The New York Fed Consumer Credit Panel: A Foundational CMD Data Set
As the Great Financial Crisis and associated recession were unfolding in 2009, researchers at the New York Fed joined colleagues at the Board of Governors and Philadelphia Fed to create a new kind of data set. Household liabilities, particularly mortgages, had gone from being a quiet little corner of the financial system to the center of the worst financial crisis and sharpest recession in decades. The new data set was designed to provide fresh insights into this part of the economy, especially the behavior of mortgage borrowers. In the fifteen years since that effort came to fruition, the New York Fed Consumer Credit Panel (CCP) has provided many valuable insights into household behavior and its implications for the macro economy and financial stability.
The CCP was one of the first data sets drawn from credit bureau data, one of the earliest features of the Center for Microeconomic Data (CMD), and the primary source material for some of the CMD’s most important contributions to policy and research. Here we review a few of the main household debt themes over the past fifteen years, and how our analyses contributed to their understanding.
Supply Chains, Student Debt, and Stablecoins—The Top 5 Liberty Street Economics Posts of 2022
“Kitchen table” issues were on the minds of our readers in 2022, though what was labeled as such was perhaps a bit broader than in the past. Supply chains—now firmly placed on the radar of Main Street—were the subject of the year’s top post by number of page views and accounted for three of the top five (we’ll consider them as one for this roundup). Student debt forgiveness and inflation were also in the news, drawing readers to our preview of various possibilities for the (subsequently announced) federal student loan forgiveness program and a quarterly update of a New York Fed economic forecast model. Posts on more technical topics were popular as well, including an update on the Federal Reserve’s balance sheet “runoff” and a discussion of stablecoins. Underscoring their broad appeal, the year’s top two posts rank among the top five in the history of Liberty Street, which dates back to 2011. Read on to see which posts resonated most with readers.
Three Key Facts from the Center for Microeconomic Data’s 2022 Student Loan Update
Today, researchers from the Center for Microeconomic Data released the 2022 Student Loan Update, which contains statistics summarizing who holds student loans along with characteristics of these balances. To compute these statistics, we use the New York Fed Consumer Credit Panel (CCP), a nationally representative 5 percent sample of all U.S. adults with an Equifax credit report. For this update, we focus on individuals with a student loan on their credit report. The update is linked here and shared in the student debt section of the Center for Microeconomic Data’s website. In this post, we highlight three facts from the current student loan landscape.
Student Loan Repayment during the Pandemic Forbearance
The onset of the COVID-19 pandemic brought substantial financial uncertainty for many Americans. In response, executive and legislative actions in March and April 2020 provided unprecedented debt relief by temporarily lowering interest rates on Direct federal student loans to 0 percent and automatically placing these loans into administrative forbearance. As a result, nearly 37 million borrowers have not been required to make payments on their student loans since March 2020, resulting in an estimated $195 billion worth of waived payments through April 2022. However, 10 million borrowers with private loans or Family Federal Education Loan (FFEL) loans owned by commercial banks were not granted the same relief and continued to make payments during the pandemic. Data show that Direct federal borrowers slowed their paydown, with very few making voluntary payments on their loans. FFEL borrowers, who were not covered by the automatic forbearance, struggled with their debt payments during this time. The difficulties faced by these borrowers in managing their student loans and other debts suggest that Direct borrowers will face rising delinquencies once forbearance ends and payments resume.
Unequal Distribution of Delinquencies by Gender, Race, and Education
This post is the second in a three-part series exploring racial, gender, and educational differences in household debt outcomes. In the first post, we examined how the propensity to take out household debt and loan amounts varied among students by race, gender, and education level, finding notable differences across all of these dimensions. Were these disparities in debt behavior by gender, race, and education level associated with differences in financial stress, as captured by delinquencies? This post focuses on this question.
Uneven Distribution of Household Debt by Gender, Race, and Education
Household debt has risen markedly since 2013 and amounts to more than $15 trillion dollars. While the aggregate volume of household debt has been well-documented, literature on the gender, racial and education distribution of debt is lacking, largely because of an absence of adequate data that combine debt, demographic, and education information. In a three-part series beginning with this post, we seek to bridge this gap. In this first post, we focus on differences in debt holding behavior across race and gender. Specifically, we explore gender and racial disparities in different types of household debt and delinquencies—for auto, mortgage, credit card, and student loans—while distinguishing between students pursuing associate’s (AA) and bachelor’s (BA) degrees. In the second post in this series, we investigate gender and racial disparities in delinquencies across these various kinds of consumer debt. We close with a third post where we try to understand some of the mechanisms behind differences in debt and delinquencies across gender and race.
Who Pays What First? Debt Prioritization during the COVID Pandemic
Since the depths of the Great Recession, household debt has increased from a low of $11 trillion in 2013 to more than $14 trillion in 2020 (see the New York Fed Household Debt and Credit Report). In this post, we examine how consumers’ repayment priorities have evolved over that time. Specifically, we seek to answer the following question: When consumers repay some but not all of their loans, which types do they choose to keep paying and which do they fall behind on?