
In the Salary Race, Engineers Sprint but English Majors Endure - tlb
https://www.nytimes.com/2019/09/20/business/liberal-arts-stem-salaries.html
======
dpark
> _Computer science and engineering majors between the ages of 23 and 25 who
> were working full time earned an average of $61,744 in 2017, according to
> the Census Bureau’s American Community Survey. This was 37 percent higher
> than the average starting salary of $45,032 earned by people who majored in
> history or the social sciences (which include economics, political science
> and sociology). Large differences in starting salary by major held for both
> men and women._

> _Men majoring in computer science or engineering roughly doubled their
> starting salaries by age 40, to an average of $124,458. Yet earnings growth
> is even faster in other majors, and some catch up completely. By age 40, the
> average salary of all male college graduates was $111,870, and social
> science and history majors earned $131,154 — an average that is lifted, in
> part, by high-paying jobs in management, business and law._

Uh, yeah. From 23-25 you’re comparing engineers vs random 4-year degrees. At
40 you’re comparing engineers vs a group that suddenly includes lawyers and
MBAs.

You’d find similar results if you compared baristas to premed students. At 23
the typical barista is earning at least minimum wage while the typical premed
student is earning literally nothing (unless moonlighting as a barista...).
Suddenly their fortunes reverse at 40 when a significant portion of premed
students have turned into established doctors.

23-25 is the time that all the advanced degrees are being earned. If you want
a fair comparison you have to compare equivalent education in each age group.
You can’t suddenly change the cohort at 40.

~~~
smogcutter
> At 40 you’re comparing engineers vs a group that suddenly includes lawyers
> and MBAs.

Sure, the fact that the career paths diverge is... the whole point. The cohort
didn’t change, one part of it went to law school and the other didn’t. Your
analogy is totally off base.

~~~
dpark
When you explicitly select people who are between 23 and 25 and have entered
the work force, you are intentionally selecting for people who do not have a
JD and are not actively earning one. The set of 23 year old lawyers is
essentially nonexistent. The set of 23 year olds working full time and also
enrolled in law school is hardly much larger.

~~~
lonelappde
Where is the evidence that they selected for employed grads?

~~~
dpark
It’s in the part of the article I quoted.

“Computer science and engineering majors ... who were working full time earned
an average of $61,744 ... higher than the average starting salary of $45,032
earned by people who majored in history or the social sciences...”

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topkai22
$141000/year is a shockingly large income for any broad group of people in the
US. According to the ACS, the median earnings for all bachelor's degree
holding full time make workers is $61k. That's for the full population, so it
should in fact be centered somewhere near age 35-40.

I don't know where the author is getting the $112k number for all men at age
40 is from, but it seems impossible from my knowledge of the ACS statistics.
Perhaps the mean drifts that high with super star executive pay? Regardless,
it makes me suspicious of the other numbers in this article- anyone have an
idea of how the author could get these earnings statistics from ACS data?

~~~
eloff
I was thinking the same thing, this doesn't seem possible.

------
gautamcgoel
I'm studying machine learning as a PhD student at Caltech. I have heard of
graduating ML PhD students from my department making $400-500k/year as a
starting salary. Heck, they could probably retire by 35. I doubt any English
major could match that... I wish the NYT article also looked at starting
salaries of fresh PhDs, not just new college grads.

~~~
dehrmann
> Heck, they could probably retire by 35.

As a PhD student (PhD students are underpaid to an almost criminal extant),
you might think that, but start with half of that going to taxes, a $2M home,
and escalating expenses. You can make it happen, but you get a bit of a
culture shock when you go from making that much money to living off $50k in
interest and living in Toledo.

~~~
OJFord
'FIRE' pursuants do not generally buy $2M homes, or no, they wouldn't manage
it!

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dasil003
My guess is this has more to do with technician roles having an acceptable
baseline and the personality type not wanting to go into management. If you
sampled just managers only, I doubt you'd see the same difference because
technical expertise is extremely valuable in management.

Regardless of the nuance of the stats though, the idea that you'd choose
between wildly differing majors based on watered down averages strikes me as a
really poor strategy. The variance on salary progression is huge, and it's not
what you learned in school but what you do on the job that fuels your
advancement. IMHO you're much better off starting by optimizing what you are
naturally interested in at a young age, develop your skills along the way, but
stay open and ready for new opportunities as you progress through your career.

~~~
plutonorm
I've never been able to break into management and now I'm 40. Compared to most
programmers I'm personable and outgoing. Getting a leg up into management is
very difficult. In 13 years as a programmer I've never worked with anyone who
achieved it. Don't bank on it being possible. If you want to get into
management you need to take radical action. Don't drift along like I did and
be bitterly dissapinted that you're stuck in development probably forever,
like I did.

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laurencerowe
> One of the largest and most popular courses in the Stanford computer science
> department is CS229 — Machine Learning, taught by the artificial
> intelligence expert and entrepreneur Andrew Ng. This course did not exist
> until 2003, when Professor Ng taught it for the first time with 68 students,
> and very little like it existed anywhere on college campuses 15 years ago.
> Today, the machine learning courses at Stanford enroll more than a thousand
> students.

Machine Learning was a standard offering in CS departments in the early
2000's. It was already a venerable subfield with much of the basic theory
having been developed in the 1970's and 1980's. I remember thinking it was
something of a curiosity and not terribly practical but it's absurd to imply
it sprung from nothing.

~~~
_delirium
I was also surprised by that bit. Tom Mitchell's influential textbook [1] came
out in 1997, and was already being used by quite a few courses within a few
years of release.

[1]
[http://www.cs.cmu.edu/~tom/mlbook.html](http://www.cs.cmu.edu/~tom/mlbook.html)

~~~
noneeeed
That was my textbook at York Uni back in 2000, it was a great book. I recently
got a new copy and quickly realised that I have forgotten most of the maths
that I used to know, so first I need to do a refresher on that :)

That book taught me an important lesson that I wish I'd learned earlier, that
for many of my courses reading the textbook would have been a good idea. My
lecturer for the ML course was unbelievably tedious, and I realised I'd
absorbed almost nothing. I sat down with Mitchell's book for a week before the
exam, did all the exercises, and got the highest mark in my degree.

I often wonder how much better I could have done, and how much more I'd have
learnt, if I'd put that sort of work into all my other modules earlier in the
course.

------
ajhurliman
Bold claims with almost no citations? Thanks for the opinions, but I think
I'll pass.

------
mips_avatar
We should have levels.fyi for more things in life. It really blew my mind how
much the tech companies pay. Made me realize I needed to prioritize those
companies for my job search.

~~~
SomeOldThrow
> Made me realize I needed to prioritize those companies for my job search.

Ehh, or just do less work at a place that pays less.

~~~
solipsism
It's a common misconception that working at these companies requires selling
your soul. Some company cultures are better than others. Some teams are better
than others.

Lots of people at these companies work a strict 40.

~~~
endtime
I've been a SWE at Google for a while, been promoted a couple times, been a
tech lead a couple times. Pretty much always worked 40 hours a week, and I
don't think this is unusual. There might be some folks working 50 hours, but I
suspect in most cases that's because they want to work 50 hours.

------
powerslacker
So for nearly two decades take a pay cut of tens of thousands of dollars just
to catch up at age 40?

Even if there were any citations to back up the claims in this article, it
wouldn't make any sense!

~~~
dehrmann
Not just that, it didn't call out opportunity cost.

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Yhippa
Can't read the article, even through the web link above.

It makes me think based on the title that lots of new college hires must be
making insane amounts of money right out of school. What happens say, 10-15
years down the road when being a good developer won't cut it and you either go
into management or IC it somehow?

I don't think everyone can do that because as you move up there are fewer
positions. Also, there are new college grads right behind you willing to do
what you're doing for way cheaper. Even if you've kept up with your skills it
seems like it's easier than ever to pick up new skills due to democratization
of learning.

~~~
dlphn___xyz
it really depends on the industry.

------
pockettanyas
It seems like median would be a much better metric than mean here.

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apollo_
the effect of compounding is notably absent in the discussion.

~~~
cellular
Author doesn't know what that is. :-)

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ajbonkoski
(sigh) They're comparing averages, so the whole theory is suspect.

Averages are a terrible way to do a comparison. Averages aren't terribly
useful unless you know that your data is Gaussian (or a sum of IID Random
Variable => see the CLT). Folks love to erroneously assume Gaussian.

In this particular problem, I would expect to see a multimodal distribution
for the liberal arts majors.. (i.e. some folks have massive salaries (famous
authors) and some have small salaries (high school English teachers)).

In such a case, the average can end up at a value that basically doesn't exist
in the underlying distribution. So you end up comparing nonsense.

------
regulation_d
> Between the ages of 25 and 40, the share of STEM majors working in STEM jobs
> falls from 65 percent to 48 percent. Many of them shift into managerial
> positions, which pay well but do not always require specialized skills.

While technically true, I would argue that many of the most successful
managers are at least in part successful because they have a really strong
background in the field they are managing. Most people want to be managed by
people who understand some of the nuances of what they're doing.

------
timwaagh
I speculate the cause is self selection. People who know they don't have what
it takes to become manager or any job that depends on soft skills are unlikely
to major in liberal arts and more likely to choose engineering. Hence, fewer
engineers move up the ladder. I can speak from experience. My parents
prevented me from choosing a masters in science management because of the
management.

------
ltbarcly3
The title of the article says "English majors", but the body says "Liberal
Arts majors".

"Liberal Arts" isn't a category of undergraduate major. It is it's own
category, which is generally only offered at 'Liberal Arts' colleges which
offer only that major. However, if you take 'Liberal Arts' to be a 'category
of categories', it could potentially include:

[https://www.internationalstudent.com/study-liberal-
arts/](https://www.internationalstudent.com/study-liberal-arts/)

    
    
      Humanities - English Literature, Modern Languages, History, and Philosophy
      Social Sciences - Anthropology, Economics, Geography, 
      Political Science, and Sociology
      Creative Arts - Fine Art, Theatre, Speech, and Creative Writing
      Sciences – Astronomy, Biology, Chemistry, and Physics
    
    

Ok, nearly any major that existed before 1940 apart from Mathematics and
Engineering.

What did the survey say exactly? Well, first of all, from everything I can
tell it only includes 4 states, Colorado, Michigan, Texas, and Wisconsin. Not
exactly representative, probably, but what schools are included?

School list (for Colorado):

    
    
      ADAMS STATE COLLEGE
      AIMS COMMUNITY COLLEGE
      ARAPAHOE COMMUNITY COLLEGE
      COLORADO MESA UNIVERSITY
      COLORADO MOUNTAIN COLLEGE
      COLORADO NORTHWESTERN COMMUNITY COLLEGE
      COLORADO SCHOOL OF MINES
      COLORADO STATE UNIVERSITY
      COLORADO STATE UNIVERSITY - GLOBAL CAMPU
      COLORADO STATE UNIVERSITY - PUEBLO
      COMMUNITY COLLEGE OF AURORA
      COMMUNITY COLLEGE OF DENVER
      EMILY GRIFFITH TECHNICAL COLLEGE
      FORT LEWIS COLLEGE
      FRONT RANGE COMMUNITY COLLEGE
      LAMAR COMMUNITY COLLEGE
      METROPOLITAN STATE UNIVERSITY OF DENVER
      MORGAN COMMUNITY COLLEGE
      NORTHEASTERN JUNIOR COLLEGE
      OTERO JUNIOR COLLEGE
      PICKENS TECHNICAL COLLEGE
      PIKES PEAK COMMUNITY COLLEGE
      PUEBLO COMMUNITY COLLEGE
      RED ROCKS COMMUNITY COLLEGE
      TRINIDAD STATE JR COLLEGE
      UNIV OF COLORADO AT COLO SPRINGS
      UNIVERSITY OF COLORADO DENVER
      UNIVERSITY OF COLORADO - BOULDER
      UNIVERSITY OF NORTHERN COLORADO
      WESTERN STATE COLORADO UNIVERSITY
    

Well, I've never heard of any of those schools, but whatever, maybe most
people go to schools I've never heard of so that's not exactly evidence of
anything.

I didn't want to go through every school, so I just picked University of
Colorado, Denver, since it seems like it's probably one of the bigger schools?

I used
[https://factfinder.census.gov/faces/nav/jsf/pages/searchresu...](https://factfinder.census.gov/faces/nav/jsf/pages/searchresults.xhtml?refresh=t#acsST)
to compare all the majors. I couldn't find a single non-STEM major that had
better incomes than even a single STEM major. I assume this is the dataset he
is taking his data from since he links to it.

So I guess what I'm saying is, this article seems to be predicated on a tiny
dataset from a few select schools from a few select states, does not include
flagship schools, (in fact it seems to only include 3rd and 4th tier schools,
no Anne Arbor, Reed, University of Portland, University of Oregon, Rice, UofT
Austin, Texas A&M, U of Wisconsin, Lawrence, Milwaukee School of Engineering,
Marquette, etc etc etc.

So before you debate 'what this means' you should know that, based on the
above, it means _nothing_ , and no general facts can be drawn from it. I
couldn't even figure out what methodology he used to come to his conclusions
(if any), or even what he means by 'liberal arts' since that's not a category
in the data.

All that, and the data I could find completely disagrees with his analysis,
and in fact shows the complete opposite.

