Student Debt Across Wisconsin Metro Areas

So far, this series has focused on average debt and the distribution of debt among Wisconsin federal loan borrowers. Here, we shift attention to Wisconsin’s 12 metro areas and provide an interactive tool to explore regional differences in student debt. Data are based on the Federal Reserve Bank’s Consumer Credit Explorer, which reports median student loan debt for federal and private loan borrowers.

Consistent with national trends, we find student debt in Wisconsin grew fastest leading up to (and in the wake of) the Great Recession and has since grown at slower rates. Debt has generally grown across all 12 metro areas, but faster in some places than others. For example, residents in the metro areas of Janesville-Beloit and Appleton have seen their debts nearly double since 2005 with the median increasing by about $8,000 during this time. Alternatively, residents of the Madison and La Crosse-Onalaska metro areas have seen their debts grow at the slowest rate (about 50%) since 2005. And residents in the Wausau and Fond du Lac metro areas have experienced declines in median debt for a few years now.

This chart helps show how different communities around the state are experiencing different trends that while sometimes similar are also distinct. It also allows users to explore some sub-groups based on borrowers’ age, census tract income, and credit score, though not all metro areas report these more detailed sub-group trends. These sub-groups help us see that residents within the same metro area do not have the same debt outcomes. For example, borrowers aged 35 to 54, tend to have higher debts than other age groups. Exploring these sub-group differences can shed new insights to help pinpoint trends and patterns within certain geographic areas.

When interpreting the data trends presented here, two limitations are worth keeping in mind. First, metropolitan areas include large geographic boundaries and debt problems may be concentrated in smaller areas (e.g., zip codes, census tracts, etc.) that get overlooked here. We do not currently have that granularity of data but, when researchers do, they can reveal important differences even within geographic areas. Since the Great Recession, for example, debt has been rising fastest in Black-majority zip codes nationwide yet the data reported in this post are unable to disaggregate debt by race/ethnicity. Second, there are many “non-metro” areas across Wisconsin that may be very different in debt outcomes but are all grouped together here. Further research should look closely at debt in rural counties just as it should look more closely at debt within metro areas.

Despite data limitations, understanding median debt across Wisconsin’s metropolitan (and over time) is essential to understanding how our state might tackle growing student loan balances with an eye towards geographic differences. Pressing issues surrounding student loan debt, however, often deal with colleges instead of the local communities where borrowers live after leaving college. Both are crucial for measuring, monitoring, and ultimately addressing student debt problems, so the next post explores how student loan debt differs across Wisconsin’s public and private colleges and universities.