Stephan, final thoughts

I've finished the book.  Here are some parting thoughts.

First, I want to mention an important point that she made earlier in the book but I forgot to blog:  Research is a classic public good, in economics jargon.  Once the results of research are out there it's impossible to control who will benefit from the information, which means that the producers of the good cannot capture all of the benefit.  In most cases this means that we have an incentives problem, because if people can't capture the benefits they won't produce it and then society won't benefit.  Science solved this with the priority system:  The first to publish something gets credit that will benefit their career and funding.  This thus incentivizes people to put information out there as quickly as possible, for the benefit of themselves as well as everyone else.

Second, as far as her recommendations later in the book, I largely agree that we need a looser coupling between the production of research and the production of scientists.  Ideally, all of our scientists should be produced in environments that produce research, but we don't need to produce all of our research in environments that produce scientists.  To that extent, I support the idea of research institutions that don't have graduate programs.  However, I would caution against using national labs as the model, as Stephan does in her final chapter.  While the national labs produce great research, being federal institutions they have absurd overhead rates and procurement bureaucracies that rival Soviet central planning for inefficiency.  I have no easy prescription for how to create effective research institutions that are not educational institutions but aren't federal either (a quick look at federal contracting shows that there are plenty of ways to set up bloated and inefficient systems outside of the federal government), but I do think we should be wary of encouraging DOE to metastasize even more than it already has.

Maybe one intermediate step would be to make it easier for university researchers to support technicians and staff scientists on grants.  This is easier said than done, but having it as a target would keep the academic science community churning out just as much research (if not more) without the wasteful by-product of PhD over-production.

On the other hand, I am deeply skeptical of her proposal to give fellowships to students and then let graduate programs compete for them.  Partly there's the fact that the programs would have an incentive to structure projects in a way that gets results out quickly and gets students out quickly (without the formative "time in the wilderness" that students spending in deep frustration but also deep learning).  However, I recognize that that may reflect my biases as an old man.  A bigger problem is that it would be tantamount to putting the federal funding agencies in charge of graduate student admissions.  While this would certainly be great from a research standpoint (putting all sorts of information in one central place for subsequent analysis) I think there would be all sorts of political insanity in what would follow.

All in all, this book was a good, insightful read.  For those who aren't academic scientists, the first several chapters do a good job of describing how the system works.  For those who are academic scientists, the last few chapters (starting with the one on the job market) do a good job of raising issues that we have not grappled with as well as we could/should.

Stephan: An alternative to the "alternative"

One periodically hears the Right-Thinking Classes talk about "alternative careers for PhDs."  This sort of talk is a joke on a number of levels.

For starters, some of them include "teaching at a 4-year college without a graduate program" as an "alternative career."  That just shows how narrow their conception of academia really is.

Of course they include working in industry as an "alternative."  It is rather strange that the most common job (when one finally lucks out after years of postdoc positions) is the "alternative."  They seem to be aware of this, and if they talk too much about industry in a roomful of postdocs somebody will eventually say "Oh, yeah?  Where are all of the companies clambering to hire us?"

But the true darlings of the Right-Thinking Classes are the trio of k-12 science teaching, science journalism, and science policy.  Now, yes, of course, we want to have scientifically literate k-12 teachers, especially (but not exclusively) in high schools.  And of course it would be nice if more journalists knew more about the science stories that they (sometimes) cover.  And who wouldn't like to know that the people making decisions about nuclear power regulation or approval of pharmaceuticals are knowledgeable about science?  Alas, there are only so many jobs in science journalism and science policy, and k-12 teaching requires a lot of other traits besides a science degree.  It isn't for everyone.

None of this stops the Right-Thinking Classes from periodically yammering about these paths.  I like Paula Stephan's response on page 181:

Yes, there is an apparent shortage of math and science teachers in the United States.*  But surely there is a more efficient way to increase the supply than by transforming people who have invested seven years of training in graduate school and another three to four as a postdoc into teachers.

Ooh, she is just ASKING to be disinvited from any further panels at funding agencies and professional societies.  Well, if she gets tired of those events, instead of getting herself disinvited she can just transfer the invite to me.  I'll be happy to consume fancy hors d'oeuvres while telling people things that they don't want to hear.

*To my knowledge, this is one of the few areas where the "shortage" rhetoric might have a factual basis, though the shortage has a lot more to do with the number of people who will accept those working conditions at the salary on offer than the number of people getting science degrees.

One more thing about Stephan and the economic return on a PhD

To her credit, Stephan's comparison of PhD earnings compared to BA/BS earnings is better than most I've seen.  For instance, she compares BA/BS holders who have been out of school for a few years to PhD holders who are new in the job market, to reflect opportunity cost. Not everyone does that. Also, she limits her analysis to PhDs and breaks them down into three categories, whereas I've seen analyses that lump together ALL doctorates.  As much as I'd love to think that my compensation is comparable to that of a dermatologist, the sad fact is that it isn't.

There is one weakness, though, albeit one that is common to all such analyses:  The average person with a PhD was probably more talented when they finished college than the average person who majored in the same subject but didn't get a PhD.  Note the "on average" part.  Of course there are dumb PhDs (just come to a faculty meeting...) and of course there are brilliant people who never went to grad school.  And of course there are people who never got a graduate degree but made outstanding use of people skills that aren't a direct part of a research degree (though they can of course contribute to research success) and there are people who got a PhD but can't work with others, and yadda yadda.

But with all of those necessary disclaimers out of the way (to head off a flood of anecdotes that people always feel the need to pour forth when you make a statement comparing two groups "on average"), it's likely that most (not all) of the people who get PhDs were in the upper tier of the talent pool before starting grad school, and they probably could have done quite well in the job market even without a PhD.  Her analysis doesn't account for that.  To be fair, nobody else does either, probably because it would be really, really hard to account for that.  Still, it's a caveat that needs to be applied when looking at those income premiums.  You don't know how much is a premium for the PhD itself and how much is a premium on traits that they possessed prior to the PhD and differentiate them from the average person with a BA/BS.

Seriously, guys, she's turning me into a Newt! Help! Help! I'm being transmuted!

Top of page 164:

Predictions of shortages of scientists and engineers occur with some frequency, despite evidence to the contrary. 

Later on that same page:

But getting egg on their face did not stop the forecast pundits.

Page 165:

Third, shortages are often predicted by groups who have a vested interest in atttracting more students to graduate school and into careers in science and engineering.

Wait, she thinks that people's pecuniary interests might affect their forecasts?  What is she, an economist or something?  Oh, right.

Page 168:

To quote the American Institute of Physics, "The proportion of new PhDs accepting postdoctoral positions has been a better job market indicator than the unemployment rate for PhDs, which is traditionally low and does not fluctuate a great deal."

AIP has always been good at putting out reliable statistical data.  The same cannot be said for APS.

Pages 168-169:

More generally, the proportion of new PhDs with definite plans to take a postdoc generally increases when the size of the graduating class increases, consistent with the idea that job market prospects are depressed due to an increase in supply.

She's just begging to be burned at the stake.

We have found a witch; may we burn her?

On page 163 Paula Stephan questioned the premise of the sweet, sweet "STEM pipeline" money:

The number of individuals receiving PhDs also depends on underlying demographics and college graduation patterns.  For example, the large increase  in the number of women receiving PhDs is due in large part to the increase in the number of women graduating from college, not to a change in the propensity of those going to college to get a PhD.41 The same is true for underrepresented minorities.  Indeed, the most effective way to increase the supply of underrepresented minorities receiving PhDs is to increase the number receiving bachelor's degrees.  This is not a trivial observation: a policy maker would achieve larger increases by building the base of students eligible to go to graduate school than by investing, as many institutions do, in changing the propensity of those who graduate to go to graduate school.

In other words, the best way to make progress at the graduate level is to make progress at the undergraduate level.  But the best way to make progress at the undergraduate level would be to make progress in k-12.  And progress in k-12 would be easier if we improved underlying social conditions, because there are plenty of things in a person's environment that matter more than their school.  And that takes us to problems that are hard for anyone to solve and are impossible for the scientific community to solve.

Also, the 41 in the quote is for a footnote, in which Stephan breaks it down more precisely and says:

Richard Freeman estimates that 70 percent of the increase in the ratio of women to men getting PhDs is due to growth in the ratio of women receiving bachelor's degrees relative to men receiving bachelor's degrees.  Likewise, 63 percent of the increase in the ratio of underrepresented minorities to non-minority PhDs is due to growth in the ratio of minority to non-minority bachelor's degree recipients.  Source: Freeman's tabulations from data obtained from the Survey of Earned Doctorates (National Science Foundation 2011c and the Appendix) and the U.S. Department of Health, Education, and Welfare.  See Stephan 2007b.

"Stephan 2007b" refers to a presentation at this meeting, but I cannot find a link to the presentation itself.

Stephan, Chapter 7

I'm several pages into the chapter on the job market for scientists.  Full credit to Stephan:  She tries to make her comparisons as apples-to-apples as possible.  For instance, on page 155 she doesn't show data comparing the salary of a new PhD with a new BA/BS recipient.  Rather, she compares PhDs 0-9 years out of grad school with BA/BS recipients ages 25-34, when they have a few years of work experience.

A few interesting things so far:
1) Although engineering PhDs generally make more than physical science PhDs, who generally make more than life science PhDs, the early-career income ratios (PhD salary in each category divided by BA/BS salary in each category) pretty much track each other over time.  All three types of PhDs can seek employment in multiple sectors, so they all seem to track the overall economy in tandem rather than the fortunes of any one particular sector.

UPDATED: 2) The PhD premium (relative to a BA/BS) is real but volatile and (apparently) declining.  She has data through 2006, showing that the PhD premium for an early-career life science PhD was barely 5%.  For physical science it was about 25% in 2006, and for engineering it was about 40% in 2006.

The volatility makes sense for a specialized credential attained by small numbers of people.  You'd expect it to be risky.

3) The later-career PhD premium is also real and somewhat more stable but still not what it used to be.  The ratios also converge, probably because people in every category branch out into more types of jobs (including management) as they progress in their careers.  An engineer working in management at a biomedical device firm probably doesn't make much more than a similarly skilled manager who works in the same firm but has a PhD in biology.  Either they know how to make their teams succeed or they don't.

4) You're still better off with an MBA.

5) For all the talk of scientists only caring about science, PhD production tracks the unemployment rate several years earlier (people are more likely to stay in school if jobs are hard to get) and the salary prospects for their field several years earlier.

It's almost as though scientists were human beings who responded to resource scarcity and incentives.

Stephan, chapter 6

Chapter 6 focuses on grant funding for university research.  The main takeaway is freaking obvious but needs repeating: The US system is highly competitive and keeps people on their toes to be productive, but it also discourages risk-taking.  The European system tends to be less competitive and may leave more room for risk-taking, but it also leaves room for sloth, and it puts the power in the hands of the senior scientists because of it is easy to keep getting funded then it is easy to get entrenched.  And it sounds all well and good and idealistic to just say "On, we will just take the best of both!" but you can't easily separate upside from downside.  If I could separate upside from downside then instead of designing a better science funding system I would design a chocolate cake that tastes incredible but doesn't make you fat no matter how much you eat.  And then I'd put Zombie Reagan in charge of balancing the budget.

Stephan also notes that "MOAR MONEY!" is no panacea.  The NIH budget doubled and it was great while the party lasted, but it also led to schools building up massive infrastructure to cash in on a growth model that didn't last. Which, in the end, made the pyramid scheme worse rather than better.

Damn those unintended consequences! This chapter should be required reading for everyone in every field ever.

Stephan, first few chapters: Workforce issues

Paula Stephan's book is hard to blog because it is detailed and descriptive rather than argumentative.  It's an interesting read, painting a very wide and detailed picture of how science works, but it's hard to pick out points to ponder or grapple with because it's not about Big Points (which is fine).  The part about intellectual property was interesting:  According to page 50, data shows that universities get more patent revenue for themselves when they let their faculty keep a larger share of the revenue (because their faculty have more incentives to commercialize) but the universities that give a larger share of revenue to faculty don't actually produce more patents.  The difference, then, must be the type and quality of research that they generate, its commercial feasibility, and the aggressiveness of their faculty in going beyond the patent office and actually pushing their idea to market.

On page 68 I learned that one reason (though hardly the only reason) why US university labs rely more on grad students and postdocs while Europeans rely more on staff scientists and similar sorts of personnel is that in the 1980's NSF started pushing faculty to put grad students on their grants rather than technicians.  I suspect that part of the reason was economic, but only partly so:  While a grad student will just about always receive less in salary and benefits than a technician (especially an experienced technician), some universities charge massive tuition for grad students and that tuition then gets covered by the research grant supporting the student.  Consequently, while at some schools the economics will favor the use of students by a wide margin, at others the margin may not be quite as wide.  Moreover, depending on their level of training, level of experience, personal abilities, and opportunities for development, a technician may be more useful than a grad student--the grad students may ultimately go farther as scientists, but it takes a while to get them there, whereas a good technician can keep a project moving forward on a consistent basis.  I suspect that part of the reason for NSF's preference is that they have long had a mandate to expand the scientific workforce because of an alleged crisis in STEM, and supporting students will do that, whereas supporting technicians will simply keep the labs humming along and producing mere science.  And this focus on students apparently started in the 1980's, which is when "A Nation At Risk" came out.

(And let me assure you that I don't buy into a dichotomy:  Clearly the world needs good lab techs AND students training to be scientists, but the answer then is to fund projects that have people in whatever mix of roles makes sense for the success of the project, not a mandate to endlessly expand the STEM workforce.)

ADDENDUM: I decided to look for the original source for the assertion about NSF.  It's a 1998 interview with then-NSF Director Rita Colwell by Science magazine.  Here's the key quote:

On a recent report of a Ph.D. glut in the life sciences: 

In the 1980s, NSF asked investigators to put graduate students on their research budgets, saying that it preferred to fund graduate students rather than technicians. But as often happens, the pendulum swung too far. There needs to be a balance. Well-trained technicians are needed to run equipment and labs, and what better way to provide opportunities for them than to build it into research grants. 

There's great respectability for those who want to be technicians, but we don't give them the opportunity. We've made it a sign of failure if you don't get a Ph.D. Other countries don't have this [negative] attitude. … With all the emphasis on graduate students, I'm not so sure that the question we're facing is one of overproduction. I think we have to look more closely at how we're using our resources. We've created a situation in the career pipeline where there is a bulge at the end of a postdoc and no place to go.

Even in 1998, people were talking about PhD gluts.  All of this has happened before and will happen again.  Of course, that was around the time that NIH doubled its research spending, so for a while things were good for life sciences PhDs.  But exponential growth can only go on for so long.

Next book: How Economics Shapes Science by Paula Stephan

The next book will be How Economics Shapes Science by Paula Stephan.  I am told that it's an excellent read, and talks a lot about job markets and research funding in science.