The Mathematics of the Ph.D. Glut
I recently had a conversation at a get-together with someone whose sister had just started a Ph.D. program in biology. I discussed some of the unpleasant realities of graduate school today and referenced Brian Vastag’s July 7, 2012 article in the Washington Post “U.S. pushes for more scientists, but the jobs aren’t there”.
I have touched briefly on the Ph.D. glut in two previous articles — The Government Did Too Invent the Internet and Top Secret Rosies: The Female Computers of World War II Video Review. Since many people including prospective graduate students still don’t realize there is a Ph.D. glut, this post gives more details on the Ph.D. glut as well as more references in the appendices below.
The Ph.D. glut is certainly a bad thing for graduate students and others who want to become scientists or mathematicians. There is also considerable and growing evidence that, far from accelerating the rate of scientific and technological progress, it has slowed the rate of progress and with it the growth of the US and global economy.
Yes, There is a Ph.D. Glut
Brian Vastag’s article represents one of the few times the Ph.D. glut and dismal career prospects in scientific research has been reported in a major media outlet like the Washington Post. In general, the major “mainstream” media reports on explicitly claimed or implied shortages of scientists, Ph.D., and all manner of STEM (Science, Technology, Engineering, and Math) workers, even though a Ph.D. glut has been the reality in most fields including mathematics and physics since about 1970 (forty-two years ago!). Even more remarkably, extensive, well-documented, verifiable, and steadily growing information on the Ph.D. glut has been readily available on the Internet since the mid 1990s (fifteen years ago!). Nonetheless both reporters and op-ed piece writers at major media outlets seem unable to use Google or other search engines to find this information!
Vastag’s article focused primarily on the current situation in biology and medicine. However, a Ph.D. glut has been the reality in almost all scientific and mathematical fields since about 1970. From time to time, the situation gets especially bad and attracts some comment. This happened in physics in 1970 and in 1992/1993 (I received my Ph.D. in Physics in 1993). The National Institutes of Health’s budget was doubled in the 1990s resulting in the recruitment of huge numbers of graduate students who now form an especially large cohort of Ph.D.’s unable to find jobs. In addition the so-called fiscal stimulus in 2009 included several billion dollars for the NIH. Both of these developments translated into more graduate students and more post-docs, but few, if any, permanent positions. Thus, biology and medicine suffers from an especially large glut at present. Smaller but still substantial Ph.D. gluts exist in virtually every STEM field.
It is worth considering some basic arithmetic. A typical professor has at least two graduate students at any time, sometimes many more. A Ph.D. programs in the United States usually lasts 5-7 years. A professor will take on and “advise” students from about age 30 as a starting assistant professor to retirement or death (say 65). This means a typical professor produces at least ten Ph.D.’s during his or her academic career in his or her academic specialty. If all the students pursue an academic career, certainly the ambition of many, this means an additional nine (9) new positions must be created over 35 years on top of the professor’s own position. Even with a fifty percent drop out rate, at least four or five new positions must be created to absorb the new Ph.D.’s. Of course, nothing of the kind has been the case for over forty years. This requires an exponential increase in the funding for an academic field relative to the size of the economy as a whole, something that occurred only briefly during and after World War II and in the early post-Sputnik days of the Cold War.
Over thirty-five years, increasing the number of faculty members in a scientific field by a factor of ten (10) corresponds to a 6.8 percent annual growth rate. A five-fold increase corresponds to a 4.7 percent annual growth rate. The World Bank gives the annual growth rates of the United States Gross Domestic Product (GDP) for the years 2007-2011 as 1.9 percent (2007), -0.4 percent (2008), -3.5 percent (2009), 3.0 percent (2010) and 1.7 percent (2011). It is rare for a GDP to grow by more than five percent in one year, let alone continuously for 35 years.
The two figures below show the United States Real Gross Domestic Product (GDP) data from 1947 to 2011 from the St. Louis Federal Reserve which is one of the major sources of official economics statistics in the United States. One can easily see that the annual real GDP growth rate in the United States has rarely exceeded the 6.8% rate needed to absorb the Ph.D. production. In fact, the average GDP growth (smoothed red curve) is substantially lower. Note also that the real (inflation-adjusted) growth rate of the US economy has been declining for decades.
The raw US real GDP data from the St. Louis Federal Reserve and the GNU Octave script used to generate the plots is provided below in Appendices III and IV.
Figure 1
United States Real GDP
Figure 2
US GDP Growth Versus PhD Production
Note that for illustrative purposes I am actually understating the size of the problem. First, I assumed seven years to a Ph.D. whereas the range is typically five to seven years. More importantly, I ignored that if each student becomes a professor and takes on graduate students as well, creating even more Ph.D.’s, the growth rate will be even greater than ten times in thirty-five years! This is an exponential process like the exponential overpopulation of rabbits without a predator.
As I can attest from personal experience, STEM students in the United States, despite being mathematically inclined, often do not perform the arithmetic above and think through what it means. This does not just happen. As mentioned, the major “mainstream” media in the United States has been filled for over forty years with repeated false claims of a shortage of scientists and mathematicians. Most science and mathematics education is very positive and never mentions the Ph.D. gluts. Similarly, career placement offices at many universities and colleges, while providing information on applying to graduate school, rarely mention the Ph.D. gluts in most STEM fields.
Political leaders in both major political parties such as President George W. Bush (Republican) and President Barack Obama (Democrat) frequently promote STEM shortage claims and may sincerely believe them. Both business leaders and senior scientists frequently claim or imply a shortage of Ph.D.’s and/or scientists (see the Wall Street Journal editorial “Our Ph.D. Deficit” by Lockheed CEO Norman Augustine and Nobel Prize-winning physicist Burton Richter below, for example).
Ph.D.’s and High Tech Jobs
It is important to understand a subtlety of STEM worker shortage claims in discussing both the actual Ph.D. glut and the Ph.D. shortage claims. Most Ph.D.’s receive specific training in their specialty. In almost all academic disciplines, it is factually false, demonstrably false that there is a shortage of Ph.D.s trained for each discipline.
When high tech companies and their lobbyists claim there is a shortage of skilled high technology workers, they usually use general language such as “there is a shortage of engineers,” “there is a shortage of programmers,” or “there is a shortage of technology talent.” However, when pressed about seemingly highly qualified, often older workers who cannot find jobs, they refer to both extensive and very narrowly defined specific skills that they claim they must have. Older often means over forty or even over thirty-five. As in the case of the forty year old husband of Jennifer Wedel, who confronted President Obama about the shortage claims, these older workers who encounter problems finding work despite seemingly strong qualifications are often not very old.
One can always assert a shortage of workers by narrowly specifying the skills required. Consider digging a ditch. Suppose I demand that prospective ditch diggers must: have at least three years paid professional experience digging ditches using the Big Box Mart Super Squabo 2.0 shovel which my company uses. A Black and Decker shovel won’t do. Not just any ditch digging, it must be three years paid professional experience digging ditches for gas pipelines in a medium sized city with a population from 50-200,000 people. Ditches for sewage lines won’t do. Digging ditches for gas pipelines in New York City won’t do because New York has a population over 200,000. And so on. Even though ditch diggers are surely not in short supply, I can find a shortage by narrowing my standards for ditch diggers. This sort of narrowing of standards is surely a symptom of either gross irrationality or an actual surplus of qualified applicants that makes it possible to impose such narrow requirements.
Of course, most people know or believe they know enough about ditch digging and other low status, frequently manual jobs that this sort of argument would provoke only laughter and disbelief. Hence similar worker shortage claims about low status, generally lower paying jobs in the United States usually involve claims that spoiled Americans are unwilling to do such hard manual labor. It is harder to evaluate the plausibility of such ultra-narrow job specifications where technical jobs such as software engineering are concerned.
A recent article by Wharton business school professor Peter Cappelli Why Companies Aren’t Getting the Employees They Need: The conventional wisdom is that our education system is failing our economy. But our companies deserve a lot of the blame themselves. discusses this excessive focus on specific skills.
The alleged shortages of high technology workers such as software engineers are thus difficult to disprove due to the specific skills issue. But in the case of Ph.D.’s, a Ph.D. represents a certification that a Ph.D. holder is qualified and trained in their specialty. Thus, this excuse does not work for Ph.D.’s, whether biologists, physicists, or mathematicians, who cannot find work in their field. It is really factually untrue, not a matter of opinion, that there is a shortage of Ph.D.s either in general or in most specific fields such as biology, physics, or mathematics where shortages are often claimed or implied.
Where are the Fact Checkers?
It is striking that the Ph.D. shortage claims have been widely repeated for over forty years by most major media including the New York Times, the Wall Street Journal, and many other companies and organizations although these claims are demonstrably false and have been demonstrably false for over forty years. Extensive information on the falsity of these claims has been available on the Internet for about fifteen (15) years. Yet, so far, articles like Brian Vastag’s recent article in the Washington Post have been extremely rare.
Newspapers and similar organizations are supposed to have fact-checkers whose job is to verify facts. The Ph.D. glut is really a matter of fact, not opinion. It can be verified by a small amount of serious investigation. What happened to the fact checkers?
Conclusion
Yes, there is a Ph.D. glut. In fact, there has been a Ph.D. glut for over forty years, since about 1970. This is inherent to the structure of the current government funded system of scientific research. It is a matter of public policy. Sometimes the Ph.D. gluts get especially bad as in physics in 1970 and 1992/1993 and now in biology and medicine, but there has always been and are sizable Ph.D. gluts in almost all scientific disciplines since 1970.
The remarkable persistence of Ph.D. and scientist shortage claims in the major “mainstream” media should raise questions about the reliability and independence of the major media. This evident lack of basic fact-checking is not what one should expect of a “free press.”
Finally and most importantly, there is considerable evidence that the Ph.D. glut has not worked. Far from accelerating the rate of scientific and technological progress, it has contributed to a slowing rate of progress.
As can be seen in the Federal Reserve data on real GDP, the real annual growth rate of the United States economy has declined over the last forty years. This is a long term trend. This decline probably reflects the limited scientific and technical progress in most fields outside of computers and electronics, especially in power and propulsion technology, since 1970.
© 2012 John F. McGowan
About the Author
John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing video compression and speech recognition technologies. He has extensive experience developing software in C, C++, Visual Basic, Mathematica, MATLAB, and many other programming languages. He is probably best known for his AVI Overview, an Internet FAQ (Frequently Asked Questions) on the Microsoft AVI (Audio Video Interleave) file format. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech). He can be reached at jmcgowan11@earthlink.net.
Appendix I: Selected Internet Resources on the Ph.D. Glut
“U.S. pushes for more scientists, but the jobs aren’t there”
The disposable academic: Why doing a PhD is often a waste of time from The Economist, December 16, 2010
What Scientist Shortage? The Johnny-can’t-do-science myth damages US research by Beryl Lieff Benderly, Columbia Journalism Review, January/February 2012
We Don’t Need More Scientists—We Need Better Ones A chemist responds to Slate’s David Plotz’s claim that not enough students are going into science and engineering. by Derek Lowe in Slate, June 17, 2012
Scientist shortage? Maybe not by Greg Toppo and Dan Vergano, USA Today, July 9, 2009
How and Why Government, Universities, and Industry Create Domestic Labor Shortages of Scientists and High-Tech Workers
By Eric Weinstein
Toil, Trouble, and the Cold War Bubble: Physics and the Academy since World War II
MIT Science Historian David Kaiser Presentation at the Perimeter Institute
PhD’s Org’s Collection on Links and Resources on Scientist and Ph.D. Shortage Claims
Women in Science by Philip Greenspun
Appendix II: Selected Internet Examples of the Never Ending STEM Shortage Claims
Our Ph.D. Deficit (Op-Ed by Norman Augustine and Burton Richter, Wall Street Journal, May 4, 2005)
Heading Off a Ph.D. Shortage. by John Vaughn and Robert Rosenzweig in Issues in Science and Technology, v7 n2 p66-73 Win 1990-91
EDUCATION; Shortage of Ph.D.’s Imminent, Report Says (January 24, 1990)
Appendix III: US REAL ANNUAL GDP DATA FROM 1947 TO 2011
This is data downloaded from the St. Louis Federal Reserve at http://research.stlouisfed.org/fred2/series/GDPC1/.
1947 1793.3 1948 1868.2 1949 1838.7 1950 2084.4 1951 2192.2 1952 2305.3 1953 2314.6 1954 2379.1 1955 2535.5 1956 2582.1 1957 2589.1 1958 2654.3 1959 2782.8 1960 2800.2 1961 2975.3 1962 3097.9 1963 3262.2 1964 3429.0 1965 3720.8 1966 3881.2 1967 3977.6 1968 4174.7 1969 4259.6 1970 4253.0 1971 4442.5 1972 4750.5 1973 4948.8 1974 4850.2 1975 4973.3 1976 5187.1 1977 5446.1 1978 5811.3 1979 5884.5 1980 5878.4 1981 5950.0 1982 5866.0 1983 6320.2 1984 6671.6 1985 6950.0 1986 7147.3 1987 7451.7 1988 7727.4 1989 7937.9 1990 7982.0 1991 8062.2 1992 8409.8 1993 8636.4 1994 8995.5 1995 9176.4 1996 9584.3 1997 10000.3 1998 10498.6 1999 11004.8 2000 11325.0 2001 11370.0 2002 11590.6 2003 12038.6 2004 12387.2 2005 12735.6 2006 13038.4 2007 13326.0 2008 12883.5 2009 12873.1 2010 13181.2 2011 13441.0
Appendix IV: GNU Octave Script Used to Make Figures
This is the GNU Octave script used to process the US REAL GDP data from the St. Louis Federal Reserve and generate the figures in the article.
% script to compute annual growth rate of US REAL GDP
%
% (C) 2012 By John F. McGowan, Ph.D.
%
data = dlmread('us_real_gdp.txt'); % federal reserve data
year = data(:,1);
gdp = data(:,2);
figure(1)
h1 = plot(year, gdp);
set(h1, 'linewidth', 3);
title("US REAL GDP (CHAINED 2005 DOLLARS)");
xlabel('YEAR');
ylabel('BILLION DOLLARS');
delta = conv(gdp, [1 -1]);
growth = delta(1:end-1) ./ gdp(1:end);
[p, s] = polyfit(year(2:end), growth(2:end)*100, 3);
fit = polyval(p, year(2:end));
target = ones(size(fit))*6.8; % need average growth rate of 6.8% to absorb new Ph.D.'s
figure(2)
h2 = plot(year(2:end), growth(2:end)*100, '+', year(2:end), fit, '-r', year(2:end), target, '-g');
set(h2, 'linewidth', 3);
title("US GDP ANNUAL REAL GROWTH RATE");
xlabel('YEAR');
ylabel('PERCENT');
legend('DATA', 'SMOOTHED', 'PHD GROWTH RATE');
disp('ALL DONE');
Isn’t the silence on this report deafening.
What is to explain suddenly all the efforts of American striving ending up unemployed and in the gutter?
It must be some ugly reality too loathsome even for fraternizing.
I would have to assume the joke is really on the bearer of the mathematical goods in media pop stands, publications and educational edifices.
The joke of it is certainly not lost on the better knowing of the people.
You know, after you threw away those university aspirants’ electric car and make a documentary about it with old and new Hollywood celebrities; you have to figure a PhD glut for the consequences of a nation throttled in a struggle to the death.
They are nothing but war refugees displaces from active roles making this country live with what would have been their lives and talents.
Shame. I would in all sincereness recommend this obituary notice style of reporting not be waved in front of its victim’s faces so.
Until editing function is authorized or restored it will edit here:
Paragraph 1
line 2: ..and made a documentary about it..
Paragraph 2
line 1: ..They are nothing but war refugees displaced..
I don’t think your post (and the previous one on the same subject) proves anything. YOu don’t need to do any math to support the assertion that in most scientific fields there are more PhDs than the academic market can absorb. This can be explained by the the need of cheap labor, but also by the fact that all graduating PhDs are not academic material. Indeed, only a small percentage is. In my experience, it is even smaller than the percentage that is actually placed. If anything, I’d say there’s certainly a shortage, not a glut of qualified PhDs in academia. And I don’t see any empirical evidence that excess supply or competition has led to more conformity. In the fields I follow (Finance, Statistics) there seems to be as much disruptive innovation and open debate as ever.
Regarding the shortage of generic qualified STEM candidates in industry I totally, completely disagree with you. Over 12 years, I have interviewed around 150 candidates for research positions in the Mathematics department of a large industrial research center, and in an alternative investments firm. As an example, my company receives 20,000 resumes/yr, of which more than half are for technical positions. Of these 10,000 candidates, we end up interviewing less than 200, and hire maybe 20. I suspect that not all 9,980 other candidates will find a job. Does it prove the existence of a glut? I don’t think so. First, it’s just shocking how many pedigreed people don’t even know the basics of their purported field; Indeed, they don’t know the basics of what’s on their own resume. Second, even if they do know the basics, they may not know the advanced subjects for which they are interviewed. Your shovel analogy misses the mark: shoveling falls in the category of nonskilled job (a job that can be taught in one day). It takes years to convert an algebraist into an analyst.
Summing up: there’s shortage of qualified people, both in academia and in industry. And there’s a glut of people who is neither good enough for academia, nor current or flexible enough for industry.
You seem to say that there is a fruit glut. But if you look closely, the market for apples clears, and the demand for oranges is zero. They’re not substitutes.
You get 20,000 (!) applications for 20 positions and you feel there’s no glut? What planet do you live on?
What you say is that the universities are pumping out armies of PhDs who do not know stochastic PDEs, C++, and whatever else the hedge funds require from their yuppie quants. That is quite true. The universities are pumping out algebraists, geometrists, probabilists, and all sorts of other freaks, who have spent 20-25 years of their lives learning how to grade (and write) homeworks and how to pump out recondite papers which nobody reads or would conceivably want to read. Pumping out papers is not the same as doing research. The difference is that actual research aims at solving actual problems, while pumping papers aims at solving imaginary problems, mostly the problem of how to publish enough papers to obtain tenure.
Meanwhile the hedge funds want yuppie quants who can write flash-trading software so the hedge funds can leech more money from the productive economy. Plus SPDE experts who are willing to write impenetrable papers justifying the activities of the quants.
As for the software firms, the situation there is laughable, because the software firms want people with experience in programming, rather than people with experience in grading homeworks and pumping out recondite papers. Which nobody will read. That is why in Silicon Valley they say that those who go to grad schools are the chumps who will end up working for the dropouts who dropped out, started a business, wrote code 24-7 for a few years, and made a buck.
The software industry is really an entertainment industry, but at least it’s making something, as opposed to banking industry, which is institutionalized vampirism.
As for the PhD system, it is indeed in trouble. The PhD students have two functions: to serve as cheap qualified labor, and to perpetuate the PhD cult. Professors only teach pumping out papers, because that’s what they know. Well, there sure seems to be a glut of homework graders and paper-pumpers out there.
Could higher education be the next bubble? But then, by now one gets the impression that everything is a bubble.
The fundamental problem with higher education, it seems, is that America – and, apparently, much of the world along with America – has lost sight of two of its traditional ideas: That one is responsible for making one’s own job, and that one is responsible for one’s own education. That’s the problem. It has been palpable for more than half a century. It is now acute. And it’s not going away.
This article addresses the market for Ph.D. mathematicians specifically:
Mathematicians and the Market
Geoff Davis, Mathematics Department, Dartmouth College
Notices of the American Mathematical Society, Vol. 44, No. 10, pp. 1307-1315, 1997.
http://www.geoffdavis.net/papers/market/market.html
Geoff Davis’s Home Page
http://www.geoffdavis.net/
Sincerely,
John
Ditch digging–Been there, done that
STEM Ph.D.–Been there, done that (19 months, not 5 years)
Academic position at a major university–Been there, done that and quit because I was a lousy teacher!
(If you find these claims hard to believe, then read the About Me page at my web site)
Been unable to find a job–NEVER been out of work a day until I retired voluntarily at age 63.
Why didn’t the glut sideline me? I believe it was not because my education made me a rocket scientist (my doctoral research was applying non-linear partial differential equations to the failure of a Thor Able Star 2nd stage rocket motor).
I believe I was not sidelined because my education taught me that solving other peoples problems was fun for me and profitable for them.
Good article John, and I agree with you. I think our education system in general has lost its way.
When I was a kid in high school we learned skills that could be applied to the job market. I remember taking metal shop where I did welding and worked with molten metal.
There was auto shop where I tore down engines and rebuilt them.
There was wood shop where I became familiar with all the tools and types of woods.
All these classes are gone from our public schools….
I know this is somewhat off-topic but you are making the point schools are graduating students that have no jobs waiting for them.
When you get into highly intellectual fields you end up competing for jobs on a global basis and well, you know how that goes.
A minor correction.
Norman Augustine was retired chairman and CEO of Lockheed Martin in 2005 when he wrote the “Our Ph.D. Deficit” op-ed in the Wall Street Journal. He retired from Lockheed Martin in 1997.
Norman Augustine served as chairman of the 2005 “Rising Above the Gathering Storm” committee. Officially, the
COMMITTEE ON PROSPERING IN THE
GLOBAL ECONOMY OF THE 21ST CENTURY
NORMAN R. AUGUSTINE (Chair), Retired Chairman and CEO,
Lockheed Martin Corporation, Bethesda, MD
Sincerely,
John
In this kind of discussion you need to mention the fact that a shortage is generally relative to how much you’re willing to pay.
It is perfectly possible for these to be a serious shortage of $10/barrel oil and at the same time a gigantic glut of $200/barrel oil.
Something similar is true for PhDs.
I don’t think it is correct to apply textbook microeconomic concepts and theories like supply and demand and prices to most markets for Ph.D.’s today. The textbook microeconomic theories generally assume a market with many competing buyers and sellers, none of whom has any significant monopoly power. Further, textbook microeconomics implicitly assumes that accurate information on the goods and services being bought and sold is freely available or so inexpensive as to be essentially free.
In the case of biology and medicine, for example, there is essentially one buyer in the United States: the National Institutes of Health (NIH). It is true that there are some biotech firms and pharmaceutical company research and development divisions, but these are closely tied to NIH as well. It is not correct to think of these as independent competitors, more like divisions of the same organization.
Other funding agencies such as the Department of Energy (DOE), National Science Foundation (NSF), and various branches of the Department of Defense play similar roles with respect to various fields of physics, mathematics, and other sciences.
Secondly, US Nationals who consider or pursue a Ph.D. in science or mathematics are systematically misinformed about career prospects. There is a big difference between going into a Ph.D. program paying (for example) $17K per year with the expectation of a low paying but secure faculty job thereafter due in part to the claimed desperate shortage of qualified people and (in reality) a one in ten chance of a similar faculty job but with less job security, independence, and creative freedom than often implied in recruiting graduate students for Ph.D. programs. The net present value calculation for the two cases will yield quite different numbers.
Sincerely,
John
I wasn’t trying to suggest that the solution is simple, but rather that there exist parties who will always declare a PhD shortage based on the idea that increased production will in the end let them hire PhDs for less money.
This idea may or may not be correct, but when someone who hires PhDs talks about a shortage, I expect this is what they are thinking.
Yes, I think when people are claiming a “Ph.D. shortage,” consciously or subconsciously, they are usually thinking “more Ph.D.’s means cheaper labor.”
They are, of course, assuming that they get the same quality for a lower salary and the policy does not drive the “best” out of the field or at least the increase in quantity of workers can offset the likely decline in quality — a rather dubious assumption if one uses the metric of practical, useful results rather than number of papers published or some similar academic metric.
My point is that I think it is meaningful and correct to speak of a “Ph.D. glut” in such an artificial market. One could also create a genuine “Ph.D. shortage” in such a market by appropriate government policies.
Sincerely,
John
“Finally and most importantly, there is considerable evidence that the Ph.D. glut has not worked. Far from accelerating the rate of scientific and technological progress, it has contributed to a slowing rate of progress.” The evidence adduced for this most important point is the graph of declining GDP shown below. He attributes this decline to “…the limited scientific and technical progress in most fields outside of computers and electronics, especially in power and propulsion technology, since 1970.”
There was no serious attempt to relate the decline in GDP with Ph.D. overproduction, no attempt to identify which disciplines have overproduced the most Ph.D.s, and no attempt to establish that the decline in GDP is attributable to a lack of progress in most technical and scientific fields outside of electronics and computers, not to mention no attempt to quantify what a lack of progress means, much less to establish it empirically. If there were an oversupply of technically skilled labor, then lack of progress in technological and scientific fields outside of computers and electronics cannot be explained by the oversupply, unless the oversupply is in the wrong fields, or there is some counterintuitive relation that causes technological advances to decline in the presence of a labor oversupply. None of this is stated clearly enough to evaluate this claim.
Confounding effects not considered in this analysis during the period from 1970 to the present, during which the labor shortage and rising wages that characterized the preceding 150 years in the US ended:
1. Automation increasingly made jobs obsolete and increased productivity;
2. American companies moved manufacturing offshore;
3. The women’s movement lead to labor increased as millions of women entered the workforce;
4. A new wave of immigrants came from Latin America;
A graph of the rate of Ph.D. production versus GDP increase doesn’t establish that increasing numbers of Ph.D.s has led to a decrease in “the rate of progress.”
The Author Responds
My article deals with growth rate; the real growth rate of the GDP has declined. It does not deal with issues of equality or distribution. There are arguments that all or most of the per capita real GDP growth since about 1980 has gone to the top 1 percent or even 0.1 percent of the United States population. The four points raised have more to do with this.
All of the factors — automation, cheaper manufacturing abroad, women entering the work force, and immigration from abroad — should increase the GDP even though they may lower wages and cause benefits to accrue to a small group at the top (maybe).
Automation has been ongoing since at least the invention of the separate condenser steam engine in the 1770s. Actually, wind mills and water mills were used prior to the steam engine and there appears to have been significant automation in some areas even before the 1770s. Automation contributes to the GDP rise. The benefits of automation seem to have been greater prior to 1970 — actually the benefits seem to have been declining in a long term trend.
Women entering the workforce can actually be interpreted as a symptom of lack of progress. Women worked full time, except for the very wealthy and powerful, up until the late 1800s when steam engines and other advances made an easier life possible for many people (yes, taking care of kids is a full time job but our ancestors had to do that and work on farms). In the United States, it seems to have become harder to maintain a “middle class” lifestyle with only one parent (traditionally the husband) working since the 1970s.
Despite all these changes, which should boost GDP, the GDP growth rate has declined over the last forty years.
Again the likely cause is poor progress in power and propulsion technologies, which is directly effected by the productivity — measured in practical results — of science/research and development. Previous waves of automation involved the introduction of better and better engines, motors, power supplies, etc. which dramatically boosted productivity.
Modern, post-1970 automation is mostly about “information technology.” No matter how fast a CPU is, it is not the same as a physical engine or motor. It can’t boost productivity as much or in the same way. Hence no flying cars.
Sincerely,
John
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