Thanks to the miracle of social media, I came across an excellent article that critiques Payscale’s data on the “return on investment” for various colleges. Forbes uses these data to rank colleges, with the assumption that the average starting or average mid-career salaries of graduates of particular universities tell us something about the value of the education provided.
I won’t go into great detail here about the analysis because the article is so darned good. But I will give you the list of the nine problems that author Russ Cannon identifies in his article about calculating the value of a college major.
- The form and setting where the data is collected isn’t conducive to accuracy.
- Sites like Payscale oversample young workers new to the job market
- Payscale in particular may over- and under-sample lots of things (like region) but we can’t know what.
- Payscale logically but problematically excludes anyone with an advanced degree.
- Also, Payscale rankings don’t (and can’t) weight my majors.
- There are very few responses for many colleges, and Payscale uses this limited data to make questionable inferences.
- More accurate (but also imperfect) state-level data sets suggest that even Payscale data on large universities may be way off.
- We can’t know what else is wrong (or right) with the data because the Payscale data is proprietary.
- There could be a MUCH better option.
Give this article a read, and you’ll get a sense for why it is so hard to calculate “return on investment” or hard calculating the value of a college major in higher education–much less predict what your own kid’s “return” will be five, ten, or twenty years from now.