New York Fed Blogs on Student Loans

Today, February 18, the Federal Reserve Bank of New York began an important 3-part blog series addressing student debt.   The series will be posted on their Liberty Street Economics blog.

Liberty street

According to a preview from the NY Fed, the series includes:

The Student Loan Landscape” (today’s post) – This entry examines the trajectory of student debt since 2004 and provides updated figures on the distribution of student loan borrowers by age and by average balance, as well as an update on their ability to obtain mortgages.

Looking at Student Loan Defaults through a Larger Window (Feb. 19) — This entry examines cohort default rates and uncovers that performance by cohort worsened in the years leading up to the Great Recession. Moreover, defaults appear to be concentrated among the lowest balance borrowers.

Payback time? Measuring Progress on Student Debt Repayment (Feb. 20) — This entry examines how fast (or slow) student borrowers are able to pay off their loans. The authors find delinquency and default rates might understate the true extent of borrower problems in the student loan market.


Charts: The Good, the Bad and the Ugly

bar_chartFor those in the economics profession, it is not unusual to hear a phrase like, “Hey, that’s a nice chart!” Recently, I stuck a simple chart that illustrated GDP into a PowerPoint slide, and it was described as “ugly.” In this world, communication is almost synonymous with a set of charts. And thanks in part to our image-filled Facebook, Pinterest, and Twitter feeds, all forms of communication are evolving into the art of designing images to tell a thousand words.

Justin Wolfers, a well-known economist, recently blogged about the power of charts in a hilarious posting, “A Persuasive Chart Showing How Persuasive Charts Are.” He provides an example from two Cornell researchers, Brian Wansink and Aner Tal, who studied participants’ reactions to pharmaceutical data presented in two different formats. First, the group simply read the results that were written out, and then a subset of the group was shown the same data in a chart form. Translating the description into a chart increased the proportion of people who believed in the drug’s efficacy from, 68 to 97 percent. The study concludes that among the participants who agreed with the statement, “I believe in science,” there was a lot more credence given to data that was presented in a chart versus simply through prose.

I suppose the simple take-away of this story could be the importance of nice charts. However, it also seems to highlight the increasing need to scrutinize charts and the relationship of data sets. There is something about a set of bars on a chart that makes the mind want to look for patterns. These patterns do not necessarily indicate any significant relationship among the data being shown.  If I charted out the time my neighbor ate dinner and the time I woke up in the morning, the chart would probably look nice. However, it would falsely indicate to a reader that there was an important relationship between these two nuggets of information, which there is not. So, we can all come across a “nice chart,” but let’s make sure that we are being critical of the sources and the relationship of the data before we arrive at any conclusions.

Do you think we are preparing our students to do this in our world of Pinterest and Facebook? Are there strong enough, well-understood conventions on data presentation incorporated into our curriculums? Share some of the off-the-wall charts you have come across….

A blog designed to act as a resource and sounding board for promoting economic education.