Improving Net Price Data Reporting

As the sticker price of attending colleges and universities has steadily increased over the past decade, researchers and policymakers have begun to focus on the actual price that students and their families face. The federal government collects a measure of the net price of attendance in its IPEDS database, which is calculated as the total cost of attendance (tuition, fees, room and board, and other expenses) less any grant aid received. (More information can be found on the IPEDS website.) I have used the net price measure in my prior work, including the Washington Monthly rankings and my previous post on the Net Price Madness tournament. However, the data do have substantial limitations—some of which could be easily addressed in the data collection process.

There are two different net price measures currently available in the IPEDS dataset—one for all students receiving grant aid (federal, state, and/or institutional) and one for students receiving any federal financial aid (grants, loans, or work-study).  The average net price is available for the first measure, while the second measure breaks down the net price by family income (but does not report an average net price.) For public institutions, both of these measures only include first-time, full-time, degree-seeking students paying in-state tuition, which can substantially limit the generalizability of the results.

Here, I use my current institution (the University of Wisconsin-Madison) as an example. The starting sample for IPEDS is the 3,487 first-time, full-time, degree-seeking freshmen who are in-state students. Of those students, net price by family income is calculated for the 1,983 students receiving Title IV aid. (This suggests that just over half of in-state Madison freshmen file the FAFSA.) Here are the net price and number of students by income group:

0-30k: $6,363 (n=212)
30-48k: $10,098 (n=232)
48-75k: $15,286 (n=406)
75-110k: $19,482 (n=542)
110+k: $20,442 (n=591)

The average net price is calculated for a slightly different group of students—those who received grant aid for any source (n=1,858). The average net price is $14,940, which is lower than the average net price faced by students who file the FAFSA ($16,409) as some students who do not receive institutional grants are included in the latter measure. However, the latter number is not reported in the main IPEDS dataset and can only be calculated by digging into the institutional reports.

I would encourage IPEDS to add the average net price for all FAFSA filers into the dataset, as that better reflects what students from financially modest backgrounds will pay. Additionally, to counter the relatively small number of students who may have a family income of less than $30,000 and to tie into policy discussions, I would like to see the average net price for all Pell Grant recipients. These changes can easily be made given current data collection procedures and would provide more useful data to stakeholders.

Tying FAFSA Data to IPEDS: The Need for “Medium Data”

It is safe to say that I’m a fan of data in higher education. Students and their families, states, and the federal government spend a massive amount of money on higher education, yet we have relatively little data on outcomes other than graduation rates and student loan default rates for a small subset of students—those who started as first-time, full-time students. The federal government currently operates on what I call a “little data” model, with some rough institutional-level measures available through IPEDS. Some of these measures are also available through a slightly more student-friendly portal in the College Navigator website.

As is often the case, some states are light years ahead of the federal government regarding data collection and availability. Florida, Texas, and Ohio are often recognized as leaders in terms of higher education data availability, both in terms of collecting (deidentified) student-level data and tying together K-12, higher education, and workforce data outcomes. The Spellings Commission in 2006 did call for a student-level dataset at a national level, but Congress explicitly denied the Department of Education this authority in the reauthorization of the Higher Education Act. Although there are sporadic movements toward “big data” at the national level, making this policy shift will require Congressional support and a substantial amount of resources.

Although I am willing to direct resources to a much more robust data system (after all, how can we determine funding priorities if we know so little about student outcomes?), a “medium data” approach could easily be enacted by using data sources already collected by colleges or the federal governemnt. I spent a fair amount of the morning today trying to find a fairly simple piece of data—the percentage of students at given colleges whose parent(s) did not complete college. The topic of first-generation students is important in policy circles, yet we have no systemic data on how large this group of students is at most colleges.

FAFSA data could be used to expand the number of IPEDS measures to include such topics as the following, in addition to first-generation status:

(1)    The percentage of students who file the FAFSA

(2)    Average/median family income

(3)    Percentage of students with zero EFC

(4)    Information on means-tested benefit receipt (such as food stamps or TANF)

(5)    Marital status

Of course, these measures would only include students who file the FAFSA—which would exclude many students who would not qualify for need-based aid, as well as some students who are unable to navigate through the complicated form. But these measures would provide a better idea of institutional diversity beyond racial/ethnic diversity and the percentage of students receiving Pell Grants and could be incorporated into IPEDS at a fairly low cost. Adding these FAFSA measures would help move IPEDS from “little data” to “medium data” and provide more useful measures to higher education stakeholders.