The main purposes of family debt


Pavel Prikhodko, Ph.D. Machine Learning

According to an article by The New York Times, Americans borrowed more money in 2017 than at the height of the credit bubble in 2008 (when the global financial system began to collapse).

NerdWallet organized some numbers on the value of debt owned by consumers in the United States as of June 2018 by type of debt. Student loans of American consumers amounted to approximately $1.41 trillion. The value of auto loans approximated to $1.24 trillion, while credit card debts of American consumers amounted to $0.93 trillion. A catchall category, identified as “any type of debt,” was valued at $13.29 trillion, and mortgages owned by customers amounted to $9 trillion.

chart (2)

Next, let’s review the statistics on the purposes of family debt in 2016. According to the Federal Reserve, the largest percentage of family debt belonged to primary residence purchases (76.1 percent). Education, claiming an 8.8 percent share of the total family debt in the country, took a distant second. About 6.3 percent of household debt in the U.S. was attributable to vehicles in 2016. Goods/services and investment (excluding real estate) held 4.3 percent and 2.5 percent shares respectively. Lastly, approximately a 0.5 percent share of family debt belonged to other residential property.

chart (3)

Family structure appears to affect the likelihood of a family going into debt. For example, approximately 88.8 percent of couples with children had debt in 2016, compared to 76.7 percent of couples without children. The share of single-adult households with children who had debt in 2016 amounted to 80.1 percent, while 73.6 percent of single-adult (aged under 55) households with no children held debt in the same year.

Discuss this article on our forum with over 1,900,000 registered members.

About Pavel Prikhodko


Pavel Prikhodko, Ph.D. Machine Learning

Pavel has worked for many years as a researcher and developer on a wide range of applications (varying from mechanics and manufacturing to social data, finance and advertising), building predictive systems and trying to find stories that data can tell.

In his free time, he enjoys being with his family.

Other posts by Pavel Prikhodko:

Leave a Reply

Your email address will not be published. Required fields are marked *