There is very little information available on how much postdocs are actually paid in the U.S., beyond data on institutional salary policies gathered by the National Postdoctoral Association. Following on from recent discussions about postdoc salaries changing as a result of proposed updates to U.S. Federal labor law, we have gathered data from a selection of institutions through Freedom of Information Requests, asking only for titles and salaries of postdocs, to see if we can identify actual postdoctoral salaries. The aggregate data, and more information, can be found at out “Investigating Postdoc Salaries” Resource. Every day, we will be releasing a discussion of each individual institution or system from which we received data. Today: University of Michigan.
Cost for FOIA Request: $300; see below
Additional notes: Data taken from publicly posted salary information including names and departments.
University of Michigan posts PDFs of salary information and so the FOIA request received the following response:
Therefore we used the publicly posted data, but appreciate the caveats that this may have in not having been presented in a manner responsive to our request.
University of Michigan was one of the institutions to cancel planned salary raises after the injunction against updates to the Fair Labor Standards Act was granted. However, in response to public scrutiny, including advocacy by postdocs at the University (see the guest post on our blog by postdoc Dr. Tammy Barnes), the salary policy was then reversed, and salaries again raised. We have received personal communication that all postdoc salaries are now above $47,476.
Therefore, the data we have may not reflect the current situation, and indeed, was dated from November 2016, so was before the injunction was granted and before our planned date of data collection of December 1st. Nonetheless it is a very large and detailed dataset which yielded a lot of information that is informing our thoughts, moving forward. In addition, it is the only dataset where we have been able to look at multiple years, as data has been posted for the last few years on the website, allowing us to look at names and see whether longitudinal information can be discerned from the data.
For example, we can look at the distribution of postdocs on NRSA stipends between 2015 and 2016, and see which scales are in use and how many postdocs are on the scale. A caveat to this is that if salaries are not fixed to the exact salaries on this scale, they will not appear; and they may well be above the level. Nevertheless it gives some interesting insights into how the scale is used.
It appears that in the 2015 dataset, a small number of salaries aligned to NIH stipends from scales going back to as far as Financial Years 2006-08; the increased scrutiny in 2016 that was applied in the lead-up to becoming compliant with FLSA updates seems to have removed most of the use of previous stipend scales from the equation. The use of 2016 stipends was still appropriate at this time as the new 2017 scale had not yet come into effect; however it is interesting to see that a number of postdocs were already on that scale. A larger number were on exactly the salary proposed for exemption from overtime.
What bears more investigation is the very large number on Year 0 vs more years of experience; clearly there are postdocs who do get raises based on the stipend scale (and these may be the postdocs on T32s and F32s, and other NRSA mechanisms). The large population on Year 0 may reflect the use of this as a minimum. Therefore we chose to look at salary ranges over time using the names of postdocs who appear year-to-year to see whether postdocs do get raises:
The largest group represented show raises of $500-$1500 from 2015 to 2016; comparing other years to see whether this trend is due to regular practices of raising salaries annually or have a contribution from salaries being raised due to the FLSA would be useful to separate these two factors. There are some extreme outliers in this plot which perhaps illustrate administrative factors rather than true salary changes, again remembering that this data is from information publicly posted and not in direct response to our request.
A very useful comparison, however, is to look at medical residents. This is a similar population to postdocs in terms of training stage in the medical track, and the data on medical residents is so clear as to be uninteresting; indeed even the year of residency is included in the title, and all residents are on the salary they should be, and see salary raises to the appropriate salary the next year. It is possible to plot how many residents there are year-to-year from this data, which is not possible with the postdoc data:
This does however reflect the fact that residents are unable to negotiate salary, whereas postdocs may have some ability to do this, making the postdoc data potentially less clear on year of expertise from salary alone.
However it does illustrate the scrutiny that medical resident salaries get versus postdoc salaries; and also the ability that institutions have to be able to curate accurate salary data.
Once the 2017 data is available, a comparison from 2014-2017 will be possible using these datasets which could make for an interesting case study on year-to-year changes in salaries.