Measuring Risk of too Much Debt in College

Measuring Risk of too Much Debt in College

Situation:   The official College Scorecard provides information on the median debt of student borrowers who finished college.   The median provides information on a typical person in the middle of the distribution.   It would be interesting to know what percent of student borrowers at a school borrowed more than a certain amount, perhaps $40,000 or $50,000.   The official web site of the college scorecard does not contain such information.

The college scorecard web site has a section with data files that contains additional information, which is not used in the on-line statistics page available to most users.   The link to the additional data is presented below.

https://collegescorecard.ed.gov/data/

A file called Most Recent Data has a variable called CUML_DEBT_P90.   This variable is the 90^th percentile of debt for people. (I believe the debt percentile pertains to people who finish school but the documentation is not clear on this point.)

Question:  Consider 4-year public universities with more than 5,000 students.    (I found 324 such universities.) Compare the median debt levels and the 90^th percentile of student borrowers at these universities.  Why is the 90^th percentile a better measure of the ability of universities to control debt of their students than the median?

Analysis: Statistics on the median debt levels and the 90^th percentile debt levels for student borrowers at 324 large 4-year public universities are presented below. 

Statistics on the median reflect the debt accumulated by a typical student at a particular school.

Statistics on the 90^th percentile reflect the experience of a student borrower who borrows more than 90% of all student borrowers at a school.

The typical or middle of the distribution experience at a school that has typical debt over 75 percent of schools is $18,298.

The above 90% of debt experience at a school that has a 90^th percentile greater than 75% of schools is $37,309.

Median Debt and 90th Percentile of Debt at 324 Public Universities
	Median Debt	90th Percentile of Debt
n	324	324
Mean	15896	34478
Standard Error	177	274
LB 95% CI	15549	33939
UB 95% CI	16244	35017
Min	5500	13750
25th	14177	31049
75th	18298	37309
Max	24250	49400

Discussion:   Why should a prospective student be concerned about the 90^th percentile of debt at a university, perhaps more so than the median debt level at the university?

The median debt does not consider risk.    The 90^th percentile of debt incurred by borrowers at a school provides more information about what can go wrong because of risk.

Some students come from a household where a parent might be able to contribute more even if the aid package requires substantial debt.   Perhaps students from households with modest means should shun universities where a large number of people exit school with a lot of debt.   The 90^th percentile is a better measure of a lot of debt than the median.

There are other sources of risk. Some schools do not maintain a full financial aid package over all four years.  

In addition, many students take more than four years to complete their degree.  It would be useful to know whether some schools are better than other schools at getting students done on time.

In any event, I believe the 90^th percentile of debt figures provide additional information on risk and that these 90^th percentile debt figures should be provided in the main College Scorecard web site and not be relegated to an obscure file in the data section of the web page.

Notes:

Note One:  The statistics presented in the chart above are not weighted by the size of the institutions.   All institutions in this particular sample are public universities offering four-year degrees with at least 5,000 students.

Note Two:  The 90^th percentile statistics by institution cannot be used to measure the number of students in the country with high debt levels.    Even weighting by number of students would not resolve this issue.  The 90^th percentile of the total population of students can be disproportionately impacted by a relatively small number of bad institutions.  The table below illustrates that the mean of schools may be inconsistent with the 90^th percentile for the entire populations

Example Showing Weighted Average of 90th Percentile is not Equal to 90th Percentile of Total
	School One	School Two	Total
Borrowers	5,000	10,000	15,000
Number of people with $30,000 in Debt	2,000	500	2,500
Number of people with $10,000 in Debt	3000	9500	12,500
90th Percentile	$30,000	$10,000	$30,000

Note Three:  The data files on the Department of Education web page are not easily analyzed.   Many of the variables in the file have alphabetic entries for some observations and these string variables are not easily read.  It would be highly useful if the Department of Education created a SAS Export file with data that was readable in SAS and other packages including STATA.

Readers of this post may want to learn more about President Obama's effort to rank colleges.   See the post below.

http://policymemos.blogspot.com/2016/04/ranking-colleges-based-on-value-and.html


Also, readers might be interested in my plan to front load aid to first-year students.

http://policymemos.blogspot.com/2016/03/elimination-of-college-debt-for-first.html