences, and nuclear, industrial radiology and biological technologies.) We also know whether a given Ph.D. recipient is working in higher education, a definition which includes both faculty and nonfaculty positions.

[2] I am using a measure of income rather than salaries alone, as STEM workers in industry may receive substantial compensation in the form of stock rather than directly in the form of a paycheck. Using salary data alone gives slightly smaller results, 5.2 percent of compensation rather than 8.7 percent, and the results show a less tight statistical estimate.

[3] None of this tells us exactly why there’s a financial difference. One possibility is that a STEM Ph.D. recipient’s career is such a tough haul for minorities that the group who perseveres is different in many ways from minorities Ph.D. recipients in non-STEM fields. This is something we just don’t have quantitative evidence about.

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The education melting pot?

My most recent post on the BROWN CENTER CHALKBOARD at the Brookings Institution.

While education is largely oriented toward teaching reading, writing, and arithmetic—and other academic subjects—we also hope that schools warm our melting pot by bringing together members of different racial and ethnic groups. Though having students of differing backgrounds attend school together does not guarantee an increase in inter-group harmony, having schools segregated by student background pretty much guarantees no increase in harmony. I’ve taken a look at who goes to school with whom at both the K-12 level and in four-year colleges. The results were not really what I was expecting—nor were they very encouraging.

I thought I would find that colleges are pretty well integrated, while finding this to be much less true for K-12. We know that many elementary and secondary schools are not terribly diverse. Some of this is an accident of geography, and some of this is an “on-purpose” of geography. (You will likely remember recent stories about race-based school district secessions. For research on the subject check out “Brown fades: The end of court-ordered school desegregation and the resegregation of American public schools.”) The bottom line from my investigation into segregation is that colleges are not so diverse either. That surprised me—and, as a college professor, disappointed me.

To measure “getting together,” I’ll use a tool called the dissimilarity index. Given a list of schools and the number of students from each of two groups in each school, the dissimilarity index can be interpreted as the minimum percentage of students in one group that would have to move from one school to another to make all the schools exactly representative of the overall population. For example: If we had two schools, the first with 10 black students and the second with 90 white students, what is the share of students in the smaller group (the black students in this illustration) that would need to switch to the other school to achieve perfect integration while moving the fewest students? In this extreme example, the math calls for shuttering the first school and moving all the black students to the second, which would then be perfectly integrated. In this case, the dissimilarity index for the initial distribution of students would be calculated to have a value of 100 percent, since all 10 black students had to move in order to achieve an integrated school. (Remember this just an interpretation of the math. No one is suggesting that minimizing the number of students moved is the only criterion or even that a perfect balance is necessity.) What really matters is that situations with high dissimilarity indices are much less diverse than situations with lower dissimilarity indices.

Let’s begin with an oversimplified view of segregation in higher education, grouping students into “minority” (black and Hispanic) and “majority” (white and Asian). In the chart below, the dissimilarity index is shown separately for K-12 public school students (data is from the Common Core of Data) and for four-year college students, including all public, private, and for-profit institutions (data is from IPEDS). The chart illustrates three stylized facts:

  1. Mixing of students within schools is nowhere near proportions of the underlying student population. If the racial distribution of students within K-12 schools were to look like the distribution in the entire K-12 population, the number of students who would have to be shuffled to different schools is equivalent to more than 60 percent of all black and Hispanic students.
  2. The dissimilarity index for four-year colleges is better than for K-12, but still isn’t very good. A 40 percent dissimilarity index brings us closer to a true melting pot than does the K-12 60 percent, but closer isn’t close. And do keep in mind that the dissimilarity index only measures diversity among the subset of students who do go to college. Four-year colleges are also somewhat more white and Asian than is the population of high school graduates and, the fraction of white and Asian high school graduates is somewhat higher still than is the fraction of white and Asian secondary school students.
  3. Both lines are shockingly flat. Essentially, nothing has changed in the last 25 years.
Black-Hispanic versus Asian-white dissimilarity index
Source: Common Core of Data, IPEDS, and author’s analysis.

In this overview graph, I’ve grouped black and Hispanic students together and Asian and white students together—not because this necessarily makes a lot of sense but rather because that’s what’s so often done. The next set of graphs shows dissimilarity indices across four groups: Asian, black, Hispanic, and white. None of these groups is monolithic either, but it’s as far as the data will take us.

This first graph shows dissimilarity indices for K-12. The first lesson is that there’s not much mixing of any of the four groups. The second lesson is that, though a slight declining trend is evident, little has changed over more than two decades. The most mixing occurs between Asian and white students (probably no surprise). Note that the second-to-the-most mixing, the second line from the bottom, is between Asian and Hispanic students. The least mixing is between Asian and black students. But fundamentally, none of the groups mixes much with any other group.

Dissimilarity index between groups, K-12
Source: Common Core of Data and author’s analysis.

One thing the graph illustrates is that thinking of “minorities” as a group, or putting Asians and whites together as a group, isn’t really supported by the data—at least not if we’re interested in which students go to school together. Note that Hispanic and black students are essentially no more mixed than are Hispanic and white students.

Turn now to the breakdown for four-year colleges. The college dissimilarity indices are lower than the indices for K-12—but not all that much lower. And again, there’s been not much change over 35 years. The lowest dissimilarity is for Asians and Hispanics; the highest is Asian and black. Once again though, the dissimilarity indices just are not that different among the various combinations of groups.

Source: IPEDS and author's calculations.
Source: IPEDS and author’s calculations.

I have to be honest, I was expecting that colleges would be much more melting-pot like than K-12. That’s because K-12 is so geographically constrained, whereas colleges draw from larger catchment areas. Colleges do a little better, but not that much. I was also expecting to see a real downward trend at the college level over recent decades given the emphasis all colleges I know put on diversity. The downward trend is not there.

Getting students of different ethnic and racial backgrounds together on each campus does not guarantee an improvement in inter-group understanding. And apparently it’s not easy to arrange. Still, I was hoping to see different numbers for colleges in the 21st century. Colleges generate our next generation of leaders. We’d be better off if our future leaders experienced more diversity instead of just reading about it in class.

UCSB undergraduate and Gretler Fellow Isabel Steffens provided research assistance for this post.

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What Should We Pay Teachers?

 The chart below, taken from the Organisation for Economic Co-operation and Development’s (OECD) just released “Education at a Glance 2017,” has been receiving considerable attention. Take a look at the big red arrow I added to see why. On the horizontal dimension: The U.S. is far to the right, way down on the list of relative teacher pay. Vertical: The U.S. bars are short, indicating that American teachers are poorly paid relative to other American workers with comparable education.
Lower secondary teachers' salaries relative to earnings for tertiary-educated workers
Source: OECD, “Education at a Glance 2017.”

The good thing about how the chart is constructed is that looking at teacher pay relative to the pay of comparable workers is exactly the right comparison. Why? Because a key element in the decision of the best and the brightest as to whether to become a teacher or to remain a teacher is how well teacher pay looks like compared to alternative careers. It’s not the only consideration, but it’s a big one.

Fundamentally, the big red arrow tells the right story. But the story isn’t perfect, and it’s informative to talk about which shortcomings matter and why.

Horizontal first. Why do we even care about international comparisons? We care because the U.S. might learn something from how other countries conduct business. And to make a particular point, notice that the exemplar of educational excellence, Finland, is most of the way to the left on the chart, while America is most of the way to the right.

The advantage of the comparisons made by the OECD is the OECD does the best it can to make the measures comparable across countries. So even if you don’t like the particular measure the OECD has chosen, the relativestandings are still valuable. Having said that, there is a reason that the comparisons are a little unfair to the United States. Teachers generally receive more of their compensation in the form of fringe benefits than do other American workers, while this is less true in other countries. A measure of total compensation would move the red arrow to the left at least a bit.

In most other industrialized countries, everyone has roughly equally expensive health insurance. In the U.S., in contrast, teachers generally get more expensive health insurance than other workers. In addition, teacher pension systems appear to be more generous than most private-sector arrangements; although, so many teachers end up without a pension and so many state pension systems are near bankruptcy that it isn’t clear how much accounting for differential pensions would matter.

Vertical now. Is the height of the U.S. bar, teacher salaries as a fraction of the earnings of all college-educated workers, the right measure? I’ll give you a couple of reasons why you might want an alternative. Warning though, down below I’m going to tell you why the exact way we measure doesn’t matter.

The OECD is measuring teacher salaries against the earnings of full-time, full-year workers. That seems to make sense in that most teachers do have a full-time job. On the other hand, one characteristic that makes teaching an attractive career is precisely that you’re unlikely to be unemployed or unable to find part-time work; its job security tends to be far higher than other occupations. The height of the bar would be higher if the comparison were made to all workers, not just full-time workers.

Also, the OECD numbers are done using means, not medians. That measures the typical pay gap, but not the gap of the typical person. The difference is that the mean includes individuals with very high pay, whereas the median really doesn’t. Since teacher salaries are much more compressed than earnings in general, the difference is substantial. Here’s a quick picture of teacher income versus non-teacher income in the United States over several decades, calculated separately by mean and median.

Note: To be specific, the chart shows the ratio of mean (and median) income for teachers to non-teachers with a bachelor’s degree or more, between ages 22 and 66, who report being in the labor force, and who report at least $1 of earnings.

Source: The Current Population Survey as provided by IPUMS-CPS, University of Minnesota, www.ipums.org.

The most recent ratio is 62 percent if measured by means and 80 percent if measured by medians. The former is pretty much in line with the OECD numbers; the latter is a lot higher.

As an aside, you probably noticed that the median measure has been flat for four decades while the mean gap has opened enormously. This is because a bigger and bigger share of income in the U.S. now goes to the upper brackets, and teachers don’t get into the upper brackets.

Which is right, mean or median? I don’t know, and I’m quite sure no one else knows either. Do people thinking about a teaching career care only about typical salaries (look at medians), or do they also care about a potential significant economic upside (look at the mean)? I doubt there is any research on the question, despite the fact that the two measures differ by nearly 20 percentage points.

To an economist, that won’t fly, no matter how you look at it. Teaching has enormous nonpecuniary rewards—thus, teacher salaries can be lower than other professions. Teaching is an incredibly difficult job—ergo, teacher salaries need to be higher than other professions. Teachers have great job security (after a couple of years on the job)—teacher salaries can be lower. Teaching requires EQ as much as IQ—teacher salaries need to be higher.Of greater importance, do we know what the right target is? The implicit notion behind the OECD figure seems to be that teacher salaries should be somewhat on par with workers with a similar educational background.

To an economist, looking at qualifications and at job characteristics can be a helpful starting point in figuring the right salary. But there’s only one acid test: Are we attracting and retaining enough great teachers? My view is that we’re getting lots of great teachers, but we’re not getting nearly as many as we need. If you agree, then you should want higher teacher salaries no matter how the averages are calculated. If you disagree, you should be okay with the status quo.

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Gender hostilities, disparities among economics professors keep women from ascending ranks

My most recent post on the BROWN CENTER CHALKBOARD at the Brookings Institution.

Women receive 57 percent of the bachelor’s degrees in the United States, but only 52 percent of the doctorates. In looking at recent datafrom the National Center for Education Statistics, we find: Women receive only 23 percent of Ph.D.s in computer science; in mathematics and statistics, the share is 28 percent; in engineering, 23 percent. STEM fields are often a path to high-paying careers, and the presence of women in the professoriate can serve as a role model for both undergraduates and graduate students.

One might hope that the gender disparities in STEM fields are legacies of a bygone era, and that there is little active opposition to women in the professoriate today. Sadly, harassment of and hostility toward female academics continues—at least in economics, the area we know best. All this is illustrated by a major contretemps in economics set off by, of all things, an undergraduate senior thesis from Berkeley.

The story begins with Alice Wu’s senior thesis, “Gender Stereotyping in Academia: Evidence from Economics Job Market Rumors Forum.” Economics Job Market Rumors (EJMR) is a web forum notionally focused on discussing the job market for economics Ph.D.s, but more often a site for gossip and discussion by self-described internet trolls. Wu web-scraped text from a million-plus posts and then used machine-learning techniques to look for correlations. She found two main results: First, nine of the top 10 words predictive of a post about a woman are explicitly sexual references (The Washington Post even bowdlerized some of these terms); second, posts about women contain 43 percent fewer academic or professional terms and 192 percent more terms related to personal information or physical attributes. Observation of the EJMR site shows that these terms tend to be used in the context of a hostile or sexual comment about a female economist.

Discussions of economists and economics as an academic profession aren’t usually the stuff of headlines. The explosion came when Justin Wolfers wrote about Wu’s paper in the Upshot column of The New York Times, followed by a piece by Elisabeth Winkler in The Washington Post’s Wonkblog. Wolfers was blunt, writing that Wu’s paper “quantifies a workplace culture that appears to amount to outright hostility toward women in parts of the economics profession.” Winkler wrote, “Women economists are hardly surprised. …. Wu has now managed to quantify that misogyny using men’s own words.”

It should be understood that EJMR is, using the words of one prominent male economist, “a cesspool.” To be clear, there’s nothing subtle about EJMR: Postings go so far as to suggest sexual assault of named female economists. Anonymity on the internet permits the kind of behavior that would get one arrested if done in person. Despite this, some economists dismiss the problem as so-called locker room talk. As another prominent male economist has written, “I personally find the forum refreshing. There’s still hope for mankind when many of the posts written by a bunch of over-educated young social scientists illustrate a throwing off of the shackles of political correctness.”

Compared to other academic fields, economists have little sympathy for political correctness. What is surprising is how many economists still don’t think that gender-based hostility has any effect on the underrepresentation of women in the profession. This might be less concerning if the professoriate in economics were making significant progress toward gender balance, but this is not the case. Even though women slightly outnumber men in getting bachelor’s, men overwhelmingly outnumber women as economics concentrators. The figure below shows that about a third of first-year graduate students and new Ph.D.s in economics are women. These numbers have been essentially unchanged for two decades. So the input end of the pipeline to the professoriate is narrow, and not approaching gender parity.

Unfortunately, the pipeline is also leaky, and female Ph.D.s do not become assistant professors nor advance to tenured positions at the same rate as men, per the Committee on the Status of Women in the Economics Profession’s 2016 Annual Report. Women full professors still comprise less than 15 percent of full professors at Ph.D.-granting institutions (the green line in the chart below), implying a very small cohort of senior women who can act as role models and mentors for female grads and undergrads. This fraction has risen very slowly, increasing by about five points in 20 years. If the female proportion of full professors were to continue at this growth rate, it will reach the graduate-school level (30 percent) in about 2080. Approaching gender parity would probably require tackling the pedagogic and information barriers that appear to dissuade women from majoring in economics at the undergraduate level.

Pipeline for departments with doctoral programs: Percent of doctoral students and faculty who are women

Source: CSWEP 2016 Annual Report | Note: (T) and (U) indicate tenured and untenured, respectively.

The recent explosion following a memo widely viewed as hostile toward women in tech written by a Google engineer suggests that problems are not at all limited to the discipline of economics. We would all like to think that having the STEM professoriate reflect something like the gender balance in society will happen naturally, or that it will happen if only K-12 would somehow make math equally attractive to girls and boys, or that at least it will happen when STEM majors learn to attract more women. Unfortunately, female academics still have to deal with open hostility from some of their peers, and with a see-no-evil attitude from many more.

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Education programs and (un)selective colleges

My most recent post on the BROWN CENTER CHALKBOARD at the Brookings Institution.

The pipeline for training America’s teachers has been the subject of much discussion, with questions and disagreements about both quantity and quality. A largely overlooked aspect of the pipeline question asks which colleges train teachers. Today’s part of that question asks: Are education majors trained at relatively less selective colleges, or is the distribution of education majors pretty much the same as the distribution of other majors? The answer turns out to be the former. Graduates with education majors are disproportionately found at schools where students have lower SAT scores. The difference in SAT scores is large enough to be thought-provoking, at the least. (For a recent look at SAT scores for teachers see Goldhaber and Walch in EducationNext.)

Let me explain how we went about measuring this. Every university reports to the federal government the number of degrees granted in different disciplines. (Some universities leave blanks in their reporting forms, but in general the coverage is quite good.) Universities also report the 25th percentile and 75th percentile of SAT scores of their student body. We averaged the two SAT numbers, by subject, and then added together the scores for math and reading. That gives us our measure for selectivity of each college. Note we’re not looking at SAT scores of education or non-education majors separately; we’re looking at how competitive the college is.

Next we take the average of each college’s combined SAT score, weighted according to the number of education majors it graduates. This gives us what you might think of as an “education selectivity” score, or the average SAT score of admits at colleges that generate the most education majors. The education selectivity score penciled out at 1060 out of 1600. We did the same for non-education majors, producing a “non-education selectivity” score, giving a result of 1116.Let me explain how we went about measuring this. Every university reports to the federal government the number of degrees granted in different disciplines. (Some universities leave blanks in their reporting forms, but in general the coverage is quite good.) Universities also report the 25th percentile and 75th percentile of SAT scores of their student body. We averaged the two SAT numbers, by subject, and then added together the scores for math and reading. That gives us our measure for selectivity of each college. Note we’re not looking at SAT scores of education or non-education majors separately; we’re looking at how competitive the college is.

Education majors are trained at less selective colleges. In other words, relatively few come from flagship universities while more come from regional colleges with lower bars for entry. But is the difference large enough to be meaningful? The education selectivity score corresponds to about the 60th percentile of college-bound seniors in reading and the 55th percentile in math. The numbers for non-education majors are the 70th and 64th percentiles respectively. The combined difference is nine or 10 percentiles. Thus the difference is not gigantic, but it’s certainly large enough to be meaningful.

While there is a noticeable difference, there is also a great deal of overlap between the colleges that train education majors and colleges that train other disciplines. That’s not very surprising. After all, even colleges with big teacher training programs train students in many other majors as well. The picture here, using bell curves as approximations, shows the selectivity distribution for education versus non-education. While the selectivity difference is noticeable, so is the overlap.

Selectivity distribution for education versus non-education

The data presented so far is for the most recent year for which data is available, 2015. Technically, the selectivity gap between education and non-education graduates appears to have risen over the last decade, but just by a couple of SAT points. For all practical purposes, as shown in the next figure, the selectivity difference is quite constant.

Difference in SAT score for education and non-education majors, by year

In the data, the “education” category presented here encompasses a number of different majors within the field. There is some difference in college selectivity across such majors, but not really all that much. The selectivity numbers for “general” education training and “specific subject areas” are about 25 SAT points higher than for “specific levels and methods” and “special education.” I will admit I was a little surprised to find the slightly low numbers for special education, given how much a teacher needs to know in this area. One should remember, though, that these are selectivity numbers for colleges—not for the individual students who select specific sub-majors.

Having documented that the college pipeline for training teachers runs through less selective colleges, how concerned should we be? We certainly don’t need all teachers to major in education at Harvard. (This happens to be a good thing, since Harvard doesn’t have an education major—although students can earn a Massachusetts middle/secondary school teaching certificate on top of their regular major.)

More-selective colleges do generally provide more academic opportunities than their less-selective brethren. They also often provide better networking opportunities. Both these elements contribute to developing future education leaders in education. (Do remember that alternative certification programs and master’s degrees are not included in any of these numbers.)

What’s more, the difference in selectivity is higher at the upper end of the selectivity distribution than it might appear based on the average numbers. The 90th percentile numbers for college selectivity are 1195 for education majors and 1380 for non-education disciplines. Those numbers correspond to SAT percentiles of 80th and 75th (education majors) versus 94th and 92nd (non-education majors), respectively. That’s starting to be a much larger difference.

So while the lower selectivity of colleges that train teachers is not so large as to be a cause of panic, it is large enough to think about whether this is the best way our system should run.

Isabel Steffens provided research assistance for this post.

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